In a recent batch talk, YC General Partner @t_blom broke down how to build a self-improving, AI-native company.
He walks through how to create recursive, self-improving AI loops, and why founders who get this right will run companies that improve while they sleep.
00:00 — Companies Are Roman Legions
00:54 — Copilots Are the Wrong Mental Model
01:55 — Extract the Domain Knowledge
02:24 — The Recursive Self-Improving Loop
04:12 — The Holy Shit Moment at YC
05:50 — Self-Optimizing Product and Support Loops
06:29 — Burn Tokens, Not Headcount
07:23 — Middle Management Is Over
08:05 — Make Everything Legible to AI
09:40 — Regenerating the YC User Manual
11:19 — Software Is Ephemeral, Context Is Valuable
12:18 — Where Humans Still Matter
This is how I got 1M users in 6 months
Finally dropping it! It's 60 pages lol
https://t.co/2qcH9lsUOM
If you repost & follow, I'll send you some extra sauce🌶️
Researchers just mathematically proved AI layoffs will destroy the economy.
Using game theory, two economists from UPenn and Boston University mathematically proved something uncomfortable.
Every company replacing staff with AI is also firing its own customers.
Laid-off workers stop spending. Revenue collapses across every sector.
Yet no firm can stop. If they don't automate, rivals cut prices and steal market share.
So everyone automates, knowing it ends badly for all of them.
The researchers tested every proposed fix:
> Universal basic income fails
> Capital taxes fail
> Profit sharing falls short
> Collective bargaining can't hold
Only one mechanism works.
A per-task automation tax that forces firms to price in the demand they destroy.
The context is already grim.
Over 100,000 tech jobs vanished last year, with AI cited in most.
The math says the cycle won't break on its own.
Introducing Tolaria! 💧
Today I am releasing a macOS desktop app for managing markdown knowledge bases, and helping both AI and humans operate them.
It’s free and open source, and always will be.
I have been working on it for three months, and I now use it to run my life and work. I personally have a massive workspace of 10,000 notes — the result of 6 years of Refactoring — which I now operate on Tolaria.
Tolaria is the main collaboration surface with my AI agents: they create new notes there, connect them to what exists, and edit existing ones. Everything is easy to understand for them, because it’s just markdown files. In a way, it’s my implementation of @karpathy's LLM wiki.
Tolaria is also the biggest experiment I have ever run about writing software with AI:
• 2000 commits
• 100K+ lines of code
• 3000+ tests / 85% coverage
• 9.9/10 code health
• 70+ architecture decision records
I am releasing it open source also to use it as a living artifact of how I do AI coding, so you can inspect at any time things like how I write docs, what's in my AGENTS file, what hooks do I run, and so on. You can find it below:
• Newsletter announcement: https://t.co/NFzPASLrNK
• Website: https://t.co/R9qTFAeQv9
• Github repo: https://t.co/ck9gfwpzZG
Let me know your thoughts!
We built our launch video in Claude Code using HyperFrames.
Now it's yours.
Open source, agent-native framework. HTML to MP4.
$ npx skills add heygen-com/hyperframes
RT + Comment "HyperFrames" to get the full source code of this launch video (must follow)