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Subagents

Helpers that get their own brief and return only the result: when they pay off, when they do not, and how to keep an eye on them.

✅ Verified 16. 10. 2026Source: official documentation →📋 Copy for your AI
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A subagent is a helper the agent sends off with a clear brief. It gets its own conversation and its own terminal, works independently, and only its summary comes back — not every intermediate step. That is why your conversation does not fill up with what it tried along the way.

When splitting the work pays off

Good fitWhy
A reasoning-heavy job (root-causing a bug, reviewing code, synthesising research)The subagent gets the whole space to itself and disturbs nobody
Work that would flood the main conversation with dataOnly the result returns, not hundreds of lines of intermediate output
Several independent branches at onceThey run in parallel — three investigations instead of three in a row
A fresh look without biasThe subagent does not see what you already assumed, so nothing stops it from saying the opposite
Poor fit — do it another wayHow
One tool call or a small file editJust ask for it directly; you save time and money
Mechanical work with logic between stepsA script — reproducible and exact
A job that needs to ask you somethingSubagents cannot ask — the main agent does that
Work that must keep running after you close the interfaceA scheduled job or a background process — see Scheduled tasks (cron)

What you see in your conversation

What appearsWhat it means
"I sent three helpers after that."The main agent keeps working; results arrive as messages
A frame with a count and statusIn the app and in the terminal you see who is running, for how long and what they did last
A way to steer or stop themWhen a subagent heads the wrong way, guide it or end it — no need to wait it out
The result as a summaryWhen you need proof too (a file listing, an HTTP code), ask for it explicitly

A subagent can neither ask you anything nor hire another subagent — nesting has a limit. When a task needs a conversation with a human, it belongs in the main conversation.

Briefing a subagent

Write the brief like a work order: what the goal is, how you will know it is done, and what it should bring back.

❯ Find what three VPS options cost from Czech providers. ❯ For each, give the price in CZK, what it includes and a link. Return nothing else. ❯ Review this code change for bugs. ❯ Return a list of findings: what, where and how it shows up. If there is nothing, say so. ❯ Go through these three sites and compare them. ❯ Give me a table: what they have, what they lack and how they differ.

When you want the answer in a machine-readable shape (a table, a list of items), you can give the subagent a fixed output shape (output_schema) — handy when a script processes the result.

How many can run

ThingHow it works
How many at onceBounded by delegation.max_concurrent_children (10 in our setup)
ConcurrencyTasks start together and results arrive as they finish
DurabilitySubagents live with the conversation that spawned them — they do not survive closing the interface
Visibility/agents in the terminal, the frame above the composer in the app

Pitfalls from our systems

What happenedWhat to do
A subagent reported "done" and nothing had changed. Its report is a claim, not evidenceVerify the outcome yourself — a file, a database query, the page's HTTP code. Put the proof into the brief
A subagent got stuck on something that needed our decisionIt cannot ask. Either give the job to the main agent, or tell the subagent up front how to decide
Work was left half-finished when the conversation endedSubagents are not a durable service. Anything that must outlive the session belongs in a scheduled job or a background process
A subagent did visible edits and the result was poorFor things that matter and are visible, the main agent is the better choice — it holds the whole brief. We keep subagents for research and for work that floods context
Ten subagents cost more than we expectedEach has its own context, so you pay for each separately. Delegate deliberately, not "just in case, everywhere"

Ready-made patterns

PatternWhat it looks like
Research several topics at once"Investigate these three questions in parallel and return five points for each."
Code reviewThe subagent hunts bugs and security risks while the main agent keeps working
Comparing optionsEach subagent examines one option and returns the same structure, so they can be compared
Gather, then decideSeveral subagents collect material and the main agent draws the conclusion

Our tips

TipWhy
Say exactly what it should returnA shapeless summary is hard to use; "a table: price, what it includes, link" is usable immediately
Say how the work will be provenThen nobody can just claim it is done
Give subagents jobs that do not depend on each otherThey then really run in parallel instead of waiting
Watch work in progressStopping a subagent that went the wrong way is cheaper than finishing a bad result

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