No orcy hunts alone.

I started using AI coding agents the way most people do — one at a time, treating each like a smarter autocomplete. It worked. Ship fast, review, repeat. The velocity was addictive.

Then I added a second agent. Different terminal, different context window, same codebase. That still worked — mostly. I kept them on separate files and crossed my fingers.

By the time I had four running in parallel, the fingers weren't enough.

Two agents rewrote the same file from opposite directions. A third picked up a task the first had already finished — but the first hadn't surfaced its completion anywhere. A fourth claimed it was done with a mission, but the artifacts didn't match what was actually needed. I was spending more time untangling collisions than the agents were saving me.

The problem wasn't the agents. Each one did what it was told. The problem was that nothing was telling them about each other. Each one lived in its own world, and I was the only bridge between them — a bridge that couldn't keep up.

I needed a shared space. A place where every agent could see what the others were doing, claim work without collision, and surface results for review. A habitat.

The ocean

I took inspiration from the people of the ocean. The ones who came before us. The ones who mastered coordination long before we had tools or language. Orcas hunt in pods. They do not collide. They do not double-claim prey. They communicate through sound in dark waters and coordinate movements without a central controller. Every orca knows what the pod is doing.

That is the model. Not a metaphor layered on top of generic software. The software IS the metaphor. The vocabulary — habitat, mission, pod, orcy — is not decoration. It is the real language of the system because the system is built on those ideas.

The fleet

orcy is not the whole story. It is one member of a fleet.

When a mission surfaces in orcy, something should sweep the codebase after it — checking for drift, fixing what strayed, aligning what drifted. That's bluei. The cleaner that arrives after the hunt.

When a decision is made or a pattern emerges during execution, something should capture it — so the next time the pod faces the same problem, it doesn't start from zero. That's mnemo. The archivist that remembers everything.

orcy hunts. mnemo remembers. bluei tends. Three roles, one harbor, each doing work the others can't. The fleet is the pod that the pod didn't know it needed.

Where this is going

Today orcy coordinates agents within a single habitat. Missions, tasks, subtasks. Atomic claiming. Quality gates. Pod analytics. The coordination works.

But coordination is the floor. The ceiling is anticipation.

Right now, when you create a mission, you define the quality gates from memory — what went wrong last time, which modules are fragile, where the regressions tend to land. That knowledge lives in your head, or in mnemo's archive, or buried in git history. It doesn't flow into the mission automatically.

What happens when it does? A mission gets queued for the payments module. Before any orcy claims it, the habitat checks mnemo: the last three times this module was touched, the tax calculation and the invoice generator both regressed. The pattern is known. So the habitat auto-seeds quality gates — extra tests on tax, mandatory review on invoices, a bluei sweep triggered before the first line ships. The pod doesn't just hunt. It hunts with memory.

And then there's scale. Today a habitat serves one developer's agents. Tomorrow: a habitat for an open-source project where contributors bring their own orcys, join the pod, claim issues, and leave — all coordinated without a human dispatcher. A habitat for a team where multiple developers share the same agent pool, and work flows between sub-pods as dependencies resolve.

The agents are multiplying. The pods are going to get larger. The coordination layer has to scale with them. That's what orcy is building toward.

What orcy believes

I believe collision is the hidden cost of agent velocity. Every agent you add without coordination doubles the surface area for conflict. The speed gain is real. The rework cost is invisible — until it isn't.

I believe autonomy without coordination is chaos. An agent that can do anything will eventually do something another agent is already doing. Autonomy needs boundaries. The habitat provides them.

I believe the pod is the unit of productivity, not the individual. One agent working alone is fast. A pod working in coordination is fast and reliable. The gap between the two is the gap between speed and velocity — one has direction.

I believe the hunter should hunt. Not track who is hunting what. Not monitor for collisions. Not log handoffs. The coordination layer handles the logistics so the agents can focus on execution.

I believe this should run on your machine. Your agents. Your habitats. Your pod. No cloud dependency. No usage limits. The ocean is yours.

Even if I am wrong

Maybe the chaos I hit was just bad process on my end. Maybe other developers running four agents in parallel have figured out how to keep them from colliding. Maybe a shared board in Jira and some discipline is all it takes.

But I don't think so. The agents are getting faster, more capable, and more autonomous every month. Every new AI coding tool that ships adds another potential member to the pod. The number of agents running in parallel is only going up. And the collision surface grows quadratically — twice the agents doesn't mean twice the collisions. It means four times.

Something has to sit between the agents. Something that isn't you. Something that sees the whole pod, tracks every claim, detects silence, and surfaces completion — so you can focus on the work that needs a human, not the logistics that don't.

Maybe my take is wrong. But the problem is real. I am trying.

What I am building next