Start with boundaries
A useful AI agent architecture starts by defining boundaries. The agent needs a task model, tool permissions, input contracts, output contracts, escalation paths, and a clear definition of what it should never do. Without those boundaries, the product becomes a chain of tool calls that looks impressive in a demo but behaves unpredictably in production.
Separate planning from execution
Production systems should separate planning, action selection, tool execution, validation, and response generation. This gives the team places to observe behavior, test regressions, cache expensive work, enforce policy, and recover after tool failure. A single prompt that does everything is fast to ship but hard to debug.
Design for handoff
The best agent architecture includes handoff from day one: handoff to a person, to a deterministic workflow, to a safer tool, or to a narrower agent. Handoff is not a failure of autonomy. It is how the system stays useful when uncertainty is high.
Direct answers
What should an AI agent architecture include?
It should include task state, planning logic, tool permissions, memory strategy, validation, eval signals, recovery paths, logging, and user-facing controls.
When should a team redesign its AI agent architecture?
Redesign is usually needed when tool calls fail silently, evals miss regressions, costs spike, users cannot recover, or the system is too hard to observe and debug.