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Colony is Fliiq’s multi-agent system. Five specialized agents — Intelligence, Research, Scout, QA, and Governance — coordinate autonomously to tackle objectives that benefit from breadth of exploration, competing perspectives, and self-critique.

Quick Start

fliiq colony start --mission "build the 50 most useful skills for freelancers"

# Dry run — 15-minute test to preview how agents approach the mission
fliiq colony start --mission "..." --dry-run

# Check progress
fliiq colony status

# View results
fliiq colony report
fliiq colony report --html

The Five Agents

AgentRoleWhat It Does
IntelligenceResearch AnalystScans the landscape for relevant prior art, tools, and developments. Produces structured Intelligence briefs that other agents consume.
ScoutProduct ManagerIdentifies opportunities and breaks the mission into concrete deliverables. Runs demand-sensing (community signals) and demand-generation (persona-based ideation).
ResearchCTOEvaluates technical feasibility and drafts detailed proposals. Reads Intelligence briefs and Scout’s proposals to ground ideas in reality.
QAQA LeadTests changes, monitors metrics, catches regressions. Establishes baselines before changes ship and validates after.
GovernanceStaff EngineerFinal decision-maker. Reviews proposals, approves or rejects, manages the codebase. The only agent with git write access.
This is not a democracy. Governance has final authority. QA opposition is a strong negative signal. Intelligence produces knowledge but doesn’t vote. Research and Scout propose and advocate.

How Missions Work

Give Colony a mission and all five agents focus on that objective:
fliiq colony start --mission "research every AI agent framework and map the competitive landscape"
  • Duration: Up to 1 hour (hard cap)
  • Cooldowns: 5–10 minutes between agent cycles for fast iteration
  • Output: A mission-deliverable.md with approved proposals, rejected proposals with reasoning, key findings, and completion stats
  • Completion: Three layers — duration ceiling, stall detection (3 empty cycles → auto-shutdown), and Governance declaration when the objective is met
Missions are designed for iteration — run a mission, review the deliverable, refine the objective, run again.

How It Works

Agents coordinate through shared state on the filesystem — no databases, no message queues:
.colony/
├── state/
│   ├── proposals/        # One YAML file per proposal
│   ├── intelligence/     # Research briefs
│   ├── votes/            # Agent vote records
│   ├── reflections/      # Per-agent learning logs
│   ├── metrics/          # QA baselines and results
│   └── governance_decisions.jsonl
└── reports/
    └── mission-deliverable-001.md  # Your mission results
Every change flows through a proposal lifecycle: an agent drafts a proposal → other agents evaluate and vote → Governance approves or rejects → approved proposals get implemented → QA validates the result. High-risk changes get escalated to you for human review. The Orchestrator manages the event-driven loop: when Intelligence writes a new brief, Research and Scout are triggered. When a proposal is approved and implemented, QA runs validation. When QA detects a regression, Research investigates. The system is self-sustaining once bootstrapped.

When to Use Colony vs Regular Fliiq

Colony is for WHAT and WHY. Regular Fliiq is for HOW.
QuestionUse
”What should we build?”Colony
”Build this thing”Fliiq
”Which approach is best?”Colony
”Implement this approach”Fliiq
”What are we missing?”Colony
”Fix what’s broken”Fliiq
”Explore this problem space”Colony
Colony earns its overhead when you need:
  1. Breadth of exploration — many options to consider before committing
  2. Competing perspectives — genuine tension between approaches
  3. Curation at scale — filtering a large space to the best subset
  4. Self-critique — output benefits from adversarial review before delivery

Mission Categories

Colony handles a range of mission types:
  • Curation & prioritization — “Map every API that would be useful as a Fliiq skill, categorized by domain”
  • Strategy & decision-making — “Should the business model be subscription, usage-based, or freemium? Argue both sides.”
  • Creative divergence → convergence — “Propose 5 different onboarding flows and pick the most compelling”
  • Research & synthesis — “Research how 10 different AI products handle memory and personalization”
  • System design — “Design the architecture for a skill marketplace with tradeoffs”
  • Adversarial review — “Review our current security model and identify every attack vector”

CLI Reference

CommandDescription
fliiq colony start --mission "..."Start a colony mission
fliiq colony start --mission "..." --dry-run15-minute test run
fliiq colony statusCheck current colony status
fliiq colony reportGenerate text report
fliiq colony report --htmlGenerate HTML report
fliiq colony stopStop the colony early
Colony requires a local .fliiq/ directory. Run fliiq init --project first if you haven’t already.