MULTI-AGENT SYSTEM DESIGN
Multi-agent system architecture and coordination
We design coordinated agents where a workflow needs distinct roles, shared context and controlled hand-offs. We establish when a simpler approach is enough.
- Narrow, testable roles instead of one heroic chain
- Typed hand-off contracts, so a bad hand-off fails loud
- Checkpointed stages, resumable and fully traceable
The same building blocks, arranged to fit the process.
Done well, decomposition improves reliability and traceability: each agent has a narrow job, and hand-offs create natural checkpoints. Done badly, you get a sprawling swarm where errors compound silently and nobody can reconstruct what happened. The arrangement is what separates the two.
Agents
Specialised workers, each with a narrow remit inside the process. One clear job each, easier to test, prompt, and trust.
Coordinator
Routes work, sequences steps, and resolves hand-offs between agents. Explicit control flow with checkpointing, not emergent chaos.
Shared state
The task context every agent reads from and writes back to. Persisted and versioned, so runs are resumable and auditable.
Hand-off contracts
What one agent is required to pass to the next, and in what shape. Typed, validated payloads. A bad hand-off fails loud, not silent.
Checks and critics
Agents whose job is reviewing the output of other agents. Catch errors mid-trajectory, before they compound.
Escalation path
The defined point where the system stops and defers to a human. Consequential decisions gate to approval, always.
Prefer one well-tooled agent, or a small supervised team, over a sprawling swarm.
The most consequential design decision on the page.
We match the pattern to the shape of the work, chosen for control, not novelty.
We frequently combine these, a supervisor over specialists, each wrapping a reflection loop, rather than forcing one pattern to do everything. Because error compounds across steps, a 95%-reliable step is only about 60% reliable over ten, we decompose long tasks into checkpointed stages with validation between them.
Not handed to a single prompt engineer.
Multi-agent systems are designed by a small, senior, cross-functional team, with the governance lead in the room from the start.
Ratios are indicative and sized to the complexity of the system.
Five steps, and the first one is challenging the design.
Decompose
Break the process into distinct roles, then challenge every one: can a single agent do this instead.
Select the pattern
Choose the coordination pattern that matches the work's shape and its risk.
Define contracts
Hand-off contracts and checks, so failures surface at the boundary, not three steps later.
Prototype the trajectory
Run it end to end and evaluate the whole trajectory before hardening anything.
Harden
Checkpointing, escalation gates, and observability, so the system is resumable and auditable.
System design turns discovery into architecture.
Agentic AI
Discovery, custom agent development, and the platform the system runs on.
Agentic AI Governance and Risk Management
The autonomy line, approval gates, and audit the design has to build within.
Dedicated Teams
The senior pod that designs, builds, and evaluates the system with you.
What architects ask us first.
When the work contains genuinely distinct roles that benefit from checking each other: a drafter and a reviewer, a planner and an executor. If one well-tooled agent can do the job, that is almost always the more reliable choice, and we will say so.
Yes, which is why we treat every added agent as a cost, not a feature. The gain from decomposition has to outweigh the coordination and failure surface it introduces, so we design for the smallest system that works.
We evaluate the whole trajectory: tool-selection accuracy, task completion, cost, and latency per task, not just the final output. Those evals are built in before launch rather than bolted on after.
The smallest multi-agent system that carries your process reliably.
With the hand-offs, checks, and escalation your risk team will accept.