Inside An AI Agent: Planning, Tool Use, Memory, Constraints, And Verification

This is a written teardown of the core components that make or break a real AI agent: planning, tool use, memory architectures, constraint handling, and verification passes. It does not ship code or a product — it is editorial — but it is the kind of editorial that a builder should have tabbed while scoping an agent project, not afterward. The framing is honest: demos look good, production falls apart, here is why. It walks through each layer with enough specificity to be useful rather than generic. What it does not do is benchmark any particular framework or give you a runnable reference implementation, so treat it as a mental model document rather than a how-to guide. Reservation: at ~2,500 words it covers a lot of surface without going deep on any single component — readers who already understand the basics will want a more focused reference. -> Best for: AI engineer scoping an agent system for the first time