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Sequential Pipeline

Tasks pass through agents in a fixed order; each step's output feeds the next.

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Definition

Tasks pass through multiple agents in a fixed order; the output of each step becomes the input of the next.

Category: Information flow

When to use

Research → analyze → write, requirements → design → build → test, ETL-style well-defined flows.

When not to use

When the task structure is unknown, or when you need heavy dynamic branching or parallel exploration.

How to implement

  1. Model the flow as fixed steps; each step declares input/output schemas.
  2. Validate every step's output — don't pass raw natural language between steps.
  3. Allow per-step retry on failure rather than re-running the whole pipeline.
  4. Insert a verifier or human approval at critical nodes.

Minimal pseudocode

TypeScript
const pipeline = [researchAgent, analystAgent, writerAgent, editorAgent];
let state = { input: userTask };
for (const agent of pipeline) {
  state = await agent.run(state);
  validate(agent.outputSchema, state);
}
return state.final;
  • pipeline.started
  • pipeline.step.started
  • pipeline.step.completed
  • pipeline.completed

Common failure modes

  • Upstream hallucinations get repackaged downstream as more credible.
  • Fixed flows don't fit dynamic tasks.
  • Missing per-step checkpoints.

Implementation checklist

  • Input/output schemas defined.
  • Each agent's permission boundary defined.
  • Every agent call carries a run id / trace id.
  • Failure, timeout, cancel, and retry strategies defined.
  • Context passed is the minimum required, not the full history.
  • High-risk actions are gated by approval or a verifier.

References