Guides
Agent Architecture Blueprint
When to build an agent, and how to keep it bounded.
A written guide and reference implementation covering the decision most teams skip: whether the problem needs a runtime planner at all. Includes a bounded-agent implementation with iteration caps, total tools, full step tracing, and the pipeline alternative side by side so the comparison is concrete.
What is inside
- A decision framework for agent versus pipeline, with worked examples of both
- Bounded agent reference implementation with hard iteration limits
- Total tool design: every tool returns a usable result or an actionable error
- Step tracing built in, because the transcript is the only real debugger
- The same task implemented as a deterministic pipeline, for direct comparison
- End-to-end evaluation setup for task completion rather than unit correctness
Built with
- Python
- LangGraph
- Pydantic
- OpenAI
Next step
Have an AI problem worth solving?
Tell me what you are trying to build. I will tell you honestly whether AI is the right tool, what it would take, and how I would approach it.
Typical reply within 24 hours
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