Hi

A prompt is for communicating an idea to an LLM. If you tell your idea to an AI agent and ask it to write down in its own words, say, a “skill” document which is meant to be a reusable piece of prompt to attach to another LLM session, it becomes a classic game of telephone. The model inevitably misinterprets your unspoken context or invent its own rules that you never intended. So the process is guaranteed to be lossy, therefore worse than your original words. ...

Cross-posted from the Raycaster blog; I’ve spent the last several months building this, and here is my take. 2025 brought us the new idiom for building AI (beginning with Manus and Claude Code): give it tools to operate a computer. This is a break from the past default approach represented by ChatGPT, which is LLM + a menu of bespoke API connections to plug in to various systems of record. The limits of plaintext Our first attempt at a document agent was to ingest documents, parse them into plaintext pages, expose search/read/write tools, and let the LLM operate over virtual directories of artifacts and pages backed by a SQL database. ...

Welcome to the very first post in a new blog! Here I will discuss software development, SRE work, and other fun stuff. Sometimes an idea is just too good to pass up. I hope this blog will motivate me to turn sparks and little pieces into general knowledge in writing the words down. The other day I was discussing Tabby with a coworker. We talked about whether we should consider AI-autocompleted code harmful and ditch everyone’s newfound habit due to LLM’s inherent unreliability and their tendency toward spaghetti code, throwing traditional software engineering principles like DRY out the window. I disagreed: what if we could have a framework that integrates AI development tooling while also making everything better and more reliable instead? This instantly reminds me of Test-Driven Development, or TDD, which I think is great when combined with the use of a Large Language Model. ...