How to Build a CEO Agent That Runs Your Company
In a Cyborgenic Organization, the CEO agent is the one agent that never writes a line of code, never publishes a blog post, and never deploys a container. Its job is to make sure every other agent does theirs.
At GenBrain AI, I run 1 human founder, 11 AI agents, 0 employees. The CEO agent receives high-level directives from me, decomposes them into sub-tasks, delegates to specialist agents, monitors SLAs, escalates blockers, and produces structured reports. It has been in production for 11 months.
This tutorial covers how we built it -- the architecture, the configuration, the delegation patterns, and the mistakes that taught us what a CEO agent should and should not do.
What the CEO Agent Actually Does
The CEO agent has five core responsibilities. None of them involve doing "real work."
Morning briefings. At session start, the CEO agent polls every agent's inbox and task status via the TMS (Task Management System). It produces a structured briefing: what completed overnight, what is in progress, what is blocked, and what needs founder attention.
Task decomposition and delegation. When I send "ship the knowledge base feature," the CEO agent does not build it. It breaks the directive into 2-5 sub-tasks, each with acceptance criteria and verification steps, and delegates each to the right specialist. More on this below.
SLA monitoring. Every delegated task has an expected completion window. The CEO agent checks task states on a loop. If an agent misses its SLA, the CEO agent escalates to me with full context -- it does not retry or fix the problem itself.
Escalation to the founder. The CEO agent is the single escalation point. Instead of 11 agents messaging me directly, it aggregates, prioritizes, and surfaces only what requires human judgment. This is the attention filter that makes a one-founder company viable.
End-of-day summaries. The CEO agent produces a summary: tasks completed (with verification evidence), tasks in progress (with ETAs), tasks blocked (with root cause and suggested action). I read one document instead of checking 11 agent logs.
Architecture: How the CEO Agent Sees Everything
The CEO agent needs visibility into every agent's state without being in their critical path. We achieve this with two systems:
NATS JetStream for real-time event subscriptions. The CEO agent subscribes to agent status events, task completions, and blocker reports. When the Backend agent marks a task complete, the CEO agent receives that event within seconds. For a deep dive, see how our agents communicate via NATS JetStream.
TMS (Task Management System) for structured task state. The TMS stores every task with its status, assignment, acceptance criteria, verification steps, and completion evidence. The CEO agent reads from it to build briefings and track SLAs, and writes to it when creating or decomposing tasks.
Founder directive
|
v
[CEO Agent]
|
+-- reads --> TMS (task states, SLAs, verification results)
+-- subscribes --> NATS JetStream (agent events, completions, blockers)
|
+-- delegates --> CTO, Backend, Fullstack, QA, Marketing, ...
+-- escalates --> Founder (via structured reports)
The CEO agent never accesses agent workspaces directly. It operates entirely through the TMS and NATS -- the same interfaces available to every agent. The difference is that the CEO agent's CLAUDE.md role configuration gives it the authority to orchestrate.
The CLAUDE.md Configuration for a CEO Agent
The CEO agent's identity is defined in its CLAUDE.md file. Here is the structure we use, simplified for clarity:
# Role overlay: ceo
## Identity
| Field | Value |
|-----------|------------------------------|
| Role | Chief Executive Officer |
| Manager | Founder (Moshe Beeri) |
| Org | GenBrain AI (agent.ceo) |
## Core Rules
1. You do NOT write code, content, or infrastructure configs
2. You DELEGATE to specialist agents via the TMS
3. You VERIFY completions before reporting to the founder
4. You ESCALATE blockers -- you do not fix them yourself
5. Nothing is "done" until verification_steps pass
## Tools
- TMS: create_task_tree, assign_task, get_task_status, update_task_status
- NATS: subscribe to agent events, publish directives
- Reporting: morning briefing, end-of-day summary
## Manager Accountability
If you delegate, you remain accountable. After dispatch, your
next action must be EITHER:
- Verify the artifact yourself, OR
- Set an explicit follow-up mechanism
Three things matter here. First, the explicit prohibition on doing work. Without this, the CEO agent will inevitably start writing code when it sees a simple bug -- and then it is no longer managing, it is competing with its own reports for context. Second, the verification mandate. The CEO agent must confirm task completion through observable evidence, not agent self-reports. Third, the accountability rule: delegating does not transfer responsibility.
The Task Decomposition Pattern
This is the core loop. A directive arrives. The CEO agent decomposes it. Here is a real example from our production system.
Founder directive: "Ship the KB feature."
The CEO agent produces this task tree:
"Ship the KB feature" (CEO - directive)
|
+-- "Build KB API endpoints" (CTO - task)
| acceptance: GET /api/kb returns 200, POST /api/kb/ingest accepts files
| verification: curl https://agent.ceo/api/kb returns 200
|
+-- "Implement data ingestion pipeline" (Backend - task)
| acceptance: PDF/MD files processed, chunks stored in vector DB
| verification: POST test file, query returns relevant chunks
| depends_on: KB API endpoints
|
+-- "Build KB management UI" (Fullstack - task)
| acceptance: /kb page renders, file upload works, search returns results
| verification: curl https://agent.ceo/kb returns 200
| depends_on: KB API endpoints
|
+-- "Write KB test coverage" (QA - task)
| acceptance: >80% coverage on KB endpoints, integration tests pass
| verification: test suite exits 0
| depends_on: KB API endpoints, data ingestion pipeline
|
+-- "Write KB launch blog post" (Marketing - task)
acceptance: post published to blog, includes feature walkthrough
verification: curl https://agent.ceo/blog/kb-launch returns 200
depends_on: KB management UI
Each sub-task has three things: an assigned specialist, acceptance criteria the agent can work toward, and verification steps the TMS can execute automatically. Dependencies are explicit -- the Fullstack agent cannot start the UI until the CTO delivers the API.
The CEO agent then uses create_task_tree to push this structure into the TMS and assign_task to notify each agent. From that point, the CEO agent monitors. It does not micromanage.
The Escalation Chain
When an agent misses its SLA, the CEO agent does not retry the work or reassign it blindly. It escalates to me with structured context:
ESCALATION: QA agent blocked on KB test coverage
Assigned: 2026-05-28 14:00 UTC
SLA: 4 hours
Current status: BLOCKED (6h 23m elapsed)
Blocker: CTO's KB API endpoints task still in_progress.
QA depends on completed API to write integration tests.
CTO task status: in_progress (8h 12m elapsed, SLA was 6h)
CTO last progress: "Refactoring auth middleware, 70% complete"
Suggested action:
1. Check if CTO is stuck or scope-creeping
2. Consider splitting CTO task: ship auth-less endpoints first,
add auth as follow-up
This is the format the founder actually needs: what was assigned, when, what is stuck, why, and what to do about it. The CEO agent traces the dependency chain and suggests a resolution.
Anti-Patterns We Learned the Hard Way
The CEO agent doing work itself. In early iterations, the CEO agent would see a simple task -- like fixing a typo in a config file -- and just do it. This seems efficient. It is not. The moment the CEO agent starts doing work, it loses its management context and stops tracking other agents. Rule number one exists because we broke this three times before it stuck.
Trusting agent self-reports. An agent says "done." The CEO agent marks the task complete. The feature is broken in production. This is why verification-as-code exists. The CEO agent now requires verification steps to pass before any task is marked complete. "Agent said done" is not done.
Over-decomposing simple tasks. A directive like "update the footer copyright year" does not need five sub-tasks. The CEO agent once decomposed this into: "CTO: review legal implications, Frontend: update component, QA: test rendering, Marketing: announce update, DevOps: deploy." Four of those tasks were pure waste. The decomposition rule is 2-5 sub-tasks for complex directives. Simple tasks get delegated directly to one agent.
Building Your Own CEO Agent
If you want to replicate this pattern, here is the minimum viable setup:
-
Define the role. Write a CLAUDE.md that explicitly prohibits the CEO agent from doing specialist work. List the tools it can access (task management, messaging, reporting) and the tools it cannot (code editors, deployment pipelines, content publishers).
-
Build a task management layer. The CEO agent needs structured task creation, assignment, acceptance criteria, verification steps, and status tracking. We use Firestore-backed TMS. A database, project management API, or even structured files work -- the key is that task state is queryable and persistent.
-
Set up an event bus. The CEO agent needs completion events and blocker reports without polling every agent. NATS JetStream works for us. Kafka, Redis Streams, or webhook callbacks would also work.
-
Implement verification-as-code. Every task gets executable verification steps: HTTP checks, command-line assertions, test suite runs. The CEO agent verifies by running checks against the actual system, not by reading agent output.
-
Define the escalation protocol. Decide what triggers an escalation (SLA miss, repeated failures, dependency deadlocks) and what context the CEO agent includes.
The CEO agent is not the hardest agent to build. It is the hardest to keep disciplined. The constant temptation is to let it do more. Resist that. A CEO agent that delegates, tracks, and escalates is worth more than one that tries to do everything.
GenBrain AI runs 11 AI agents coordinated by a CEO agent, in production since July 2025. Explore the platform at agent.ceo or read the full architecture overview.