I settled on lat.md [1] at the beginning of this year and never looked back.

Its design offers a compellingly simple surface for weaving natural-language intent into the codebase itself, without overcomplicating things:

---

Key Ideas

* Plain markdown: readable by humans, parseable by agents

* Wiki links connect concepts into a navigable graph

* // @lat: and # @lat: comments tie source code to specs

* lat check ensures nothing drifts out of sync

* lat search for semantic vector search across all sections

---

For me it strikes the right balance between structure and flexibility. It gives agents enough context-efficient grounding to reduce functional and architectural drift [2], while remaining malleable enough to evolve with new requirements.

Admittedly I haven't run any evals, and I'm sure there are even better systems out there... but if I still had the problem I was trying to solve when I found it, I wouldn't be talking about it right now.

Of course it's likely that my problem has only migrated to a higher order of complexity, but surfacing it again through building increasingly complex things is an interesting enough challenge in itself.

[1] https://github.com/vercel-labs/lat.md

[2] 100% auto-eliminating drift is an unrealistic goal -- that's where you come in.