Product 02

Agent Orchestration

Infrastructure to run AI agents safely.

orchestration · live agents

$ agent.status --live

● dev-spawner-sonnet     building TKT-485
● improver-daemon         scanning patterns
● closer-agent            reviewing PR #1444
● meta-orchestrator       routing tickets
● openclaw-gateway        3 sessions active
○ postmortem-daemon       idle · last run 4m

$ locks.list --active
→ 100 active locks · 0 conflicts

$ tickets.this_week
→ 1 357 total · +12 today · 92% done

OPS is the brain. Orchestration is the execution layer. Multiple agents, structured tasks, human-in-the-loop on sensitive ops, coordination locks.

Bounded autonomy, not chaos.

Talk to the founder

Capabilities

How agents stay aligned.

Multi-agent coordination

Locks, heartbeats, fencing tokens. Concurrent agents never step on each other.

Bounded autonomy

Dry-run, readiness checks, kill switches. Agents act only inside known bounds.

Human-in-the-loop

Destructive ops require explicit confirmation. No surprises.

Tickets & sprints

Structured work units, not free-form prompts.

Remote code API

Operate agents from your phone. Sandboxed, audited, safe.

Audit trail

Every command journaled, replayable. Nothing happens silently.

Architecture

The execution layer, exposed.

A look at how agents coordinate, lock resources, and report. Every piece is observable.

LAYER 01

Spawner

Boots an agent with role, memory pull, and sprint context.

LAYER 02

Locks

Fine-grained file and resource locks with fencing tokens.

LAYER 03

Daemons

Improver, closer, postmortem, capacity. Background workers.

LAYER 04

Tickets

Work is a ticket. Assigned, tracked, reviewed, closed.

LAYER 05

Sprints

Tickets grouped, scoped, time-bound. Feedback loops are structured.

LAYER 06

Mission Control

The dashboard. Live agent status, locks, tickets, errors.

Safety guardrails

Autonomy doesn't mean reckless.

Dry-run by default

Sensitive operations simulate first. The diff is shown. The human confirms.

Readiness checks

Before any destructive action, preconditions are verified. If any fail, the agent halts.

Kill switches

A single command stops every running agent. You retain the off switch.

Audit trail

Every command, every file edit, every API call by every agent is logged. Replayable.

Comparison

Why not LangChain / CrewAI / AutoGen?

They're great for prototypes. We built GNETICS for production.

Frameworks

Prompt orchestration in code
Stateless by default
Best-effort retries
Plenty of imagination
You build the safety layer

GNETICS

Structured patterns + dry-run
Persistent memory layer
Locks + fencing + heartbeats
Bounded autonomy by design
Safety is the substrate

When to use what

Frameworks: research, single-shot tasks, demos. GNETICS: agents touching code, data, customers.

Ready to run agents in production?

Talk to us about orchestration. Limited beta cohorts.

Request Early Access