The recurring failure in agent work is often not the first answer. It is the gap between steps.
A task starts well, then waits for a person to approve a draft, confirm a record, or handle an exception. If the software treats each step like a separate prompt, the context gets fragile and the handoff becomes the weak point.
OpenAI’s Agents API points at a better pattern. With sessions, the agent can keep working across multiple steps, resume after approval, and preserve the run as something reviewable. OpenAI also says session events can be reviewed, and that guardrails or human review can pause work without breaking turn continuity.
That changes the design choice. For a claims check, invoice exception, or policy-sensitive draft, the question is not whether an agent can do the work. It is where the work should pause, what the reviewer needs to see, and what must be stored for audit and support.
In practice, this favors workflows built around durable sessions and explicit review points, not a chain of disconnected prompts. That usually means better traceability, fewer brittle handoffs, and a clearer path for operations teams to support the system after launch.