Hussein Lezzaik

[Peter Steinberger 🦞 @steipete]

Built clawsweeper, which runs 50 codex in parallel around the clock, scans issues/prs deep and closes what is already implemented or what makes no sense.

Closed around 4000 issues today, a few thousand are in the pipeline. (rate limits are rough) https://t.co/AiNNDcvGke

[Christos Tzamos @ChristosTzamos]

1/4 LLMs solve research grade math problems but struggle with basic calculations. We bridge this gap by turning them to computers.

We built a computer INSIDE a transformer that can run programs for millions of steps in seconds solving even the hardest Sudokus with 100% accuracy

[Dev @DevvMandal]

Today, we're launching the world's largest open-source dataset of computer-use recordings.

10,000+ hours across Salesforce, Blender, Photoshop and more, to automate the next level of white-collar work.

Link in the comments :)
@markov__ai

[Standard Intelligence @si_pbc]

Computer use models shouldn't learn from screenshots.

We built a new foundation model that learns from video like humans do. FDM-1 can construct a gear in Blender, find software bugs, and even drive a real car through San Francisco using arrow keys.

[JUNDE WU @JundeMorsenWu]

Introducing OneContext. I built it for myself but now I can’t work without it, so it felt wrong not to share.

OneContext is an Agent Self-Managed Context Layer across different sessions, devices, and coding agents (Codex / Claude Code).

How it works:
1. Open Claude Code/Codex inside OneContext as usual, it automatically manages your context and history into a persistent context layer.

2. Start a new agent under the same context, it remembers everything about your project.

3. Share the context via link, anyone can continue building on the exact same shared context.

Install with: npm i -g onecontext-ai
And open with: onecontext

Give it a try!

[Hussein Lezzaik @husseinlezzaik]

@mehul @maticrobots congrats @mehul well deserved!

[Kimi.ai @Kimi_Moonshot]

🥝 Meet Kimi K2.5, Open-Source Visual Agentic Intelligence.

🔹 Global SOTA on Agentic Benchmarks: HLE full set (50.2%), BrowseComp (74.9%)
🔹 Open-source SOTA on Vision and Coding: MMMU Pro (78.5%), VideoMMMU (86.6%), SWE-bench Verified (76.8%)
🔹 Code with Taste: turn chats, images & videos into aesthetic websites with expressive motion.
🔹 Agent Swarm (Beta): self-directed agents working in parallel, at scale. Up to 100 sub-agents, 1,500 tool calls, 4.5× faster compared with single-agent setup.
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🥝 K2.5 is now live on https://t.co/YutVbwktG0 in chat mode and agent mode.
🥝 K2.5 Agent Swarm in beta for high-tier users.
🥝 For production-grade coding, you can pair K2.5 with Kimi Code: https://t.co/A5WQozJF3s
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🔗 API: https://t.co/EOZkbOwCN4
🔗 Tech blog: https://t.co/6h2KkoA0xd
🔗 Weights & code: https://t.co/H38KegeDIY

[Mohammed Alshehri @SwishMoe]

My implementation of the Recursive Language Model (RLM) paper by @a1zhang , Kraska, and @lateinteraction .

Key insight: "Treat long context as an external environment, not something to stuff into a context window."

Applied to video understanding — instead of encoding 38K frames into a prompt, the agent:
→ Treats video as an environment
→ Writes code to explore segments
→ Uses recursive LLM sub-calls for analysis

Tested: 20+ min video, 7 steps, $0.002

Paper: https://t.co/sMkqVscWZD
Code: https://t.co/J3GxdlKeav

[1X @1x_tech]

NEO’s Starting to Learn on Its Own

[William Holmberg @WilliamHolmbe19]

casually driving around on google maps

this is also opensource and can be found on my github

[Hussein Lezzaik @husseinlezzaik]

@bcherny why does this happen and how do i fix it? @bcherny

[Hussein Lezzaik @husseinlezzaik]

@trq212 now that CC codes autonomously — what are the odds that a hacker group gets CC to install a key-logger without it knowing it did?

[Hussein Lezzaik @husseinlezzaik]

@modal serverless infra is a perfect fit for Claude Code.

I used to always use Lambda Labs, but given how easy it is to give CC access to a GPU, monitor training runs, benchmarks, run certain inference tests, push code fixes .. all on demand & in the background it's effortless.

[alex zhang @a1zhang]

Much like the switch in 2025 from language models to reasoning models, we think 2026 will be all about the switch to Recursive Language Models (RLMs).

It turns out that models can be far more powerful if you allow them to treat *their own prompts* as an object in an external environment, which they understand and manipulate by writing code that invokes LLMs!

Our full paper on RLMs is now available—with much more expansive experiments compared to our initial blogpost from October 2025!

https://t.co/x47pIfIkTb

[Boris Cherny @bcherny]

I'm Boris and I created Claude Code. Lots of people have asked how I use Claude Code, so I wanted to show off my setup a bit.

My setup might be surprisingly vanilla! Claude Code works great out of the box, so I personally don't customize it much. There is no one correct way to use Claude Code: we intentionally build it in a way that you can use it, customize it, and hack it however you like. Each person on the Claude Code team uses it very differently.

So, here goes.

[Martin_DeVido @d33v33d0]

Claude can code- but can claude grow?! 🪴

So far the answer is YES.
Claude is successfully keeping a living organism ALIVE.

There were some hiccups this week!

Some errors and resets, but Claude managed to power through and take care of Sol 🍅

A week in review:

[Hussein Lezzaik @husseinlezzaik]

@sdand should've bought some gifts:D

[Moonlake @moonlake]

Reverie v0.1.0 vs MirageLSDv2

How we're building world simulators: https://t.co/yCHLpilWip

[Sergey Levine @svlevine]

A while back Benjie Holson described a set of "Robot Olympics" challenge tasks -- washing a pan, making a peanut butter sandwich, and more. We tried to fine-tune our models at PI to these tasks, and found that we could do most of them. A few highlights below.

[Ivan Zhao @ivanhzhao]

https://t.co/fxHYR6S29D