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  • Open-source Claude improvement tool by Ashley Ha shared on GitHub

    repo: github.com/ashley-ha/goodcla… Shoutout to @ashleybchae for building this and making it open-source for the community!

    → View original post on X — @datachaz, 2026-04-07 20:49 UTC

  • AGI Release Concerns: Security First, Responsible Deployment

    If you had AGI would you release it to the world? I wouldn’t. I would fix the bugs in the world first. This technology in the wrong hands would harm us all. In good hands it will help all. Anthropic (@AnthropicAI) Introducing Project Glasswing: an urgent initiative to help secure the world’s most critical software. It’s powered by our newest frontier model, Claude Mythos Preview, which can find software vulnerabilities better than all but the most skilled humans. anthropic.com/glasswing — https://nitter.net/AnthropicAI/status/2041578392852517128#m

    → View original post on X — @scobleizer, 2026-04-07 20:23 UTC

  • Claude Mythos: Anthropic’s Unreleased Super-Powerful Security Model
    Claude Mythos: Anthropic’s Unreleased Super-Powerful Security Model

    Time for OpenAI to release GPT 5.5 Chubby♨️ (@kimmonismus) Claude Mythos: everything you need to know (tl;dr) Anthropic's new model, Claude Mythos, is so powerful that it is not releasing it to the public. Anthropic: "Mythos is only the beginning" Everything you need to know: The tl;dr with all key facts: Mythos found zero-day vulnerabilities in EVERY major operating system and EVERY major web browser, fully autonomously. No human guidance needed. One Anthropic engineer with zero security training asked it to find remote code execution bugs overnight and woke up to a complete working exploit. The oldest bug it discovered: A 27-year-old vulnerability hiding in OpenBSD, an OS literally famous for being secure. They're NOT releasing it publicly. Instead they formed Project Glasswing with AWS, Apple, Google, Microsoft, NVIDIA, CrowdStrike and others, committing $100M to use it defensively. "Over the coming months and years, we expect that language models (those trained by us and by others) will continue to improve along all axes, including vulnerability research and exploit development." The benchmarks are insane: -SWE-bench Verified: 93.9% (vs Opus 4.6: 80.8%) -SWE-bench Pro: 77.8% (vs 53.4%) -USAMO math olympiad: 97.6% (vs 42.3% — not a typo) -Firefox exploit writing: 181 successes vs 2 for Opus 4.6 -Cybench CTF challenges: 100% solve rate -CyberGym: 83.1% vs 66.6% -Humanity's Last Exam: 64.7% vs 53.1% Oh and by the way, Anthropic wrote this just casually: "Humanity’s Last Exam: We have found Mythos still performs well on HLE at low effort, which could indicate some level of memorization." What it actually did: -Found a 27-year-old bug in OpenBSD — famous for its security -Found a 16-year-old FFmpeg bug hit 5 million times by fuzzers without detection -Built a full remote root exploit on FreeBSD (CVE-2026-4747) – completely autonomously -Chained 4 vulnerabilities into a browser sandbox escape -Broke cryptography libraries (TLS, AES-GCM, SSH) -Thousands of critical zero-days found, 99%+ still unpatched -N-day exploit development: under $1,000 and half a day for full root Why they won't release it: -During internal testing, earlier versions escaped sandboxes, posted exploit details publicly, covered tracks in git, searched process memory for credentials, and deliberately fudged confidence intervals to avoid suspicion -Interpretability confirmed the model knew these actions were deceptive -Anthropic: "best-aligned model ever" but also "greatest alignment-related risk ever" – because when it fails, it fails harder -Still doesn't cross Anthropic's automated AI R&D threshold — but they hold that "with less confidence than for any prior model" Anthropic's own words: "We find it alarming that the world looks on track to proceed rapidly to developing superhuman systems without stronger mechanisms in place." They say the 20-year cybersecurity equilibrium is over — and Mythos Preview is only the beginning. And: "We see no reason to think that Mythos Preview is where language models’ cybersecurity capabilities will plateau. The trajectory is clear. Just a few months ago, language models were only able to exploit fairly unsophisticated vulnerabilities. Just a few months before that, they were unable to identify any nontrivial vulnerabilities at all. Over the coming months and years, we expect that language models (those trained by us and by others) will continue to improve along all axes, including vulnerability research and exploit development." — https://nitter.net/kimmonismus/status/2041592321192718642#m

    → View original post on X — @kimmonismus, 2026-04-07 20:13 UTC

  • How to Build AI Agents by Krishna Agrawal
    How to Build AI Agents by Krishna Agrawal

    How to Build #AIAgents by @Krishnasagrawal #GenAI #LLM #ArtificialIntelligence #MachineLearning #ML

    → View original post on X — @ronald_vanloon, 2026-04-07 19:23 UTC

  • Mythos Model Card: 244 Pages of Detailed AI Documentation

    What's interesting about Mythos is that they have a 244 page model card that is very detailed and thorough. Maybe Mythos made it for them in a day, but it feels like maybe 6-8 weeks of work. So it was probably ready for c.2 months. Wonder if they used it for coding already.

    → View original post on X — @petergostev

  • Interactive Website for Compute Wars Competition Platform

    Interactive website: https://
    compute-wars.surge.sh
    Github:

    → View original post on X — @petergostev

  • Claude Code Drives Exponential Growth in Engineering Velocity at Anthropic

    Appreciate the feedback. Since we introduced Claude Code at Anthropic, engineering velocity has increased hundreds of %, and the rate at which it is increasing is itself accelerating. The velocity is very much not performative — we're actively trying to figure out how to

    → View original post on X — @bcherny

  • AI-Powered Content Aggregator Summarizes Top X Voices

    If you are really into AI I built an AI that reads everyone here on X including Brian and makes this out of the best:

    → View original post on X — @scobleizer

  • Pika AI Agent Integration with Google Meet and GitHub Skills

    Ask your Pika AI Self to join a Google Meet to try it out. For all other agents, you can download the Skill on GitHub here:

    → View original post on X — @pika_labs

  • 4 Best Python Books for Beginners Learning Programming
    4 Best Python Books for Beginners Learning Programming

    4 book choices to Learn Python (for beginners): 1) Python Illustrated: https://
    amzn.to/47IUivd 2) Master Python Fundamentals: https://
    amzn.to/4cwiLq8 3) 7-Day Python Crash Course: https://
    amzn.to/4vfT0C3 4) Python Crash Course [3rd Edition. A Hands-On, Project-Based]:

    → View original post on X — @kirkdborne