AI infrastructure feels brittle because every primitive beneath it moves. Here's what I learned building and killing infrastructure in a field that reinvents itself every quarter.

A practical walkthrough of building an assistant with persistent memory using Cria.

How do you add memory to your agent or LLM? What works and what does not? How do you use multiple memory systems at once to cover each others weaknesses?

Not all context is sacred. Design your agent's memory around what happens when critical information gets dropped.

I benchmarked Mem0 and Zep on MemBench to understand why production agents were failing. Memory systems cost 14-77x more and were 31-33% less accurate than naive long-context.

An introductory guide to how LLMs handle 'memory', from context windows to retrieval systems and everything in between.

Why we built infrastructure for LLM context management, and what problems it solves.