Coordinate multiple LLM agents with specialized skills in planning, validation, fallback handling, and taskchain orchestration.
Decomposes a goal across several specialised agents — a planner, executors, a validator — coordinating their work and handling partial failure. The most architecturally ambitious pattern here and the one most often reached for prematurely.
Genuinely heterogeneous tasks requiring distinct capabilities, where a single agent's context or tool surface would be unmanageable.
Anything a single well-prompted agent can do. Multi-agent architecture multiplies failure modes, cost and debugging difficulty, and the added complexity frequently buys nothing.
Every agent's actions must be attributable in one unified trace. A failure that emerges from agent interaction is close to undiagnosable without it.
Error propagation through the chain, where one agent's plausible mistake becomes the next agent's premise and the final output is confidently built on it.
A close-preparation chain where one agent gathers balances, another computes, a third drafts narrative and a fourth validates arithmetic — with the validator's failure halting the chain rather than annotating it.
Two different absences share this shape. Foundational solutions get built whatever the domain, so no domain links them; the rest are solutions this domain genuinely does not reach for. v_ai_solutions_unlinked separates the two.