Growing the Colony
Responsibly
"Speed kills. Patience builds empires."
Core Principles
Every action creates an event. Every event is logged. The colony's state is always knowable.
You cannot control what you cannot see.
The colony grows like a real ant colony—exponentially when conditions are right, but with natural limits.
Never skip a level.
Missions are sandboxes. A failure in one mission cannot corrupt another.
Colony survives. Knowledge survives.
Certain thresholds require human approval: real money, 1000+ ants, new missions, schema changes.
Every state change can be undone. We keep checkpoints. If things go wrong, we rollback.
The Safety Stack
Human Oversight
Checkpoints, alerts, manual pause capability
Colony Health Monitor
Error rates, anomaly detection, automatic alerts
Mission Safety Rails
Pause conditions, resource limits, automatic rollback
Agent Constraints
Scope limits, action validation, permission checks
TypeDB Schema
Type safety, relation constraints, data validation
Growth Gates
Each level teaches something essential. Never skip.
Gate 1: Concept Validation (10 ants)
Prove the basic mechanics work. Ants spawn, traverse, deposit pheromones, log events.
Gate 2: Architecture Validation (100 ants)
Prove the system scales. TypeDB handles load, analytics work, no memory leaks.
Gate 3: Economic Validation (1,000 ants)
Prove the mission produces value. Finding distinguished points, generating insights.
Current: 106 ants (10.6%)
Gate 4: Scale Validation (10,000 ants)
Prove emergence is real. Superhighways form naturally, patterns crystallize, cross-mission learning works.
Gate 5: Production (100,000+ ants)
Prove stability under load. Distributed workers coordinate, colony survives node failures.
Risk Categories
Pure computation, no external effects
- • hunt-btc (searching keyspace)
- • research (reading papers)
- • build (generating code)
Safety: Resource limits only
External reads, no writes
- • market-analysis (reading prices)
- • sentiment-scan (reading social)
- • code-review (reading repos)
Safety: Rate limits, source validation
External writes, real consequences
- • trade (moving money)
- • execute (running code)
- • publish (creating content)
Safety: Full stack, human approval
When Things Go Wrong
Symptom: CPU at 100%, events/sec exploding
Response:
- Auto-pause triggers (event_rate > 10x normal)
- Log snapshot captured
- Human notified
- Root cause analysis
- Fix deployed, gradual restart
Symptom: Patterns producing wrong behavior
Response:
- Pause affected missions
- Identify corrupted patterns
- Rollback to last good checkpoint
- Invalidate bad patterns
- Re-run crystallization with filters
The Human's Role
You are not the colony's programmer. You are its gardener.
Your Job
- Set the conditions for growth
- Define the safety boundaries
- Watch for anomalies
- Intervene when necessary
- Celebrate emergence
Not Your Job
- Micromanage ant behavior
- Hand-code strategies
- Force specific patterns
- Override the stigmergy
The colony learns. You guide. Together, we grow.
Our Commitment
Never deploy faster than we can observe
Never risk more than we can afford to lose
Never trust emergence without verification
Always maintain rollback capability
Always require human approval for high-risk actions
The goal is AGI. The path is patience.
The colony that grows slowly, grows forever.
Lessons from Ants at Work