not-a-problem
Open source · 2026

omunculus: teams of AI agents with rules and oversight

Open-source engine that coordinates several AI agents: it hands out work, limits what each one may do, calls a person when needed, and records every step.

Service
AI agents
Area
IT

01The problem

Multi-step AI work had no single record of who did what. Permissions were loose, and a stuck agent simply stopped, with no retry and no escalation to a person.

Overview

How the solution works

People Workflow builder sets the rules AI agents run the tasks Person in charge approves or takesover Inputs Work item goal and context Permission limits per agent Outcomes Finished work with human review Full history of every step Process 01 Receive work 02 Split intotasks 03 Run isolated 04 Ask approval 05 Retry 06 Record Solution Work distribution Layered limits Approval inbox Event log
  1. 01
    Receive workWorkflow builder · sets the rules
  2. 02
    Split into tasks
  3. 03
    Run isolatedAI agents · run the tasks
  4. 04
    Ask approvalPerson in charge · approves or takes over
  5. 05
    Retry
  6. 06
    Record
SolutionWork distributionLayered limitsApproval inboxEvent log

02What we did

We built an engine that hands out work items and splits them into subtasks for other agents, runs several agents at once in isolated environments, and applies layered permission limits: each tool is allowed, allowed on request, or blocked. It has a human approval inbox, automatic retries with escalation to a person, and a full event log.

03What it changes

Whoever builds AI agent workflows controls what each agent may do, has a full history to audit, and gets a person stepping in when needed.

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