Agents & multi-step workflows
AI that carries a task across tools and steps, with checks between steps and a human where it matters.
02 · Agents & multi-step workflows
Agents that finish multi-step work
Agents look great in a demo, then loop, skip steps or act on a wrong guess once real inputs arrive. The fix is rarely a better prompt. It's structure.
Getting it right
- Deterministic code for every step that doesn't need judgment
- Explicit steps and state, so every run can be inspected and resumed
- Checks between steps, and a human approval where a mistake is expensive
- Budgets on retries and spend
What I build
- Pipelines that plan, retrieve, act and verify
- Agents that operate across existing tools and APIs
- Human review queues for low-confidence cases
- Multi-agent systems where one agent checks another
Proof
Typical stack
LangGraph · CrewAI · AutoGen · Google ADK · Redis · Postgres · OpenTelemetry
Questions
When is an agent framework worth it?
When the flow has loops, checkpoints or approval gates. For a fixed sequence of steps, plain functions are simpler and easier to test.
Where should a human be in the loop?
At actions that are expensive to undo, and wherever the system's own checks say it isn't confident.