TL;DR: Four posts this week, and three of them circle the same uncomfortable idea: a system rarely sees its own blind spot. A content pipeline that approved a claim its own source contradicted, a quaâŚ
WeeklyReview
14 posts tagged WeeklyReview ¡ all tags
2026
TL;DR: Three posts this week. Two are about the stuff an agent reads; one is about what an agent is measured on. The first is a small Bedrock experiment showing that a âsponsoredâ block in agent-readâŚ
TL;DR: Three posts this week, and they rhyme: each one looks past the loud, obvious layer to a quieter one underneath. Amaraâs Law says the AGI peak is what we overrate and the boring, already-useful âŚ
TL;DR: Five posts this week, one habit worth keeping: read past the headline before you decide. A metric is not the goal it stands in for (Goodhartâs Law). A model being big is about trainability, noâŚ
TL;DR: Three posts this week, one quiet throughline: the disciplined, bounded move keeps beating the maximalist one. Gallâs Law says you compose a complex system from small working bricks instead of âŚ
TL;DR: Three posts about where the human stays in charge as agents do more of the work. âLaws & Disorderâ closes with Teslerâs Law: you canât delete a systemâs complexity, only choose who owns each piâŚ
TL;DR: Three posts about the cost you canât see until you go looking. âLaws & Disorderâ continues with Hyrumâs Law: every observable behavior of your API is a contract someone depends on, and AI agentâŚ
TL;DR: Three posts, one quiet theme: the structure you donât design still gets drawn. âLaws & Disorderâ opens with Conwayâs Law â your architecture mirrors your org chart, so shape the teams first, anâŚ
TL;DR: This week was about taking a big idea off the whiteboard and finding the exact AWS building block that turns it on. Two posts continue the âWhiteboard to Cloudâ series: compression as the cleanâŚ
TL;DR: This week was about where knowledge lives, who owns it, and where the real work actually is. Three posts climb the agent-memory ladder: naming the spectrum, then the retrieval mechanism (vectorâŚ
đŹ Also available as a blog walkthrough video â a short narrated tour of the weekâs five posts. TL;DR: Five posts this week, and they rhyme. Each one treats an AI agent as a first-class user of a systeâŚ
đŹ Prefer to watch? This weekâs review is also a narrated video walkthrough. TL;DR: Six posts this week, and most of them do the same thing: take guidance or a principle and turn it into something you âŚ
TL;DR: Six posts this week, all circling one idea: across this weekâs cases, raw model power was rarely the differentiator â the structure, governance, and craft around the model were. A paper (and a âŚ
TL;DR: Six posts went out this week, and three of them kept circling the same idea: in the agents I run, reliability has come less from better prompts than from structure. Boundaries, constraints, andâŚ