About AgentStack Atlas

Most AI agent tutorials show you individual tools. We show you how production teams actually combine them.

Why This Exists

The AI agent ecosystem moves fast. Every week brings new frameworks, vector databases, and orchestration patterns. But when you're building something real, you need to know what actually works together—not just what's theoretically possible.

AgentStack Atlas documents complete production stacks: the full combination of orchestration, memory, RAG, tools, evaluation, and models that teams are shipping today. Not marketing demos. Not academic papers. Real systems handling real traffic.

What We Document

Every stack entry covers six critical layers:

• Orchestration — The framework coordinating agent behavior
• Memory — How state persists across conversations
• RAG — Retrieval-Augmented Generation setup
• MCP/Tools — External integrations and capabilities
• Eval/Tracing — Monitoring and improvement pipeline
• Models — The LLMs powering the agent

Plus honest notes on cost, latency, and caveats. No fake benchmarks. No inflated claims.

Verification Process

Stacks are marked as either verified or reported:

• Verified — We've confirmed this stack is in active production use, either through direct communication with the team or public documentation.
• Reported — The stack has been submitted but we haven't independently verified it. These may be based on conference talks, blog posts, or community reports.

We aim for accuracy over volume. If something's wrong, let us know.