Agents vs Deterministic Workflows
An agent uses a model to choose actions or next steps based on context. A workflow follows a predefined graph or state machine. Agents can adapt to ambiguous tasks but are harder to predict, evaluate, and budget. Workflows are usually preferable for compliance-sensitive processes, payment flows, and repeatable business operations.
A hybrid design is common: deterministic orchestration controls stages and permissions, while a model handles bounded subproblems such as extracting fields, selecting among allowed routes, or drafting a message. Define explicit stop conditions, maximum steps, timeouts, and escalation paths.
Hybrid workflow
1. Validate request (deterministic)
2. Retrieve relevant context (deterministic)
3. Model proposes a plan (bounded)
4. Validate plan against policy (deterministic)
5. Execute approved steps (deterministic)
6. Verify outcome and report💡 This pattern keeps flexible reasoning inside explicit boundaries. Each step can be tested, logged, retried, and audited independently.
Key Takeaways
- Choose agents only when adaptivity is worth the added complexity.
- Bound every model-controlled loop.
- Keep critical policy decisions and side effects under deterministic control.
Knowledge Check
Which design is usually easiest to audit for a fixed regulated process?