Series

IA Foundations

AI engineering fundamentals, one mechanism per episode.

7 episodes

01 Twenty AI concepts you need to understand in 2026 The complete visual guide to how AI works, from the basics to the frontier. Six sections, twenty concepts, no spare jargon. 23 May 2026 02 AI Foundations · 02: The LLM does nothing. The harness does. The most common mistake of 2026 is not separating the model from the harness. It costs money and security. 13 Jun 2026 03 Why asking AI to review its own code does not work (and what does) IA Foundations 03: asking the same model to self-correct can degrade reasoning. The multi-agent alternative reaches 82.6% on HumanEval. 20 Jun 2026 04 The 5 subsystems that separate an agent that works from one that only looks like it works Last week I wrote that the LLM does nothing, the harness does. This post opens the hood: the five subsystems every working agent needs. 27 Jun 2026 05 Your agent is degrading in silence. I built a 9-eval suite to prove it Measuring only the final output hides regression. Without per-step, per-role evals, agents get worse unseen. The 9 golden cases that stop … 04 Jul 2026 06 Your LLM agrees with what you want to hear. And that is an architecture bug, not a prompt bug Sycophancy is automated confirmation bias. You fix it with architecture: independent models, confidence-weighted consensus and a primary … 11 Jul 2026 07 IA Foundations 07: a 1M token window solves nothing if the information lands in the middle Lost in the middle is not a bug, it is an attention pattern. Position beats context size, and a critical rule on line 300 is accuracy thrown … 18 Jul 2026