Call your customer, call your shot, or call capital

This from Aashay is totally spot-on and the generational divide he’s describing is real. It roughly maps onto a framework he and I have been talking about for a while.

Historically, there are two schools of thought: calling your customer vs. calling your shot. The former (PG) is talking to users, iterating fast and letting the market teach you. The latter (Thiel) is developing deep conviction, having a secret and making a big bet towards a future that you own.

Roughly speaking, calling your shot and calling your customer are two paths to the same destination: internal conviction.

Aashay is describing the new phenomenon of “king making” or engineered success via the right cap table/club deal/a priori social proof. The setup at inception is everything.

So now we have three approaches: “big swings” (call your shot), “fast swings” (call your customer), and “make kings” (call capital).

The problem with “make kings” isn’t that it doesn’t work. It can work. The problem is what it costs you.

1. Consensus isn’t necessarily predictive of outlier outcomes in a power-law denominated distribution. The “obviously best” companies today often have no bearing on what actually works in the future. At the limit, OpenAI started as a nonprofit and is today the most valuable startup in history. Kingmaking selects for companies that look like winners based on pattern-matching. But in a power law distribution, winners/outliers are definitionally an anti-pattern.

2. Borrowed conviction is structurally fragile. Without an internally derived animating spirit/vision, you lack the internal scaffolding to sustain (through hard moments/local troughs). Much like companies who crib from competitors, they lack the insight and conviction to know why they’re doing what they’re doing or what to do next.

Borrowed conviction comes packaged with borrowed structure: raise big, hire fast, beat plan. That locks you in and creates path dependency early, when flexibility, experimentation, and learning are still the main thing. It’s building a tanker when the whole point is still in the turning.

The final distinction between big swings and fast swings, and king-making is permissionless vs. permissioned entrepreneurship. Big swings and fast swings are both permissionless paths to conviction. One through vision, one through learning. King making is permission-based; it only works on the basis of elite buy-in/consensus.

So “calling capital” and becoming a hypercapitalized club deal isn’t wrong per se. It’s just that it needs to come after you (the founder) already developed internal conviction and the vision to go put beaucoup bucks to use uniquely and productively. Once you’ve developed that on your own/without permission, getting into the club can transform you into a substantive, obvious winner. This is fundamentally the process of producing legibility and narrative momentum.

At Slow, we believe deeply in founder-led/internal paths to conviction. Whether that happens heads-down in a notebook (calling your shot) or heads-up in the market (calling your customer) doesn’t matter. We can fund you to conviction/insight or meet you once you have it. But it has to come from you, not us.

So if you’re developing conviction internally, call me maybe.

Read more in this related post from my partner Will.

American exceptionalism is at stake in the fight over the Fed

America has the most robust, deep capital markets in the world. This is now under serious threat from Trump and we have a limited window to save it.

In America it’s not just our companies but our government and households that can access capital more easily than those abroad. This access to capital (along with the American spirit of optimism necessary to risk it) is our greatest compounding advantage. It finances our system of entrepreneurial capitalism, energy infrastructure, consumer credit, defense projects, etc.

Our equities trade at a premium and we borrow at a discount because of:

1. Trust, stability, and the rule of law. We have non-arbitrary regs/enforcement, a professionalized civil service, robust and independent courts, etc. Collectively it’s property rights and stability that make investors comfortable parking their money in the US

2. Our capital account surplus. When we send dollars abroad (trade deficits) those dollars have to go somewhere. They wind up as the world’s reserve currency (strengthening and made possible by #1) and they are invested back in the US to finance more growth domestically

Trump is simultaneously undermining each of those in innumerable ways, risking America’s system of free and fair markets and undermining the engine of our global safe haven status.

He is dragging us backward to be a corrupt oligarchy of middling ambition like Russia or Turkey (equities at 4x earnings and junk-rated sovereign debt) because he can’t imagine more or better for America. The ability to access cheaper capital is a huge, compounding, competitive advantage. This is what’s at stake in the fight over the Fed.

Prediction markets for real estate

Polymarket is now doing local home price prediction markets. Basically you can bet on whether or not an index of home prices/rents will go up or down in a given geography over a given period of time.

This is actually not as dumb as it looks and speaks to what I think is the actual point and purpose of prediction markets (if they can get sufficient liquidity).

Quick recap: I think sports betting and sports betting experiences are dumb and bad. In practice this includes most/all prediction markets. But in theory prediction markets have two really valuable features:

1. They create new information which is socially/economically useful

2. They allow people/firms to hedge out idiosyncratic risks just like an airline trading oil as a key input to its business

Back to home price markets. This reminds me of an idea from a few years ago for city-specific REITs, basically you could invest in an index of real estate down to a reasonably local level. These never really took off and I don’t think any of those companies still exist.

It’s not about making money; it’s about hedging the risk that home prices will go up too much, impairing your ability to afford your current housing or buy a home in your local market. We’re all basically short housing and have to cover that short every month, day, year.

From a certain point of view this is just another demand-side subsidy to the housing problem if it works.

NYC Breakfast

AIC is a team of software industrialists with a mission to transform the critical robotics supply chains for physical AI that underpin America’s economic power and national security at wartime speed.

America’s Innovation Corporation (AIC) is a software-led, growth buyout holding company actively searching for profitable Original Component Manufacturers in the electronics industry to acquire, modernize, and scale. Our mission is to transform the critical supply chains that underpin America’s economic power and national security.

​Slow believes deeply in the mission and is excited about what AIC is building.

​If you’re interested in AIC’s mission, please join us for breakfast in the city with CEO Alex Torrey. AIC is hiring for:

1. A chief of staff with a heavy finance background

2. Machine learning engineers

3. Software engineers

Read to the end for a how-to guide for writing well with AI and an invite to a private dinner in New York.

I’m back after a nice two-week break. This is the longest pause I’ve taken in my newsletter in ≈16 months.

Second-Order AI - models get better, so what?

At both the app and model layers, everyone is basically chasing some version of “max token throughput.” That is, the single plotline: “How do I make AI better and get it to do more things?”

This is great and makes sense given the civilizational scale of the technology we’re already operating at. But it does wind up feeling a bit hollow. Sort of a brute force “more, more, more” approach to summoning The Machine God.

The more interesting question isn’t what AI can do. It’s what happens after it does it. The first-order effects of AI are mechanical and obvious: cheaper digital production, personalization, observation, coordination. So what? What happens next?

This is probably the single most exciting opportunity set in 2026 and beyond: investing in the second-order impacts of improved AI.

AI Breaks Things. Now Fix Them.

AI amplifies volume until existing filtering/routing mechanisms collapse and need to be rebuilt.

• Hiring: Applications are free to send. Volume explodes. Recruiters can’t distinguish candidates. Resume screening stops working. The whole funnel breaks.

  • Slow company: MeritFirst, Tofu, Stealth

• Outbound sales: Sophisticated campaigns available to everyone, flooding channels. The well gets poisoned and new GTMs replace it.

  • Slow company: Memelord, Stealth

• Code collaboration: Git was built for scarce, human-written code. Whatever replaces it will be built for abundance.

  • Slow company: Stealth

• Trust and security: Everything on the internet is fake. Content, identities, credentials. Systems that assumed human-scale production and human-verifiable authenticity stop working.

  • Slow company: Outtake, Sublime Security, Stealth

• Deployment: more apps, faster releases, more integrations, etc. SIs are critical chokepoints and will become very powerful this cycle.

  • Slow company: Stealth, Stealth

These problems are already real and the solutions are being built today or will be soon.

Obviously we’ve already invested in these ideas and are looking for more. The full list of what will get broken and needs to be rebuilt is much longer, maybe infinitely so. I’m curious where you’re looking and where else this dynamic is going to play out.

Net-New Opportunities

Then there’s whole categories that only make sense once AI capabilities are mature.

• The complement shift: Intelligence commoditizes. Its complements become the new scarcity: trust, taste, judgment, access, meaning. As production gets cheaper, people will pay for what can’t be produced.

• Org compression/the end of companies: Coordination costs drop and small teams can do big things, dropping minimum company sizes. We might even see a return of temporary, purpose built companies (like film productions or joint-stock companies).

These are further off and squishier based on proliferation and capabilities that we don’t yet QUITE have.

So what?

The social, economic, and political upheaval and change this civilizational technology wreaks will be epochal.

There’s a ton of money to be made improving AI right now (duh) but there’s a lot more creative ways to build businesses using AI in novel ways and fixing what it breaks. The most exciting opportunities and n-of-1 businesses will be in the second order impacts.

Growth after outbound

I’ve written before about how AI is going to kill outbound performance:

The scale of outbound sales will increase by orders of magnitude and the well will become permanently poisoned. Your bot’s emails and calls will just go unanswered. Your AI generated SEO blog posts will go unread. The only way to build a business in that future will be bottoms up demand generation brand, audience, captive distribution, virality, reputation, network.

As outbound becomes less performant it will be part of a channel mix/halo strategy not unlike display advertising before.

At the company level, we’re seeing founders respond in a bunch of ways: becoming media brands, showing up to more conferences, building creator-led companies, acquiring their own distribution outright. All reasonable.

But how do you bet at the theme- rather than company-level? There’s historical precedent. Masa built SoftBank by buying and building tech magazines and tech conferences, most famously paying Sheldon Adelson $700 million for COMDEX. If software was gonna be huge, he’d own the places where software people gather. [Aaron Witt is running a version of this today with BuildWit (vertical software for construction) and Dirt World (a construction conference).]

But obviously conferences and media brands aren’t great standalone venture investments in 2026. So what’s the contemporary equivalent?

If trusted networks and warm intros become everything when cold outreach dies, then the investable layer might be platforms that aggregate or route through those networks. Influencer marketplaces and audience platforms. Paid intro routing (Boardy and Superconnector are building versions of this).

Every company is going to have to respond to the deterioration of traditional outbound. There are obviously going to be platform-level bets to make on that theme.

How I use AI (and How I Don’t): Bicycles for the mind vs motorcycles for the mid

I’ve been an avid fan of LLMs as a writing copilot and editor since ChatGPT launched. My usage has massively accelerated over the last few months since I largely can’t type on a computer (wrist injury)

1. Speak notes aloud (via wispr bc no desktop Claude voice mode) and brain dump, often with screenshots and/or prior essays. This is very useful to just get the most raw versions of an idea together without self conscious constraints.

2. Claude asks me clarifying/challenging questions (prompt: “interview me asking questions one at a time to help flesh this out”) to organize/substantiate the idea, after which I give an outline/flow

3. Claude generates a first skeleton draft putting my notes into the flow

4. I move to a word processor (google docs or bear) and re-write paragraph by paragraph (also via wispr).

5. I send back to Claude for comments and feedback before repeating step #4.

6. Once I’m satisfied, I send it to Pangram to make sure I’ve sufficiently re-written everything and hold myself accountable.

7. Publish

My goal with AI as a writing partner (and remember, writing is thinking) is to do more and better, rarely just to do it “faster”. A bicycle helps you go further faster but still requires a great deal of effort and provides conditioning. A motorcycle is much faster but relying on it will atrophy your muscles and lungs.

I am very worried about how many smart people are just writing longer because is now cheap. They’re using intellectual ICEs instead of burning calories; reading and writing that makes us all dumber and less informed.

If you’re not using AI to write/think, you’re not maxing out what you can do. If you’re only using AI to write, you’re part of the problem.

AI is the new plastic; it can enable novel processes and beautiful designs or cheap, disposable crap. It’s up to you.

Cyber Dinner

​AI is breaking $1.5T of security market cap.

​For 30 years, cybersecurity has worked because attacks have had known limitations. Businesses have also had a concept of control: how to secure within a perimeter, how to vet vendors, and how to remediate gaps or accept known risks. The $1.5T security market cap was built on the assumption of visibility and control. That known landscape is gone with AI.

This winter I’m teaming up with ex/ante and Outtake to host a dinner and discussion in NY about the changing threat landscape and how new and existing security companies will meet that.

Sign up here!

Long letter. lots of links. still can’t type. ball up top.

NY CoS/founding biz hires

I’ve got three portfolio companies hiring for founding biz/ops/chief of staff roles in New York right now. Getting the right person to help build each of these businesses is very important to me.

• A defense-adjacent manufacturing platform is looking for a chief of staff to be the engine behind their acquisition strategy. This company is led by a repeat founder who’s building AI to acquire and transform specialized electronics manufacturers. You’ll build growth buyout models that blend traditional GBO mechanics with software-driven operational improvements, lead diligence on targets, structure transactions, and serve as analytical thought partner to the CEO. 5-7 years in IB and/or PE required, industrials/manufacturing experience required.

• A dev tools company betting that the AI platform shift creates a once-in-a-generation opportunity to replace foundational infrastructure is hiring a founding business generalist. The technical founder is building what could become the new standard for how humans and AI collaborate on code. He needs a right hand to run day-to-day operations while he does deep product work and closes F500 deals. Startup background is a must.

• A vertical AI company building a self-driving network of agents for healthcare is looking for a gap filler/an extension of the CEO. This repeat founder has a compelling theory: LLMs make it possible to embed agents directly into existing workflows without behavior change or new tooling. The company is already moving tens of thousands of transactions and expanding fast. Prior startup experience required, open to new/recent grads with the right intensity.

Each of these companies is well-funded and led by a very experienced founder. These are opportunities for ambitious grinders to get in early at companies we’re extremely bullish on. They’re all still operating in stealth so if you’re interested, reply directly with your Linkedin and a one sentence blurb.

It goes without saying that each of these companies is also hiring engineers. The dev tools company in particular is looking for Rust engineers.

Nash equilibrium (defection)

Chris Paik wrote one of my favorite recent overviews/takes of the current venture market in psychology.

TLDR: there’s basically no upside in being disciplined, honest, self-critical, etc and disproportionate upside with relatively minimal downside to doing/being the opposite of all of those. I don’t mean to just totally black-pill everyone. I think it’s possible to carve out a lane doing things “the right way” but it requires having an investment culture and a set of very high-trust LPs. It is objectively harder and only works for the love of the game but may not be the EV-maximizing strategy.

The whole thing is worth reading (it’s two pages)but this section in particular is the most striking to me and gets at one of the core anxieties/debates.

From Chris:

The Nash Equilibrium of Defection

-If You Cooperate (Discipline) and They Defect (Chase): Your competitor wins the “hot” logo. They get the press, the markup, and the reputation for “access.” You are left with a “disciplined” portfolio of obscurities. LPs view you as irrelevant. You fail to raise your next fund.

-If You Both Defect (Chase): You both bid up the asset. Valuations skyrocket, pricing out future upside. Returns for the vintage regress to the mean. However, you both survive to play another round because you both have “access” to the category winners.

In this game, Chasing Momentum is the Nash Equilibrium. The penalty for missing the boat (career risk) is immediate and severe, while the penalty for overpaying (return risk) is delayed by 7–10 years. Therefore, no rational GP can afford to be the only disciplined investor in a momentum market.

Chris and I have yet to have a chance to work closely together though I hope that changes. He seems like a really sharp guy.

The roll-ups are still rolling

I spoke to Madeline Renbarger of Newcomer for her piece about VC-funded buyouts and roll-ups. I’ve written about this many many times before. But I think it’s worth reiterating the difference between what we’re doing and what the mega funds are doing:

The big distinction is leading w capital vs leading w product. We want to fund product companies that go to market by buying operating companies and they want to buy businesses.

We fund product 0 to 1 development to ensure that founders can underwrite transformational outcomes from future acquisitions rather than going on a buying spree before understanding where they are differentiated owners. So often that means a typical seed round upfront.

This helps preserve a lot of optionality to either remain a software company, build an operating company, buy operating companies, or some combination thereof. We’ve seen instances where businesses expected to buy companies and instead found that they can succeed by building an operating business themselves without any need for M&A at all. Leading with capital is like building a sales team before you have a product.

from the article:

Slow Ventures has funded several roll-up startups without putting up a lot of upfront capital. Instead, Slow looks to seed companies to build the AI tech needed for these roll-ups, but the founders then raise additional capital to fund these large-scale acquisitions.

Slow invested early in Teamshares, which buys up small businesses using a model that enables employees to gain an equity stake after the owners sell. Teamshares said in November that it plans to go public via SPAC. Slow was also an early investor in Metropolis, which raised a $1.6 billion equity and debt round this fall to roll-up parking lots and automate check-out with AI.

Read the Slow GBO deck here.

Creator 2025

This deck from Megan and the Creator team goes over the five important themes for creators this year:

1. People matter, brands don’t

2. Own the niche, not the category.

3. Build worlds, not products.

4. AI culls the undifferentiated

5. Short the mass market.

From their letter:

In February of this year, we closed and launched Slow Ventures Creator Fund I on the heels of a simple idea: the next great companies would be built by creators. Not celebrities or influencers, these creators are capable builders with real trust, informed insight, big ambition, and an instinctive grasp of community, storytelling, and distribution.

This fund not only represents years of quiet iteration and foundation building, but importantly, is the first institutional fund backing creators directly with seed capital. We are grateful to have LPs like MIT, University of Michigan, TIFF, Rutgers and many others support our pursuit to fund this new path for entrepreneurship.

This deck recaps much of what we’ve observed in our first year: the themes that matter as well as the ones that don’t. The best creator businesses don’t chase views, they expand their niche expertise into new worlds. They turn narrative into community, community into revenue, and revenue into durable companies. Our early investments in Jonathan Katz-Moses, Steven Bartlett, Tayla Cannon (and more!) show that this model unlocks multi-product franchises rooted in trust, mission, and execution.

Technological and cultural shifts have rewritten the means of attention, influence, and consumption, which have fundamentally changed where value is created, captured, and funded. We are in the era of the individual. But in a world of frictionless scale, the winners won’t be the loudest. They’ll be the creators who know exactly why their audience shows up and who leverage their communities to solve real problems.

Cyber Dinner

​AI is breaking $1.5T of security market cap.

​For 30 years, cybersecurity has worked because attacks have had known limitations. Businesses have also had a concept of control: how to secure within a perimeter, how to vet vendors, and how to remediate gaps or accept known risks. The $1.5T security market cap was built on the assumption of visibility and control. That known landscape is gone with AI.

This winter I’m teaming up with ex/ante and Outtake to host a dinner and discussion about the changing threat landscape and how new and existing security companies will meet that.

Sign up to join here.

Abundance

I’ve spent the last year supporting and working with Abundance New York. This is a great organization working to build a more vibrant and dynamic New York led by people who believe our powers are rooted in growth and change.

In 2025 Abundance New York:

• Won high-friction policy fights. Helped get congestion pricing back on track and passed City Charter amendments enabling fast-track rezonings and up to 130% increases in housing capacity.

• Unlocked housing supply. Backed City of Yes and key rezonings in Midtown, LIC, and Jamaica, and pushed the Brooklyn Marine Terminal plan through delivering 6,000 homes (40% affordable).

• Built reach and leverage. Grew to 4,300 members across 45 Council districts, generated ~$800k for aligned candidates, and launched a voter guide viewed 375k+ times that filled a real civic vacuum.

I wanted to share their annual report highlighting all of the great work they’ve done this year and the big wins they’ve put up along with an appeal to join the organization/join the fight for a brighter New York.

And now Ryder Kessler one of the co-founders of Abundance New York is leaving the organization to run for office! I hope you’ll join me in supporting his campaign for NY State Assembly to make the whole state more abundance-filled.

I had wrist surgery on Tuesday and can’t type. Since then, I’m really enjoying wispr for voice to text.

It’s the deployment, dummies

All model development could stop today and we’d still have decades of implementation work to realize the promise of AI. The bottleneck isn’t scaling raw capabilities and the task of our time isn’t developing the machine god. It’s successfully deploying AI throughout the economy to accelerate GDP and raise living standards worldwide.

We’ve done this before, and it took forever

Computerization took roughly two decades. The shift to the cloud is still ongoing after 15-20 years. There’s no reason to think AI will be faster. Most of the economy isn’t using AI at all. A large portion has a top-down mandate to “do AI” but is failing to deploy anything meaningful or quickly. Only a tiny sliver of businesses and developers are credibly AI-native.

Why implementation is failing

Companies that want to move fast can’t. It takes vision and risk. And even when the will exists, organizational inertia, internal politics, patchwork infrastructure, etc. get in the way. It’s not just “change management is hard” (it obviously is).

Most companies don’t have data infrastructure anywhere close to what AI requires. Meanwhile, the complexity of enterprise environments is rising faster than the capabilities and visibility of those tasked with transforming them.

Where I’m looking

• Collaboration: Git was built for scarce, human-written code. Now enterprises are generating more AI code and shipping less of it. Whatever replaces Git will be built for that reality.

• Services: SIs/consultants are a critical chokepoint ill-suited to the task. There’s a huge opportunity to build new service providers on back of new capabilities and power AI transformation, better, faster, cheaper.

• Growth by buyouts: The product company acquires and transforms the operating business directly while owning all the upside.

• Apps: When you’re selling work you can fit within existing workflows like a person, just better, faster, cheaper.

Over the next decade there’s a foundation model-sized opportunity in deploying AI into critical systems throughout our economy and around the world. Developing the technology is not enough.

Cyber Dinner

​AI is breaking $1.5T of security market cap.

​For 30 years, cybersecurity has worked because attacks have had known limitations. Businesses have also had a concept of control: how to secure within a perimeter, how to vet vendors, and how to remediate gaps or accept known risks. The $1.5T security market cap was built on the assumption of visibility and control. That known landscape is gone with AI.

This winter I’m teaming up with ex/ante and Outtake to host a dinner and discussion in NY about the changing threat landscape and how new and existing security companies will meet that.

Apply to join here.

Virtue signaling

Elite consensus is starting to turn on the “anti woke” aesthetic and vice signaling. Sports betting is the canary in the coal mine for the great re-wokening that is coming. Get ready to see CEOs libbing out again within the decade.

New sincerity comes next. Everyone will talk about kindness, craft, moral virtue as the ways to redeem your soul and the character of the nation. Decency will go from being not just not cringe to actively in vogue. Eventually that will metastasize into facsimile and performance and we’ll reach the 2020-style ethics again.

Gen Z pining for peak millennial aesthetics and culture is more evidence of this larger trend. Prepare for libbed out “awesome sauce” imminently.

I Read

• The peasant logic of MAGA politics. On an abundance vs. scarcity mindset and the politics/ sociology of zero-sum thinking

• Tech bros head to etiquette camp as Silicon Valley levels up its style. More fun coverage of our etiquette school this time in the Washington Post. This is definitely a thing! I expect we’ll be taking etiquette school on the road next year. Hitting more cities, more founders, more venues.

• Shock jockey capitalism. Good long peace from Will Manidis on the increasing tendency to compete over “who can say the biggest number” in venture/startups.

• Syria after Assad: A year in numbers. Things in Syria are still really bleak but this is a bit of a white pill with some hope on the horizon starting to come through in the numbers.

• Power Law And The Long Tail - AVC. I was reminded of this (old) piece from Fred Wilson over the last week because of a reference from Euclid Ventures. Even if all of the money gets made on one end of the distribution (the biggest winners), all the time gets put in on the other (with the relative losers). It might seem non-economic to do that but in a business where your reputation and your network are everything, devoting that time does make sense and the emotional investment is so high.

This week was SF for our small holiday party + some meetings + the etiquette school book launch (more below).

I’m getting wrist surgery next week which will make typing hard. Expect shorter prose.

Pivots: changing the vector or the destination

Pivots can really suck for founders and we don’t want to pressure people to “make it work” when it’s not working/isn’t gonna work. In general, we don’t support people trying stuff just to try it when the original idea has clearly failed

But there’s a lot of space between that and the obvious fact that in very early companies you’re largely betting on people and general directions; the rest is subject to change and experimentation.

So what kinds of pivots should you do/do I (generally) support? I think there’s basically two kinds:

1. Type 1 pivot: change the angle of approach on a consistent vision or focal point. This is just wiggly early stage experimentation and iteration with consistent commitment to a vision of the future.

2. Type 2 pivot: change the end point and thus the way you get there. This constitutes changing the company entirely. It almost never works because you’re starting over at a disadvantage (less money and time).

Much of my investing/process with founders is about working backward from big themes and stories to companies that are worth owning in that future and finally how to start working toward them today. Within that framework, pivoting/changing the angle of approach is a question of “how” not “what” or “why.” So type 1 pivots are not only common but good.

And anecdotally, when founders ask me for an opinion, their pivots usually fail. But when founders tell me about a decision, their pivots usually work/go well.

Make of it what you will but I think it largely comes down to conviction and speed of execution. This is over enough examples and time to be a pattern.

Of Course We’re in an AI Bubble

A couple weeks ago Fred Wilson referenced Evan O’Donnell’s work tracking token usage to demonstrate that we’re not in an AI bubble. He concludes that “The current infrastructure spend rates are justified if the current rate of AI usage continues. If the growth rates start to decline, there could be trouble.”

But this is the wrong mental model/wrong question to ask.

In the 2000 crash, (revenue) multiples were blown out. And again in the 2021 private tech bubble. But here there is no doubt about the (token/revenue) growth being real. The multiples, at least in the public markets, are sane. Instead, this time around the revenue/usage itself is dubious.

No sane person is arguing that AI companies aren’t growing exceptionally quickly: from VC backed apps to Nvidia this is obviously true. The questions are in the retentive quality and earning power of that growth. Valuations, obviously, are forward looking.

In more strictly market terms, Felix Salmon claimed that we’re not in an AI bubble because 1) it’s not a get rich quick scheme 2) there are no greater fools 3) it’s not speculative. This is wrong on all three counts.

1. There are get rich quick schemes. There are ample ways to get rich very quickly from AI investing and many people are cashing in on. These include: selling stock in the hot companies (there are active secondary markets and they function like public companies), raising capital as an SPV provider and charging origination fees (the practice has been widely documented), and most significantly just raising huge sums of capital for funds (mgt fees to invest 500M at a time will make you very rich upon signing the docs).

2. There are greater fools. It’s not strictly speaking “retail” but there is absolutely a retail-like cohort of HNWI clamoring for exposure here. They are/will be the bag holders, as very likely will Joe Public both through the IPO market and government guarantees.

3. It is highly speculative. Just because the speculation is (mostly) happening in private/semi-private markets, doesn’t mean it’s not speculation. With #1 and #2, there are ample opportunities for purely speculative investing.

You don’t need to work my word for this - the inflaters of the bubble will say so themselves! The argument is not that AI is not a bubble but rather whether or not bubbles are good or “worth it.” It’s a Carlotta-Perez-style argument. TLDR bubbles are good/have utility because they lay the groundwork for R&D and buildout of ultimately useful infrastructure.

The question isn’t “are we in an AI bubble.” We are. The question is “so what?” What do you/we do or do differently?

Hamlet’s seed round

Most of the power that matters to businesses building in meatspace lives in four hour council meetings. And most companies only experience local politics as a blunt yes or no on a project. The actual logic sits in badly indexed hearings, PDFs, and livestreams that nobody watches. The arcane obscurity of local council meetings is one of the key mechanisms by which NIMBYism holds back dynamism and abundance.

Hamlet is trying to flip that. Take the raw exhaust of local democracy and turn it into something you can actually reason over when you decide where and how to build. Hamlet ingests agendas, minutes, and meeting video across cities and turns them into structured intelligence. Covid put local government online and LLMs made their proceedings parsable.

Customers developing data centers, energy projects, and housing use Hamlet to see when issues, parcels, or asset types they care about show up on an agenda. They can search across transcripts, pull exact quotes, and understand how individual councilmembers think about a given use. Hamlet helps critical industries build better, faster, and with more community engagement/support.

Over time, Hamlet is building a local decision graph and operating system for doing business in cities: agents and tools on top that handle site selection, risk scoring, and briefing prep. It also helps unblock a major artery of permitting, community engagement, and local development. If you care about an abundant future in the real world, you have to care about councils, boards, and the information systems that sit on top of them.

We are excited to share that we have led Hamlet’s seed round, with participation from Animo and Crosslink. Hamlet has raised nearly $10M to date.

Hamlet CEO Sunil Rajaraman is the most Abundo-pilled founder we have backed to date. Sunil is a repeat founder and seasoned operator, having founded or helped build Scripted, GoodRx, and Metromile. Most importantly, he has real vision and conviction for making local government a more effective, operable interface for operators and communities.

You can read more about the company in Techcrunch and you can watch Hamlet TV on Apple TV and Youtube. Hamlet TV is hilarious - it’s just the most out of pocket moments from local council meetings as a compilation.

Links

• How this 21-year-old college student used AI to build ‘Learning with Lyrics’. This is my favorite instagram account right now.

• You’re on Ozempic? How Quaint. We’re all gonna be on GLP-1s and they’re gonna be better and better (they might not even technically be GLP-1s pretty soon).

• Democrats have their own extremist problem.

Etiquette Guide

Slow’s Etiquette Guide for modern business has launched on Amazon! Tech and startups aren’t outsiders anymore. We’ve won.

Slow is doing important work to make sure people show up accordingly with poise and grace suitable to the task of running the world. The titans of industry used to build museums and cultural institutions. Etiquette school might be the start of reviving that noblesse oblige among founders.