After two days with Claude Fable 5, the best way I can describe it is 'relentlessly proactive' – here is an example where I inserted a screenshot of a bug and it started custom Python CORS servers and used pyobjc-framework-Quartz to capture
LLMS
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Frontier AI models fail to change ‘three words’ to ‘four’ when appropriate
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This is an interesting test, and the frontier models (GPT-5.5 Pro Extended, Claude 5 Fable Max) do fail. They refuse to turn the "three words" into "four" if that fits better Prompting the AI to act like a translator surfaces the problem, but it still avoids changing the wording
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Anticipation for Gemini 3.5 Pro in fierce competition
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Really curious for Gemini 3.5 Pro. The competition is currently fierce. It needs to be a big release.
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How to prompt like a pro with Replit Agent
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How to prompt like a pro with Replit Vague prompts just mean more rewrites. Here's how to get Agent to build the right thing the first time. Open thread ↓
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GPT 5.5 cracks cmatrix, 80% milestone in 18 months, Bellard tasks hardest
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GPT 5.5 cracked cmatrix, one of the easiest of the 200 tasks. @jyangballin on why 80% is maybe a year and a half out, and why the hardest instances (SQLite, the PHP interpreter, the Tiny C compiler) trace back to one developer, Fabrice Bellard. From Benchtalks #2. pic.twitter.com/k6F6KgFP0D
— Snorkel AI (@SnorkelAI) 11 juin 2026GPT 5.5 cracked cmatrix, one of the easiest of the 200 tasks. @jyangballin on why 80% is maybe a year and a half out, and why the hardest instances (SQLite, the PHP interpreter, the Tiny C compiler) trace back to one developer, Fabrice Bellard. From Benchtalks #2.
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North Mini Code GGUFs from Unsloth: run locally with Ollama or vLLM
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Our community moves fast. Unsloth GGUFs are already up. Run North Mini Code locally with a llama.cpp setup, Ollama, or vLLM, with quants from 9GB to full BF16
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Shoutout to michaelasper and corruptbytes for oMLX support
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A huge shoutout to michaelasper on Hugging Face/corruptbytes on Reddit for building support in oMLX
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Llama.cpp support under review thanks to michaelw9999
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The #1 ask, delivered by devs. llama.cpp support is under review thanks to michaelw9999 on GitHub/ElectronicStranger53 on Reddit
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DARPA AI Cyber Challenge: multi-agent LLM discovers zero-day vulnerabilities
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At the DARPA AI Cyber Challenge, Team Atlanta from Georgia Institute of Technology demonstrated a multi-agent LLM framework that discovered zero-day vulnerabilities in large codebases and automatically generated, tested, and deployed functional patches without human intervention.… pic.twitter.com/gBxsiw7Jgl
— Lucian Fogoros (@fogoros) 11 juin 2026At the DARPA AI Cyber Challenge, Team Atlanta from Georgia Institute of Technology demonstrated a multi-agent LLM framework that discovered zero-day vulnerabilities in large codebases and automatically generated, tested, and deployed functional patches without human intervention.
