Agents Versus Workflows
Agents Versus Workflows
Key jargon
| Term | Plain-language meaning |
|---|---|
| Workflow | A mostly predefined path through known steps. |
| Agent | A system in which a model selects some next actions based on observed state. |
| Autonomy | The degree of freedom to choose goals, steps, tools, or timing. |
| Determinism | The extent to which the same input follows the same path and produces the same result. |
Key concepts
- Use a workflow when the path is known; introduce agentic choice only where variability creates measurable value.
- Autonomy is a design variable, not a binary product category.
Concept map
flowchart LR
A["Known path favors workflow"] --> B["Unknown choice invokes agent"]
B --> C["Harness bounds autonomy"]
C --> D["Evaluate outcome and path"]A workflow follows code-defined paths. An agent uses a model to choose some next steps or tools based on current state and observations.
| Use a workflow when | Consider an agent when |
|---|---|
| Steps and decisions are known | Paths cannot be enumerated economically |
| Determinism and auditability dominate | Flexible interpretation creates real value |
| Failure cost is high | Actions remain bounded and observable |
| A rules engine expresses policy | Tool selection needs semantic judgment |
Many effective systems combine both: deterministic outer workflow, model-assisted decisions inside narrow nodes, deterministic validation, and human approval at consequential transitions.
Exercise
Classify invoice extraction, travel research, database migration, incident triage, and deleting unused cloud resources. Identify which decisions should remain deterministic.
Principle
Start with the simplest architecture that works. Autonomy adds state space, cost, latency, and failure modes.