Why I stopped using Vector DBs for AI Memory (and used Git + Markdown instead)

A developer has released lean-ai-memory, an open-source framework that replaces vector databases with Git and Markdown for AI agent memory. The project aims to provide a zero-cost, serverless, and transparent alternative to heavy infrastructure for storing conversation context.

Hey DEV community 👋 Like many of you, I've been heavily experimenting with AI Agents recently. But as a software architect who hates unnecessary overhead, watching the community default to spinning up heavy Vector DBs and complex graph frameworks just to store conversation context felt like massive over-engineering. We often use massive systems to solve small problems. I wanted an AI memory system that is zero-cost, serverless, and completely transparent. So, I built a lean alternative. 🔥 Talk is cheap, here is the repo: https://github.com/phucphungbk/lean-ai-memory https://github.com/phucphungbk/lean-ai-memory Instead of adding new layers of infrastructure, I looked at what we already have: I’m sharing this with a completely open mindset. Instead of optimizing it in a silo, I want to see how this framework holds up in the wild. I'm highly anticipating the community bringing their own battle-tested custom rules into the system to push its boundaries. I’d love for you guys to clone it, tear the architecture apart, run some tests, and drop your feedback or PRs. Let me know what you think in the comments Happy coding 🚀