Jonathan

Building | force of chaotic good

prev. @Roblox @NEA @utaustin @DiligentRobots, @TrueVentures

[Jonathan @wonathanjong]

@Thariq_q yuppppppppp

[Jonathan @wonathanjong]

@googrish this is huge! why use a generalized model, when you can train your own with ease!

[girish @googrish]

“don’t train your own model” is common ai advice. it's wrong. your token bill's the proof.

today, we’re excited to launch castform into open preview. castform is the easiest way for you to train your own model, on your own data.

open-weights models are performant and much cheaper. when trained on your task & proprietary data, they beat closed models. the thing standing between you and that was weeks of plumbing & years of ml expertise.

with castform, model training is as simple as prompt engineering. @castformai

bring your agent traces or raw corpora. castform turns it into training data, picks the right algorithmic recipes, manages gpus, and gives you an ide to watch and chat with your model as it learns.

see what you can build with castform👇

[Thariq @Thariq_q]

I got tired of managing 8 Claude Code tabs, so I built Pokegents, an open source multi-agent workspace for coding agents.

It has a Pokémon-themed dashboard/chat UI, persistent agent identities, MCP messaging, notifications, session cloning, and a local orchestration server.

[Tiffany Day @tiffdidwhat]

HALO is now yours…

[Rage ❉ @ragecvlt]

😹🫵

[Om Patel @om_patel5]

stop spending money on Claude Code.

Chipotle's support bot is free:

[Jonathan @wonathanjong]

@idavidrein https://t.co/wFxw0YZhmd

Read this book and lmk what u think

[Michael Dempsey @mhdempsey]

(New Essay) VC-Backed Startups are Low Status

The traditional VC-backed startup path is becoming low status in the same way investment banking did. An aesthetic collapse across institutions, ideas, and founders paired with the world's tiring of tech has recently accelerated this shift.

Some thoughts on the cascade, the generational divide, Anthropic vs. OpenAI, what comes next, and more.

[Dmitrii Kovanikov @ChShersh]

I just can't anymore

[dax @thdxr]

you can vibe code all of it

who cares

lie to yourself

pretend it's a clever strategy

but everyone will know

they can feel it in your work

how lazy you've become

how little you care

because how you do one thing

is how you do everything

[tamagui @tamagui_js]

Tamagui 2 FINALLY here

...and it's a ridiculously loaded release.
we've been hitting the gym, and we're back

[Fede’s intern 🥊 @fede_intern]

China is trying to win by commoditizing the complement and I believe they are close to succeeding.

For the last two decades, the West exported cognition because it owned the platforms, the cloud, the software distribution, and the talent concentration. If the cognitive engine becomes cheap, portable, and good enough, that asymmetry weakens. A small country can buy or download the same cognitive machinery, then apply it to its own bureaucracy, its own companies, its own language, its own domain problems.

The West has dominated the thinking and services world. Software, finance, media, research, management layers, and the export of expertise. The US is the cleanest example. In 2024, US services exports were about 1.1 trillion dollars, the highest on record. The US and the West sells thinking at scale. AI threatens to flatten that advantage because AI turns thinking into infrastructure.

China dominates the atoms world. Industrial capacity, manufacturing throughput, physical supply chains, cost curves. In 2023 China produced about 28 percent of global manufacturing value added.

If you can make the layer next to you cheap and abundant, you drain its pricing power and force value to move somewhere else. In AI, the complement is model access. For a lot of Western companies, the business is still basically gated intelligence sold as an API. China has every incentive to make that layer feel like electricity: available everywhere, cheap, hard to monopolize.

Open weight releases are part of that play: DeepSeek, Qwen, Kimi and MiniMax are only a few of the chinese open source models. Once strong models are common, model access stops being a moat. It becomes a commodity input.

A huge fraction of what we call services is legible work: reading, writing, coding, summarizing, translating, drafting, answering, generating variations, searching a space of options. That layer is now replicable and it is getting local. Apple is publishing technical reports about on device foundation models, including aggressive quantization aimed at making serious inference run on consumer hardware. When strong models run on a laptop, countries stop importing thinking as a service. They import weights, or they distill, fine tune, and deploy inside their own borders.

I believe that:
1. China stays strong in atoms because it already has the scale advantage.
2. The West still leads in many areas that require deep institutions and long accumulated competence, including parts of frontier research and high trust services.
3. But AI compresses the services premium by making a large portion of cognition cheap and replicable. That is why open models matter. They are a weapon that attacks the margin structure of the thinking economy.
4. If you sell intelligence, this is bad news. If you own distribution, hardware, data, or a workflow people cannot easily leave, you survive. If you own atoms and you get thinking for free, you get a scary combination.

I would love to know if anybody believes I'm wrong.

[dax @thdxr]

this costs $20K and it's on consumer hardware and this model is very very good

lot of companies are already spending $10-20k per dev per year on cloud inference

can't believe we're here already

[Jonathan @wonathanjong]

@jasonbosco king shit

[Will Manidis @WillManidis]

convinced that adults have totally forgotten how to have fun in conversation. every conversation is either "checklist catch up on life events" or "grave discussion of public events we must feel sad about". we've totally lost the sense of play. hold your beliefs loosely, laugh.

[Jonathan @wonathanjong]

once I’m 25 and my frontal lobes are fully developed it’s over for you hoes

[Jonathan @wonathanjong]

@aditimerch @Nature you legend. incredible work

[Aditi Merchant @aditimerch]

What if we could autocomplete DNA based on function?

Today in @Nature, we share semantic design—a strategy for function-guided design with genomic language models that leverages genomic context to create de novo genes with desired functions.🧵

https://t.co/P5qVJB3qIY