The original title is "AI agent architecture: components of a system that survives real traffic"

Short summary

A detailed breakdown of production AI agent architecture, covering the core loop (input, decide, act, observe), orchestrator design, tool failure handling, memory types (short-term, long-term, episodic, working), and planning with checkpoints. The article emphasizes that production complexity lives in handling unhappy paths — malformed outputs, tool failures, and unreachable goals — not the happy path covered in tutorials. Human-in-the-loop checkpoints are framed as architecture, not workaround.

• •Production agent complexity is in handling unhappy paths, not the happy path tutorials cover
• •Orchestrator, tools, memory, and planning are the four core architectural components
• •Tool design quality directly affects model invocation accuracy, not just model capability

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