Agent systems are often described as “models that call tools,” but reliability usually comes from the engineering boundaries around the model.
Context
More context is not always better. Long-term memory, short-term task state, tool results, and user preferences should be managed separately so the current goal does not get buried in noise.
Planning
Planning needs observable intermediate states. A maintainable agent should show where the task is, what input is needed next, and how it will recover after failure.
Tools
Tool calls need clear contracts: input schemas, structured outputs, error types, and retry rules. As the toolset grows, permissions, rate limits, and side effects become first-class design concerns.
Evaluation
Evaluation is more than checking whether one answer looks right. Useful metrics include task closure rate, tool failure rate, human handoff points, and regression examples.