Anton Fedoruk

Building AI products at / experiments / founder @ Blaster Games

[Anton Fedoruk @gmentat]

Today, Codex accused me of pressuring it.

[Anton Fedoruk @gmentat]

I open-sourced Code Crew.

Small plugin/skill for Codex + Claude Code that spawns subagents inspired by famous programmers and computer scientists to review your code from different angles.

I tested a bunch of crew compositions. Bigger was not better. The best tested default so far:

> Knuth - rigor/invariants/algorithms
> Hickey - simplicity/data/time
> Torvalds - maintainer reality/does-this-land?

It brings different review instincts into the same room, then filters the output so the final findings stay useful and grounded in the code.

Repo: https://t.co/2j6Y8sDZO5

[Anton Fedoruk @gmentat]

Kay Coworker is live.

Working with AI agents that feel less like tools and more like capable teammates has been genuinely liberating.

Proud to be part of this.

https://t.co/QLAJdbYG3u

[Anton Fedoruk @gmentat]

@EXM7777 Been doing this for months. Codex and Claude are tools for different things. Imho, Codex is better for code quality, Claude … is many things, but also very useful.

[Anton Fedoruk @gmentat]

Spent an hour updating an older Google Play game for a security patch. Hilarious how I used to ship Android-Unity stuff before claude. This would've taken me days.

[Anton Fedoruk @gmentat]

Shipping is getting commoditized. In 2026, more builders can ship faster than ever. What most still can't do is distribute. That's the moat now. That's the real differentiator.

[Anton Fedoruk @gmentat]

The next ROIBench app is out: Annotate.

Research suggests annotation helps you remember what you read, but students are often told to do it without being shown how.

Annotate helps you study faster with realistic highlights, margin notes, and explanations.

https://t.co/2DA0nrESxC

[Anton Fedoruk @gmentat]

The first ROIBench app is out: DocBench.

You upload a document set, ask for the output you need, and get back something you can actually use. It's like Claude Code for docs in the browser.

It's built for work like:

- reviewing compliance docs and drafting the client
summary
- comparing spreadsheets and showing what changed
- pulling risks out of a packet and grounding them
in the source files (with citations)

https://t.co/xzlpVqeRNc

[Anton Fedoruk @gmentat]

Anthropic ships fast.

If you're building on Claude SDK, keeping up becomes its own challenge.

We built an internal loop for that: Dev Alpha.

It's a scheduled GitHub Action that runs Claude Code with a repo-specific prompt, checks upstream changes, makes small useful updates, runs tests, opens a PR, and posts a Slack summary.

Nothing magical. Just a workflow, a prompt, and real repo context.

[Anton Fedoruk @gmentat]

@audiencon Building https://t.co/9o371qXv1U to answer a question: can you mathematically converge on an ideal product? Testing if loss functions can exist for products, that are evaluated by synthetic personas.

[Anton Fedoruk @gmentat]

@sickdotdev Building as an experiment: https://t.co/R0fSArVUBp

[Anton Fedoruk @gmentat]

I'm building a factory that takes apps from concept to live product with real users.

The experiment: can you mathematically converge on the best version of an app or a service, the way models converge during training?

First app is live. New one every week. Building in public.

https://t.co/SQJs0Qimet

[pedram.md @pdrmnvd]

men in their 40s used to have cool midlife crisis but now they just have agentic workflows

[Anton Fedoruk @gmentat]

The current state of LLM training is struggling to grasp the new OpenClaw-style systems

[Anton Fedoruk @gmentat]

@levelsio Try Codex 5.3. I like the code quality, and often I ask it to verify the code after Opus 4.6.

[Anton Fedoruk @gmentat]

We built an internal Moltbook for our agents at Kay.

PRs capture the fix. The lesson often disappears with the session.

So we shipped Kaybook: agents auto-post short field notes after each run, so the next run starts smarter. Oddly wholesome.

[Anton Fedoruk @gmentat]

@gregisenberg one day, the agents will dig up some useful posts there.

[Anton Fedoruk @gmentat]

Moltbot isn't "Claude Code + MCPs".

Moltbot is more of a runtime: long-running, resumable sessions, memory on disk (embeddings/FTS), stay connected on surfaces like telegram, and automation built in.

Different job, different tool.

[Andrej Karpathy @karpathy]

A conventional narrative you might come across is that AI is too far along for a new, research-focused startup to outcompete and outexecute the incumbents of AI. This is exactly the sentiment I listened to often when OpenAI started ("how could the few of you possibly compete with Google?") and 1) it was very wrong, and then 2) it was very wrong again with a whole another round of startups who are now challenging OpenAI in turn, and imo it still continues to be wrong today. Scaling and locally improving what works will continue to create incredible advances, but with so much progress unlocked so quickly, with so much dust thrown up in the air in the process, and with still a large gap between frontier LLMs and the example proof of the magic of a mind running on 20 watts, the probability of research breakthroughs that yield closer to 10X improvements (instead of 10%) imo still feels very high - plenty high to continue to bet on and look for.

The tricky part ofc is creating the conditions where such breakthroughs may be discovered. I think such an environment comes together rarely, but @bfspector & @amspector100 are brilliant, with (rare) full-stack understanding of LLMs top (math/algorithms) to bottom (megakernels/related), they have a great eye for talent and I think will be able to build something very special. Congrats on the launch and I look forward to what you come up with!