Love OpenClaw but don't trust the security? Now you can have your own private agent running in Pokee secure sandbox, with 1000s of secure tool integrations. Vibe code on a GitHub repo, automate sales, deep research—all from 1 agent. https://t.co/0Je7al0WNX Open to first 100 ppl! https://t.co/LiyCJD0oNG

New post on the OpenAI Developer Blog: how we use skills for open-source maintenance, from planning and coding to testing and release-readiness checks with GitHub Actions. Hope it's useful for your projects too 🙌 https://t.co/KkoTaOUutn

https://t.co/BPRYrJGHpp

https://t.co/idnz88Stdw

https://t.co/idnz88Stdw

This really is an all time photo. A protestor shouting about the pros of immigration is interrupted by an Islamic terrorist throwing a bomb jumping over him. https://t.co/3TyBfewCYT

Democracy without secure elections is merely a facade https://t.co/KTLSYdsyXc

New this AM: Anthropic has filed its lawsuits against the Trump administration over the supply chain risk designation https://t.co/hmEB80FkYm

BREAKING: Alibaba tested 18 AI coding agents on 100 real codebases, spanning 233 days each. they failed spectacularly. turns out passing tests once is easy. maintaining code for 8 months without breaking everything is where AI completely collapses. SWE-CI is the first benchmark that measures long-term code maintenance instead of one-shot bug fixes. each task tracks 71 consecutive commits of real evolution. 75% of models break previously working code during maintenance. only Claude Opus 4.5 and 4.6 stay above 50% zero-regression rate. every other model accumulates technical debt that compounds with every single iteration. here's the brutal part: - HumanEval and SWE-bench measure "does it work right now" - SWE-CI measures "does it still work after 8 months of changes" agents optimized for snapshot testing write brittle code that passes tests today but becomes completely unmaintainable tomorrow. they built EvoScore to weight later iterations heavier than early ones. agents that sacrifice code quality for quick wins get punished when the consequences compound. the AI coding narrative just got more honest. most models can write code. almost none can maintain it.

Grok 4.1 is currently reviewing the entire corpus of EU legislation, one regulation at a time. 21 / 149,183 so far. Each with a single verdict: keep or delete. https://t.co/kkICWmoVSL

If you’re working with lots of slide decks and need a better way to search through them, Surreal Slides makes it simple 🌀 Built around LlamaParse, it parses presentation files into clean, structured data, turning raw slides into something AI can truly understand. Each slide is extracted, summarized, and organized before being stored in @SurrealDB for flexible retrieval. From there, you can query your entire presentation library in natural language through an agentic interface: no need to manually scan files or remember where a specific slide lives. Take a look at the demo below👇 GitHub Repository: https://t.co/jsTnjkUoED

You can now use Claude Code and GitHub CLI directly inside Perplexity Computer. We gave it an open issue on Openclaw. Computer: → Forked the repo → Wrote a plan to fix the bug → Opened Claude Code and implemented it → Submitted a PR via GitHub CLI https://t.co/MpVPchNqJa

Meta’s AI smart glasses are now facing a class-action lawsuit over privacy concerns. An investigation found subcontractor workers reviewing highly sensitive user footage captured by the devices. Wearable AI may be powerful, but it’s also forcing a new debate about surveillance, consent and who really sees what we record. https://t.co/9fsPtUZx9b @techcrunch @SarahPerezTC

BREAKING: Cluely CEO officially responds to TechCrunch https://t.co/EtAurp5zgZ

BREAKING: Cluely CEO officially responds to TechCrunch https://t.co/EtAurp5zgZ

With the passing of Khamenei, every leader that Peter invited to his Petoria pool party in “E Peterbus Unum” (2000) is now deceased, while Family Guy is still on the air. https://t.co/dJGbFRPhl4

Built an Apple Silicon / MLX port of your autoresearch — runs natively on Mac, no PyTorch needed. The loop found that depth=4 beats depth=8 on M4 Max because more optimizer steps > more parameters in a 5-min budget. https://t.co/BRvG6kLzuc @karpathy

Introducing, Runway Characters. Real-time intelligent avatars that turn the internet into a conversation. Deployable anywhere via the Runway API, Runway Characters can be customized in any way across every style. All with the ability to embed bespoke knowledge banks, custom voices and instructions. Start integrating Runway Characters directly into your apps, websites, products and services today. Available now at the link below.

The good/bad part about agentic codeing is the barrier to getting nerdsniped is now much lower https://t.co/CiGerRgM8H https://t.co/z6p0W229YM

Penguin-VL Exploring the Efficiency Limits of VLM with LLM-based Vision Encoders app: https://t.co/VZ8IvEdjN3 paper: https://t.co/XSM2GGVcCz https://t.co/ovxWSRJG0n

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C++ devs: your AI-assisted flows just got even smarter! With the new symbol‑level context and CMake‑aware build tools, your agents now have access to rich C++ specific intelligence directly in VS Code. Learn more: https://t.co/ErgApqTzZc

shout-out to @nicopreme and @jxnlco for being based gods and hooking me up with a ChatGPT Pro subscription for my OSS contributions! cheers 🙇‍♂️ https://t.co/HACBr3Dvme

KARL Knowledge Agents via Reinforcement Learning paper: https://t.co/sTeBtxk5Ls

MatAnyone 2 is out on Hugging Face Scaling Video Matting via a Learned Quality Evaluator paper: https://t.co/KPMaG8teJ2 app: https://t.co/wkMpaOdoCh https://t.co/ZSQNrOKcv4

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