Afik Cohen

🤖 cto & co-founder @houdinirobotics • 𝕥𝕣𝕒𝕟𝕔𝕖 𝕕𝕛 • ᴍᴇᴛᴀᴘʜʏsɪᴄɪᴀɴ
🌉 SF, CA

@[email protected]

[成龍 @graphtraversal]

at walmart rn and everyone looks abliterated and quantized

[Afik Cohen @aphex]

we're building #6, #11, #12 @houdinirobotics

[Vishal Singh @vishalsingh2972]

There is no moat, but there are still countless problems to solve. And where there are problems, there are opportunities.

The biggest opportunities right now:

1. build for solving loneliness (the more AI floods everything, the more people crave real human connection, IRL and small social)

2. build for agents that need to spend money (they're getting virtual cards and budgets, someone builds the spend controls, fraud protection, receipts)

3. build for people drowning in AI output (everyone generates infinite drafts now, the bottleneck moved to reviewing and choosing, build the judgment layer)

4. build for the burnout economy (everyone is expected to always be on and always optimizing, and the backlash toward rest, slowness, and enough is building)

5. build for verifying humans (deepfakes broke trust, every dating app, marketplace, and video call needs proof-of-human)

6. build for the physical world (the trades, hardware, robots that AI is finally reaching)

7. build for the agent that answers the phone (every local business misses calls, a voice agent that books the job creates real value)

8. build for the aging population (millions of older adults want to stay healthy, sharp, independent, and connected)

9. build for the LLM-search land grab (being the cited answer is the new SEO)

10. build for the newly automated (the paralegal, analyst, and marketer whose job just changed and needs to reskill fast)

11. build for the seat-pricing collapse (software moving from per-seat pricing to per-outcome, whoever nails outcome billing wins a category)

12. build for AI enablement (millions of businesses still use nothing beyond basic AI tools, someone has to onboard them)

13. build for the agency everyone resents (businesses pay thousands to agencies for repetitive work, an agent that does most of it can undercut the model)

14. build for verticals on outdated software (dentists, HOAs, contractors, and local businesses overdue for an AI-native rebuild)

15. build for reviving dead software (thousands of abandoned apps with real users, agents can maintain what a team couldn't)

16. build for markets too small to matter before (500 lobster fishermen was never worth a team, now it can be a real business)

17. build for agents hiring agents (an emerging machine economy needs escrow, reputation, identity, and dispute resolution)

18. build for the anti-AI premium (as everything gets generated, human-made and analog become status symbols people pay more for)

19. build for distribution-first (anyone can build the product now, so the audience becomes the advantage, media first, product second)

20. build for the reinvention of college (traditional degrees are being questioned, practical skills and alternative education are becoming more valuable)

21. build for a world with more free time (if AI takes the busywork, what people do with those hours becomes a massive opportunity)

22. build for the return to the physical (screens fill with AI slop, people crave the real world, hands-on, local, and analog)

23. build for the caregiving wave (the population is aging fast, millions are caring for parents, and families need better support)

24. build for the longevity shift (people want to live to 100 healthy, and an industry is forming around managing personal health)

25. build for the housing and rootlessness problem (people struggle to afford stable homes, creating opportunities for new housing and community models)

26. build for spiritual hunger (as institutions change, the need for meaning, ritual, purpose, and belonging is growing)

KEEP BUILDING.

[Afik Cohen @aphex]

@Steve_Yegge

[Afik Cohen @aphex]

glad I've had my gas city set up since January. getting every system patched this week took a few slack messages to my mayor ⛽ @Steve_Yegge

[Alan Wells @alanwells]

Just spent the last 7 days on the front lines of the vulnpocalypse fending off an active cyber attack on one of our products.

Some thoughts:

- Software factories are going to be required equipment for everyone. There’s just no way to keep up with the pace of highly automated adversaries without one.

- We were lucky because we had spent the last few months getting our software factory running well. It is nice to have for product development but proved to be absolutely essential this week.

- At the minimum you need to have a coding server in the cloud pre-provisioned with read only access to all your logs and all the services you depend on for observability. With that in place you are a prompt away from reasonably good situational awareness, ongoing monitoring with loops, and ability for coding agents to validate fixes against your actual, observed attack patterns.

- Shared coding server also unlocks multiplayer incident response where everyone can see every session and jump in as needed. Sharing session links that can be forked is much higher bandwidth than re-explaining things.

- You don’t need to be Ramp/Stripe/Uber scale to have a working software factory in the cloud. We are a team of 3. Ours is built with an @opencode server (thanks @thdxr!), a forked version of compound engineering optimized for automated workflows (thanks @kieranklaassen!) and a multiplayer agent in slack that handles crons (we have our own harness but pick your favorite here).

- To get our software factory up and running well, we had to stop all new product development for ~6 weeks and just focus on getting the validation systems working that enabled us to reliably shipping PR without human code review. This felt very painful in the moment but was totally worth the eventual speedup in velocity.

- KYC for @AnthropicAI & @OpenAI cyber programs is now easy and quick (at least for defensive access), but a day felt like a lifetime this week. Submit your app now before you really need it.

- Getting Mythos access unlocked a deeper level of analysis that helped us shift from reactive mitigation to proactive patching. Wish we had done this a few weeks earlier. Get started now!

[Afik Cohen @aphex]

@jjkaplowitz @a16z @edgarpavlovsky @nickco @barrett_io @natabr75 ill be at long horizons for most of the day but count me in if there's room, I'll have one of our quadrupeds with me too 🐶

[Talmage Johnson @talmagejohnson_]

Hey! Hopefully this post catches you before you end up doomscrolling for another few hours, left feeling like garbage.

It's really not worth it, my friend.

Instead, go build, learn, take a walk outside, call a friend, or even sit in silence. You'll feel much better.

[Nikita Bier @nikitabier]

Technical moats are mostly over at this point. If you’re building something that is meant to be durable, the only moats now are:

• Proprietary data
• Network effects
• A physical component

[Andrej Karpathy @karpathy]

Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel.

- Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all.
- Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract.
- Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code.
- And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while.

The funnel is driven by a combination of factors:
1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel.
2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel.
3. Access. Free-tier, paid-tier, internal.

So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.

[Afik Cohen @aphex]

@bcherny

[Emm | scenario.com @emmanuel_2m]

I'm not sending my deck anymore 😂

[Afik Cohen @aphex]

@taylorhou @quantbagel @houmanoids yeah check us out at https://t.co/reFWbye4E1. nice to meet more @hf0 friends after spending the summer with @emily_yu 🤠

[Afik Cohen @aphex]

i had opus 5.5 submit $10,000 worth of health insurance claims for me while I slept. luigimaxxing

[Paul Graham @paulg]

There were a lot of things that only worked because there's a limit to the rate at which humans can operate. We're about to find out what all of them are, as they break.

[anabology @anabology]

I gave Claude another 18 hours.. and I think this one is the best one yet

Macrohard: Windows XP

I'm blown away

[Josh Holder @joshgholder]

@sensho I think it’s a bit early to call it, but it is pretty wild. The demo from @GeneralistAI blew my mind, and ~2 weeks later Astra is casually matching it

[sensho @sensho]

oh my god i just tried gpt 6 astra ultrafast controlling a robot in a sim... it's literally so over for specialized robotics models. it'll just be super fast agents. never been more pilled on scaling laws.

[Tim Denning @Tim_Denning]

I’m in love with this sentence:

You need to be more afraid of wasting your life than embarrassing yourself.

[Afik Cohen @aphex]

brb installing a gascity mayor on my muse (cc @Steve_Yegge)

[Federico Viticci @viticci]

I don't think people realize you can install Claude Code inside Muse lol

[Derek Grudnicki @drkcsm]

When a friend in SF says they’ll bring their “dog” to the park 😂 @aphex @JakeMaltesen

[Afik Cohen @aphex]

a dog even a cat person can like 🐶

[Derek Grudnicki @drkcsm]

When a friend in SF says they’ll bring their “dog” to the park 😂 @aphex @JakeMaltesen

[Afik Cohen @aphex]

@amitku dm'd! can bring one of our quadrupeds with me to this one 🐶