Multi-Agent Teams
Some questions are too broad for one agent to research in one context window. Teams is agentFast's own native multi-agent orchestrator — a supervisor decides what to investigate, sub-agents each take one angle as a full run of their own, and their real cost rolls up into one number on the parent. It is registered through the same adapter seam as LangGraph, CrewAI, and the rest — the sixth orchestration option, not a bolt-on.
Its own context window
One angle's research can't crowd out another's or push the parent toward compaction — each child gets a full window of its own.
Its own budget
worker_max_iterations and worker_max_tokens are sized per child, not shared with siblings — one runaway angle can't starve the others.
Its own step tree
Every LLM call, tool call and guardrail check a child makes is a full trace, exactly like a single-agent run — nested under the parent in the dashboard.
Its own crash recovery
A child checkpoints exactly the way any other run does. The roster is written before any child starts, so resume never loses or re-runs finished work.
- 1Admission is lazy, not upfront
Children are admitted up to max_parallel as slots free — not all planned at once — because a child's usage only reaches the parent once it actually finishes.
- 2Real numbers, read back from the store
The moment a child finishes, its persisted token counts and cost — not the in-memory result — are added to the parent's totals.
- 3The ceiling sees real accrued spend
Because admission tops up as children complete, the parent's budget check is judged against what the team has actually spent, not an upfront guess.
# demo/research.sh — driven directly against the runtime
sdk: team
team:
max_parallel: 2
max_tasks: 2
worker_max_tokens: 40000Flat, not recursive
Children cannot spawn grandchildren — the supervisor plans a flat list once, up front. That keeps the budget ceiling and recursion depth both bounded.
Children don't talk to each other
Each child is independent by construction. If one angle's findings should inform another, that happens in synthesis, after both finish.
A dead angle doesn't sink the team
on_child_failure: continue (the default) synthesises from whatever succeeded, and names the angle that didn't in the report.
Teams shares the exact same durable execution, guardrails, and observability every other adapter gets — see it running on the ResearchAgent, or read the full mechanics in the docs.
agentFast is the production layer — memory, 50 tools, observability, evals, guardrails, human-in-the-loop — for LangGraph, CrewAI, the Claude & OpenAI Agent SDKs & Vanilla. Own it for life.
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