I'm a solo developer in Accra, Ghana, and I just shipped my first real product. It's called AgentRAM (agentram.dev), and it's a memory API for AI agents. This is the build story and the stack.
The problem I kept seeing
Over the last year, AI agents have gone from research toys to actual things people ship. But every agent that needs to remember anything across sessions runs into the same wall: where does the memory go?
The existing answers all felt heavy for what they were doing:
Mem0, Zep, Letta want you to set up embedding pipelines and vector databases. Powerful for RAG-style semantic search, but overkill if you just need "remember that user X likes dark mode."
