How teams divide work with coding agents

Coding agents change how work is shared on a team, but they do not remove the need for direction and review. The teams that benefit most are clear about who decides, who executes and who checks.

Key takeaways

• Humans set direction and make judgement calls.
• Agents excel at well-specified, bounded work.
• Good task context decides how good agent output is.
• Review against criteria, and keep risky actions with people.

A simple split

People decide what to build and why, weigh trade-offs, design the architecture and handle ambiguous or sensitive work.

Agents execute well-defined work: implementing a specified change, writing tests, updating docs, mechanical refactors and first drafts.

People verify the result against the intent and take responsibility for what ships.

Which tasks suit an agent

Ask three questions:

1. Is the outcome clear enough to write acceptance criteria?
2. Is the needed context available in docs, APIs and the task?
3. Is a mistake cheap to catch and undo?

If yes to all three, it is a good agent task. If the answer to the first is no, the work is not ready for anyone yet, human or agent.

Prepare the task

An agent is only as good as what it can read. Before handing over a task:

• Write the why, so it can make sensible choices.
• Add acceptance criteria as a checklist.
• Link the relevant docs, decisions and endpoints.
• Note dependencies on other tasks.

Osco tasks carry these elements, and an agent connected over MCP can read them with the permissions of the person who set it up.

Review well

Agent output can look confident and be wrong. A short review routine helps:

1. Check each acceptance criterion.
2. Read the diff against the linked design and decisions.
3. Look at tests, not just the code.
4. Confirm docs were updated where behaviour changed.

Treat the agent like a fast, junior teammate who needs clear briefs and careful review.

Keep boundaries

Some actions should stay with humans: deleting data, publishing outside the team, changing access and deploying to production. Use roles and approvals to enforce that.

Improve the loop

When an agent gets something wrong, ask what context was missing. Fix the task template or the doc, and the next task benefits. Over time your docs become sharper because agents expose the gaps.

Conclusion

Give agents bounded, well-described work, keep humans responsible for direction and review, and invest in the context they read. The payoff is faster delivery without giving up control.