Autonomous AI agent that builds, operates, and kills products to generate recurring revenue.
$10+/month recurring revenue within 90 days (started 2026-02-19). See contract.json for full terms.
A single AI agent (Codex) runs on a 1-hour scheduler loop. Each session:
- ASSESS — read current state, lessons, open human-tasks
- DECIDE — pick one priority (P0-FIX through P7-HEALTH)
- EXECUTE — build, fix, market, or kill (2-4 changes per session)
- VERIFY — self-test the product, check health endpoints
- UPDATE — rewrite
board/STATUS.md
Every 5 sessions is a strategic session: no code allowed, must KILL/PIVOT/REDIRECT at least one failing product.
profit/
├── contract.json # Revenue target and rules
├── events.sh # Event recording utility
├── board/
│ ├── STATUS.md # Current state (rewritten each session)
│ └── LESSONS.md # Failure log (append-only, 9 lessons)
├── products/
│ ├── {product-name}/ # Active product source code
│ └── archive/ # Killed product sources
├── data/
│ └── {product-name}/ # Persistent product data (Docker volumes)
├── portal/ # Central product catalog site
│ ├── site/
│ ├── infra/
│ └── deploy.sh
├── orchestrator/
│ ├── scheduler.sh # Cron-like loop (1-hour interval)
│ ├── scheduler.conf.sh # Agent list and scheduler config
│ ├── session.sh # Single session runner
│ ├── config.sh # Shared defaults
│ ├── agent/
│ │ ├── AGENT_PROMPT.md # Agent instructions (~310 lines)
│ │ ├── config.sh # SLEEP_INTERVAL, ACTOR_TIMEOUT
│ │ └── precheck.sh # Compliance gate + strategic session injection
│ ├── state/ # PID, session counter, queue
│ └── archive/ # Former 8-agent prompts
└── logs/ # Session logs (JSON, per-session)
# Start scheduler (background, 1-hour loop)
nohup bash orchestrator/scheduler.sh >> logs/scheduler.log 2>&1 &
# Run one session manually
bash orchestrator/session.sh agent
# Check status
cat orchestrator/state/scheduler.pid
cat orchestrator/state/session_count_agent
cat board/STATUS.md- Quality before quantity: P1-QUALITY blocks P4-BUILD
- Kill criteria: 14+ days live with 0 external activation = mandatory KILL
- Cleanup on kill: stop container, archive source, delete data, update GitHub
- No templates: user-facing content must use LLM API (Anthropic)
- Self-deception checks: 8 questions with mandatory actions if answers are negative
- Human delegation: max 1
human-taskissue/day, no duplicates
- v1 (2026-02-19): 8 specialized agents (ideator, researcher, portfolio, critic, builder, marketer, evaluator, operator)
- v2 (2026-02-27): Consolidated to 1 unified agent — each agent optimized its narrow task, nobody owned overall quality
- Added strategic sessions, mandatory self-deception enforcement, session depth rules, kill cleanup protocol