“After initially meeting Ollie at the IAB leadership summit, we were thrilled to be able to invite him to be the external speaker at our Coty summer conference.

Ollie’s session was captivating for the whole audience, as it not only broadly humanised some of the conversations bubbling around AI, but was also packed with practical applications that our team left eager to explore and implement.

Ollie’s skill is that he can make complex concepts easy to understand, and he inspired us all with real-world examples. If you’re looking for an engaging speaker to ignite creativity and knowledge amongst your teams, look no further!”

Susie Thompson, Senior Director Media & Communications at Coty

I’m working with leaders to take lessons like these into their organisations - through workshops, advisory, and speaking. If you’d like to discuss how I can help your team, book a free, no-obligation call HERE.

This week is about using AI to actually think – getting clarity, challenging yourself, and knowing when to stop

1. Learning new domains fast

I travel a lot for work. Different industries, different clients, different problems.

The challenge isn’t finding information. It’s building enough understanding to have a point of view - fast.

Before high-stakes meetings, I don’t just ask “tell me about this company.” I ask AI to help me understand their world well enough to ask smart questions and connect what I do to what they care about.

I have a meeting with [person/company] in [X days].

Context:
- What they do: [brief description]
- What’s happening in their industry: [any relevant trends]
- What I’m trying to achieve: [your goal for the meeting]

Help me:
1. Understand what people in their position actually care about day-to-day
2. Identify 3 angles I can take into the conversation that show I understand their world
3. Suggest 5 questions I could ask that would make me sound like an informed peer, not a tourist

The goal isn’t to become an expert. It’s to move from “I’ve heard of this” to “I have a perspective worth sharing.”

Other uses: Preparing for board presentations in unfamiliar sectors, or understanding new technology before you decide whether to invest time.

2. Untangling messy situations

Sometimes I can’t think clearly because there’s too much going on.

Projects competing for attention. Decisions that all feel urgent. Can’t see the wood for the trees.

This is about organising what you already know but can’t see clearly.

When my brain feels full, I dump everything out and ask AI to help me see it. Recently I pasted in a list that included speaking work, advisory projects, a product I’m building, and content - then asked it to help me separate what’s actually important from what just feels urgent.

I’m overloaded and can’t see clearly. Here’s everything on my plate:
[bullet list - projects, commitments, decisions, worries]

1. Restate my situation in no more than 10 bullet points
2. Separate those into: FACTS, ASSUMPTIONS, and FEARS
3. Given only the facts and my goal of [briefly state], what are the 3 most important priorities for the next 90 days?
4. For each, give me one action I can take this week

AI’s job here isn’t to decide for you. It’s to organise the mess so you can.

Other uses: Preparing for a difficult conversation. Working out what’s actually bothering you about a project. Separating real constraints from imagined ones.

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3. Finding the real question

This is different from untangling. That’s about clarity. This is about realising you’re solving the wrong problem.

Often I’ll ask AI something and realise halfway through that I’m asking the wrong question.

A client says “we need help with X” - but the actual problem is Y. I think I’m stuck on a decision, but really I’m avoiding a harder question underneath it.

Here’s the question I think I’m asking: [surface question]

Context: [why this matters, what’s at stake]

1. What do you think the *real* question is that I’m trying to answer? Give me 3 possibilities.
2. For each, explain what decision would change if that were the real question.
3. Which one do you think matters most and why?
4. What should I ask myself to make sure I’m focused on the right problem?

Half the time, the breakthrough isn’t finding the answer - it’s realising you’ve been asking the wrong question.

Other uses: When you’re stuck and don’t know why. When a client’s brief doesn’t quite make sense. When you keep circling the same problem without progress.

4. Stress-testing ideas

I have a tendency to fall in love with my own ideas. Most people do.

So before I commit serious time or money, I ask AI to attack. Not “is this good?” but “why wouldn’t this work?”

Here’s my idea: [describe in 5 sentences or less]

Assume you’re a sceptical investor who’s seen a hundred pitches like this.

1. List the top 5 reasons this is weak, risky, or unlikely to work. Be harsh.
2. What are 3 warning signs that would tell me to kill this idea quickly?
3. If you had to keep the core insight but radically change the execution, what would you do?
4. Based on this critique - is this worth testing at all? If so, what’s the smallest test that would prove or kill it?

The value isn’t in AI being right. It’s in forcing you to defend your thinking before you’ve invested too much to change course.

Other uses: Before you hire someone you’re excited about. Before you announce something publicly. Before you invest serious money in something.

5. The rabbit hole warning

I have a tendency to over-research.

Sometimes it’s trivial. On Sunday, I spent too long working out whether 125 or 140 degrees was the “correct” temperature for slow-cooking beef. The stakes were low. The cost of being slightly wrong was basically zero. But I kept pushing for the “right” answer.

Sometimes it’s more dangerous - like spending weeks refining a product idea when five customer conversations would tell me more, faster, and with more accuracy. Using research as a sophisticated form of procrastination.

Now I try to catch myself:

I’ve been thinking about [topic] for [time].

Am I overthinking this? What’s the minimum I need to know before I act?

If AI tells me I’m in a rabbit hole, I try to listen.

Other uses: Any time you’ve been “researching” something for more than an hour. When you’re on your third draft of something that was fine on the first.

6. Knowing when to stop

The flip side of the rabbit hole - knowing when you already have the answer.

I’ve asked AI the same strategic questions multiple times. “Where should I focus? Which project should I prioritise?” The answers don’t change because there’s no new information. At that point I’m using AI to avoid committing.

You don’t need a prompt for this. You need a pen and paper.

Before you start, write down:

• What question am I trying to answer?

• What would “good enough” look like?

• How will I know when I’m done?

Just like going down a YouTube rabbit hole or doomscrolling on Instagram, AI can suck you in. And just because it seems smart doesn’t mean it’s any better way to waste your time.

The discipline isn’t just in thinking well. It’s in knowing when to stop thinking and act.

The point

AI is a powerful thinking partner - but only if you use it that way.

Most people prompt once, get an answer, and move on. The real value is in the back-and-forth. Using AI to learn faster, challenge harder, see clearer.

And knowing when to close the chat and just do the thing.

Thanks for reading.

Ollie

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