docs.dev vs Wolbarg

Point your coding agent at your repo and your docs; it opens a docs branch, your team reviews on the rendered page, publishing is a commit. Runs on your Cloudflare, no...

Why most local multi-agent workflows don't need PostgreSQL for semantic memory, and when they actually do.

About docs.dev

Point your coding agent at your repo and your docs; it opens a docs branch, your team reviews on the rendered page, publishing is a commit. Runs on your Cloudflare, no platform fee, no metered AI. Reviews, branches, and rollbacks come free, because it is just git. Your content in their database, and an export button you hope works when you leave. Writing AI is the agent you already have; reader-facing AI runs on your Workers AI.

About Wolbarg

Why most local multi-agent workflows don't need PostgreSQL for semantic memory, and when they actually do. When people build an AI application, the database choice looks obvious: PostgreSQL, maybe Redis for caching, maybe pgvector for semantic search. This post is about that decision, and why SQLite is often the better fit for local multi-agent workflows. Local agents usually run on one machine, one process, maybe a handful of agents sharing context. Strip away the marketing and the list is short: low latency, simplicity (no migrations, users, or roles to wrestle with), local execution (offline works, no cloud bill), reliability (transactions, not half-written memories), and persistence (a file you can copy, back up, or delete).