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Agentic AI for serious engineers
Part I · Build
03 ·2026-03-25 ·2 min

Workflow First, Agent Second

Why you should reach for deterministic workflows before agents. Decision criteria, architecture comparison, and the engineering instinct that saves production systems.

Every time a team builds an agent, they should first ask: would a workflow do the job? This chapter makes the comparison concrete by implementing the same task both ways and measuring the differences.

What this chapter covers

  • The deterministic workflow — building a reliable pipeline for document question answering
  • The bounded agent — the same task with LLM-driven decision-making
  • Same task, two ways: the comparison — accuracy, latency, cost, and debuggability metrics
  • Design guidance: when to choose which — decision criteria for workflows vs agents
  • Planning and single-agent design — state management and bounded autonomy
  • Failure modes specific to this chapter — what breaks when you choose wrong

Code companion

The working code for this chapter is in src/ch03/:

  • workflow.py — Deterministic workflow implementation
  • agent.py — Bounded agent implementation
  • state.py — State management
  • compare.py — Side-by-side comparison runner

Get the full chapter

The complete chapter text is available in the book.

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