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AI leader with 10+ years building production machine learning and generative AI systems…
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AI Council
AI Council 2026 track host announcement! Help us welcome Zachary Mueller as host and curator of the brand-new Model Systems track. As a former Technical Lead at Hugging Face, Zach led development on Accelerate, one of the most widely used distributed training libraries in the ML ecosystem, and worked on core pieces of the Transformers Trainer API that thousands of teams rely on daily. He now serves as Head of Developer Relations at Lambda. Zach started his ML journey in 2019 through the fast.ai program and quickly became a key contributor in that ecosystem. The Model Systems track covers the full lifecycle of model development: pre-training pipelines, fine-tuning strategies, distillation, small-model architectures, and RLE-adjacent techniques. Talks emphasize efficiency, scaling laws, post-training improvements, and the practical engineering behind model quality. It’s designed for teams building or adapting their own custom models. Join us May 12–14 in SF → https://lnkd.in/eEYHApCF
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Jan Winkler
When powerful open-source models are accessible to all, differentiation shifts from the technology you choose to the expertise you build into them. Konstantine Buhler, Partner at Sequoia, joins Kari Briski, VP of Generative AI Software for Enterprise at NVIDIA, to unpack how the agent economy transforms work and what it takes to stay ahead. 🎥 Watch the full conversation: https://bit.ly/3Kxi8Sj
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Michael Ryaboy
Thanks to the resurgence of RL, LLMs are finally able to reliably coordinate tools and reasoning to do high-precision retrieval. Companies like Happenstance, Clado, and Mintlify have already shifted to agentic search, and it's only a matter of time until anything less feels broken to users. Link to full blog in comments.
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Maksim Golivkin
📈 More LLMs, higher quality!! 💰 Gemini, Cursor (Composer) & GPT-5 reviewed Claude plans & implementation on 27 PRs Only 35% of issues were found by multiple LLMs. The rest of the findings? Completely unique to a single tool. Claude caught a CSRF bypass and WebSocket auth gaps that nobody else touched. GPT-5 flagged flow-breaking type errors. Cursor caught race conditions and a few bugs. Dropping any one tool would leave blind spots. Claude is the strongest reviewer, however, in Claude Code it has the most context as well. Subjectively, Cursor Bugbot delivers best insights & actual bugs on Github - Composer run on local changes is not as productive. My next steps are 1) Quantify quality of Copilot & Bugbot reviews on Github 2) try claude-octopus (link in comments) & acpx for stability of the setup
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