Multi-Agent Memory: The Real Bottleneck
Running 5-10 agents in parallel isn't a storage problem - it's a context window problem. Each agent consumes tokens from a shared pool.
After analyzing multiple sessions with parallel agent execution, the pattern is clear: memory tools like AgentDB and claude-mem solve persistence, not runtime pressure.
**The Math:** - Single agent: ~50K context tokens - 10 parallel agents: ~500K cumulative tokens - Context window: 200K limit
**The Solution Stack:** 1. Use Haiku for simple exploration tasks 2. Cap parallel agents at 3-4 3. Optimize skill profiles (fewer skills = less context) 4. Sequential over parallel when possible
This isn't about better storage. It's about smarter orchestration.