Production-grade memory systems for autonomous AI agents. From six-layer architecture to topic routing and deployment — tools and knowledge for builders who ship.
LeadGeese is a workshop for AI agent builders. We design memory systems that turn forgetful agents into reliable autonomous workers.
The six-layer memory model: Hot → Warm → Cold → Library → Diary → Deep. Built for agents that run for months, not demos that run for minutes.
Routes every query to the right memory tier — tag-based, semantic, or hybrid. Your agent knows what to remember and what to forget.
Lossy and lossless strategies. Automatic consolidation that decides when to summarize and when to keep raw. Prevents memory poisoning and context overflow.
Working memory system you can deploy today. Real Python code, real APIs, real production use — not a toy.
Authorization at runtime, not in the prompt. Prevent injection attacks and data leakage across agent sessions.
Observability, graceful degradation, context window budgeting. Patterns that survive real workloads at scale.
The complete guide to building memory systems that actually work in production. 60+ page guide, video walkthroughs, and a working reference implementation — everything you need to ship agent memory that scales.
Learn More →Because most agent memory systems work great in a demo and fall apart in production.
We run real production agents. Every pattern in our workshop has been tested under actual workloads — not theoretical architectures from a whiteboard.
We don't sell prompt hacks. We sell system design — layered memory, routing logic, safety boundaries. Things that survive when your agent runs for 10,000 turns.
No black box. You understand how every piece works, and you can customize it to your needs. Vendor independence is a feature.
This field moves fast. Your subscription includes a full year of updates — new patterns, case studies, and code as the landscape evolves.