Module 04

Task Orchestration

How agents break work into steps

TL;DR

How agents break work into steps

> Overview

Agents do not solve complex problems in one shot. They decompose them into a sequence of smaller steps, like a project plan. This module teaches PMs how to think about step decomposition, how each step adds latency and cost, and how to design workflows that balance thoroughness with speed. Understanding orchestration is essential for writing realistic PRDs for any agentic feature.

> Why This Matters for Your Product

Every extra step in an agent's chain adds latency and cost. A 3-step chain might take 5 seconds and cost $0.01. A 10-step chain might take 30 seconds and cost $0.05. Your UX must account for this. You also decide where to add validation checkpoints where the agent verifies its work before moving on. This directly shapes the user experience.

> Interactive & tools

Example agent chain

Anatomy of an agent chain (example: support agent)

Total: ~4.8s, ~$0.016

Latency calculator

Latency calculator

Total expected response time: 10s

UX threshold: medium (2s instant, 5s ok, 15s+ risk drop-off)

Fixed vs. dynamic

Fixed vs. dynamic orchestration

Fixed orchestration

  • Predetermined sequence every time
  • Simple, predictable, easy to debug
  • Good for well-understood workflows

Best for: Stable, repeatable workflows

Dynamic orchestration

  • Agent decides steps based on input
  • Flexible, handles edge cases
  • Harder to predict cost and latency

Best for: Variable or exploratory tasks

Related Engineering Patterns

These are the technical patterns your engineering team will implement. Understanding them helps you have better conversations.

Prompt ChainingPlanningPrioritization

See the full decision framework

Sign up free to see this module's Key Decisions, the questions to ask your engineering team, and play the interactive Task Orchestration game.

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