What to do
An assistant responds inside a developer-led workflow; an agent can plan multiple steps, inspect a repository, run tools, and modify files toward a goal. Choose based on the level of autonomy the task can safely tolerate.
Control is the key distinction
Autocomplete and chat keep the developer in the tightest loop. Agents operate across a longer horizon and may search files, execute commands, edit several modules, or open a pull request. Product labels vary, so inspect actual permissions and behavior rather than relying on the word agent.
Match autonomy to task risk
Assistants fit ambiguous design work and small edits where continuous judgment matters. Agents are useful for bounded, testable work such as updating repetitive APIs, resolving a well-described issue, or drafting tests.
- Prefer low autonomy for production access and irreversible operations.
- Use agents where success can be checked automatically.
- Require review for generated code regardless of interface.
Compare the operational cost
An agent may save typing but consume more model tokens, CI minutes, and reviewer attention. Evaluate completed, accepted tasks rather than lines generated. Include setup, supervision, rollback, and failed-run cost.
Practical checklist
Continue researching
This guide is an editorial framework, not a product endorsement. Recheck vendor documentation and your organization's requirements before making a purchasing or security decision.