Agents went from party trick to production in a year. The teams succeeding aren't using magic โ they're using a clear, layered stack.
An agent is only as good as its tools, its memory, and its guardrails. Model choice is the easy part.
The core layers
Each layer is independently swappable, which is what keeps agents maintainable.
- Model + tool-calling for the reasoning core
- Retrieval + memory for grounding and continuity
- Orchestration for multi-step control
- Evals + tracing so you can debug failures
Start simple
A single tool-using model with good logging beats an elaborate multi-agent graph you can't debug.
The Bottom Line
Add complexity only when a real failure forces it โ observability first, cleverness later.