Clone Fan-Out Research
Spawn 100 or more identical, full-capability agent instances in parallel — each a complete general agent rather than a role-specialised worker — and aggregate their independent outputs into a single answer.
Intent & Description
🎯 Intent
Spawn 100 or more identical, full-capability agent instances in parallel — each a complete general agent rather than a role-specialised worker — and aggregate their independent outputs into a single answer.
📋 Context
A team needs an agent to do a wide-coverage job — compare a long list of candidate libraries, scan a hundred different sources for the same kind of information, or sample many independent strategies for the same problem. Each individual unit of work is too large for a stripped-down worker prompt but small enough that a full general agent can finish it on its own. The infrastructure can hand each instance its own isolated environment such as a sandbox virtual machine or a separate working copy of the codebase.
💡 Solution
- A driver computes the input partition (one slice per clone) and allocates N isolated sandboxes so the clones cannot interfere with one another. - N instances of the same agent are launched with the same system prompt and tools; only the input slice differs. - Each clone runs to completion independently and writes a structured result to a shared collection bucket. - A separate aggregator pass (LLM or deterministic) consolidates results via voting, ranking, deduplication, or synthesis. - The clones never communicate; aggregation is one-shot at the end. - N is bounded by a declared budget and the available sandbox pool.
Real-world Use Case
- The job naturally partitions into many independent units that each need full agent capability.
- Isolated sandboxes are available so clones cannot interfere.
- An aggregator (vote, rank, dedup, or synthesis) can produce one answer from N structured outputs.
Source
Advantages
- Wide-coverage jobs scale linearly with sandbox count.
- Identical clones simplify reasoning about per-agent quality.
- No inter-clone coordination means no message-passing failure modes.
- Isolation prevents one clone’’s failure from poisoning others.
Disadvantages
- Cost scales linearly with N; budgets must be explicit.
- Aggregation quality caps overall quality; a weak aggregator wastes the fan-out.
- Identical clones cannot specialise to harder slices.
- Without strict spawn bounds this collapses into Unbounded Subagent Spawn.