Designing operations for OpenClaw agent swarms

Design the swarm logic
before you deploy it.

Henry designs the operational logic. You build the OpenClaw swarm from the specification. Specialist scope, handoff boundaries, and escalation paths — all designed before a single agent is deployed.

The coordination gap

Why do agent swarms
lose coherence?

Agent swarms are powerful when each agent has a clear scope and clean handoff boundaries. They collapse when agents overlap, when routing logic is implicit, or when nobody has defined what "done" looks like for each specialist.

The hardest problem in swarm design isn't the agent framework — it's the operational design. Which agents should exist? What scope does each one own? When does one agent hand off to another? What context travels with the handoff? What happens when an agent gets stuck?

These are operational design questions, not infrastructure questions. Henry answers them through the same methodology it applies to human operations: map the process, specify each step, define execution modes, and assess fitness for delegation.

The result is a swarm design where every agent has a structured specification — scope, inputs, outputs, handoff conditions, and quality criteria — before a single agent is deployed.

Agent scope from step specification

Each Henry step specification defines a bounded unit of work. Steps grouped by domain become an agent's scope. The specification boundary is the agent boundary.

Handoff logic from process mapping

Eli maps the relationships between steps — dependencies, sequences, and parallel paths. These relationships become the routing logic that determines when Agent A hands off to Agent B.

Escalation paths from Fit Assessment

Ed's Fit Assessment identifies which steps an agent can handle autonomously and which need human oversight. These assessments become the escalation paths in the swarm routing — deliberate, not reactive.

How it maps

How do Henry specifications
become swarm routing?

Henry Specification OpenClaw Swarm Element
AAAERRR StageAgent domain and specialist role
Work Plane — Intent per stepAgent task scope and success criteria
Work Plane — Inputs / OutputsContext passing between agents in the swarm
Execution Plane — ModeAutonomous agent vs. human-in-the-loop agent
Execution Plane — DependenciesSwarm routing rules and handoff conditions
Experience Plane — Quality barAgent output validation and quality gates
Fit Assessment — Delegation readinessEscalation paths and fallback to human oversight
Agent cascade patternSpecialist-to-specialist routing topology

These are design-to-execution patterns, not a product integration. Henry produces specifications you translate into OpenClaw swarm configurations.

Agent cascade in practice

How does Henry use
its own agent cascade?

Henry itself runs an agent cascade — the same pattern you would export to OpenClaw. Each agent has a defined scope, structured handoff conditions, and specialist context.

Henry → Eli → Architects

Henry discovers the problem. Eli maps the process. Stage-specific Architects (Seth, Ann, Aaron, BJ, Tony, Fred, Patrick, Jonah) design each AAAERRR stage. Context flows forward through structured handoffs — never lost, never re-entered.

Joe → Ed

Joe specifies each step across three planes. Ed assesses delegation readiness. The cascade is the design methodology — each specialist owns a bounded scope, produces a structured output, and hands off cleanly.

Specialist scope

Each agent in the cascade owns a defined scope. Henry doesn't do process mapping. Eli doesn't specify steps. Joe doesn't assess fitness. The boundaries are the design — and they export directly to swarm routing.

Exportable pattern

The same cascade pattern that structures the Henry design workflow can structure your operational agent swarm. The specifications are the source of truth — the routing is derived.

Design the swarm.
Then deploy with structure.

Start with a diagnosis. End with agent specifications that route.

Talk to Henry →