On Rent Seeking

2026.10.18

CLXXIV

[No Risk, No Reward; What 8 Mile Taught me About B2B SaaS; Pantheon of Investors; The Post Hoc HBS Case Disease; I Love the Current Thing; No Knockout Risk; Doxxing VCs; Love, too Requires Sacrifice]

Thesis: There are no free lunches; trying to function like there are is a chief sin.

[No Risk, No Reward]

I'm a founder, but I still have the spirit of an investor.

I'm bootstrapping, but running a hacker house means I interact with Venture Capitalist's (VCs) quite regularly.

Maybe 5 years ago, before I really started entering the startup world, I had this impression that maybe half of VCs would have some good behaviors that made them like the legendary investors I look up to.

Unfortunately, I think it's much more like 1 in 50 of VCs who have this kind of behavior. A lot of them are professional pattern matchers who are running from risk and original thought. Pattern matchers give the appearance of being employable, but are easy to dupe.

The underling issue leading to this is a lack of consequences when you are wrong or say something that isn't true.

You think no one's keeping track, but we are.

[What 8 Mile Taught me About B2B SaaS]

WARNING: Spoilers for 8 mile in this section.

I finally watched 8 Mile a couple of weeks ago and loved it. It perfectly encapsulates how you should think about building a startup.

Basically, Eminem's character, Rabbit, is trying to use rap to make it out of the trailer park. He spends the movie getting beat up spiritually and physically. While he does, he watches everyone else saying they'll make it out while wasting their time on frivolous things like fights and rap battles and parties and TALKING about making it out.

At the end of the film, he has this amazing rap battle where he absolutely kills the competition.

At the end of the battle, his friends want to celebrate with him, saying he's the king now, etc.

Instead, Rabbit literally goes back to his shift at this factory job to make more money to get studio time. This way, he can record a demo that he owns to start sending around to try and get a deal.

In brief, he found the one thing that would get him what he want and said no to everything else.

Talking about rapping is not the same as rapping.

Likewise, spending your days running around to networking events or getting on the phone with yappers is not going to move your business forward.

For WhiteWhale, literally the only two things that matter are product and customer acquisition (retention is downstream of product; conversations about retention exist to improve product). Some other things need to be attended to, like finances, and they get handled until they're done; the focus, though, is clear.

[Pantheon of Investors]

I've spent a lot of time studying legendary investors & traders. Nick Sleep & Qais Zakaria, Mark Spitznagel, Peter Thiel, Nassim Taleb, Warren Buffett, Charlie Munger, Carl Ichaan, Jim Simmons, Bill Gross, Jeff Bezos.

I think it'd be kind of silly to allege that there's this one crazy pattern that these people all follow. But here are three commonalities relevant for this post:

• First Principles: None of them use 'pattern matching' to justify investments; they might find an idea because it was like another good idea, but that's not enough to make the investment. It has to stand on it's own merits.

• Time Scale Awareness: They are all aware of the timescales that it may take them to be right and build structures that let them hold the investment for that long.

• Price Awareness: They understand that a solid business at a great price can get a better return than an exceptional business at an obscene price.

They invest a lot of their time in getting these things right. Think, Sleep & Zakaria flying to Zimbabwe to evaluate some companies. The deep understanding of the investment is one of the key drivers of their returns, the the equivalent of Rabbit getting studio time.

I think this actually neatly contrasts a lot of things I'm seeing from the plurality of current VCs do. I’m seeing a lot of:

• Surface Level Pattern Matching becomes the thesis, which makes the VCs really easy marks.

• An investment ‘eventually working’ is good enough; pressed a VC with a 7 year fund cycle on when AI would take everyone’s jobs, and he said, “10, 20, 50 years - it’s going to happen!”

• Infinite Price Tolerance: If they think it’ll change the world, they’ll pay literally any price.

This all isn’t so good and I think results in a lot of shallow thoughts and spray and pray diversification that none of the above investors would tolerate.

[The Post Hoc HBS Case Disease]

There's this really weird thing among many of the MBA type where they gravitate to stories of successful businesses from the past. These stories always come with a post hoc justification of why the business over came it's problems.

The issue with this is that it can make you sound smart but it can also be complete and utter bullshit. It results in more pattern matching than critical thinking.

It's quite challenging to understand cause and effect in complex systems but we as humans have an urge to do so - of course we do!

This is worse when we already have priors about how the world works and are trying to justify them. If I am a turkey and I get fed every day by a farmer, it'd be convenient for me to think the farmer was friendly and had my best interest at heart. Then, I'd get free food the rest of my life.

At day 1000 of being fed, my trust is the highest. Then I am slaughtered for meat!*

There are these things called HBS (Harvard Business School) Case Studies that come, obviously, from HBS, and get circulated to the other schools. Basically, they outline a problem that a real business faced, and then ask the students to come up with a solution.

Then, the teacher reveals the solution that was actually used.

Listen, studying history is obscenely useful! I literally just gave you three strategies I’ve extracted from studying investors. One important note here is that I can tell you those things, but I’m also independently verifying them as I continue to use them in practice myself!

However, at a business school, building a culture around problem solving via Case Studies, seems to promote this cultural where "knowing about" how Costco does it's pricing is mistaken for the same thing as either being able to come up with a good pricing model yourself or being able to identify a good one.

These really are not the same thing! A massive important difference is that whoever made these decisions at Costco was at risk; they had to make the right decision. Sitting in a classroom reading a case study gives you no risk if you 'make a decision' in the case study that would fucking bankrupt the business as long as you can justify it to a prof who also doesn't really have any risk at all either.

'Knowing trivia' becomes tantamount to making you employable! For some reason, this is more of a currency than being competent is, which makes me really sad.

_{*For more on the Turkey Problem, see Taleb’s Fooled by Randomness or this blog post of mine.}

[I Love the Current Thing]

I used to be under the impression that maybe half of the VC I met were going to be like the legendary investors I look up to; in practice, I think that there's less than one in fifty I would trust deploying my capital or trust to be involved in my business if I took money from them.

Part of the problem, I think, is that the Post Hoc HBS Case Disease is flourishing among them right now.

A behavior I've noticed among these people is that they tend to talk about the most recent highly valued, rapidly growing company as if the reason it's worth so much was obvious. The amount of times I've heard a VC casually mention Mercor or Cursor in a way that is drenched in confidence, that says "I KNOW why it went up and to right so fast" is obscene.

The thing is, they DON'T know what went right. They know the things that everyone else is saying about it, including some dude with a twitter thread. These are not the same things as the things that really went right!

One of the reasons this is sooooooo problematic is because they then use this shaky narrative to dictate their future investments.

This is actually even worse than you'd think because the above narratives are often about companies with completely opaque financials where it's not yet clear what % of their valuation is based on sticky, value creation, or how much would get absolutely ripped to pieces in a public market. Which, by the way, is where many companies have to go to ever get liquidity, because where else are you going to find more dollars to support trillion dollar valuations?

I don't care enough to research the narratives VC's are talking about, but I'll give you one that's gleaned from maybe half a dozen conversations I’ve had in the last quarter. To be clear, I don't concede ANY of these points, but it's what I'm seeing out there in the wild:

• OpenAI & Anthropic are 'doing so well' because they have a generalized product that can automate all of knowledge work

• Humanoid robots are a technology general enough to automate all of manufacturing

• LLMs with a ton of training data 'solved knowledge' work, so LLMs with a lot of data will solve robots

• Companies like Mercor that sold data to OpenAI & Antrhopic made a lot of money, so companies that sell data to robot companies will make a lot of money!

• We should invest in robots and data collection companies for robots, QED

This narrative becomes law and then everyone invests in these things. You ask questions like "why don't we figure out automated forklifts" or "are there significantly simpler systems or automatons that would be improvements without full humanoids" or "how do you solve for statelessness" or "why not robots with 8 arms wouldn't that be more efficient" and then you just get non answers from them.

I get it, robots are cool, and you might be right; but how you get there is so important! Because the nuance you derive from evaluating the claim “are robots the right form factor for automating factories” on it’s own merits potentially contains the kernel for a super interesting thesis that maybe involves but maybe doesn’t involve human robots.

If you just say “Yes, obviously, look at LLMs!” you miss the chance for original thought, which can make a lot of difference.

[No Knockout Risk]

The real underlying issue isn't that the above disease has proliferated among the ranks of the capital allocators; I think perhaps it is a symptom of a root cause is that there's no knockout risk.

If these people were investing in public markets the way they invest in startups, we'd see far more Leopold Aschnenbrenners.

There's a lot of plot armor in private markets that can insulate you from consequences. Nobody seems to register the fact that if you have a fund with a 7 year time cycle you shouldn't really be talking about 50 year time cycles unless you're genuinely capable of holding an investment for 50 years.

It's kind of a weird distortion. The other distortion is that if you have a 7 year fund, you make investments in year 1 and 2 and 3, and some of the companies are worth more in year 4 or 5 or 6 and you don't actually make any money from it, you can still raise a second fund with more AUM. This is regardless of whether or not ALL of the companies you invested in in fund one go bankrupt eventually; if they go bankrupt later, it doesn't matter, because you've already raised a fund with 10x more AUM so now you're actually rich. [See zombie unicorns]

This isn’t so good: you can make a considerable amount of money even if you're very, very wrong!

Also, another distortion is that a single person can be a very good investor, but that doesn't necessarily mean that he or she is inherently enable to build a 25 person company full of good investors, either. The track record can get them enough AUM to hire people and turn it into a business, but that doesn't mean that they should hire people and turn it into a business!

[Doxxing VCs]

I go back and forth on 'naming and shaming' VCs who spew bullshit or fuck over founders.

I generally lean towards not sharing these things online for a lot of reasons; basically, though, I think there is something that happens to information when it is made available online that just makes it seem less real and more questionable. It enters a noisy pool.

That said, internally at our Hacker House, C House, we strongly encourage founders to share their experience with Venture Capitalists. What it's like talking with them, working with them, etc. We take this so seriously that we've turned down events with VCs because there has been bad feedback from residents about them, like yanked term sheets.

We're all constantly trying to evaluate if these investors are attempting to have their own ideas that they can independently justify or if they're following the crowd without validating.

I'd encourage you to behave this way in your own community and networks, too: have a real memory, and share it among peers when appropriate. Don't make a habit of shit talking, because that’s not going to move your startup forward. But, if someone asks you what you think about so and so, sharing is quite important to actually hold people even just a little accountable.

If you like hearing about start ups and ai and ethics and philosophy from a slightly unhinged & verbose person who is in the trenches, please hit me with a subscribe.

[Love, too Requires Sacrifice]

Anything worth while, business success, market returns, and even love, it all requires risk and sacrifice.

Giving one thing to get another.

Claims and promises that aren’t backed by action, that don’t accept the consequences of conviction, are meaningless.

In the longest term, the world doesn't reward people who try to shelter themselves from all risk.

Put yourself out there. Believe in something and act on it. If you’re wrong, you’re wrong.

Spend yourself on that which you’re convicted in and that which you love, unabashedly. You’ll find that when you give yourself this way, you’re not actually diminished; you’re made to be more than you ever were before.

I’ll leave you with Jack London:

Live Deeply,