Agentic systems
Agentic AI vs automation
The short answer
Use deterministic automation when the workflow and correct behaviour can be specified explicitly. Use an agent when the system genuinely needs to interpret changing context, choose among tools and decide what to do next.
What deterministic automation does well
Deterministic systems are predictable, testable and inexpensive to operate. They suit validation, routing, calculations, permissions, policy rules and workflows where the possible states are known in advance.
What an agent adds
An agent adds discretionary planning. It can inspect context, choose a tool, observe the result and decide on the next step. Agents earn their place when a rigid workflow would need an impractical number of branches, or when language and ambiguous state are intrinsic to the task.
The cost of agentic behaviour
Flexibility introduces uncertainty. A production agent needs constrained tool access, explicit state, stopping conditions, recovery behaviour, task-level evaluation and observability. With those in place, autonomy becomes a controlled capability.
The usual answer is hybrid
Most useful systems combine both. Deterministic software controls permissions, state transitions, calculations and safety boundaries. The model interprets language, synthesises information or chooses among allowed actions. Separating the two makes the system easier to reason about and evaluate.