PinnedMicheal Lanham·May 23You’re About to Pick the Wrong Help Desk Agent Stack. Here’s How to Not.A beginner’s guide to choosing an “agentic platform” in 2026, for the developer handed a deadline before the technology.
PinnedMicheal Lanham·May 9, 2024The Art of Reasoning with GPTsCover of GPT Agents In Action by Micheal Lanham
PinnedMicheal Lanham·Dec 4, 2021Painting with Genetic AlgorithmsIn my next book for Manning publications, Evolutionary Deep Learning, I outline and demonstrate numerous techniques to improve and enhance…
Micheal Lanham·2h agoOne Reply Beat 500 Million Steps of PPO at Breakout.Weight-Space Programming, Day 5 of 7: what a written policy beats, where it breaks, and what PPO can do with it.
Micheal Lanham·1d agoThe Viral Qwen Fix Fits in a LoRA Nobody Trained: Direct Weight Edits vs Fine-Tuning for LLMsWeight-Space Programming, Day 4 of 7: the 48.1% fix is two patch cables, and our own test of that idea failed as written.
Micheal Lanham·2d agoChanging a Refund Limit Took Two Weights. On a Trained Network It Took Three Tries and a Hack.Weight-Space Programming, Day 3 of 7: a model with no tools can audit, write and patch tiny classifiers, and the dumbest baselines tie two…
Micheal Lanham·3d agoWe Taught an Embedding Model New Words With 384 Numbers Each and No Training.Weight-Space Programming, Day 2 of 7: writing jargon into a token table works, a glossary won anyway, and here’s when the edit still pays.
Micheal Lanham·4d agoAn LLM Rewrote 0.016%Weight-Space Programming, Day 1 of 7: one headline sold two different abilities, and a five-cent picture named the game.
Micheal Lanham·5d agoThe Busy Wednesday Problem: How Confounders Teach Your AI Agent SuperstitionsInstinctual Learning, Part 9 of 9: why a tired night’s low mark must be subtracted before your agent learns a single thing about the food.
Micheal Lanham·6d agoImagine Before You Act: What Tolman’s Rats Teach AI Agents About World ModelsInstinctual Learning, Part 7 of 9: keep a model of the world before the task needs it, then check the plan against it before you act.