Comparison
Plan-and-Execute vs Workflow vs Agent
Plan-and-Execute and Workflow vs Agent are both common AI/LLM terms but cover different ideas. Here is a quick side-by-side.
When you would reach for Plan-and-Execute
Tasks where the high-level structure is predictable but individual steps need autonomy.
A research agent: Sonnet produces a 7-step plan; Haiku executes each step; if step 4 fails, Sonnet re-plans from there.
When you would reach for Workflow vs Agent
Always reach for workflow first. Move to agent only when the next step genuinely cannot be predetermined.
A workflow: incoming email → classify → route to template responder. Deterministic.
Frequently asked
What is the difference between Plan-and-Execute and Workflow vs Agent?
Plan-and-Execute: Plan-and-execute splits agent loops into a planning step (produce the full step list up front) and an execution step (run each step). Cheaper than per-step ReAct and easier to inspect. Workflow vs Agent: A workflow is a deterministic pipeline where humans hard-code the LLM call sequence. An agent lets the LLM decide which steps to take. Anthropic's recommended default is workflow first, agent only when needed.
When should I use Plan-and-Execute vs Workflow vs Agent?
Tasks where the high-level structure is predictable but individual steps need autonomy. Always reach for workflow first. Move to agent only when the next step genuinely cannot be predetermined.
Are Plan-and-Execute and Workflow vs Agent the same thing?
No. Plan-and-Execute is agents & tools; Workflow vs Agent is agents & tools. They are related but address different parts of the AI stack.