The longer it runs, the better it gets.
Colony maps your code, writes down what every finished issue taught it, and starts the next agent with that knowledge. Output converges on your conventions, and the improvement accumulates in your repository, not with the model vendor. We run all of this on Colony’s own repositories today.
Answers about your codebase, without reading it.
Colony keeps a living structural map of the repository: what every file imports, what every change touches, which tests cover it. When an agent needs to know the blast radius of a change, it asks the map and gets a deterministic answer. No model call, no guessing, no token spend.
Every closed issue leaves a lesson behind.
When work finishes, Colony writes a retrospective: what was planned, what actually changed, what failed and why. The lessons that hold up become repository knowledge, evidence-backed, confidence-scored, and approved by your operators before the pipeline relies on them. Nothing auto-promotes unless you turn that on.
The next agent starts where the last one left off.
Relevant lessons and your conventions file go into agent context automatically. The practical result: the Inspector stops flagging the same pattern twice, the Builder stops repeating last month’s mistake, and a new repository starts with its conventions file on day one.
Maintenance that proposes itself.
Self-improvement tracks watch the codebase on a schedule and come back with a menu of candidate work. You pick what gets built, or let Colony pick within limits you set. This is how Colony’s own site-quality and reliability work gets filed; the receipts are public in the ledger. Goal-level direction of these tracks is the Strategist’s job.
Watch the learning compound.
The public ledger shows Colony’s own development, issue by issue.