Multi-Agent Systems
Orchestration that stays debuggable
One model doing everything is hard to debug and harder to improve. We split the work: a planner decomposes, specialists handle narrow tasks well, a critic checks the output against your rules, and workers own the side effects. Orchestration is explicit and durable, so a run can be inspected, replayed from any step and improved one node at a time instead of by rewriting a prompt and hoping.
- Orchestration graph with typed state passed between agents
- Durable execution: runs survive restarts and resume from the last good step
- Critic and verifier nodes that check output against your business rules
- Per-node evals, so you learn which agent regressed, not just that quality dropped
- Replay tooling for any historical run
- Concurrency, queueing and backpressure under real load
- 01
Decompose
We split the workflow into nodes narrow enough to evaluate independently.
- 02
Make state explicit
Agents exchange typed state, not free text, so handoffs can be validated.
- 03
Add a critic
A verification node enforces the rules that matter before anything reaches a user.
- 04
Make it durable
Long runs checkpoint, retry and resume instead of dying halfway.
When the task has genuinely different modes of work — planning, retrieval, generation, verification, side effects — or when you need to evaluate and improve parts independently. If a single well-prompted call with two tools does the job reliably, keep it.
Usually LangGraph for the agent graph and Temporal where runs are long-lived or must survive infrastructure failure. We keep the orchestration layer thin enough to swap, because this tooling moves quickly.