selling more than spectacles by a few orders of magnitude
INNOVATION
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Defining Agentic Engineering: Chapter 12 Guide
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Just added the 12th chapter to my Agentic Engineering Patterns guide, but it's the first one in the sequence: I figured it was time to try and answer the obvious question, "What is agentic engineering?"
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Agentic Iterative Development Replaces Traditional Spec-Based Approaches
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This feels outdated, I think agentic iterative development is here now. Moving from specs -> validation. Validation driven dev
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RAG Deployment Gap: Model Capability Versus Production Reality
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Benchmarks go up every month but most companies still can't get a basic RAG pipeline to work reliably. There's really a big gap between model capability and actual deployment.
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Constraints Drive AI Engineering Creativity Beyond Hardware
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Love this challenge. Constraints force creativity. The best AI engineering often comes from "how do I make this work with what I have" not "give me more GPUs."
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Canadian AI Scene Thrives with Momentum in Montreal, Toronto, Edmonton
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Proud that the Canadian AI scene keeps shipping! Montreal, Toronto, and Edmonton have been punching way above their weight for years. AI was always international, the funding just wasn't.
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OpenSquirrel: Rust IDE with AI agents as central unit
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Karpathy asked. I delivered. Introducing OpenSquirrel! Written in pure rust with GPUI (same as zed) but with agents as central unit rather than files. Supports Claude Code, Codex, Opencode, and Cursor (cli). This really forced me to think up the UI/UX from first principles instead of relying on common electron slop. github.com/Infatoshi/OpenSqu… Andrej Karpathy (@karpathy) Expectation: the age of the IDE is over Reality: we’re going to need a bigger IDE (imo). It just looks very different because humans now move upwards and program at a higher level – the basic unit of interest is not one file but one agent. It’s still programming. — https://nitter.net/karpathy/status/2031767720933634100#m
→ View original post on X — @thom_wolf, 2026-03-15 22:03 UTC
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Evidence Levels and n=1 Experimentation in AI Evaluation
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You seem over-indexing on "Everything here could have been done without ChatGPT". But that's the least interesting bit. We don't "need to prove this before anyone can believe" – there are levels of evidence short of proof. We don't need "clear, resounding successes" to try n=1
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Nemotron’s Intentional Limitations in AI Model Design Strategy
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i have a pet theory that Bryan and co cannot make Nemotron TOO good bc otherwise it would scare off customers. it needs to be “good enough to reflect everyone’s baseline consensus on SOTA techniques to lower the bar for neolabs + be maximally useful for synthetic data bc that is