Search: “framework”

benchmarking agents by their ability to play video games 🎮 We are excited to launch VideoGameBench on Antim Labs, created by @a1zhang, Thomas L. Griffiths (@cocosci_lab), @karthik_r_n, and @OfirPress

I predicted in January that 'harness' would be the AI buzzword of H12026 - seems accurate so far. Everyone is talking about harnesses but I'm not confident that the majority of people (including me!)

Getting LLMs to simulate “true” randomness or generate diverse outputs is surprisingly difficult. We found a simple prompting trick that solves this by having the model generate and manipulate a rando

Make your next Replit purchase more rewarding with Amex Offers®. Eligible American Express® Card Members can enroll and earn a 50 statement credit after they enroll and spend a minimum of 100 in one o

Meet Kimi K2.6 agent - Video hero section, WebGL shaders, real backends. From one prompt. 🔹 Video hero sections - cinematic aesthetic, auto-composited 🔹 WebGL shader animations - native GLSL / WGSL, l

Video hero sections, built right in. K2.6 agent calls video generation APIs to create real cinematic footage for your hero, not stock placeholders. Composited into the page, synced to scroll, with sha

And yes, Lush/SN used a homegrown Lisp interpreter, to which a compiler was added in the early 1990s. @TradeTexasBig Oh, it wasn't even CL, it was its own language! https://lush.sourceforge.net/lush-m

in 1996 mitzenmacher showed that sampling two backends and picking the better one drops max load exponentially vs. random selection one extra comparison. that's the whole trick we built pinecone assis

Million of recipes. Fuzzy ingredient data. One afternoon to solve it. 🍳⚡ Will Templeton, CTO and co-founder at Allspice, explains why Pinecone is their fundamental building block: ❌ No weeks of cluste

4/5 We upgraded our original 3-line “be correct” prompt → a much more detailed prompt that enforced a hierarchy of constraints for correctness, regression safety, and minimality. Basically, get the LL

Sonilo is now available in ComfyUI via Partner Nodes: AI video-to-music that generates soundtracks synchronized to your footage. @Sonilo_music reads visuals, pacing, and emotional cues so audio stays

DAIR.AI (Democratizing AI Research) is an organization focused on AI education and research democratization, frequently sharing updates on their X (formerly Twitter) account about prompt engineering,

The security and privacy of your information are a top priority. We’re committed to being transparent and taking quick action when issues arise. We're sharing more technical details and FAQs here: htt

Agent skills are great. I wanted to share some of my favorites from Jesse Vincent's 'Superpowers' skill pack 𝚠𝚛𝚒𝚝𝚒𝚗𝚐-𝚙𝚕𝚊𝚗𝚜 skill produces much better plans than any harness' built in plan mode that I'

haha cool, this worked. an MCP server that allows Claude to build it's own reusable skills https://github.com/yoheinakajima/selfMCP (1473 LoC) basically a server with skills to CRUD skills in this vid

im excited about agent harnesses because i think are the first stable agent abstractions we can build on top (which is why we're investing so much in deepagents) we always wanted to run llms in a loop

Pinecone now has a native extension for Gemini CLI. gemini extensions install https://github.com/pinecone-io/gemini-cli-extension → 9 MCP tools → 7 skills (quickstart, query, assistant, RAG and more)

A bit over a decade ago, we got fuzzers. A fuzzer is an automated vulnerability-finder that repeatedly runs a target program with semi-random inputs. One particular fuzzer, American Fuzzy Lop, was not

Rob Schaper posted a reply on X (Twitter) praising Harrison Chase (@hwchase17) and the LangChain team for their work on agent harnesses, predicting the concept would become widespread within days. ...

The referenced tweet (X post) from @petergostev is not publicly accessible, and no search results directly describe a specific 'Open Claw tourist attraction' in central London tied to the @aiDotEng...

Tesla puts a lot of effort into ensuring that our cars don’t run over animals More than 350 million vertebrate animals are killed by human driven vehicles every year. In general, autonomous vehicles a

NEW: Meta announces Muse Spark. All you need to know: * It's their new multi-modal reasoning model. * Strong at multi-agent orchestration and multi-modal reasoning. * Contemplating mode orchestrates m

NEW paper from Google on multi-agent research agents. It's one of the first systems that handles end-to-end LaTeX generation, targeted literature reviews, and conceptual diagrams as a decoupled, stand

5/5 Across the board, results show the business impact and differentiation of sovereign specialized intelligence, and the opportunity for companies to reach AI independence. Thanks to @nvidia, @Gong_i

Must-read paper from Sakana AI on orchestrating coding agents for scientific research. (bookmark it) This is an important read with lots of useful insights if you are building multi-agent systems. I l

New work from Meta AI on agents that manage their own search. (bookmark it) A ReAct agent keeps every failed attempt in one context, making useful evidence harder to find. To improve on this, they pro

Banger paper from Stanford, Together AI, and colleagues. Why is this an interesting paper? Today's LLM agents must write out every reasoning step as text before they can search, run code, or take acti

Recursive self-improvement is one of the most discussed ideas in AI right now. RSI-Anything measures it in code repair, GUI agents, lab planning, and chemistry. They find that the lab-planning score m

Banger paper from Google DeepMind on co-evolving an agent's harness and its weights. (bookmark it) If you already log your harness changes and results, those logs can become training data for the mode

- deepagents is durable by design - built on langgraph with state machine primitives hardener over years - deepagents is extendable, pick the exact pieces you want or make your own - deepagents is ope

Mistral AI demonstrated a tooling solution for engineering drawings that employs the **Mistral Large** model across **four zoom levels**, automatically inspecting and verifying plan details until an e

The blog post “Multi‑Agent Self‑Supervision: Recursive self‑improvement through collective intelligence” by @hardmaru describes how multiple AI agents can jointly supervise and refine each other’s lea

Recommended NVIDIA paper on memory-efficient post-training RL. A very interesting technique for scaling RL for LLMs. The main takeaway is that you can update all of a model's weights with RL and still

Today on AI:AM, @swyx is back. Astra is 'a fully capable AI Engineer' for $6/hr, so what's left of the job he named? Plus Cursor → SpaceX, whether agent labs survive, and a preview of @aidotengineer N

We're expanding our approach to content provenance to include text in response to EU regulatory requirements, while recognizing the significant limitations of current text watermarking technology. Our

Elon was thinking about superintelligence long before anyone in the mainstream even understood where superintelligence was heading He was deeply involved in the conversation around Nick Bostrom’s Supe

🚨 Yesterday, the 'White House Accord on Super Intelligence' was signed. What was supposed to be about AI safety and accountability was instead a PROBLEMATIC endorsement of self-regulation. My comments

OpenAI’s “How we think about securing frontier RL training runs” (released September 29 2026) explains the company’s approach to safeguarding large‑scale reinforcement learning experiments. It details

Keep your agent harness minimal, folks. This paper from MIT CSAIL shows why. (bookmark it) While being very minimal it looks effective and promising for building self-improving agents. They present JA

This is huge. Xiaomi just open-sourced 7k+ reinforcement learning task environments used to train MiMo, covering code, cybersecurity, general tool use, visual web development, and music-related tasks.

Pay attention to System One models if you are building custom harnesses and agentic workflows. Great to see DSPy integrate Jev and now support System One models for calibrating agentic workflows. I'm

The era of omni agents is upon us. This is a great report by the Qwen Team on their omni-modal agents. They present Qwen3.8-Omni-Flash, a natively multimodal model trained for long-horizon agent tasks

⚡ Meet Qwen-Audio-3.1! ASR, TTS & Realtime are fully upgraded, joined by two new models: TTS-Next for audio creation and ASR-Next for audio understanding. Five models, one complete audio stack: unders

arXiv:2609.25388v1 Announce Type: cross Abstract: A classical question in statistics is which observable quantities to condition on when drawing inferences about unobservable targets. For conformal pr

Nice paper showing a better way to evolve agent skills. And they achieve 40–70% less token cost compared to frontier evolving methods. The idea is to let agents improve their skill prompts by ranking

“HUMANZS LAUNCHED THE JOB” Ok, I don’t like the spelling here, but the gist of this Mozilla cybersecurity researcher rings true. The six new incidents aren’t about the second coming of Skynet, they ar