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When requirements keep changing, the expensive part is not the code. It is re-explaining everything each session. A method that keeps the spec in the repo and treats every pivot as a reviewed delta.
Aircraft maintenance manuals solved the problem of readers who can't ask what you meant. I took ASD-STE100's rules and applied them to tool descriptions, error messages and prompts for AI agents.
Building agents on the JVM with Embabel · Part 7
My agent refused to run a single action. The @Condition gate was FALSE and nothing in the agent could ever make it TRUE, because Embabel builds an action's effects from what you declare, not from what your condition reads.
Building agents on the JVM with Embabel · Part 6
Turning my JVM agents into MCP tools took one dependency and one annotation. It also took three silent failures -- a starter that suppresses the web server, a shell that eats your CLI flags, and an annotation default that publishes exactly zero tools without telling you.
Building agents on the JVM with Embabel · Part 1
My first afternoon with Embabel, the JVM agent framework. I added one action too many, the planner quietly stopped early, and a cryptic get(...) must not be null taught me how GOAP, goals, and AgentInvocation actually fit together.
AI agents are a new kind of reader, and they don't want your rendered HTML. llms.txt is a tiny Markdown convention that hands them a clean index instead. Here's what it is, why it matters now, and how I wired it into my own Spring Boot site, with one URL path serving two different files by host.