Agentic Patterns

Summary

Research / Agentic Patterns Start Overview The universal architecture emerging across all frontier agentic systems. Convergence. Claude Code, OpenAI Codex, Gemini CLI, LangGraph, CrewAI, Google ADK, Amazon Bedrock — built by different companies, in different languages, under different constraints. They converged on the same design. Not because they copied each other. Because the constraints are physics. Finite context windows. Tools that need a protocol. Safety that can’t depend on the model obeying. Tasks too complex for a single invocation. Any team that builds long enough arrives here. Which kind of system are you building? The patterns in this guide apply universally, but their weight depends on which seam in the agent ecosystem you’re working on. Read in the order that matches your problem. If you are building…You care most about…Start withA domain context substrate (an MCP server that gives any agent structured access to one domain: a codebase, a screen, a system)Deterministic extraction, fixed ontology, behavior contracts installed at the user’s project/tool-protocols, /instructions, /anti-patternsA personal AI runtime (an agent that the user owns, that runs in the background, with long-running state)Memory architecture, compaction-resident state, hooks, scheduler-gated background work/memory, /enforcement, /multi-agentA multi-agent shell (an orchestrator over other people’s agents, with chat-platform reach)Adapter patterns, isolated sub-agent tool registries, settings architecture, cost controls/multi-agent, /enforcement, /cost-management These categories aren’t airtight — many systems blur them. But knowing which one is your load-bearing concern keeps you from over-applying patterns that don’t fit your seam. The 8 Postulates These are not suggestions. They are the load-bearing walls of every production agentic system. Violate them and you will rediscover why they exist. #PostulateWhat to do1Start with a persistent instruction fileCreate a CLAUDE.md, AGENTS....