Designing incremental document updates
Make the update as small as the change. Explore hashes, chunk boundaries, and safe publication.
Retrieval, agents, evaluation, fine-tuning, cost.
Real production problems, thought through properly,
one scenario at a time.
RAG & retrieval. Finding the evidence is the hard part. The model only words it.
No walls of theory. Start with a situation,
explore the trade-offs, then make your call.
Make the update as small as the change. Explore hashes, chunk boundaries, and safe publication.
Same fieldnote, two doors. Take the written guide if you think in sentences.
Take the widget if you would rather move something and watch
the system answer back.
The whole story in order: foundations, implementation, the architecture decisions and why they went that way.

This is my growing collection of GenAI architecture scenarios, from retrieval today to agents, evaluation, fine-tuning and cost as the notebook grows: the questions worth asking, the trade-offs worth making, and the experiments that make them click.
Part portfolio. Part field guide. Always a work in progress.
Start with my first fieldnoteA note when a new fieldnote goes up: the problem, the approaches, and the lab. Nothing else, and one click to stop.