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The Software Quality and Productivity Crisis Executives Won’t Address

Reflections From the Long View – 50 Years in Software Consulting

Over my five decades in software consulting, I’ve witnessed remarkable transformations in our industry—from punch cards to cloud computing, from mainframes to microservices to AI coding. But in the past few years, I’ve observed something deeply troubling: a significant decline in interest in—and concern over—both software quality and productivity.

At first, I dismissed it as the bias of age. Perhaps I was simply romanticising the past. So I did what any good consultant does: I looked for data to either validate or refute my impression.

What I found was worse than I imagined. The decline is not only real and measurable—it’s being actively ignored by the very people with the power to address it. We don’t have a technology crisis. We have a leadership crisis—one that may require us to embrace #NoLeadership and take matters into our own hands.

But here’s something that troubles me even more: I suspect that without a long-term perspective, folks might never have noticed this decline at all. If you’ve only been in the industry for five or ten years, the current state might seem normal. You might assume that 75% project failure rates, $1.52 trillion in technical debt, and 69% of developers losing significant time to inefficiencies is simply “how software development works.” It isn’t. It’s how software development has deteriorated under leadership neglect.

The Crisis in Numbers

Let me establish a baseline. Recent industry surveys reveal:

  • 75% of business and IT executives expect their software projects to fail (Beta Breakers, 2024)
  • Only 39% of projects actually meet success criteria (Beta Breakers, 2024)
  • Technical debt in the US reached $1.52 trillion in 2022 (Consortium for Information & Software Quality, 2022)
  • 69% of developers report losing 8+ hours weekly to inefficiencies—20% of their time (Atlassian, 2024)
  • 91% of CTOs identify technical debt as their biggest challenge (STX Next, 2023)

That last statistic is crucial. Hold onto it.

What Executives Know Privately

Internal surveys—the ones shared only amongst technology leadership—paint a clear picture of awareness:

According to the STX Next Global CTO Study, 91% of CTOs cite technical debt as their biggest challenge heading into 2024 (STX Next, 2023). Not second biggest. Not a concern. Their biggest challenge.

A 2024 survey by Morning Consult and Unqork found that 80% of business and technology leaders acknowledge that technical debt causes delays, cancelled projects, and higher costs (Oliver Wyman, 2024).

McKinsey research shows that CIOs estimate technical debt amounts to 20–40% of the value of their entire technology estate, and some 30% of CIOs surveyed believe that more than 20% of their technical budget ostensibly dedicated to new products is diverted to resolving issues related to tech debt (McKinsey & Company, 2023).

Protiviti’s Global Technology Executive Survey found nearly 70% of organisations view technical debt as having a high level of impact on their ability to innovate (Protiviti, 2024).

The message is unambiguous: executives know.

What Executives Do About It

Here’s where the story becomes damning.

Industry research consistently recommends that companies allocate 15–20% of their IT budgets to proactive technical debt management. According to Oliver Wyman’s 2024 analysis, only a small minority of companies actually earmark this recommended amount (Oliver Wyman, 2024).

Instead, most organisations don’t tackle technical debt until it causes an operational meltdown. At that point, they end up allocating 30–40% of their budget to massive emergency transformation programmes—double the recommended preventive investment (Oliver Wyman, 2024). It’s like Y2K again and again.

Let me put this plainly: executives know the problem, know the solution, know the cost of prevention, yet consistently choose to wait for the crisis.

But it gets worse.

The Priority Charade

I examined CIO priority surveys from 2022–2024 across multiple sources. Here’s what consistently makes executives’ top 5 priorities:

  1. Cybersecurity
  2. AI/GenAI adoption
  3. Digital transformation
  4. Cloud migration
  5. Cost optimisation

Here’s what’s conspicuously absent:

  • Software quality
  • Developer productivity
  • Technical debt remediation
  • Testing (QC) and QA investment

Despite 91% of CTOs citing technical debt as their biggest challenge, it doesn’t make the top five priorities in any major CIO survey from 2022–2024.

Think about that disconnect. The thing keeping CTOs awake at night doesn’t even warrant a place in their stated priorities.

The Public Deception

The gap between private knowledge and public communication is where this crosses from negligence into active deception.

I reviewed annual reports and earnings call transcripts from major technology companies for 2023–2024. Here’s what CEOs told shareholders:

Microsoft’s CEO claimed GitHub Copilot increases developer productivity by ‘up to 55%, whilst helping them stay in the flow and bringing the joy back to coding’ (Microsoft, 2023).

Google boasted that ‘more than a quarter of all new code at Google is generated by AI’ (Clouded Judgement, 2024).

Amazon, Meta, and other tech giants celebrated AI productivity gains and record revenues in their annual reports.

Now here’s what these same executives didn’t mention in their shareholder communications:

  • The 75% project failure expectation that their own industry acknowledges
  • The $1.52 trillion in technical debt
  • The 69% of developers losing 8+ hours weekly to inefficiencies
  • The fact that only 39% of projects meet success criteria
  • The 91% of CTOs who cite technical debt as their top concern

I read through annual shareholder letters from JPMorgan Chase, Caterpillar, Chubb, Microsoft, and SoftwareOne. Not one CEO mentioned software quality concerns, technical debt, or developer productivity issues in their 2023–2024 letters to shareholders.

Not. One.

The Productivity Paradox

This creates a particularly egregious contradiction. Microsoft trumpets 55% productivity gains from AI tools in earnings calls (Microsoft, 2023). Meanwhile, independent research shows:

  • 69% of developers lose 8+ hours weekly to inefficiencies (Atlassian, 2024)
  • Only 20% of professional developers report being happy with their jobs (Stack Overflow, 2024)
  • Tech worker burnout jumped from 49% to 68% in just three years (Techotlist, 2024)
  • Developer productivity is neither well-understood nor enabled, according to Atlassian’s research (InfoWorld, 2024)

So which is it? Are developers 55% more productive, or are they losing 20% of their time to inefficiencies and burning out at record rates?

The answer: executives are measuring—and reporting—what makes their stock price rise, not what’s actually happening on the ground.

The Investment That Never Happens

Perhaps the most damning evidence is in the budgets. McKinsey’s research identifies the solution clearly: proactive technical debt management through consistent investment (McKinsey & Company, 2023). Deloitte’s 2024 Tech Trends report notes that leading companies target 15% of IT budgets for technical debt management (Deloitte, 2024).

Yet Oliver Wyman’s analysis found that only a small minority of companies actually allocate this recommended amount. The majority wait for crisis, then spend 30–40%—double the preventive cost (Oliver Wyman, 2024).

It’s the equivalent of knowing your building needs foundation repairs, having engineers tell you it will cost £100,000 now or £250,000 after collapse, and choosing to wait for the collapse.

Except we’re not talking about one building. We’re talking about the entire industry making this choice simultaneously.

The Trend Is Accelerating—And Why It Takes Decades to See It

The executive action gap isn’t static—it’s widening. Between 2020 and 2024:

2020–2021: The pandemic forced rapid digital transformation. Organisations rushed to cloud, creating massive technical debt. Software supply chain failures accelerated by 650% (Consortium for Information & Software Quality, 2022).

2021–2022: Rather than addressing the debt created, executives doubled down on speed. Cybercrime losses from software vulnerabilities rose 64% in 2020–2021, then another 42% in 2021–2022 (Consortium for Information & Software Quality, 2022).

2022–2023: 72% of organisations reported falling behind in digital transformation because of technical debt, with rushed cloud transitions cited as the primary cause (ReadyWorks, 2023).

2023–2024: Instead of addressing mounting technical debt, executives shifted focus to AI. For the first time, AI and Machine Learning vaulted to #2 in executive priorities, having not appeared in the top five the previous year (Evanta, 2024).

At each stage, executives had the data. At each stage, they chose the next shiny object over addressing fundamental problems.

Here’s what troubles me: if you started your career in 2019 or 2020, this accelerating decline is all you’ve ever known. You entered the industry during the pandemic rush, when corners were being cut at unprecedented rates. You’ve never experienced a development environment where quality was genuinely prioritised, where technical debt was proactively managed, where 75% project failure wasn’t expected.

You might think this is normal.

It’s not. In the 1990s and 2000s, whilst projects certainly failed and technical debt existed, there was a prevailing culture that quality mattered. Teams pushed back on unreasonable deadlines. Architects had authority to insist on sound technical decisions. “Technical debt” was something you reluctantly accumulated and felt obligated to address, not something you casually accepted as inevitable.

The shift has been gradual enough that it’s nearly invisible year-to-year. But viewed across decades, it’s stark. We’ve normalised dysfunction.

This is why long-term perspective matters. Trends that seem acceptable in isolation become alarming in context. A developer who’s experienced 15 different organisations over 30 years can see patterns that someone at their first or second company cannot. The boiling frog doesn’t notice the temperature rising. Those of us who remember when the water was cooler do.

The CrowdStrike Crystallisation

On 19 July 2024, a single CrowdStrike update crashed 8.5 million Windows machines globally, grounding flights, disabling emergency services, and causing an estimated $10 billion in damage. The root cause? A missing array bounds check—Computer Science 101 error handling that nobody implemented (Trendy Tech Tribe, 2025).

This wasn’t sophisticated. This was basic software craftsmanship that failed at every level of the deployment pipeline.

Three months later, in October 2024 earnings calls, did executives mention this as a wake-up call about software quality? Did they announce new quality initiatives?

No. They continued celebrating AI productivity gains whilst CTOs privately listed technical debt as their #1 concern.

What struck me most about the CrowdStrike incident wasn’t that it happened—any system can have bugs. What struck me was the industry’s reaction: brief panic, followed by… nothing. No industry-wide soul-searching. No renewed focus on basic software quality. Just a continuation of the same practices that led to it.

Twenty years ago, an incident of this magnitude would have triggered genuine introspection. Now? It’s Tuesday.

That normalisation of failure is what long-term perspective reveals. It’s not that we’ve stopped noticing problems—it’s that we’ve stopped being concerned about them.

What This Reveals About Executive Leadership

After 50 years in this industry, I can state with confidence: we are witnessing a systematic failure of executive integrity.

Executives aren’t ignorant. They have the data. They commission the surveys. They attend the conferences where CTOs present their concerns. They know that:

  • 91% of CTOs cite technical debt as the biggest challenge
  • 75% of projects are expected to fail
  • 69% of developers lose significant time to inefficiencies
  • Only 39% of projects meet success criteria
  • The recommended 15–20% investment in technical debt management yields better long-term returns than crisis spending

Yet they choose:

  1. Not to allocate recommended budgets for technical debt management
  2. Not to make quality a strategic priority despite CTOs’ and developers’ concerns
  3. Not to mention these challenges in public communications to shareholders
  4. To celebrate AI productivity gains whilst developers report record inefficiency
  5. To focus on the next hype cycle (AI) rather than address fundamental problems

This isn’t a failure of knowledge. It looks to me like a failure of courage and integrity. A failure of the very concept of leadership.

Why Executives Choose Inaction

The calculus is simple and cynical:

Short-term wins are rewarded. Announcing AI adoption, digital transformation, and cost cutting drives stock prices up. Announcing a 15% budget allocation to technical debt management does not.

The crisis is slow. Technical debt doesn’t cause immediate, visible collapse. It degrades gradually. By the time it causes catastrophic failure, the executive who created it has often moved on. The average tenure of a Fortune 500 CEO is less than 8 years (and median in 2022 was 4.8 years). Why invest in quality improvements that won’t pay dividends until you’re long gone?

Metrics are gamed. Report AI productivity gains whilst ignoring developer efficiency losses. Celebrate revenue growth whilst hiding project failure rates. Show cost optimisation whilst deferring necessary maintenance.

Accountability is absent. No executive has faced consequences for the $1.52 trillion in technical debt. No CEO has been fired for the 75% project failure rate. No board has demanded answers for why only 39% of projects meet success criteria.

Historical memory has faded. Here’s where long-term perspective becomes crucial: many current executives have never worked in an environment where quality was genuinely prioritised. They entered leadership during the “move fast and break things” era. They’ve optimised their entire careers for velocity over sustainability. They literally don’t know what they’re missing. (See also: the Software Crisis – since 1968)

The system rewards those who optimise for optics over outcomes—and increasingly, it’s selecting for leaders who’ve never experienced anything different.

The Cost of This Failure

Whilst executives optimise for quarterly earnings, the real costs accumulate:

Financial: The US alone spends $2.41 trillion annually on poor software quality, with $1.52 trillion in technical debt (Consortium for Information & Software Quality, 2022). By waiting for crisis instead of investing preventively, companies spend double the recommended amount.

Human: 83% of developers experience burnout (Haystack Analytics, 2021). For the first time ever, senior developers report lower job satisfaction than juniors (Stack Overflow, 2024). The industry is haemorrhaging experienced talent—the very people who remember when things were different and might push for change.

Innovation: With 30% of IT budgets consumed by technical debt management and 20% of developer time lost to inefficiencies, there’s little capacity left for actual innovation.

Security: Software supply chain failures increased 650% between 2020 and 2021 (Consortium for Information & Software Quality, 2022). Cybercrime losses continue accelerating. Each shortcut creates new vulnerabilities.

Trust: When executives celebrate productivity gains whilst developers report record inefficiency, when they commission CTO surveys showing 91% cite technical debt as their top concern yet never mention it to shareholders, they erode trust throughout the organisation.

Institutional Knowledge: Perhaps most insidiously, as experienced developers get sick of the eternal indifference and leave, we’re losing the people who remember that it didn’t use to be this way. Each generation of new developers enters an environment slightly worse than the one before, with no reference point for what’s been lost.

The Case for #NoLeadership

Here’s what five decades in this industry has taught me: waiting for executive leadership to fix this crisis is futile. They know what needs to be done. They choose not to do it.

Perhaps it’s time we stop waiting for them.

#NoLeadership isn’t a complaint—it’s a philosophy. It’s the recognition that real change in software quality and productivity won’t come from boardrooms optimising for quarterly earnings. It will come from engineers, developers, and teams who decide to take ownership themselves.

But there’s a challenge here, especially for those without long-term perspective: if you’ve never experienced a development environment where quality was prioritised, how do you know what to fight for? If you entered the industry in the past 5-10 years, you might genuinely believe that constant firefighting, accumulating technical debt, and 75% project failure rates are just “how software works.”

They’re not. And #NoLeadership starts with understanding that the current state isn’t inevitable—it’s a choice we’re collectively making. A choice we can unmake.

Consider what happens when we embrace #NoLeadership:

Teams set their own quality standards. Don’t wait for executives to prioritise quality. Build it into your definition of done. Make technical debt visible on every sprint board. Refuse to call something “done” that you wouldn’t be proud to support.

Engineers allocate their own time. If leadership won’t dedicate 15% of budget to technical debt, developers can dedicate 15% of their sprint capacity. One day per sprint. Non-negotiable. Not asking permission—just doing it.

Quality becomes a team responsibility. Stop escalating quality decisions upward. If your team knows a codebase needs refactoring, refactor it. If tests are missing, write them. If documentation is lacking, create it. Own your craft.

Transparency replaces theatre. Track real metrics: hours lost to technical debt, actual bug rates, time spent on rework, developer satisfaction. Make them visible. Not to shame anyone, but to make the invisible visible.

Peers hold each other accountable. Code reviews become about long-term maintainability, not just immediate functionality. Pull requests that create obvious technical debt get challenged. Not by managers—by peers who know they’ll inherit the mess.

We share stories of how it used to be—and could be again. Those of us with long-term perspective have a responsibility to tell younger developers that the current dysfunction isn’t normal. To share what sustainable software development looks like. To paint a picture of what they’re entitled to demand.

This isn’t anarchism. It’s professionalism. It’s recognising that waiting for executives to prioritise what they’ve demonstrated they won’t prioritise is a losing strategy.

What #NoLeadership Looks Like in Practice

I’ve seen pockets of this emerging organically:

The team that implemented “Tech Debt Tuesdays”—dedicating every Tuesday to addressing technical debt, regardless of what management priorities were set. Their velocity appeared to drop 20%. Their actual productivity—measured in sustainable output and reduced rework—increased significantly.

The engineers who created a “Technical Debt Registry”—documenting every shortcut, every deferred refactoring, every known issue. Made it public within the organisation. No permission asked. Just transparency about what was really happening.

The developer who started tracking “Time to Real Done”—measuring not when a feature shipped, but when it was actually stable, tested, documented, and maintainable. Shared the data widely. Made it impossible to ignore the gap between “shipped” and “done.”

The teams adopting “Two-Track Development”—running parallel tracks for new features and quality improvement. Not asking whether they could dedicate time to quality. Just doing it as part of their professional responsibility.

The teams embracing the Antimatter Principle—attending to folks’ needs as a matter of course.

The senior developers who mentor juniors on what sustainable development looks like—not by lamenting “the old days,” but by teaching practices and standards that newer developers never learned because they entered an industry already in crisis.

These aren’t acts of rebellion. They’re acts of practitioners’ integrity. They’re what happens when craftspeople decide that waiting for permission to do good work is itself unprofessional.

And critically, they’re how we preserve and transmit knowledge of what sustainable software development looks like—creating reference points for those who’ve never experienced it.

The Limits and Risks

Let me be clear: #NoLeadership isn’t a panacea, and it comes with real constraints.

You can’t allocate budget you don’t control. Teams can manage their own time, but they can’t approve capital expenditure for infrastructure improvements or hire additional staff.

You may face consequences. Some organisations will punish teams who prioritise quality over velocity metrics, even when that quality improves long-term outcomes. Career risks are real.

Coordination remains necessary. #NoLeadership works for team-level quality decisions. System-wide architectural changes still require coordination that often needs executive sponsorship.

Not everyone will join you. Some teams will continue optimising for the metrics management rewards. You may end up maintaining higher quality in isolation whilst surrounded by deteriorating systems.

Without historical context, it’s hard to know what’s worth fighting for. If you’ve never seen sustainable development practices in action, how do you know which battles matter? This is where mentorship and knowledge sharing become crucial.

These limitations matter. #NoLeadership can’t replace executive action—it can only compensate for executive inaction within the sphere teams actually control.

But here’s what it can do: it can prevent your team’s work from contributing to the crisis. It can create islands of quality in seas of technical debt. It can demonstrate that another way is possible. And it can preserve your own professional integrity whilst the industry around you optimises for quarterly earnings.

Most importantly, it can create reference points. When a junior developer experiences your team’s practices—where quality matters, where technical debt is managed, where 75% failure isn’t expected—they learn what’s possible. They gain perspective that might take decades to acquire otherwise. They become carriers of institutional knowledge about what sustainable software development looks like.

That’s how cultures change: one team at a time, creating examples that others can point to and say, “That’s what we might be doing.”

A Challenge to the Industry

To executives reading this: the data is unambiguous. You know what needs to be done. The question is whether you’ll do it, or whether your teams will be forced to work around your inaction.

To CTOs and technology leaders: if 91% of you cite technical debt as your biggest challenge, why doesn’t it appear in executive priorities? Stop keeping your concerns private. Make them public. Make them impossible to ignore. Risk it.

To senior developers and engineers with long-term perspective: You have a special responsibility. Share your experience. Mentor those who’ve never known anything but crisis mode. Paint a picture of what sustainable development looks like. Your historical perspective is valuable—use it to help others understand that the current state isn’t inevitable.

To developers and engineers: you don’t need permission to do good work. You need the courage to prioritise it even when incentives push you toward shortcuts. #NoLeadership a.k.a. #Fellowship means taking ownership of quality within your sphere of control.

To those new to the industry: If you’ve entered software development in the past 5-10 years, I invite you to consider something crucial: the environment you’re in—the constant firefighting, the technical debt, the 75% failure rates—this isn’t “just how software development works.” It’s how software development has deteriorated. Seek out the older developers, the ones who’ve been doing this for decades. Ask them how things used to be. Learn what you’re entitled to demand.

To teams: you can start today. Dedicate 15% of your sprint to quality. Make technical debt visible. Track real metrics. Hold each other accountable. Don’t wait for executive prioritisation that isn’t coming.

The Path Forward

After 50 years, I’ve learned this: sustainable software quality requires both executive commitment AND professional autonomy. Ideally, we’d have both.

But if we must choose between waiting for executive action that isn’t coming and taking professional responsibility for the work we control, I choose the latter.

#NoLeadership is about recognising when waiting for executive direction means accepting executive dysfunction. It’s about developer communities deciding that their craft matters more than their executives’ quarterly earnings optimisation.

The data shows executives know what needs to be done. They choose not to do it. Perhaps it’s time we stop waiting for them to change their minds and start changing what we can control.

Every sprint in which you dedicate time to quality is a choice. Every pull request you review for maintainability is a choice. Every piece of technical debt you document is a choice. Every standard you refuse to compromise is a choice. Every story you share about how development used to be—and could be again—is a choice.

Make better choices. Don’t wait for permission.

The industry won’t be fixed by executive leadership that’s demonstrated it won’t lead on quality. It will be fixed by teams who decide that professional integrity matters more than executive approval. By experienced developers who share their perspective with those who’ve never known anything different. By practitioners who refuse to accept that the current dysfunction is inevitable.

That’s #NoLeadership. Not a lament—a commitment to integrity.

And for those of us with long-term perspective, it’s also a responsibility: to notice the trends others can’t see, to remember what’s been lost, and to fight to restore what made this profession worth pursuing in the first place.


Are you practising #NoLeadership in your work? What quality standards have you set for yourself regardless of executive priorities? And if you’ve been in the industry long enough to see the trends—what changes have you noticed? Share your experiences in the comments.

Further Reading

Ali, J. (2024, June 4). 268% higher failure rates for Agile software projects, study finds. Engprax. https://www.engprax.com/post/268-higher-failure-rates-for-agile-software-projects-study-finds/

Atlassian. (2024, July 15). New Atlassian research on developer experience highlights a major disconnect between developers and leaders. Work Life by Atlassian. https://www.atlassian.com/blog/developer/developer-experience-report-2024

Beta Breakers. (2024). Software survival in 2024: 2023 statistics and quality assurance. https://www.betabreakers.com/blog/software-survival-in-2024-understanding-2023-project-failure-statistics-and-the-role-of-quality-assurance/

Clouded Judgement. (2024, November 1). Amazon, Google, Microsoft & Meta on AI and CapEx. https://cloudedjudgement.substack.com/p/clouded-judgement-11124-amazon-google

Consortium for Information & Software Quality. (2022, December 6). Software quality issues in the U.S. cost an estimated $2.41 trillion in 2022. Synopsys News. https://news.synopsys.com/2022-12-06-Software-Quality-Issues-in-the-U-S-Cost-an-Estimated-2-41-Trillion-in-2022

Cortex. (2024). The 2024 state of developer productivity. https://www.cortex.io/report/the-2024-state-of-developer-productivity

Deloitte. (2024). Tech trends 2024: Core workout—From technical debt to technical wellness. Deloitte Insights. https://www.deloitte.com/us/en/insights/topics/technology-management/tech-trends/2024/tech-trends-core-it-modernization-needed-for-tech-wellness.html

Evanta. (2024). Top 3 priorities for CIOs in 2024: 2024 Leadership Perspective Survey. https://www.evanta.com/resources/cio/survey-report/top-3-priorities-for-cios-in-2024

Haystack Analytics. (2021, July 12). 83% of developers suffer from burnout, Haystack Analytics study finds. https://www.usehaystack.io/blog/83-of-developers-suffer-from-burnout-haystack-analytics-study-finds

InfoWorld. (2024, July 15). Developer productivity poorly understood, report says. https://www.infoworld.com/article/2520803/developer-productivity-poorly-understood-report-says.html

McKinsey & Company. (2023, April 25). Breaking technical debt’s vicious cycle to modernize your business. McKinsey Digital. https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/breaking-technical-debts-vicious-cycle-to-modernize-your-business

Microsoft. (2023, October 25). Microsoft fiscal year 2024 first quarter earnings conference call. Microsoft Investor Relations. https://www.microsoft.com/en-us/investor/events/fy-2024/earnings-fy-2024-q1

Oliver Wyman. (2024, July). 5 actions to reduce technical debt in businesses. https://www.oliverwyman.com/our-expertise/insights/2024/jul/reducing-technical-debt.html

Protiviti. (2024). Technical debt remains a major burden. https://www.protiviti.com/us-en/global-technology-executive-survey-tech-debt-major-burden

ReadyWorks. (2023). 2023 CIO priorities: Overcoming challenges and making progress. https://www.readyworks.com/blog/2023-cio-priorities-overcoming-challenges-and-making-progress

Stack Overflow. (2024). Professional developers: 2024 Stack Overflow Developer Survey. https://survey.stackoverflow.co/2024/professional-developers

STX Next. (2023, November 14). STX Next report highlights the challenge of technical debt. Technology Magazine. https://technologymagazine.com/articles/stx-next-report-highlights-the-challenge-of-technical-debt

Techotlist. (2024). Tech burnout 2025: Digital overload. https://techotlist.com/blogs/programming-languages-and-development-trends/tech-burnout-2025-digital-overload

Trendy Tech Tribe. (2025, December 15). Why software is getting worse: The 2025 quality crisis. https://trendytechtribe.com/tech/software-quality-crisis-2025

People are NOT our greatest asset; it’s the relationships BETWEEN people that is the greatest asset

We’ve all heard it countless times. It’s printed on office walls, declared in annual reports, and repeated in town halls: ‘Our people are our greatest asset.’ It’s meant to be inspiring, a testament to an organisation’s commitment to its workforce. But this well-intentioned phrase is fundamentally missing the point.

The truth is otherwise – and more much powerful: People are NOT our greatest asset; it’s the relationships BETWEEN people that is the greatest asset.

The Limitations of Individual Talent

Let’s be clear: talented individuals matter hardly a jot. Skills, expertise, creativity, and dedication all come a distant second to relationships. Here’s the uncomfortable reality: you can assemble a room full of the most brilliant, capable people in your industry and still end up with a dysfunctional organisation that fails to deliver results.

We’ve all seen it. The team of stars that never quite gels. The merger of two successful companies that somehow produces mediocrity. The leadership team full of impressive résumés that can’t seem to make a decision. Individual excellence, in isolation, guarantees nothing.

Why? Because organisations don’t function through the sum of individual capabilities. They function through the quality of connections, interactions, and collaborative exchanges between people.

From Vague Platitudes to Clear Action

Here’s where the shift from the clueless platitude of ‘people are our greatest asset’ to ‘relationships are our greatest asset’ becomes transformative: it changes everything about what you actually do.

When organisations declare they’re investing in people, what does that mean in practice? Better salaries? More training courses? Improved benefits? Free fruit in the kitchen? These aren’t bad things, but they’re scattergun approaches that hope something sticks. The focus remains frustratingly vague, and leaders are left wondering: ‘Are we doing enough? Are we doing the right things? Why is the needle not moving?’

In contrast, when you recognise that relationships are your greatest asset, the path forward becomes remarkably clear. Suddenly, you have specific, observable, measurable phenomena to work with. You can ask concrete questions: Who talks to whom? Where do silos exist? Which teams collaborate effectively and which don’t? Who are the connectors? Where are the bottlenecks? Who’s isolated? Which cross-functional relationships are missing?

Focus on people confuses action because:

  • Individual development is endless and unbound—there’s always another skill to learn, another qualification to pursue, another workshop to attend
  • It’s difficult to know when you’ve invested ‘enough’ in any given person
  • The return on investment is opaque—did that training course actually improve anything?
  • It can inadvertently promote individualism and internal competition rather than collaboration
  • It defaults to generic solutions (send everyone on the same leadership course) that ignore context

Focus on relationships clarifies action because:

  • You can map the current state—literally draw it out and see where connections are strong or weak
  • You can identify specific gaps—’Marketing and product development never speak’ is actionable; ‘we need better people’ is not
  • You can design targeted interventions—’Let’s create a weekly cross-functional stand-up’ beats ‘let’s improve communication skills’
  • You can measure change—relationship density, collaboration patterns, and information flow are all observable
  • You can see immediate impact—when two previously siloed teams start working together, results follow quickly

Consider the difference in leadership conversations:

People-focused approach: ‘We need to invest in our people. Let’s increase the training budget and improve our benefits package.’

Relationship-focused approach: ‘Our network analysis shows that the engineering team is completely disconnected from customer support. No wonder our products miss the mark. Let’s create a monthly session where support shares customer insights directly with engineering, and let’s pair each engineer with a support person for a day each quarter.’

The first is well-meaning but vague. The second is specific, actionable, and directly addresses a visible problem in the organisation’s relationship infrastructure.

This clarity extends to every level. Want to improve innovation? Don’t just ‘invest in creative people’—look at whether people from different disciplines actually interact. Want to speed up decision-making? Don’t just ’empower people’—examine whether decision-makers have strong relationships with those who have the information they need. Want to improve employee retention? Don’t just ‘value people’—investigate whether individuals have meaningful connections with colleagues or feel isolated.

The beauty of focusing on relationships is that it makes the invisible visible. You’re no longer operating on faith that your ‘investment in people’ will somehow pay dividends. You’re working with the actual architecture of how your organisation functions—and you can see, adjust, and improve it in real time.

What Makes Relationships the Real Asset

When we shift our focus from people to the relationships between them, everything changes. Here’s what organisational relationships actually create:

Trust and psychological safety. Relationships built on trust allow people to take risks, admit mistakes, ask for help, and challenge ideas without fear. This is where innovation happens. A brilliant individual who doesn’t trust their colleagues will hoard information and play it safe. That same person, embedded in trusting relationships, becomes exponentially more valuable.

Knowledge flow and collective intelligence. The most valuable knowledge in any organisation isn’t stored in individual heads—it’s created in the spaces between them. When an engineer talks to a customer service representative, when a junior employee questions a senior leader, when cross-functional teams actually collaborate rather than just coordinate, new insights emerge that no individual could have generated alone.

Resilience and adaptability. Strong relationship networks create organisational resilience. When someone leaves, strong relationships mean their knowledge and connections aren’t lost entirely. When crises hit, it’s the strength of relationships that determines whether teams pull together or fall apart. You can’t download resilience from a talented individual’s brain—it exists in the fabric of how people relate to each other.

Speed and efficiency. Consider two scenarios: In one, you need information from another department and must navigate formal channels, wait for responses, and overcome territorial barriers. In another, you can call someone you’ve built a relationship with and get what you need in a five-minute conversation. Strong relationships are the organisation’s nervous system, allowing information and decisions to flow at the speed of trust rather than the speed of bureaucracy.

Meaning and engagement. People don’t just work for salaries or even for purpose statements on walls. They stay and give their best work when they’re part of something larger than themselves—when they feel connected to others in meaningful ways. Relationships are what transform a workplace from a collection of individuals into a community.

The Practical Implications

If relationships are truly our greatest asset, how should this change what organisations do?

Design for connection, not just individual productivity. Stop optimising exclusively for individual efficiency. Steve Jobs understood this when he designed Pixar’s headquarters in the late 1990s. Rather than separating animators, computer scientists, and executives into different buildings, he brought everyone under one roof with a massive atrium at its centre. He deliberately placed the post boxes, cafeteria, meeting rooms, and even the toilets in the central atrium, forcing people to leave their offices and cross paths with colleagues they might not otherwise encounter. As Brad Bird, director of The Incredibles and Ratatouille, observed: ‘The atrium initially might seem like a waste of space…But Steve realised that when people run into each other, when they make eye contact, things happen.’ John Lasseter, Pixar’s chief creative officer, confirmed the impact: ‘Steve’s theory worked from day one…I’ve never seen a building that promoted collaboration and creativity as well as this one.’

Consider: Does your office layout foster serendipitous encounters or isolate people? Do your meeting structures allow for relationship-building or just agenda items? Does your remote work policy account for the relationship-building that happens in informal moments?

Measure what matters. We measure individual performance obsessively. But when was the last time your organisation assessed the quality of relationships across teams? Network analysis can reveal who’s connected, who’s isolated, and where silos exist.

Companies like Four Groups have pioneered methods to make this practical and actionable. Their 4G approach helps organisations understand and predict how relationships and culture impact performance, moving beyond simple org charts to visualize actual working relationships through tools like their Visual Team Builder. Crucially, they’ve demonstrated how to quantify relationship quality and link it directly to financial metrics and KPIs—transforming what was once seen as a “soft” intangible into measurable business intelligence. When a UK-based organisation can predict how a proposed reorganisation will impact collaboration patterns before implementing it, or identify which relationship breakdowns are costing them in delivery delays, relationships shift from being merely important to being strategically manageable.

Employee engagement surveys might ask not just ‘do you feel valued?’ but ‘do you have strong working relationships with colleagues across the organisation?’ (See also: Gallup’s book ‘First Break All The Rules‘).

Invest in relationship infrastructure. Training programmes shouldn’t focus solely on building individual skills. Invest in cohort-based learning that builds cross-functional relationships. Create mechanisms for people to collaborate across boundaries—innovation labs, rotation programmes, cross-functional projects with real stakes. Budget time and resources for team-building that actually builds relationships, not just awkward icebreakers.

Hire and promote for relational capacity. Yes, skills and experience matter. But also evaluate: Can this person build trust? Do they create bridges or walls? Are they generous with knowledge and credit? Can they navigate disagreement constructively? Patrick Lencioni identifies three essential virtues that make someone an ideal team player: they must be humble (putting the team above themselves), hungry (self-motivated and driven to contribute), and people smart (emotionally intelligent in their interactions with others). Individuals who possess all three virtues don’t just perform well—they elevate the performance of everyone around them through the quality of relationships they build. The most talented individual who damages relationships is ultimately a serious net negative to the organisation.

Protect relationships during transitions. Reorganisations, redundancies, and rapid growth all strain relationship networks. Before making major changes, map the critical relationships that make work flow. Ask: How will this change impact collaboration patterns? What relationships are at risk? How can we preserve and rebuild connection?

Give relationships time. Trust and strong working relationships can’t be rushed. Be wary of constant reorganisations, aggressive hiring sprees without proper integration, or cultures that celebrate constant churn. Relationship capital takes time to build and can be destroyed quickly.

The Paradox at the Heart of Organisations

Here’s the beautiful paradox: when you focus on relationships rather than just individuals, people actually become more valuable. Not because they’ve changed, but because they’re now embedded in a network that amplifies their capabilities, compensates for their weaknesses, and multiplies their impact.

A talented designer in isolation is somewhat valuable. That same designer, with strong relationships with engineers who understand her vision, product managers who seek her input early, and junior designers she mentors—that designer’s impact extends far beyond what she could create alone. This is where Lencioni’s virtues of being humble, hungry, and people smart become force multipliers: humility allows for genuine collaboration without ego barriers, hunger drives the relationship-building effort required to make things happen, and being people smart ensures those connections are productive rather than destructive.

The organisation that declares ‘our people are our greatest asset’ is making a promise to invest in individuals. That’s good, but flawed. The organisation that recognises relationships as its greatest asset makes a different commitment: to cultivate the conditions where people can connect, collaborate, and create value together in ways that transcend and far exceed individual contribution.

Moving Forward

The next time you’re tempted to simply parrot ‘our people are our greatest asset’, pause and go deeper. Ask yourself: Are we actually creating an environment where relationships can flourish? Are we measuring, protecting, and investing in the connective tissue that makes this organisation more than a collection of talented individuals?

Because at the end of the day, individual talent can walk out the door. But strong organisational relationships—the patterns of trust, collaboration, and collective capability that exist between people—that’s what’s truly irreplaceable. That’s the asset worth protecting and developing above all others.

Attending to people and their needs is undoubtedly important. But it’s what happens between people that makes the real difference.


Further Reading

Baker, W. E. (2000). Achieving success through social capital: Tapping the hidden resources in your personal and business networks. Jossey-Bass.

Coyle, D. (2018). The culture code: The secrets of highly successful groups. Bantam Books.

Cross, R. L., & Parker, A. (2004). The hidden power of social networks: Understanding how work really gets done in organizations. Harvard Business School Press.

Isaacson, W. (2011). Steve Jobs. Simon & Schuster.

Lencioni, P. M. (2002). The five dysfunctions of a team: A leadership fable. Jossey-Bass.

Lencioni, P. M. (2016). The ideal team player: How to recognize and cultivate the three essential virtues. Jossey-Bass.

Putnam, R. D. (2000). Bowling alone: The collapse and revival of American community. Simon & Schuster.

‘Head of Software’ is the Most Ridiculous Job Title in Tech

‘The way you get programmer productivity is not by increasing the lines of code per programmer per day. That doesn’t work. The way you get programmer productivity is by eliminating lines of code you have to write. The line of code that’s the fastest to write, that never breaks, that doesn’t need maintenance, is the line you never had to write.’

~ Steve Jobs

Steve Jobs understood something that most tech companies today have never grasped: software isn’t the solution—it’s the problem we’re trying to avoid.

So why are we hiring people whose entire job is to create more of it?

The Fundamental Absurdity

Appointing a ‘Head of Software’ is like hiring a ‘Chief of Pollution’ or ‘VP of Bureaucracy’. You’ve just put someone in charge of expanding the very thing you’re trying to minimise.

Every line of code is technical debt waiting to happen. Every feature is a maintenance burden. Every interface is a potential point of failure. The most productive thing any programmer can do is attend to folks’ needs whilst writing less code, not more.

Yet here we are, creating management positions dedicated to producing more software. It’s organisational insanity.

Who Actually Needs Less Code?

Here’s where it gets interesting. Almost everyone in your organisation benefits from less code:

Users don’t care about code at all—they want their problems solved simply and reliably. Every additional line of code is a potential source of bugs, slowdowns, and confusing interfaces.

Future developers (including your current team six months from now) need less code because they’re the ones who have to understand, debug, and modify what gets written today.

Operations teams need less code because simpler systems break less often and are easier to troubleshoot at 3 AM.

Support teams need less code because fewer features means fewer ways for users to get confused or encounter problems.

Finance teams need less code because maintenance costs scale directly with codebase size.

Security teams need less code because every line of code represents potential attack surface.

Management needs less code because simpler systems deliver faster, cost less to change, and are easier to understand and plan around.

Executives need less code because it means lower operational costs, faster competitive response, and fewer technical risks that could derail business objectives.

So who actually wants more code? Primarily the people whose careers depend on managing complexity: consultants who bill by the hour, developers who equate job security with irreplaceable knowledge of arcane systems, and—you guessed it—Heads of Software whose organisational importance scales with the size of their technical empire.

The incentive misalignment becomes crystal clear when you realise that almost everyone in the company benefits from less software except the person you’ve put in charge of it.

What the #NoSoftware Movement Gets Right

The smartest companies are embracing what Seddon (2019) calls ‘software last’—the radical idea that maybe, just maybe, we try solving problems without software first.

Post-it notes don’t have bugs. Paper processes don’t need security patches. Manual workflows don’t crash at 3 AM. When you implement a #NoSoftware solution, you get:

  • Immediate deployment (no months of development)
  • Zero maintenance costs (no code to update)
  • Perfect flexibility (change the process instantly)
  • No technical debt (because there’s no tech)

But if your organisation has a ‘Head of Software’, this person’s career incentives are most likely completely misaligned with these benefits. Their success is measured by building more software, not by eliminating the need for it.

The Perverse Incentives Problem

A ‘Head of Software’ faces a career-ending dilemma: if they’re truly successful at their job, they work themselves out of a job.

Think about it:

  • Their budget depends on having software to manage
  • Their team size depends on code that needs maintaining
  • Their importance depends on systems that require oversight
  • Their promotion prospects depend on shipping new features

Every line of code they don’t write threatens their organisational relevance. Every problem they solve without software makes their department smaller. Every process they streamline through manual methods reduces their empire.

This creates the most backwards incentive structure imaginable. Invitation: reward the person who eliminates software, not he or she who maximises it.

A Different Approach

The problem isn’t just the titles—it’s also the incentives.

Any technology leader, regardless of their title, can be measured by outcomes that matter: needs met, customer satisfaction, business agility, time-to-market, operational efficiency. Not by lines of code shipped or systems deployed.

The best CTOs and VPs of Engineering already understand this. They’re constantly asking ‘do we really need to build this?’ and ‘what’s the simplest solution?’ They default to buying instead of building, to manual processes instead of automation, to elimination instead of addition.

The Real Problem: We’re Solving for the Wrong Thing

Successful businesses do best when they focus on attending to folks’ needs. Not technology needs. Not organisational needs. Not even business needs in the abstract—but the actual needs of real people.

When you create a ‘Head of Software’ role, you’re explicitly organising around technology instead of around folks. You’re saying that software is important enough to deserve dedicated leadership, whilst the people who use that software get… what? A ‘Head of Customer Success’ buried three levels down in the org chart?

This backwards prioritisation shows up everywhere:

  • Product roadmaps driven by technical capabilities rather than user problems
  • Success metrics based on system performance rather than user outcomes
  • Resource allocation favouring engineering elegance over customer value
  • Decision-making that asks ‘can we build this?’ before asking whether we have a customer problem worth solving

The most successful companies flip this entirely. They organise around customer needs and treat technology as a servant, not a master.

The Hidden Costs of Technology-First Thinking

When you organise around a ‘Head of Software’, you’re committing to a worldview where every problem looks like a coding opportunity:

  • New process needed? Build an app.
  • Communication breakdown? Create a dashboard.
  • Data scattered? Write integration scripts.
  • Users confused? Add more features.

This technology-first thinking ignores what folks actually need and the true costs:

  • Development time (months before you can even test the idea)
  • Maintenance burden (forever ongoing costs)
  • Complexity debt (every feature makes the next one harder)
  • Opportunity costs (whilst you’re coding, competitors are executing)

The Post-it Note Test

Here’s a simple test for any ‘Head of Software’ candidate: ask them to solve their three most recent workplace problems using only Post-it notes, conversations, and manual steps.

If they can’t even conceive of non-software solutions, they’re exactly the wrong person for the job. You’re hiring someone whose only tool is a hammer in a world full of problems that aren’t nails.

What Steve Jobs Would Do

Jobs didn’t revolutionise technology by hiring software heads—he revolutionised it by eliminating software complexity. The original iPhone succeeded because it made smartphones feel simple, not because it had more features than competitors.

If Jobs were running your company, he’d probably fire the ‘Head of Software’ and replace them with someone whose job was to remove features, simplify workflows, and make technology invisible.

The #NoSoftware Career Path

Instead of promoting people for building systems, consider promoting them for eliminating systems:

  • Junior Process Designer: Makes workflows efficient without code
  • Senior Simplification Specialist: Removes unnecessary software from existing processes
  • VP of Manual Excellence: Proves complex processes can work with simple tools
  • Chief Elimination Officer: Responsible for company-wide software reduction

Watch how this changes everything. Suddenly your best people are incentivised to solve problems the fastest, cheapest, most flexible way possible—which is almost never more software.

The Bottom Line

Every successful ‘Head of Software’ will eventually eliminate their own position. If they’re doing their job right, they make software so unnecessary that the company doesn’t need someone to manage it.

But that will never happen as long as we reward people for creating software instead of eliminating it.

The next time someone suggests hiring a ‘Head of Software’, ask them this: ‘What’s the #NoSoftware solution we’re trying first?’

If they don’t have an answer, you’ve found your real problem.


The most productive programmer is the one who writes no code. The most valuable software leader is the one who makes software unnecessary. And the smartest companies are the ones brave enough to commit to #NoSoftware.

Further Reading

Seddon, J. (2019). Beyond command and control. Vanguard Consulting.

The Thinking Game vs The Doing Game

Why Smart People Choose Ideas Over Action

There’s something seductive about living in the world of ideas. For many intelligent people, thinking isn’t a prelude to action—it’s the main event. They’re not paralysed by analysis; they’re genuinely more comfortable, more stimulated, and more at home in the realm of concepts than in the messy world of implementation.

And honestly? There are reasons for this preference.

The Appeal of Pure Thought

Thinking feels productive without the risk. When you’re exploring an idea, researching a concept, or working through a theoretical problem, you get all the satisfaction of intellectual engagement with none of the vulnerability of putting something real into the world. Every insight feels like progress, every connection between concepts feels like achievement.

The world of ideas is controllable. In your head, or in discussion with other smart people, ideas can be elegant, complete, and perfect. You’re operating in a domain where you’re competent, where the rules make sense, where intelligence directly translates to results.

It’s immediately rewarding. Encountering something new, having an insight, or engaging in stimulating intellectual discussion provides instant gratification. Action, by contrast, often involves long periods of grinding through mundane details before you see any payoff.

The Comfort of Competence

Many intelligent people grew up being rewarded for thinking well. School, university, academic careers, many corporate environments—they all signal that understanding concepts, analysing problems, and demonstrating intellectual sophistication are the most valuable skills.

So it’s natural that people gravitate towards what they’re good at and what gets them recognition. If you’ve spent twenty years being praised for your ability to think through complex problems, why wouldn’t you prefer that to the uncertain world of execution?

In the thinking realm, smart people are undeniably smart. They can engage with complex ideas, see patterns others miss, and make sophisticated connections. In the doing realm, intelligence helps, but it’s often secondary to persistence, practical skills, building interpersonal relationships, market timing, or just plain luck.

In the world of pure ideas, social skills, networking ability, and relationship-building don’t matter much – but in the real world of execution, your ability to work with others, persuade people, and navigate interpersonal dynamics often matters much more than raw intellectual horsepower.

The Crucible of Reality

There’s another comfort in thinking that’s harder to admit: as long as your idea stays in your head, it remains perfect. The brilliant business concept, the novel you’ll write, the app that would change everything—they’re all flawless until you actually try to build them.

Implementation means subjecting your ideas to the crucible of reality—and reality is an unforgiving judge. It doesn’t care how elegant your theory is or how many edge cases you’ve considered. It only cares whether your solution actually works when real people use it in real situations with real constraints.

The crucible of reality reveals gaps between your assumptions and truth, between your models and actual behaviour, between what should work and what does work. It means discovering that your elegant solution has seventeen unexpected complications. It means producing something that’s embarrassingly far from the perfection you imagined.

Many smart people intuitively understand this, and they’re not necessarily wrong to be hesitant. In the world of pure thought, you’re never wrong in ways that matter. In the crucible of reality, you’re wrong constantly—and publicly.

The Execution Gap: Even Business Recognises This

The preference for thinking over doing isn’t just an individual quirk—it’s such a pervasive pattern that business literature has extensively documented it. Larry Bossidy and Ram Charan’s seminal book Execution: The Discipline of Getting Things Done (2002) was written precisely because they observed brilliant strategists and intellectually gifted leaders consistently failing at implementation.

Their core insight? Execution isn’t just applied thinking—it’s a fundamentally different discipline requiring different skills, different mindsets, and different types of intelligence. Most organisational failures aren’t due to bad strategy but to the massive gap between what gets planned in boardrooms and what actually gets delivered in the real world.

And here’s the uncomfortable truth: implementation is hard, hard, hard. It’s not just different from thinking—it’s genuinely more difficult in ways that pure intellectual work rarely prepares you for. Implementation means dealing with broken systems, uncooperative people, unexpected technical constraints, shifting requirements, budget limitations, and a thousand tiny decisions that no amount of upfront planning can anticipate.

Where thinking rewards you for considering all possibilities, implementation punishes you for not choosing one path and sticking with it through inevitable setbacks. Where thinking values elegant solutions, implementation forces you to accept clunky workarounds that actually function. Where thinking celebrates sophistication, implementation demands brutal simplification.

As Saint-Exupéry wrote, ‘Perfection is achieved, not when there is nothing more to add, but when there is nothing left to take away’ (1939). Implementation forces this kind of perfection—the perfection of ruthless elimination. But for minds that find beauty in complexity and sophistication, this gets rehected as dumbing down rather than improving.

Execution feels like playing by different rules entirely.

The book validates what smart people rarely intuit (not so smart, then): strategic thinking and execution operate by different rules. In strategy sessions, the person with the most sophisticated analysis wins. In execution, success goes to whoever can navigate complex human dynamics, persist through mundane details, build coalitions amongst stakeholders with conflicting interests, and adapt when reality inevitably differs from the plan.

Bossidy and Charan found that many leaders treated execution as something beneath their intellectual pay grade—a ‘just make it happen’ afterthought to the real work of strategic thinking. But execution, they argued, actually requires more complex judgement calls, more nuanced people skills, and more tolerance for ambiguity than pure strategy work.

No wonder intelligent people gravitate towards the thinking realm. It’s not just more comfortable—the business world itself has yet to acknowledge that execution is a different game entirely.

The Social Rewards of Sophistication

In many intellectual communities, the person who can reference the most research, identify the most nuanced considerations, or explain the most complex frameworks gets social status. Depth of knowledge and sophistication of thinking are currency.

Actually shipping something? That’s often seen as crude, commercial, or anti-intellectual. The person who says ‘I’ve been thinking about this problem for years’ gets more respect than the person who says ‘I built something that partially solves this problem.’

This creates environments where thinking is not just more comfortable—it’s actively more rewarded than doing.

The 85/15 Reality

So how much time do smart people actually spend thinking versus doing? For many, it’s genuinely about 85% thinking, 15% doing—and they prefer it that way.

This isn’t necessarily wrong. The world needs people who think deeply, who explore ideas thoroughly, who can see implications and connections that others miss. Pure researchers, theorists, and analysts provide enormous value.

But it’s worth being honest about what you’re optimising for.

Two Different Games

The Thinking Game rewards depth, sophistication, and intellectual rigour. Success means understanding more, seeing further, and thinking more clearly than others. The goal is insight, elegance, and ‘truth’.

The Doing Game rewards results, persistence, and practical problem-solving. Success means creating things that work, solving real problems, and producing value for others. The goal is impact, utility, and change.

Both games are valid. Both are valuable. But they require different mindsets, different skills, and different comfort zones.

The Honest Question

The real question isn’t ‘How can I think less and do more?’ It’s ‘Which game do I actually want to play?’

If you genuinely prefer the thinking game—if you find more satisfaction in understanding complex systems than in building simple solutions—then lean into that. Become the person who helps others think more clearly about problems. Embrace being the researcher, the adviser, the person who sees what others miss.

But be honest about the choice. Don’t pretend you’re preparing to do when you’re actually choosing to think. Don’t frame your preference for ideas as ‘not being ready yet’ to act.

The Hybrid Approach

Some people find ways to bridge both worlds. They use thinking as a tool for better doing, or they find ways to make their thinking actionable. They might:

  • Write to share their insights
  • Teach to help others implement better solutions
  • Consult to apply their analytical skills to real problems
  • Build tools that help other people think more clearly

The key is recognising that thinking and doing aren’t necessarily sequential—they can be integrated in ways that honour both preferences.

Embracing Your Preference

There’s nothing wrong with preferring the comfort of thinking. The world needs people who go deep, who consider implications, who think through complex problems before others rush to solutions.

But own that preference. Be honest about what energises you, what you’re genuinely drawn to, and what kind of contribution you want to make.

Because the real problem isn’t smart people who think too much—it’s smart people who aren’t honest with themselves about what they actually want to do with their intelligence.


Postscript: I’d much prefer to be doing Organisational Ai Therapy than thinking and writing about it. But until I luck in to that…


Further Reading

Bossidy, L., & Charan, R. (2002). Execution: The discipline of getting things done. Crown Business.

Heath, C., & Heath, D. (2007). Made to stick: Why some ideas survive and others die. Random House.

Kahneman, D. (2011). Thinking, fast and slow. Farrar, Straus and Giroux.

Klayman, J., & Ha, Y. W. (1987). Confirmation, disconfirmation, and information in hypothesis testing. Psychological Review, 94(2), 211-228.

Pfeffer, J., & Sutton, R. I. (2000). The knowing-doing gap: How smart companies turn knowledge into action. Harvard Business Review Press.

Saint-Exupéry, A. de. (1939). Wind, sand and stars. Reynal & Hitchcock.

Tetlock, P. E., & Gardner, D. (2015). Superforecasting: The art and science of prediction. Crown Publishers.

Wu Wei: The Art of Effortless Progress

A follow-up to ‘Swimming Against the Tide

In ‘Swimming Against the Tide’, I long ago painted a picture of organisations perpetually swimming against the current—expending enormous energy just to maintain position, let alone make meaningful progress upstream toward greater effectiveness. This metaphor captured something essential about the modern business experience: the exhausting sense that we’re always fighting against forces beyond our control.

But what if there’s another way?

The Old Man and the Maelstrom

The ancient Chinese philosopher Zhuangzi tells a story that perfectly illustrates another way of thinking about our river of change.

An old man deliberately plunged into a massive waterfall and whirlpool—a maelstrom so violent that even strong swimmers would be dashed against the rocks. Onlookers were horrified, certain they were witnessing a suicide. But to their amazement, the old man emerged safely downstream, walking calmly along the bank.

When asked how he survived what should have been certain death, the old man explained: ‘I followed the way of the water. When it went down, I went down. When it swirled, I swirled with it. I didn’t fight against it or try to impose my own direction. I became one with the water, and it carried me safely through.’

This is Wu Wei (無為)—often translated as ‘non-action’ or ‘effortless action.’ It doesn’t mean doing nothing. Rather, it means working with natural forces rather than against them, finding the path of least resistance that still leads where you want to go.

Reimagining the River

Let’s return to our flowing river metaphor, but with fresh eyes. What if, instead of seeing the current as something to battle against, we saw it as information—a signal about where natural forces want to take us?

The river isn’t uniformly flowing downstream. There are eddies, cross-currents, and backflows that a skilled navigator can use. There are places where the current actually runs toward our goal—greater effectiveness, and the art lies in recognising and positioning ourselves to benefit from these swirls.

Consider how market forces, technological changes, and social shifts aren’t just obstacles to overcome—they’re also opportunities to make progress toward our goals. The organisation that learns to read these currents, rather than simply resist them, might find itself making progress, with a fraction of the effort.

The Paradox of Effortless Effort

This doesn’t mean abandoning all ambition or effort. Wu Wei isn’t passive; it’s intelligently responsive. It’s the difference between:

  • Forcing solutions versus finding elegant solutions
  • Fighting change versus flowing with beneficial change whilst guiding direction
  • Exhausting resistance versus strategic positioning
  • Rigid planning versus adaptive responsiveness

The organisation practising Wu Wei still has clear intentions and goals. But it achieves them by working with the grain of reality rather than against it. It looks for the natural leverage points, the places where small actions create large effects.

The Organisational Maelstrom

Like the old man in Zhuangzi’s story, organisations often find themselves caught in powerful forces that seem chaotic and dangerous. Market disruption, technological change, regulatory shifts, talent wars—these can feel like being swept into a maelstrom.

The instinctive response is to fight, to swim against the current with all our strength. But what if we could learn from the old man’s wisdom?

Instead of forcing cultural change, observe where positive change is already emerging naturally, then go with that flow whilst oh so gently guiding direction.

Instead of fighting market trends, find ways to align your core strengths with where the market is naturally heading.

Instead of imposing rigid processes, watch where work naturally wants to flow and design systems that support and channel that energy.

Instead of swimming directly upstream, look for the eddies and cross-currents that can carry you forward towards your destination with less effort.

This requires the same awareness the old man had—being alert to the whole system, reading the patterns of the forces around you, and finding ways to move in harmony with them rather than against them.

Why Wu Wei Threatens Professional Authority

Beyond Method Critique

But here we encounter the deeper reason why concepts like Wu Wei get systematically domesticated. Wu Wei doesn’t just challenge particular methods—it threatens the entire structure of professional authority over organisational change.

The Domination System of Professionalism

Professionalism, at its root, is a domination system that convinces people their natural responses are illegitimate and dangerous. It teaches managers to fear being seen as unprofessional, feel obligated to follow prescribed methodologies, feel guilty for trusting their intuitive judgment, and feel shame about authentic organisational responses that don’t conform to professional standards. (FOGS)

Creating Dependency

The system creates a class of experts who get to define what counts as legitimate organisational behaviour. These professionals then sell interventions that suppress natural organisational wisdom in favour of professional methodologies—convincing people that without expert guidance, frameworks, etc., organisations would collapse into chaos.

What Wu Wei Demonstrates

Wu Wei demonstrates the opposite: natural organisational forces are superior to professional interventions. What professionalism teaches people to suppress—authentic response to what’s actually happening—is exactly what organisations need most.

The Domestication Imperative

This is why Wu Wei gets automatically translated back into strategic frameworks. Acknowledging its full implications would undermine the fundamental premise that justifies professional authority: that natural organisational responses are inadequate and require expert management.

The Existential Threat

The old man in the maelstrom represents a superior way of engaging with chaotic forces—one that doesn’t require a professional methodology. This threatens the entire apparatus of organisational development, change management, and strategic planning.

Beyond the Binary

Perhaps the real insight is that we don’t have to choose between stagnant stasis and exhausting struggle. There’s a third way: moving beyond the entire framework of effort-based approaches.

The organisations that master this art don’t just survive the currents of change—they learn to become one with them. They discover that the most profound progress sometimes comes not from any kind of swimming at all, but from abandoning the assumption that progress requires struggle against natural forces.

Sometimes transformation happens when we stop trying to manage the current and allow ourselves to be moved by it—not passively, but with the kind of responsive awareness the old man showed in the maelstrom.

The Question Reframed

So let me pose a different question than the one I asked 15 years ago:

Is your organisation ready to abandon the assumption that all progress must come through struggle? Can it discover what lies beyond the choice between frantic effort and resigned stasis?

The river is still flowing. But perhaps the question isn’t how to navigate it, but whether we’re ready to become one with its flow.

—Bob


Further Reading

Hansen, C. (2000). A Daoist theory of Chinese thought: A philosophical interpretation. Oxford University Press.

Slingerland, E. (2000). Effortless action: The Chinese spiritual ideal of Wu-wei. Journal of the American Academy of Religion, 68(2), 293–328.

Slingerland, E. (2003). Effortless action: Wu-wei as conceptual metaphor and spiritual ideal in early China. Oxford University Press.

Walker, M. D. (2014). Zhuangzi, Wuwei, and the necessity of living naturally: A reply to Xunzi’s objection. Asian Philosophy, 24(3), 275–295.

Watson, B. (Trans.). (2013). The complete works of Zhuangzi. Columbia University Press.

Ziporyn, B. (Trans.). (2009). Zhuangzi: The essential writings with selections from traditional commentaries. Hackett Publishing.

The Secret Career Advantage Most Developers Ignore

Why understanding foundational principles could be your biggest competitive edge

Whilst most developers chase the latest frameworks and cloud certifications, there’s a massive career opportunity hiding in plain sight: foundational knowledge that 90% of your peers will never touch.

The developers who understand systems thinking, team dynamics, and organisational behaviour don’t just write better code—they get promoted faster, lead more successful projects, and become indispensable to their organisations. Here’s why this knowledge is your secret weapon.

The Opportunity Gap Is Massive

Walk into any tech company and you’ll find dozens of developers who can implement complex algorithms or deploy microservices. But try to find someone who understands why projects fail, how teams actually work, or how to think systematically about performance bottlenecks. You’ll come up empty.

This creates an enormous opportunity. When everyone else is fighting over who knows React best, you can differentiate yourself by understanding why most React projects fail. Whilst others memorise API documentation, you can diagnose the organisational problems that actually slow teams down.

The knowledge gap is so wide that basic competency in these areas makes you look like a genius.

You’ll Solve the Right Problems

Most developers optimise locally—they’ll spend weeks making their code 10% faster whilst completely missing that the real bottleneck is a manual approval process that batches work for days. Understanding systems thinking (Deming, Goldratt, Ackoff) means you’ll focus on the constraints that actually matter.

I’ve watched developers become heroes simply by identifying that the ‘performance problem’ wasn’t in the database—it was in the workflow. Whilst everyone else was arguing about indices, they traced the real issue to organisational design. Guess who got the promotion?

When you understand flow, variation, and constraints, you don’t just fix symptoms—you solve root causes. This makes you dramatically more valuable than developers who can only optimise code.

You’ll Predict Project Outcomes

Read The Mythical Man-Month, Peopleware, and The Design of Everyday Things, and something magical happens: you develop pattern recognition for project failure. You’ll spot the warning signs months before they become disasters.

Whilst your peers are surprised when adding more developers makes the project slower, you’ll know why Brooks’ Law kicks in. When others are confused why the ‘obviously superior’ technical solution gets rejected, you’ll understand the human and organisational factors at play.

This predictive ability makes you invaluable for planning and risk management. CTOs love developers who can spot problems early instead of just reacting to crises.

You’ll Communicate Up the Stack

Most developers struggle to translate technical concerns into business language. They’ll say ‘the code is getting complex’ when they should say ‘our development velocity will decrease by 40% over the next six months without refactoring investment’.

Understanding how organisations work—Drucker’s insights on knowledge work, Conway’s Law, how incentive systems drive behaviour—gives you the vocabulary to communicate with executives. You’ll frame technical decisions in terms of business outcomes.

This communication ability is rocket fuel for career advancement. Developers who can bridge technical and business concerns become natural candidates for technical leadership roles.

You’ll Design Better Systems

Christopher Alexander’s Notes on the Synthesis of Form isn’t just about architecture—it’s about how complex systems emerge and evolve. Understanding these principles makes you better at software architecture, API design, and system design interviews.

You’ll build systems that work with human organisations instead of against them. You’ll design APIs that developers actually want to use. You’ll create architectures that can evolve over time instead of calcifying.

Whilst other developers create technically impressive systems that fail in practice, yours will succeed because they account for how humans and organisations actually behave.

You’ll Avoid Career-Limiting Mistakes

Reading Peopleware could save your career. Understanding that software problems are usually people problems means you won’t waste months on technical solutions to organisational issues. You won’t join dysfunctional teams thinking you can fix them with better code.

You’ll recognise toxic work environments early and avoid getting trapped in death-march projects. You’ll understand which technical initiatives are likely to succeed and which are doomed by organisational realities.

This knowledge acts like career insurance—you’ll make better decisions about which companies to join, which projects to take on, and which battles to fight.

The Learning Investment Pays Exponentially

Here’s the beautiful part: whilst everyone else is constantly relearning new frameworks, foundational knowledge compounds. Understanding team dynamics is just as valuable in 2025 as it was in 1985. Systems thinking principles apply regardless of whether you’re building web apps or AI systems.

Spend 40 hours reading Peopleware, The Mythical Man-Month, and learning about constraints theory, and you’ll use that knowledge for decades. Compare that to spending 40 hours learning the latest JavaScript framework that might be obsolete in two years.

The ROI on foundational knowledge is massive, but almost no one invests in it.

The Joy of True Mastery

There’s something else most developers miss: the intrinsic satisfaction of developing real mastery. Pink (2009) identified mastery as one of the core human motivators—the deep pleasure that comes from getting genuinely better at something meaningful.

Learning React hooks gives you a brief dopamine hit, but it’s shallow satisfaction. You’re not mastering anything fundamental—you’re just memorising another API that will change next year. There’s no lasting sense of growth or understanding.

But learning to think systematically about complex problems? Understanding how teams and organisations actually function? Grasping the deep principles behind why some software succeeds and others fail? That’s true mastery. It changes how you see everything.

You’ll find yourself analysing problems differently, spotting patterns everywhere, making connections between seemingly unrelated domains. The knowledge becomes part of how you think, not just what you know. This kind of learning is intrinsically rewarding in a way that framework tutorials never are.

How to Build This Advantage

Start with the classics:

  • The Mythical Man-Month – Brooks (1995)
  • Peopleware – DeMarco & Lister (2013)
  • The Design of Everyday Things – Norman (2013)
  • Notes on the Synthesis of Form – Alexander (1964)
  • The Goal – Goldratt & Cox (2004)
  • The Effective Executive – Drucker (2007)

Apply immediately:

Don’t just read—look for these patterns in your current work. Practise diagnosing organisational problems, identifying constraints, predicting project outcomes.

Share your insights:

This isn’t about positioning yourself or impressing managers—it’s about thinking aloud, finding likeminded peers, and building mental muscle memory. Writing and teaching helps to articulate fuzzy understanding into clear principles, which deepens your grasp of the material.

Write to clarify your own thinking. When you read about Conway’s Law, don’t just nod along—write about how you’ve seen it play out in your own teams. Trying to explain why your microservices architecture mirrors your organisational structure forces you to really understand the principle. The act of writing reveals gaps in your understanding and solidifies genuine insights.

Teach to expose what you don’t know. Explaining systems thinking to a colleague immediately shows you which parts you actually understand versus which parts you’ve just memorised. Teaching helps to develop intuitive explanations, real-world examples, and practical applications. You’ll often discover you understand concepts less well than you thought.

Build pattern recognition through articulation. Each time you write about a problem through the lens of Peopleware or analyse a workflow using Theory of Constraints, you’re training your brain to automatically apply these frameworks. Writing about the patterns makes them become more like second nature—mental muscle memory that kicks in when you encounter similar situations.

Create your own case studies. Document your experiences applying these principles. “How I used Goldratt’s Theory of Constraints to diagnose our deployment bottleneck” isn’t just content for others—it’s also cognitive practice. You’re building a library of patterns that your brain can reference automatically.

Think through problems publicly. Whether it’s a blog post, internal wiki, or even just detailed notes, working through organisational problems using foundational frameworks trains your mind to see systems, constraints, and human factors automatically. The more you practise applying these lenses, the more natural they become.

The goal is developing intuitive expertise—reaching the point where you automatically think about team dynamics when planning projects, or instinctively spot organisational dysfunction. This cognitive muscle memory is what separates developers who’ve read the books from those who’ve internalised the principles.

Connect the dots:

Use this knowledge to explain why projects succeed or fail. Make predictions. Build ability and credibility as someone who understands the bigger picture.

The Secret Is Out

The tragedy of developer education is that we’re taught to optimise for looking productive whilst systematically avoiding the knowledge that would make us actually productive. Organisations reward visible coding whilst discouraging the learning that would prevent project failures.

But this creates opportunity. Whilst everyone else chases the same technical skills, you can build knowledge that’s both more valuable and more durable.

The secret career advantage isn’t learning the latest framework—it’s understanding the timeless principles that determine whether software projects succeed or fail.

Most developers will never figure this out. But now you know.

Ready to build your secret advantage? Pick one foundational book, or even just a precis or summary, and start reading today. Your future self will thank you.

Further Reading

Ackoff, R. L. (1999). Ackoff’s best: His classic writings on management. John Wiley & Sons.

Alexander, C. (1964). Notes on the synthesis of form. Harvard University Press.

Brooks, F. P. (1995). The mythical man-month: Essays on software engineering (Anniversary ed.). Addison-Wesley Professional.

Conway, M. E. (1968). How do committees invent? Datamation, 14(4), 28-31.

DeMarco, T., & Lister, T. (2013). Peopleware: Productive projects and teams (3rd ed.). Addison-Wesley Professional.

Deming, W. E. (2000). Out of the crisis. MIT Press. (Original work published 1986)

Deming, W. E. (2000). Out of the crisis. MIT Press. (Original work published 1986)

Drucker, P. F. (2007). The effective executive: The definitive guide to getting the right things done. Butterworth-Heinemann. (Original work published 1967)

Goldratt, E. M., & Cox, J. (2004). The goal: A process of ongoing improvement (3rd rev. ed.). North River Press.

Marshall, R. W. (2021). Quintessence: An acme for software development organisations. Leanpub.

Norman, D. A. (2013). The design of everyday things (Revised and expanded ed.). Basic Books.

Pink, D. H. (2009). Drive: The surprising truth about what motivates us. Riverhead Books.

Seddon, J. (2008). Systems thinking in the public sector: The failure of the reform regime… and a manifesto for a better way. Triarchy Press.

Senge, P. M. (2006). The fifth discipline: The art and practice of the learning organisation (Revised ed.). Random House Business Books.

Tribus, M. (1992). The germ theory of management. SPC Press.

FlowChainSensei’s Hitchhiker’s Guide to Tech Startups

DON’T PANIC!

Yes, this post iattempts to be comprehensive in covering a vast array of considerations for launching a tech startup. It may seem daunting at first glance – much like contemplating the infinite complexity of the universe. But remember: there’s no need to tackle everything at once. This guide is designed to be a reference companion throughout the startup journey, not a checklist to complete before breakfast. Take it one section at a time, focus on what’s most relevant to the current stage, and remember that even the most successful founders started with just one small step.

Audience and Scope: This guide is written primarily for founding teams of 1-3 people in early planning stages, scaling from solo founder scenarios to small team situations. Use the sections relevant to your current stage and team size.

Inception vs. Implementation: The framework and briefing establish strategic direction. Detailed implementation planning happens over subsequent weeks through focused work sessions on specific areas.


Part 1: Strategic Foundation Framework

Legal and Regulatory Framework

When to revisit: Immediately (Week 1), then quarterly for compliance updates, and before any major business model changes

Understanding the legal landscape is crucial for any tech startup. The UK regulatory environment provides both opportunities and obligations that founders must navigate carefully.

Business Structure and Formation

  • Limited company formation remains the preferred structure for most tech startups
    • Provides liability protection and credibility with customers and investors; enables equity distribution and investment
  • Consider partnership structures and shareholding arrangements early
    • Early clarity prevents costly restructuring later; proper documentation protects all parties
  • Understand director responsibilities and company law obligations
    • Directors have legal duties that carry personal liability; understanding these prevents inadvertent breaches

Intellectual Property Protection

  • Register trademarks early to protect brand identity
    • UK trademark registration costs £170-200 but protects valuable brand assets; international expansion requires broader protection
  • Consider patent protection for genuine innovations
    • Patents provide 20-year protection but cost £4,000-8,000; only worthwhile for truly novel technical innovations
  • Implement robust copyright and design right strategies
    • Automatic protection exists but registration strengthens enforcement; crucial for content-heavy businesses

Data Protection and Privacy Compliance

  • UK GDPR compliance is mandatory, not optional
    • Non-compliance fines reach 4% of annual turnover; privacy-by-design reduces compliance costs and builds user trust
  • Implement proper consent mechanisms and data handling procedures
    • Clear consent reduces legal risk; transparent data policies increase user confidence and conversion rates
  • Consider appointing a Data Protection Officer if processing large volumes of personal data
    • Legal requirement for high-risk processing; demonstrates compliance commitment to customers and partners

Consumer Rights and Trading Standards

  • Comply with Consumer Rights Act 2015 requirements
    • Legal obligation that affects refund policies, service quality standards, and customer relationship management
  • Understand distance selling regulations for online services
    • 14-day cooling-off periods apply to most online sales; clear terms reduce customer disputes
  • Implement fair contract terms and transparent pricing
    • Unfair terms are unenforceable; transparent pricing increases conversion and reduces support queries

Trust, Safety, and Verification Systems

When to revisit: Immediately for basic framework (Week 2-3), then monthly during first year as user base grows

Building trust in digital platforms requires systematic approaches to safety, verification, and community management.

User Authentication and Verification

  • Implement robust identity verification systems
    • Multi-factor authentication reduces fraud by 60-80%; builds user confidence whilst reducing platform liability
  • Consider requiring phone number, email, or social media verification
    • Reduces bot accounts and spam; phone verification particularly effective for location-based services
  • Develop user rating and review systems
    • Peer ratings build community trust and enable self-policing; clear feedback mechanisms improve service quality
  • Create processes for handling disputed identities
    • Swift dispute resolution maintains user confidence; documented procedures reduce support time

Content Moderation and Community Guidelines

  • Establish clear community standards and acceptable use policies
    • Clear guidelines reduce moderation burden; transparent enforcement builds user trust in platform fairness
  • Implement automated content filtering for common violations
    • Automation scales more effectively than manual moderation; reduces response time for harmful content
  • Develop escalation procedures for complex cases
    • Human oversight ensures context-sensitive decisions; appeals processes maintain user confidence
  • Create reporting mechanisms for users to flag inappropriate content
    • Community-driven moderation leverages user knowledge; empowers users to maintain platform quality

Security and Fraud Prevention

  • Implement comprehensive security measures including encryption and secure data storage
    • Security breaches cost average £3.2 million; proactive security investment prevents larger costs
  • Develop fraud detection systems and suspicious activity monitoring
    • Early fraud detection prevents losses and protects legitimate users; automated systems scale more effectively
  • Create incident response procedures for security breaches
    • Rapid response minimises damage; transparent communication maintains user trust during incidents

Technology Infrastructure and Data Management

When to revisit: Month 1-2 for architecture decisions, then quarterly for scaling and security reviews

Technical decisions made early significantly impact long-term scalability, costs, and capability.

Platform Architecture and Hosting

  • Choose scalable hosting solutions that can grow with the business
    • Cloud platforms like AWS or Google Cloud provide scalability without large upfront costs; enable rapid geographic expansion
  • Implement proper database design and data architecture
    • Good data architecture prevents expensive migrations later; enables advanced analytics and personalisation features
  • Plan for load balancing and high availability from the start
    • Downtime costs revenue and damages reputation; redundancy planning prevents service disruptions

Search Functionality and User Experience When to revisit: Month 2-3 for MVP implementation, then quarterly for optimisation based on user behaviour data

Effective search and discovery capabilities often determine platform success or failure.

Core Search Features

  • Implement robust search algorithms with relevant ranking
    • Poor search functionality drives users to competitors; good search increases engagement and transaction volume
  • Enable advanced filtering and categorisation options
    • Filters help users find relevant content quickly; reduces search friction and improves conversion rates
  • Consider implementing recommendation systems based on user behaviour
    • Personalised recommendations increase engagement by 15-25%; creates additional revenue opportunities

Search Optimisation and Performance

  • Monitor search performance and user behaviour analytics
    • Data-driven optimisation improves user experience; identifies content gaps and user preferences
  • Implement search result caching for improved performance
    • Faster search results improve user satisfaction; reduced server load decreases hosting costs
  • Plan for search functionality that scales with inventory growth
    • Search performance must maintain quality as content volume increases; early architecture decisions affect long-term capability

Payment Processing and Financial Infrastructure

When to revisit: Immediately (Week 1-2), then annually for rate optimisation and when adding new payment methods

Financial infrastructure decisions impact cash flow, user experience, and regulatory compliance.

Payment Gateway Selection and Integration

  • Research and compare payment processor fees and features
    • Payment processing fees directly impact margins; choosing the right processor saves 0.5-1% on transaction costs
  • Implement multiple payment options to maximise conversion
    • Payment method preferences vary by demographic; offering preferred methods increases completion rates by 10-30%
  • Ensure PCI DSS compliance for payment card processing
    • Legal requirement for card processing; non-compliance risks fines and reputational damage

Billing and Revenue Models When to revisit: Month 3-6 for pricing validation, then every 6 months for optimisation based on user behaviour and market conditions

Subscription models in particular require sophisticated billing infrastructure and pricing strategies.

Subscription Management Systems

  • Implement robust subscription billing with automated renewals
    • Automated billing reduces churn from payment failures; improves cash flow predictability
  • Plan for pricing tier management and promotional pricing
    • Flexible pricing enables market testing and promotional campaigns; supports growth and retention strategies
  • Develop dunning management for failed payments
    • Effective dunning management recovers 15-30% of failed payments; reduces involuntary churn

Transaction Billing Systems

  • Implement robust payment processing with real-time transaction handling
    • Real-time processing reduces cart abandonment and improves user experience; immediate confirmation builds customer confidence
  • Plan for dynamic fee structures and commission management
    • Flexible fee models enable competitive positioning and market adaptation; tiered commission structures incentivise higher-value transactions
  • Develop automated reconciliation and settlement processes
    • Automated reconciliation reduces manual errors and processing time; faster settlement improves cash flow and vendor satisfaction
  • Implement split payment capabilities for multi-party transactions
    • Split payments enable marketplace models and partner revenue sharing; automated distribution reduces operational overhead
  • Create transparent fee calculation and dispute resolution systems
    • Clear fee transparency reduces customer complaints; systematic dispute handling maintains trust and reduces support burden
  • Plan for international payment processing and currency conversion
    • Multi-currency support enables global expansion; competitive exchange rates reduce barriers for international customers
  • Establish fraud detection and risk management for transactions
    • Proactive fraud prevention protects revenue and customer data; risk scoring reduces chargebacks and financial losses

Financial Reporting and Analytics

  • Implement proper revenue recognition and financial tracking
    • Accurate financial reporting enables informed decision-making; required for tax compliance and investor relations
  • Monitor key metrics like Monthly Recurring Revenue (MRR) and customer lifetime value
    • Financial metrics guide strategic decisions; essential for fundraising and growth planning
  • Plan for international expansion with multi-currency support
    • Multi-currency capability enables global growth; reduces barriers for international customers

Customer Support and Community Management

When to revisit: Month 2-3 for basic setup, then monthly during growth phases and quarterly for optimisation

Customer support infrastructure must scale with growth whilst maintaining quality standards.

Support Infrastructure and Processes

  • Implement comprehensive help documentation and FAQ systems
    • Self-service options reduce support volume by 30-50%; improves customer satisfaction through immediate answers
  • Choose scalable customer support platforms
    • Integrated support platforms provide better analytics and automation; improve response times and quality
  • Develop standard operating procedures for common support scenarios
    • Consistent support quality builds customer confidence; reduces training time for new team members

Community Building and Engagement

  • Create channels for user feedback and feature requests
    • User input drives product development; engaged communities provide valuable market insight
  • Develop user onboarding processes and educational content
    • Effective onboarding reduces churn by 20-40%; improves user adoption of key features
  • Plan for community moderation and management
    • Active community management prevents toxicity; fosters positive user interactions and platform loyalty

Market Research and Customer Development Strategy

When to revisit: Ongoing during first 6 months, then quarterly for market intelligence and competitive analysis

Understanding markets and customers drives all other strategic decisions.

Market Validation and Sizing

  • Conduct primary research to validate market demand
    • Direct customer feedback prevents building unwanted products; identifies real user needs and pain points
  • Analyse competitive landscape and positioning opportunities
    • Competitive analysis reveals market gaps and positioning strategies; helps avoid saturated market segments
  • Define target customer segments and personas
    • Clear customer definitions guide product development and marketing; improve conversion rates and customer satisfaction

Customer Development Process

  • Implement systematic customer interview and feedback collection
    • Regular customer contact drives product-market fit; identifies opportunities for improvement and expansion
  • Monitor customer acquisition costs and lifetime value metrics
    • Understanding unit economics drives sustainable growth; guides marketing spend and pricing decisions
  • Develop systems for tracking and analysing customer behaviour
    • Behavioural data reveals user preferences and friction points; enables data-driven product optimisation

Future Strategic Options (Horizon 2/3)

When to revisit: After achieving profitability and establishing proven business model (typically 18-24 months post-launch)

Long-term strategic options require early consideration but delayed implementation.

Market Expansion Opportunities

  • Evaluate potential for geographic expansion
    • Geographic expansion multiplies addressable market; requires understanding of local regulations and preferences
  • Consider adjacent market opportunities and vertical expansion
    • Adjacent markets leverage existing capabilities; provide growth without starting from scratch
  • Assess partnership and licensing opportunities
    • Strategic partnerships accelerate market entry; licensing provides recurring revenue with minimal operational overhead

Technology Evolution and Innovation

  • Plan for emerging technology adoption
    • Early adoption of relevant technologies provides competitive advantage; requires ongoing technology monitoring
  • Consider API development for third-party integration
    • APIs create ecosystem opportunities and additional revenue streams; increase platform value and user retention
  • Evaluate acquisition opportunities and consolidation strategies
    • Strategic acquisitions provide capabilities and market access; consolidation can improve market position

Note: Advanced strategic planning begins only after successful market validation and proven unit economics. Focus on core market success before considering expansion models.


Part 2: Partnership Inception Meeting Framework

Note: This meeting establishes strategic direction and framework. Detailed implementation planning happens through focused work sessions over the following 4-6 weeks.

Purpose and Vision Alignment (15 minutes)

  • Define core mission and long-term vision for the platform
    • Essential foundation that guides all strategic decisions; prevents mission drift and ensures consistent brand messaging
  • Establish shared values and ethical framework
    • Creates decision-making filter for difficult choices; attracts like-minded customers, employees, and partners
  • Discuss personal motivations and what success means to each partner
    • Prevents future conflicts by surfacing different definitions of success early; ensures both partners remain motivated
  • Align on impact goals: environmental, social, and economic outcomes
    • Quantifiable impact metrics enable authentic ESG reporting; attracts impact investors and conscious consumers
  • Clarify the “why” behind the business beyond financial returns
    • Strong purpose enables premium pricing through brand loyalty; provides resilience during market downturns

Legal Structure and Compliance Framework [Priority 1] (15 minutes)

  • Decide on business entity structure (limited company recommended)
  • Assign responsibility for legal setup and compliance
  • Review content policies and moderation strategy
  • Discuss IP protection and trademark registration needs
  • Plan for GDPR compliance and data protection measures
  • Establish terms of service and privacy policy development

Business Model Validation and Revenue Strategy [Priority 1] (15 minutes)

  • Validate subscription tier structure and pricing strategy
  • Validate transation fee structure and pricing strategy
  • Define value propositions for free vs. premium tiers
  • Review market research and competitive analysis findings
  • Establish target customer segments and personas
  • Discuss go-to-market strategy and timeline
  • Set revenue targets and key milestones

Partnership Structure and Equity Discussion (15 minutes)

  • Define roles and responsibilities for each party
  • Discuss equity arrangement and percentage allocation
  • Establish decision-making authority and governance structure
  • Review time commitment expectations and availability
  • Agree on vesting schedules and cliff periods

Technical Architecture and MVP Scope [Priority 1] (15 minutes)

  • Review current MVP progress and technical decisions
  • Define Phase 1 feature set and launch requirements
  • Discuss search functionality implementation approach
  • Plan scalability requirements and technical debt management
  • Establish development timeline and resource needs
  • Review security and data protection requirements

Trust, Safety and Search Strategy [Priority 2] (15 minutes)

  • User verification and authentication approach
  • Search algorithm strategy and competitive differentiation
  • Content moderation and community guidelines
  • Dispute resolution processes and escalation procedures
  • Platform safety measures and risk mitigation

Operational Planning and Resource Allocation (15 minutes)

  • Define immediate hiring needs and skill gaps
  • Plan customer support infrastructure and responsibilities
  • Discuss payment processing setup and financial management
  • Establish quality assurance and testing procedures
  • Review operational costs and budget requirements

Next Steps and Action Items (20 minutes)

  • Assign immediate action items and ownership
  • Schedule follow-up meetings and check-in cadence
  • Establish communication protocols and project management tools
  • Set deadlines for key deliverables and milestones
  • Plan for legal documentation and partnership agreements

Priority Parking Lot (Deferred Items)

Marketing and PR Strategy [Priority 3]

  • Defer to Month 4-6: Focus on product-market fit before marketing investment

Metrics and Analytics Implementation [Priority 3]

  • Defer to Month 2-3: Implement after basic functionality is operational

Future Strategic Options [Priority 4]

  • Defer to Horizon 2/3 planning (Month 12+): Focus on core market success first

Part 3: Implementation Roadmap and Planning Tools

Prioritisation Framework

Impact vs. Effort Scoring Matrix Score each item 1-5 (5 = highest impact/lowest effort)

High Impact, Low Effort (Priority 1 – Quick Wins)

  • Business entity formation (Impact: 5, Effort: 2)
  • Basic terms of service (Impact: 4, Effort: 2)
  • Payment processing setup (Impact: 5, Effort: 3)
  • Basic analytics implementation (Impact: 4, Effort: 2)

High Impact, High Effort (Priority 2 – Strategic Investments)

  • Core MVP development (Impact: 5, Effort: 5)
  • Search functionality (Impact: 5, Effort: 4)
  • User authentication systems (Impact: 4, Effort: 4)
  • Customer support infrastructure (Impact: 4, Effort: 4)

Implementation Timeline

Pre-Launch Phase (Months 1-3)

Legal and Structural Foundation

  • Business entity formation: 2-3 weeks, £200-500
  • Partnership agreement execution: 3-4 weeks, £1,500-3,000
  • Basic terms of service and privacy policy: 1-2 weeks, £500-2,000
  • VAT registration (if applicable): 1-2 weeks, Free-£200

Technical Development

  • Website hosting infrastructure setup: 1-2 weeks, £100-500/month
  • Core MVP feature completion: 8-12 weeks, £15,000-50,000
  • Basic search functionality: 3-4 weeks, £3,000-8,000
  • Payment processing integration: 2-3 weeks, 2.9% + 20p per transaction
  • User authentication systems: 2-3 weeks, £1,000-3,000

Soft Launch Phase (Months 4-6)

Limited User Testing

  • Closed beta with 50-100 invited users: 4-6 weeks, £500-2,000
  • User feedback collection and platform refinement: 3-4 weeks, £300-1,500
  • Search algorithm optimisation: 2-3 weeks, £2,000-5,000

Operational Validation

  • Customer support process testing: 2-3 weeks, £500-1,500
  • Quality control and authentication processes: 3-4 weeks, £1,500-4,000

Public Launch Phase (Months 7-9)

Market Entry

  • Public platform launch: 2-3 weeks, £3,000-10,000
  • Marketing campaign execution: 8-12 weeks, £5,000-25,000
  • Social media presence establishment: 4-6 weeks ongoing, £1,000-4,000/month

Scale Preparation

  • Customer support team expansion: 3-4 weeks, £25,000-45,000/year per hire
  • Technical infrastructure scaling: 2-3 weeks, £500-2,000/month additional
  • Advanced search features: 6-8 weeks, £8,000-20,000

Ready-to-Use Planning Templates

Vendor Evaluation Scorecard Payment Processor Evaluation (Score 1-10)

  • Processing fees competitive (< 3%)
  • UK Direct Debit support
  • Subscription billing features
  • Transaction billing features
  • API quality and documentation
  • Customer support responsiveness
  • Compliance and security certifications
  • Integration complexity (lower score = easier)
  • Failure handling and retry logic

User Research Interview Script Market Validation Interview (30 minutes)

Opening (5 minutes) “Thank you for your time. We’re researching how people currently solve [problem area]. This isn’t a sales call / conversation – we genuinely want to understand your experiences and challenges.”

Current Behaviour (10 minutes)

  • How do you currently handle [problem area]?
  • What tools or services do you use?
  • What’s frustrating about current options?
  • How often do you encounter this problem?

Problem Validation (10 minutes)

  • Have you ever wanted a solution that…?
  • What would make you trust a new service in this area?
  • What concerns would you have about trying something new?

Solution Testing (5 minutes) “Imagine a service that [brief solution description]…”

  • What would make this valuable to you?
  • How much would you pay monthly for this service?
  • What features would be most important?

Contingency Planning

Plan B Options for Major Decisions

Payment Processing Contingencies

  • Primary: Stripe + GoCardless
  • Plan B: PayPal + Worldpay (if primary rejects application)
  • Plan C: Square + bank transfer (if all major processors reject)
  • Nuclear Option: Manual invoicing until revenue justifies enterprise processor

Technical Architecture Alternatives

  • Primary: Custom development
  • Plan B: White-label solution
  • Plan C: WordPress + plugins for rapid prototype
  • Pivot Option: Simple directory without complex features

Revenue Model Pivots (Notional)

  • Primary: Subscription-based access
  • Plan B: Transaction fees (2-5% per transaction)
  • Plan C: Freemium with premium features
  • Last Resort: Advertising-supported free platform

Stakeholder Communication Framework

Monthly Investor Update Template

  • Executive Summary (2-3 sentences on key achievements and challenges)
  • Key Metrics Dashboard
  • Major Accomplishments (3-4 bullet points)
  • Key Challenges (2-3 items with action plans)
  • Financial Summary (revenue, expenses, cash position)
  • Team Updates (hires, departures, key achievements)
  • Ask (specific help needed from investors)
  • Next Month Focus (3-4 key priorities)

Crisis Communication Templates

Service Outage Communication “We’re currently experiencing technical difficulties that may affect platform access. Our team is working to resolve this immediately.

Status: Investigating
Estimated Resolution: [timeframe]
Affected Services: [specific areas]

Updates every 30 minutes at [status page link]. We apologise for the inconvenience.”


Conclusion

Successfully launching a tech startup requires careful orchestration of numerous business elements beyond product development. Using strategic planning frameworks helps balance immediate execution needs with longer-term growth opportunities. Addressing the foundational areas outlined in this guide proactively will significantly improve the likelihood of sustainable growth and long-term success.

Consider prioritising legal compliance, trust and safety measures, and basic operational procedures before launch, whilst developing longer-term strategies for emerging opportunities and transformational growth. Remember: the goal isn’t to complete everything immediately, but to build a sustainable foundation for systematic growth.


Colophon

This comprehensive startup guide was collaboratively developed through an iterative process of strategic planning, business analysis, and practical implementation guidance. The framework presented here draws upon established business methodologies, UK regulatory requirements, and contemporary startup best practices.

Document Creation Process: The strategic analysis and actionable recommendations were developed through extensive dialogue between human expertise in business strategy, technology, and startup operations, enhanced by Claude (Anthropic’s AI assistant) and FlowChainSensei for research synthesis, structural organisation, and comprehensive coverage of technical and regulatory considerations.

Methodology: This post mentions multiple strategic frameworks including the Three Horizons planning model, Impact vs. Effort prioritisation matrices, and risk-weighted analysis to provide both immediate tactical guidance and long-term strategic vision.

Intended Use: This guide serves as a living document designed to evolve with the startup’s growth and changing market conditions. It is intended for use by founding teams, advisors, and stakeholders as both a planning tool and operational reference throughout the business development lifecycle.Pleas take it and evolve it as you need.

Version: 1.0
Date: 12 June 2025
Format: WordPress blog post
License: This work is licensed under a Creative Commons Attribution 4.0 International License. You are free to share and adapt this material for any purpose, even commercially, as long as you provide appropriate attribution to FlowChainSensei.

“In the beginning the Universe was created. This has made a lot of people very angry and been widely regarded as a bad move. Starting a business has similar effects, but with better potential returns.” – With apologies to Douglas Adams

Further Reading and References

Business Strategy and Planning

Blank, S., & Dorf, B. (2012). The startup owner’s manual: The step-by-step guide for building a great company. K&S Ranch.

Baghai, M., Coley, S., & White, D. (1999). The alchemy of growth: Practical insights for building the enduring enterprise. Perseus Publishing.

Osterwalder, A., & Pigneur, Y. (2010). Business model generation: A handbook for visionaries, game changers, and challengers. Wiley.

Subscription and Platform Business Models

Baxter, R. (2015). The membership economy: Find your super users, master the forever transaction, and build recurring revenue. McGraw-Hill Education.

Warrillow, J. (2018). The automatic customer: Creating a subscription business in any industry. Portfolio.

Parker, G. G., Van Alstyne, M. W., & Choudary, S. P. (2016). Platform revolution: How networked markets are transforming the economy and how to make them work for you. W. W. Norton & Company.

UK Legal and Regulatory Framework

Competition and Markets Authority. (2020). Online platforms and digital advertising: Market study final report. CMA.

Information Commissioner’s Office. (2023). Guide to the UK General Data Protection Regulation (UK GDPR). ICO.

Partnership Formation and Governance

Wasserman, N. (2012). The founder’s dilemmas: Anticipating and avoiding the pitfalls that can sink a startup. Princeton University Press.

Feld, B., & Mendelson, J. (2016). Venture deals: Be smarter than your lawyer and venture capitalist (3rd ed.). Wiley.

Trust, Safety, and Content Moderation

Gorwa, R., Binns, R., & Katzenbach, C. (2020). Algorithmic content moderation: Technical and political challenges in the automation of platform governance. Big Data & Society, 7(1), 1-15.

Gillespie, T. (2018). Custodians of the internet: Platforms, content moderation, and the hidden decisions that shape social media. Yale University Press.

Payment Processing and Financial Technology

Arvidsson, N. (2019). The story of payments: From barter to Bitcoin. Springer.

Bank of England. (2021). Central Bank Digital Currency: Opportunities, challenges and design (Discussion Paper). Bank of England.

Customer Experience and Community Building

Reichheld, F., & Markey, R. (2011). The ultimate question 2.0: How Net Promoter companies thrive in a customer-driven world. Harvard Business Review Press.

Wenger, E., McDermott, R., & Snyder, W. M. (2002). Cultivating communities of practice: A guide to managing knowledge. Harvard Business School Press.

Risk Management and Crisis Planning

Kaplan, R. S., & Mikes, A. (2012). Managing risks: A new framework. Harvard Business Review, 90(6), 48-60.

Coombs, W. T. (2014). Ongoing crisis communication: Planning, managing, and responding (4th ed.). SAGE Publications.

Startup Operations and Scaling

Blumenthal, N., & Gilboa, D. (2021). Vision to reality: Nine lessons on how to transform your startup into a billion-dollar business. Currency.

Horowitz, B. (2014). The hard thing about hard things: Building a business when there are no easy answers. Harper Business.

Government and Industry Resources

Companies House. (2024). Guidance for limited companies. Retrieved from https://www.gov.uk/government/organisations/companies-house

HM Revenue & Customs. (2024). VAT: Registration and rates. Retrieved from https://www.gov.uk/vat-registration

UK Government. (2015). Consumer Rights Act 2015. Retrieved from https://www.legislation.gov.uk/ukpga/2015/15/contents

Normative Learning: The Only Kind That Sticks

“If behaviour has not changed, then learning has not happened.”

~ FlowChainSensei

 

“Is there anyone so wise as to learn by the experience of others?”

~ Voltaire

These two statements, separated by centuries, reveal an uncomfortable truth: most of what we call “learning” isn’t learning at all. It’s books, theories, articles, and information consumption dressed up as education—a cognitive sleight of hand that leaves us feeling informed whilst remaining fundamentally unchanged.

Voltaire’s question implies what we all secretly know but rarely admit: there really isn’t anyone wise enough to learn from others’ experiences, despite how desperately we wish we could. Yet we’ve built an entire industry around this impossible promise.

We’ve built an entire industry around what we might call “academic learning”—the consumption of theories, frameworks, and insights through books, blogs, courses, and conferences. But this isn’t learning at all. It’s intellectual entertainment that masquerades as growth whilst leaving our actual behaviour untouched.

True learning—what we might call normative learning—bears no resemblance to this information transfer model. It doesn’t happen through reading, studying, or absorbing theories. It rewires our reflexes, reshapes our habits, and fundamentally alters how we show up in the world through direct experiences and engagement with reality. Most importantly, it challenges and transforms the deep assumptions and beliefs that govern our behaviour, including the collective assumptions we inherit from our cultures, organisations, and communities.

The Great Academic Learning Deception

We live in an age of unprecedented access to books, articles, courses, and theories, yet behaviour change remains stubbornly elusive. Corporate bookshelves groan under the weight of business bestsellers whilst workplace cultures stagnate. LinkedIn feeds overflow with insights and frameworks whilst personal transformation stays frustratingly out of reach. Students consume mountains of content for degrees they’ll never truly use.

This disconnect exists because we’ve been sold a fundamental lie: that consuming information equals learning. We’ve built entire industries around this deception—publishing houses, business schools, conference circuits, and content creation empires that profit from our confusion of input with outcome.

But reading about leadership doesn’t make you a leader any more than reading about swimming makes you a swimmer, or reading about boxing equips you to enter the ring with Mike Tyson. Studying theories of communication doesn’t improve your relationships – or even your communication. Consuming productivity content doesn’t make you productive. These activities might make you feel productive, informed, or intellectually stimulated, but they’re not learning—they’re elaborate forms of procrastination and titillation disguised as self-improvement.

Consider the executive with a library of leadership books who continues to micromanage. The person who’s read every article on mindfulness but still reacts with the same old patterns. The entrepreneur who consumes business content voraciously whilst their actual business struggles. They’ve mistaken consumption for learning, input for transformation.

Why Books and Theories Can’t Produce Real Learning

The academic learning industrial complex wants us to believe that knowledge is transferable—that someone else’s insights, packaged into books, courses, or frameworks, can somehow become our learning. But this fundamentally misunderstands how learning actually works.

Voltaire understood this centuries ago. His rhetorical question—”Is there anyone so wise as to learn by the experience of others?”—implies the obvious answer: no. Yet we keep trying to be that impossibly wise person who can skip the hard work of actual experience.

Here’s the simple test: Can you ride a bicycle by reading about cycling? Can you become a parent by studying child development? Can you learn to negotiate by memorising tactics? The answer is obvious when put this way, yet we somehow believe leadership, creativity, and complex problem-solving are different.

Experience can’t be transmitted. What we call “learning” in academic contexts is really just exposure to other people’s processed experiences. But experience is irreducibly personal. The insights that emerge from direct engagement with challenging situations can’t be conveyed through someone else’s description of their insights from their situations. The wisdom earned through making real mistakes with real consequences can’t be downloaded from someone else’s case study.

Context determines meaning. Theories and frameworks strip away the messy particulars that make situations real and learning possible. They present sanitised, generalisable versions of what were originally contextual, particular experiences. But learning happens precisely in those messy particulars—in the specific constraints, relationships, pressures, and dynamics that make each situation unique.

Books promote passive consumption, learning requires active engagement. Reading about leadership whilst sitting comfortably in your chair creates no resistance, demands no real choices, requires no accountability for results. You can agree with everything, feel inspired, and remain completely unchanged. Real learning happens only when you’re forced to act, make choices, and deal with the consequences of those choices in real time with real stakes and real people.

Academic learning reinforces the illusion of knowledge. Perhaps most dangerously, consuming content about a topic can create the feeling of understanding that topic. This “illusion of knowledge” actually impedes real learning by providing the psychological satisfaction of growth without requiring the behavioural change that indicates actual growth. You feel like you’ve learned, so you stop seeking the experiences that would produce real learning.

The Messy Advantages of Real Learning

Everything academic learning sees as a problem, normative learning sees as an advantage:

Failure is required, not avoided. Academic learning protects you from failure with carefully curated success stories and proven frameworks. But failure is where learning happens fastest. When a chef burns a dish, they immediately understand heat control in ways no cookbook can teach. When a manager’s delegation fails, they learn about communication and trust through direct experience. Academic learning can’t replicate this because sanitised case studies carry no real consequences.

Discomfort signals progress. If your “learning” always feels comfortable and affirming, you’re probably just consuming content that confirms what you already believe. Real learning feels awkward because you’re literally rewiring your brain. A surgeon’s first operations feel terrifying. A new parent’s first weeks feel overwhelming. An entrepreneur’s first failures feel devastating. This discomfort isn’t a bug—it’s the feature that indicates actual change is happening.

Time investment forces commitment. Academic learning promises quick results through intensive courses and summary frameworks. But real capabilities develop through sustained practice. This apparent “constraint” of time actually becomes an advantage—it forces the deep practice that creates lasting change. There are no shortcuts to becoming a skilled craftsperson, effective leader, or capable parent.

Real stakes create real learning. Academic learning happens in artificial environments designed to be safe and controlled. But you learn fastest when something important is at risk. A startup founder learns about customer needs through the threat of business failure. A surgeon develops precision through the responsibility for patient outcomes. A parent learns patience through the reality of affecting another human being. Real stakes aren’t obstacles to overcome—they’re the essential conditions that make learning urgent and memorable.

The Collective Delusion of Academic Learning

The problem runs deeper than individual self-deception. We’ve created entire cultures and institutions built around the false premise that learning happens through information consumption. This collective delusion shapes everything from how we structure education to how we approach professional development.

Educational systems optimised for content delivery. Schools and universities are designed around the assumption that learning means information transfer. Students sit passively whilst experts deliver content, then demonstrate “learning” by reproducing that content on tests. But this produces graduates who can recite theories they’ve never applied, frameworks they’ve never tested, and concepts they’ve never understood in solving real problems.

Corporate cultures that confuse training with development. Organisations spend billions on training programmes, conferences, and educational content, then wonder why their cultures don’t change. They’ve bought into the collective assumption that exposing people to ideas about leadership, innovation, or collaboration will somehow produce leaders, innovators, and collaborators. Meanwhile, the actual development of these capabilities requires sustained practice in real situations with real accountability—something most corporate “learning” programmes carefully avoid.

Professional communities built around content consumption. Entire industries have emerged around packaging and selling “insights” to people who mistake consuming insights for developing capabilities. Business thought leaders, productivity gurus, and self-help experts profit from our collective confusion of input with outcome, selling us the comforting illusion that transformation can be purchased rather than earned through practice.

The credentialism trap. Perhaps most perniciously, we’ve created systems that reward academic learning—degrees, certifications, badges—whilst ignoring actual capability. This creates perverse incentives where people optimise for credentials rather than competence, consuming educational content to signal learning rather than to actually learn. Agile certifications being a case in point.

What Normative Learning Actually Looks Like

Normative learning happens through direct engagement with reality, not through consuming content about reality. It emerges from practice, experimentation, failure, reflection, and iteration. It’s messy, uncomfortable, and can’t be packaged into neat frameworks or digestible articles.

It happens through doing, not reading. A master craftsperson learns through years of working with materials, feeling resistance, making mistakes, and gradually developing an intuitive understanding that no book could convey. A skilled therapist develops their abilities through thousands of hours with real clients, not by studying therapy theories. An effective leader emerges through the repeated experience of making decisions, dealing with consequences, and gradually calibrating their approach based on real feedback from real situations.

It’s contextual and embodied. Unlike the abstract knowledge found in books and theories, normative learning is always situated in specific contexts with real constraints, real people, and real stakes. It lives in your body, your reflexes, your gut feelings developed through experience. A seasoned entrepreneur can sense when something feels “off” about a business deal not because they’ve read about red flags, but because they’ve internalised patterns from direct experience with hundreds of real situations.

It challenges assumptions through collision with reality. Books and articles can present new ideas, but they can’t force you to confront your assumptions the way reality does. When your theoretical framework meets actual results, when your preferred approach encounters resistance, when your assumptions crash into contrary evidence—that’s where real learning begins. Not in the comfortable consumption of aligned content, but in the uncomfortable confrontation with disconfirming experience.

It transforms behaviour by necessity. In normative learning, behaviour change isn’t a hoped-for side effect—it’s the inevitable result of engaging with reality over time. And indeed, it’s the point. When you repeatedly practise something in real contexts with real feedback, your behaviour must change or you fail. There’s no hiding behind theoretical knowledge or abstract understanding. Either you develop the ability to perform, or you don’t.

How Real Learning Actually Happens

If reading, studying, and consuming content isn’t learning, then what is? Real learning—normative learning—happens through direct engagement with reality over time. It can’t be packaged, purchased, or consumed. It must be earned through practice.

Work alongside people who can already do it. The fastest way to learn anything is to work directly with someone who has already developed the capability you want. Not by studying what they’ve written about their work, but by actually doing the work with them. Watch how a skilled negotiator prepares for difficult conversations. See how an experienced manager handles team conflicts. Observe how a master craftsperson approaches tricky materials. Then gradually take on more responsibility as your capabilities develop.

Try things, see what happens, try again. Real learning emerges from cycles of action and feedback. Start a small business to learn entrepreneurship. Volunteer to join a project to learn about teaming. Take on speaking opportunities to learn communication. The learning happens in the gap between what you expect and what actually occurs. Each cycle teaches you something no book could convey.

Let failure teach you what success cannot. Academic learning only shows you what works. But you learn fastest from what doesn’t work. Every failed experiment reveals assumptions you didn’t know you had. Every mistake shows you the boundaries of your current capabilities. Instead of avoiding failure, actively court it as your fastest teacher. Start projects where failure is likely but consequences are manageable.

Practise with others, not alone. Real learning happens in community with others who are also developing the same capabilities. Not communities that discuss concepts, but communities that practise together. Join a writing group where people actually write, not where they talk about writing. Find business partners who are building companies, not studying business. Work with others who will challenge your work and hold you accountable for results.

Keep going when it gets hard. Academic learning has clear endpoints—you finish the course, complete the book, earn the certificate. Real learning never ends. You don’t “complete” learning to be a parent, leader, or entrepreneur. You develop these capabilities through continuous practice over years. The people who succeed are those who keep practising when the initial enthusiasm fades and the work becomes routine.

Designing for Normative Learning (Not Content Consumption)

If behaviour change through direct engagement with reality is the goal, how do we create environments that support real learning rather than academic informaion transfer? The principles are fundamentally different from content-based approaches:

Use real projects with real consequences. Instead of case studies or simulations, work on things where your decisions actually matter. Start a side business instead of studying entrepreneurship. Volunteer to lead a struggling team instead of taking teambuilding courses. The psychological pressure of real consequences forces the kind of attention and care that artificial scenarios can’t replicate.

Do the work, don’t talk about doing the work. Spend your time actually practising the skill you want to develop, not discussing it. If you want to learn communication and empathy, have difficult conversations. If you want to learn creativity, create things. If you want to learn problem-solving, solve problems. Discussion and analysis can support your practice, not replace it.

Track what you actually do differently. Stop measuring how much content you’ve consumed. Start tracking specific behaviour changes. Can you delegate more effectively this month than last month? Are your difficult conversations going better? Are you making decisions faster? If your day-to-day behaviour isn’t changing, your “learning” is just entertainment, nothing more.

Work with the chaos, not around it. Real situations are messy, unpredictable, and complex in ways that can’t be captured in frameworks or theories. Instead of trying to simplify this complexity, learn to work with it. The messiness isn’t an obstacle to learning—it’s exactly what teaches you to handle real-world challenges that don’t fit neat categories.

Commit to long-term practice. Real capabilities develop through sustained practice over months or years, not through intensive workshops or crash courses. Set up sustainable practice routines that you can maintain over time. Consistency beats intensity when it comes to developing lasting capabilities.

Accept that everything depends on everything else. You can’t change your behaviour in isolation from your environment, relationships, and circumstances. Instead of trying to control all variables, learn to work within real constraints with real people who have their own agendas and limitations. This complexity isn’t a bug—it’s the essential condition that teaches you to navigate real-world challenges.

How to Tell If You’re Actually Learning

Most people can’t distinguish between feeling informed and being transformed. Here are the simple tests that reveal whether you’re engaging in real learning or just consuming content:

The Monday morning test. What are you doing differently this week because of your “learning” efforts? If you can’t point to specific behaviour changes in your actual work, relationships, or daily routines, you’ve been consuming content, not learning. Real learning always shows up in changed behaviour.

The explanation test. Can you teach someone else to do what you’ve “learned” through hands-on demonstration, not just description? If you can only talk about it but can’t actually do it with someone watching, you haven’t learned it yet. Real learning creates the ability to perform, not just discuss.

The resistance test. Does your learning feel difficult and sometimes uncomfortable? If it always feels pleasant and affirming, you’re probably just consuming content that confirms what you already believe. Real learning creates cognitive dissonance as new experiences challenge old assumptions.

The failure test. Are you failing regularly in your learning efforts? If you never fail, you’re not pushing the boundaries of your current capabilities. Real learning requires attempting things beyond your current skill level, which inevitably means failing, adjusting, and trying again.

The time test. Are you investing weeks and months in developing capabilities, or are you looking for quick insights and rapid results? Real learning takes sustained effort and focus over time. If you’re always jumping to the next shiny method or framework, you’re avoiding the deep practice that creates lasting change.

The stakes test. Does your learning have real consequences? Are you practising in situations where your performance actually matters to you or others? If there are no real stakes, you’re not creating the conditions that force genuine capability development.

If you’re failing most of these tests, you’re probably trapped in academic learning disguised as personal development. The good news is that recognising this is the first step towards real learning.

Why Your Environment Fights Against Real Learning

Individual behaviour change is hard enough, but it becomes nearly impossible when your environment is set up to reward the wrong things. This isn’t about motivation or willpower—it’s about how systems work.

Your workplace rewards activity, not results. Most jobs reward being busy, attending meetings, and completing training programmes rather than actually developing capabilities or producing better outcomes. If your organisation measures learning by hours spent in training rather than behaviour change, it’s incentivising academic learning over real learning.

Your social circle discusses ideas instead of testing them. If your professional network consists of people who love talking about concepts, sharing articles, and debating theories, you’re surrounded by academic learners. Real learners surround themselves with people who are actually doing things, making mistakes, and getting better through practice.

Your default habits favour consumption over creation. Most people’s daily routines are optimised for consuming content—reading articles during commute, listening to podcasts whilst exercising, scrolling social media during breaks. These habits train your brain to be a passive consumer rather than an active practitioner.

Your identity is tied to knowing, not doing. If you get satisfaction from being the person who’s read the latest business book, knows the current frameworks, or can discuss trends intelligently, your identity is built around academic learning. Real learners get satisfaction from getting better at doing things that matter.

The solution isn’t to change your entire environment overnight—that’s usually impossible. Instead, make small changes that align your environment with real learning:

  • Join communities where people practise together, not just discuss together
  • Set up your daily routine to prioritise doing over consuming
  • Measure yourself by behaviour change, not content consumption
  • Find at least one person who will hold you accountable for actual results, not just good intentions

Your environment will either support real learning or undermine it. Design it intentionally.

Breaking Free from the Academic Learning Trap

The transition from academic to normative learning requires fundamentally different approaches and expectations. It means abandoning the comfortable illusion that learning can be consumed and embracing the challenging reality that learning must be earned through practice.

Stop consuming, start creating. Instead of reading about what others have done, start doing something yourself. Instead of studying entrepreneurship, start a business—even a small one. Instead of reading about leadership, volunteer to lead something—even if it’s just organising a group dinner. Instead of consuming content about creativity, create something—even if it’s terrible at first. The learning happens through the creating, not through the consuming.

Seek discomfort, not confirmation. Academic learning feels good—it confirms what we already believe and presents us with insights that align with our existing worldview. Normative learning feels uncomfortable because it forces us to confront the gap between our assumptions and reality. If your “learning” always feels comfortable and affirming, you’re probably just consuming content that makes you feel smart.

Practise daily, not intensively. Academic learning promotes the illusion that you can learn a lot in a short time through intensive courses and boot camps. Real learning happens through daily practice over months and years. Spend 30 minutes each day actually practising the skill you want to develop rather than spending weekends consuming content about that skill.

Join communities of practice, not communities of discussion. Find groups of people who are actually doing the thing you want to learn, not groups that discuss the thing you want to learn. If you want to learn writing, join a writing group where people actually write and critique each other’s work. If you want to learn business, find other entrepreneurs who are building companies. Communities of practice hold you accountable for results and provide feedback based on actual performance.

Measure behaviour change, not knowledge acquisition. Stop tracking what you’ve read, watched, or studied. Start tracking what you’ve actually done differently as a result of your learning efforts. Keep a simple log: “This week I tried X differently because of what I learned from doing Y.” If your behaviour hasn’t changed, your “learning” is actually just consumption.

Use books as tools, not teachers. Books and articles can serve as tools to support real learning—helping you reflect on your practice, providing frameworks to make sense of your experience, or pointing you towards possibilities you hadn’t considered. But they are tools to support practice, not substitutes for practice. Read to inform your doing, not to replace your doing.

Simple Ways to Start Learning for Real

Here are specific actions you can take this week to begin the transition from academic to normative learning:

Pick one skill and practise it daily. Choose something you can practise for 15-30 minutes each day. If you want to learn public speaking, record yourself giving a short presentation each morning. If you want to learn negotiation, practise with small stakes—negotiating better terms on a subscription, asking for a discount at a local shop, or requesting a deadline extension. Daily practice beats weekend seminars.

Start a project where failure is likely but affordable. Launch a small business that might fail but won’t bankrupt you. Volunteer to lead a project at work that stretches your capabilities. Start a blog where you’ll publish weekly even if no one reads it. The key is choosing something where failure teaches you more than success would, but the consequences aren’t devastating.

Find one person who’s already good at what you want to learn. Ask if you can work with them, help them, or observe them in action. Most people are willing to share their knowledge if you’re genuinely interested in learning, not just picking their brain. Offer to help with something they need in exchange for the opportunity to learn alongside them.

Join a group that practises together. Look for communities where people actually do things together, not just discuss things. Writing groups that critique actual work, entrepreneur meetups where people share real challenges, sports teams, maker spaces, volunteer organisations—any group where you’ll practise with others and get feedback on your performance.

Track your behaviour changes weekly. Keep a simple log: “This week I did X differently because I practised Y.” Focus on specific, observable changes in how you act, not on how much you know or how inspired you feel. If you can’t point to behaviour changes, you’re probably consuming content instead of learning.

Replace one consumption habit with one practice habit. Instead of reading business articles during your commute, practise giving presentations out loud. Instead of listening to productivity podcasts whilst exercising, use that time to practise a physical skill. Instead of scrolling social media during breaks, practise a 5-minute creative exercise. Small substitutions add up over time.

The goal isn’t to eliminate all content consumption—it’s to make practice your primary learning method and use content consumption as a tool to support your practice. Start with one change this week. Real learning begins with doing, not planning to do.

The Stakes of Abandoning Academic Learning

In a world of rapid change and increasing complexity, the ability to learn normatively—to actually develop new capabilities through direct engagement with reality—becomes a critical survival skill for individuals, organisations, and societies. Those who can abandon the comfortable illusion of academic learning and embrace the challenging reality of normative learning will thrive. Those who remain trapped in content consumption disguised as education will find themselves increasingly obsolete.

Individual stakes. People who continue to mistake reading for learning, studying for developing, and consuming for growing will find themselves with impressive libraries and empty capabilities. They’ll know about many things but be able to do very few things well. In a world that rewards actual performance over theoretical knowledge, this gap becomes increasingly dangerous.

Organisational stakes. Companies that continue to invest in training programmes, educational content, and knowledge management whilst ignoring the development of actual capabilities will be outcompeted by organisations that focus on building real competence through practice. The ability to execute consistently and adapt quickly matters more than the ability to discuss best practices and cite frameworks.

Societal stakes. Educational systems that continue to optimise for content delivery rather than capability development will produce graduates who can’t solve real problems, adapt to changing circumstances, or create value in the world. Meanwhile, the challenges we face—climate change, inequality, technological disruption—require people who can actually do things, not just think about things.

The stakes are particularly high for leaders, educators, and anyone responsible for developing others. If you’re designing “learning” experiences that don’t produce behaviour change, you’re not facilitating learning—you’re enabling the collective delusion that consumption equals development. You’re part of the problem, not the solution.

The uncomfortable truth remains: if behaviour hasn’t changed, learning hasn’t happened. Reading doesn’t count. Studying doesn’t count. Consuming content doesn’t count. Only sustained engagement with reality that transforms how you actually behave in the world counts as learning.

This isn’t to say that books, articles, and theories are worthless. They can serve as tools to support real learning—helping you reflect on your practice, providing frameworks to make sense of your experience, or pointing you towards possibilities you hadn’t considered. But they are tools, not learning itself. The learning happens when you close the book and engage with reality.

The question isn’t whether this standard is too high. The question is whether you’re ready to abandon the comfortable illusion of academic learning and embrace the challenging reality of normative learning. Whether you’re willing to stop consuming other people’s processed experiences and start generating your own. Whether you’re prepared to measure your learning not by what you’ve read or studied, but by how your behaviour has actually changed.

The choice is yours. But choose consciously. Don’t let the academic learning industrial complex convince you that transformation can be purchased, downloaded, or consumed. It can’t. It can only be earned through the slow, difficult, rewarding work of repeatedly engaging with reality until reality changes you.

As Voltaire knew centuries ago, there really isn’t anyone wise enough to learn from others’ experiences. We all must learn through our own. That’s normative learning. It’s the only kind that sticks.

Postscript

If you’ve read through to the end of this post, don’t take it on face value. You’ve learned nothing. Go apply it. You might then experience some normative learning through action.

The Theatre of Optics

The Illusion of Action: Perception vs. Genuine Problem-Solving

Humans have developed a remarkable skill that transcends mere performance—the art of appearing to address problems whilst artfully avoiding their effective resolution. This phenomenon is not merely a quirk of our genes but a deeply entrenched mechanism that permeates political institutions, corporate environments, and bureaucratic structures with remarkable consistency.

Imagine a world where the energy invested in crafting the perception of action were redirected towards actual problem-solving. Where press conferences, policy statements, and corporate initiatives were judged not by their blustering rhetoric, but by their measurable, tangible impact. Such a vision seems almost revolutionary in its simplicity, yet remains frustratingly distant from our current reality.

The disconnect between appearance and substance has become so normalised that we frequently fail to distinguish between meaningful action and mere elaborate theatre. Politicians deliver impassioned speeches that sound transformative yet change nothing. Business leaders launch initiatives wrapped up in impressive language, creating the illusion of progress whilst maintaining precisely the status quo.

Problem Management as Performance

In both governmental and business spheres, we see sophisticated dances of seeming proactivity. Leaders, politicians and executives have evolved an intricate set of strategies designed to create the perception of action without any real action. This involves overblown press releases, meticulously staged press conferences, and grandiose statements that sound remarkably impressive yet deliver minimal concrete outcomes.

Why Perception Trumps Substance

The Political Machine

Political systems and businesses are particularly adept at this performative approach. Politicians frequently invest substantially more energy in crafting narratives about potential solutions than in implementing genuine, transformative changes. |It’s almost as if they have no clue about even the basics of how to effect real change. The electoral cycle rewards those who can convincingly blather about progress rather than those who quietly and effectively resolve systemic challenges.

Business’s Cosmetic Approach

Corporate environments mirror their political cousins with remarkable fidelity. Companies frequently launch elaborate initiatives that look impressive on annual reports, investor presentations and in the media, but create zero real-world impact (aside from speding even more money on bullshit rhetoric and actions). These initiatives aim to demonstrate corporate responsibility and commitment to change without fundamentally altering existing power structures or addressing root problems.

The Psychology of Perceived Action

Why We Fall for the Illusion

Humans are remarkably susceptible to the appearance of action. Our cognitive biases prefer a compelling narrative of potential change over the often mundane, incremental work of just getting on with fixing things. This psychological vulnerability allows leaders in both politics and business to consistently profess change over actually doing anything.

Breaking the Cycle

Demanding Genuine Accountability

To move beyond this performative approach, society might choose to recognise its vulnerability to bullshit, and develop effective ways of both seeing it and rejecting it. This requires:

  • Cultivating a culture that values quantifiable outcomes over hand-wavy flourishes
  • Developing robust, independent approaches to assessment
  • Choose metrics that reflect the genuine needs of the people affected, from their point of view
  • Encouraging transparency and genuine quantified reporting
  • Supporting teams and organisations that demonstrate authentic problem-solving approaches

Conclusion

The chasm between being seen to address a problem and actually resolving it represents one of the most significant challenges in contemporary organisational and political life. Until we collectively demand and reward genuine, substantive action, we will continue to be governed by the theatre of perceived progress – the Theatre of Optics.

Workplace Fear to Workplace Care

The Shadow

Walk into any workplace, and you’ll sense it: The bastard colleague who sends emails at midnight. The dickhead team lead who never takes a full lunch break. The eager new hire already showing signs of burnout. In offices, homes, and coffee shops across Britain, the same concerns surface: “Can we Britons keep working like this? Will speaking up cost me my job?”

These aren’t isolated worries—they’re symptoms of what organisational psychotherapy recognises as learned responses to workplace pressures, passed down through generations of office culture.

The Beneath

Looking deeper reveals familiar patterns:

  • The manager who demands constant availability isn’t just controlling—they’re recreating patterns from the shared assumptions and beliefs they acquired early in their career
  • The organisation celebrating long hours isn’t just overworking—it’s perpetuating outdated and irrelevant measures of commitment
  • The employee afraid to take lunch or leave on time isn’t just anxious—they’re responding to unspoken cultural pressures – products of eveyone’s shared assumptions and beliefs

The data backs this up: rising burnout rates, increasing workplace dissatisfaction, low employee engagement, growing mental health challenges. But numbers alone won’t change ingrained habits and collective assumptions and beliefs. We might choose to understand why these patterns persist.

Old Habits

Our relationship with work often mirrors other relationships—it needs boundaries, respect, and trust to thrive. Consider how we’ve normalised behaviours that undermine all three:

  • Boundaries dissolved through constant email availability
  • Self-worth tied to presence and visibility (presenteeism)
  • Personal needs pushed aside for work demands
  • Achievement measured by exhaustion levels

Workplace Dynamics

Progressive workplaces use insights from psychology and behavioural science to understand how companies develop their personalities and habits. This reveals:

  • Leadership styles – and the eshewing of leadership entirely – shape team behaviour
  • Change creates fear and anxiety
  • Team dynamics reflect wider patterns
  • Where cynicism comes from and what it means

Inviting Change

Change happens through small, consistent actions. Just as therapy works best with practical steps, workplace transformation needs clear actions, founded on the idea of surfacing and reflecting on the organisation’s shared assumptions and beliefs:

  1. Building Better Cultures
    • Creating psychological safety in meetings
    • Developing systems that support wellbeing
    • Making rest as normal as work
  2. Redefining Success
    • Respecting boundaries
    • Attending to folks’ needs, beyond mere profit (“Nobody gives a hoot about profits” anyways Cf. Demings First Theorem
    • Valuing collaboration over (intra- and inter-team, intra- and inter-departmental) competition
  3. Daily Practices
    • Regular surfacing and reflecting on shared assumptions and beliefs up, down and across the organisation
    • Open discussions about needs
    • Clear communication about expectations
    • Recognition of different working styles

Moving Forward

Changing workplace culture isn’t simple or quick. It happens gradually, through consistent small actions and shifts in thinking. The goal isn’t to transform everything overnight—it’s to build healthier, more sustainable ways of working together. Ways that embed and encourage continual updating of shared assumptions and beliefs.

We’re not just changing policies. We’re developing better relationships—with work, with colleagues, and with our own psyche. These changes ripple outward from thw workplace, affecting our families, communities, and society.

The first step is having the courage to begin. The next is being curious about the organisation’s collective psyche – what kinds of change is needed?

Are You Ever Heard?

The Illusion of Connection

In a world where we’re more connected than ever, a paradox emerges: genuine listening seems to have become a rare commodity. As I reflect on my own circle of friends, I’m struck by a sobering realisation—not a single one ever listens to me. I suspect this isn’t merely a personal gripe; it seems symptomatic of a broader societal shift.

The Erosion of Attentiveness

Digital Distractions: The New Normal

Our smartphones ping incessantly, social media feeds refresh endlessly, and the 24/7 news cycle demands constant attention. In this cacophony of digital noise, the art of listening has become collateral damage. We’ve developed a collective attention deficit, skimming the surface of conversations without diving deep.

The Cult of Self: Mirror, Mirror on the Wall

Social media platforms have transformed us into curators of our own public image. In this ecosystem of likes and shares, we’ve become adept at broadcasting but inept at receiving. The irony? As we chase validation, we inadvertently create a vacuum of genuine connection.

The Hidden Costs of Being Unheard

The Loneliness Paradox

Despite having hundreds of ‘friends’ online, and even IRL – in real life, many of us feel profoundly alone. This disconnect between quantity and quality of relationships breeds a unique form of isolation—one where we’re surrounded by people yet starved for any meaningful interactions.

Trust in Free Fall

When our words fall on inattentive ears, it chips away at the bedrock of trust in our relationships. Over time, this erosion can lead to a cynical worldview where we question the authenticity of all our connections.

Reclaiming the Lost Art of Friendship

Quality Over Quantity: The New Social Currency

Is it time to recalibrate our social metrics? Instead of tallying followers, or even friends, how about we measure the depth of our conversations? One friend who truly listens is worth more than a thousand who merely hear.

The Mirror Principle: Be the Change

If we aspire to be heard, we might first choose to become accomplished listeners. By offering others our undivided attention, we not only enrich their lives but also set a new standard for our interactions.

A Call to Listen

This isn’t just about personal fulfillment; it’s about preserving the fabric of human connection in an increasingly disconnected world. The next time you’re in a conversation, challenge yourself to listen—truly listen. You might be surprised at the doors it opens and the connections it deepens.

In a world that’s always talking, sometimes the most revolutionary act is to simply listen.

Organisational Psychotherapy: Actions Speak Louder Than Words

In the realm of organisational development, there’s a growing recognition that effective and sustainable transformation requires more than just talk therapy. Whilst traditional approaches to organisational psychotherapy have often relied heavily on dialogue and discussion, a new paradigm is emerging—one that places action at the core of the therapeutic process. This post explores how taking concrete actions can dramatically accelerate the surfacing and examination of shared assumptions and beliefs within organisations.

The Limitations of Talk Therapy in Organisational Settings

The Comfort of the Couch

Superficial organisational psychotherapy often mirrors individual therapy—lots of talking, analysing, and theorising. Whilst these discussions can provide valuable insights, they can also create a false sense of progress. Organisations might feel they’re addressing issues when, in reality, they’re merely dicking about.

The Gap Between Theory and Practice

Just as a person in therapy might intellectually understand their issues without changing their behaviour, organisations can become adept at discussing their problems without acting to address them. This gap between understanding and action can lead to frustration and stagnation.

Action as a Catalyst for Organisational Insight

Embodied Learning

When organisations take action, they engage in a form of embodied learning. Rather than just thinking and talking about change, they experience it. This visceral experience can reveal assumptions and beliefs that might never surface in a meeting room or therapy session.

The Shock of the New

Action often creates situations that challenge the status quo. When Zappos implemented holacracy, a self-management system, it quickly revealed deeply held assumptions about hierarchy and decision-making that no amount of discussion had previously uncovered.

Going to the Gemba

There’s a host of material in the Lean literature about going to the Gemba – the place where work actually takes place – to learn what’s actually happening (rather than what managers think is happening).

Practical Approaches to Action-Oriented Organisational Psychotherapy

Experimental Culture

Foster an environment where small, controlled experiments are not just allowed but encouraged. When Spotify introduced its “squad” model, it did so incrementally, allowing the organisation to learn and adapt as hidden assumptions about teamwork and accountability came to light. See also: Toyota Kata – the Improvement Kata.

Real-World Simulations

Create scenarios that mimic real-world challenges. When IDEO wants to help a company innovate, they often use the “Deep Dive” technique—a compressed timeframe to solve a specific problem. This intense, action-oriented approach quickly surfaces team dynamics and hidden biases.

Reverse Engineering Success and Failure

Instead of just discussing past successes or failures, actively recreate the conditions that led to them. When Toyota practises its “Go and See” philosophy, managers physically go to the site of a problem, often revealing assumptions about processes that weren’t apparent from reports or discussions alone.

The Role of Reflection in Action-Based Organisational Therapy

Structured Debriefing

After each action or experiment, conduct thorough debriefings. The U.S. military’s “After Action Review” process is an much-studied model, focusing not just on what happened, but why it happened and what beliefs or assumptions influenced the outcomes.

Narrative Reconstruction

Encourage team members to construct narratives around their experiences. When Pixar reviews its film production process, team members share stories about their experiences, often revealing underlying assumptions about creativity and collaboration that wouldn’t emerge in a traditional review.

Overcoming Resistance to Action-Oriented Approaches

Fear of Failure

Many organisations resist action-oriented approaches due to a fear of failure. Leaders might choose instead to reframe failure as a valuable source of information.

The Illusion of Consensus

Talk-based approaches can sometimes create an illusion of consensus that action can quickly dispel.

The Therapist as Action Catalyst

In this new paradigm, the organisational therapist becomes less of a traditional counsellor and more of an action catalyst. They invite the design of experiments, the creation of scenarios, and facilitate reflection processes that turn everyday organisational activities into opportunities for deep insight and learning.

Conclusion: From Talking the Talk to Walking the Walk

Organisational psychotherapy that emphasises action over talk represents a powerful evolution in how we approach organisational change and development. By moving beyond the comfort of discussion and into the realm of concrete action, organisations can more quickly and effectively surface the hidden assumptions and shared beliefs that truly drive their behaviour.

This approach doesn’t negate the value of dialogue—rather, it provides a richer context for those conversations. When words are grounded in recent, relevant experiences, they carry more weight and lead to more meaningful change.

As organisations navigate increasingly complex and rapidly changing environments, the ability to quickly surface, examine, and evolve shared assumptions and beliefs becomes ever more valuable. Action-oriented organisational psychotherapy offers a path not just to talking about change, but to embodying it.

This approach aligns with the spirit of Kurt Lewin’s work on action research and organisational change. Lewin emphasised the importance of action in understanding and changing social systems. By embracing action as a core component of organisational psychotherapy, we open the door to deeper understanding and more profound transformation.