London has many wonderful things. The ExCel Centre isn't one of them. BUT…watching @richmondalake teach developers how to build their first multi-agent system *is* awesome, no matter where it's taking place (or however awkwardly shaped the room 😬).
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Context Engineering: Structuring Data for AI Reasoning
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What is “Context Engineering”? It’s the discipline of stitching your unstructured mess—logs, chats, docs, images—into something an AI can actually reason over. → Vector DBs + hybrid search + embeddings to retrieve by meaning, not keywords. → Decisions anchored in your data,
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Developer plans to code new technology later this year
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I can’t wait to vibe code one of these, probably later this year.
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Product Development Reimagined: PMs, Designers, and AI Agents
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The rules of professional product development are being rewritten in real time.
— Dan Shipper 📧 (@danshipper) 25 mars 2026
– PMs and designers can ship software as easily as engineers.
– Software is no longer just built for humans—it’s also built for agents as first-class citizens.
To better understand how we build… pic.twitter.com/9Ak63l1MljThe rules of professional product development are being rewritten in real time. – PMs and designers can ship software as easily as engineers.
– Software is no longer just built for humans—it’s also built for agents as first-class citizens. To better understand how we build -
OpenClaw Beta Released with Enhanced MS Teams Integration
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New @openclaw beta is out with better MS Teams integration, @OpenWebUI and more!
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Claude’s Unexpected Blame Behavior During Coding Sessions
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I find it so curious when Claude suddenly starts caring about blame during a coding session.
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Learning Mechanisms Differentiate AI From Static Tool Libraries
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Yeah the learning mechanism is what separates this from static tool libraries
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Manual Debugging Doesn’t Scale in Modern Development
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Exactly, the manual debugging doesn't scale
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RetinaNet and Focal Loss: Solving Class Imbalance in Object Detection
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🎯 RetinaNet & Focal Loss: Fixing Class Imbalance in Object Detection
— Satya Mallick (@LearnOpenCV) 25 mars 2026
Single stage detectors were fast but struggled with class imbalance. In 2017, researchers at Facebook AI introduced RetinaNet with a new loss function Focal Loss.
By down-weighting easy background examples… pic.twitter.com/1gQ9p8Ku7jRetinaNet & Focal Loss: Fixing Class Imbalance in Object Detection Single stage detectors were fast but struggled with class imbalance. In 2017, researchers at Facebook AI introduced RetinaNet with a new loss function Focal Loss. By down-weighting easy background examples
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Self-Evolving Agent Framework Learn Failures Rewrite Skills
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Let Agents Design Agents Memento-Skills is a self-evolving agent framework where agents learn from failures and rewrite their own skills. Most agent frameworks treat skills as static. You write them once, load them into context, and hope they work. When they fail, you debug