Crew44

Crew44's default workspace includes a Partner, an Engineer, a Product Lead, and a Designer, and each one owns a role, a model, and its own skills folder. They hand off the baton with a one-line brief rather than passing the whole conversation along. The result is agents that stay focused on their job instead of acting as interchangeable generalists. No more all-rounders.

You pick the model for each role instead of locking the whole app to one. A strong model can plan while a fast one handles simple edits, so you're not paying premium rates for a rename. That per-task flexibility is one of the clearest reasons to split work across agents rather than run everything on a single model. It's a small setting. It adds up.

Everything stays on your machine, and Crew44 doesn't need an account to use. For anyone working with private code or notes, that removes a whole class of worry about where data ends up. It also means the app works without a cloud dependency. The tradeoff is real. You manage your own setup. That's the cost of keeping things local.

Each agent accumulates skills and memory over time, so what an agent figures out on Monday is still available on Thursday. That's the core fix for the fresh-contractor problem, where every new session forgets your conventions. The more you run the crew, the more useful it gets. It compounds.

One agent, the Partner, mines every run for new skills, memories, and routing tweaks, and proposes them with evidence attached. You click Accept and nothing else writes to disk, so the crew can improve itself without changing your setup behind your back. It's a nice middle ground between full automation and manual bookkeeping. Nothing writes until you say so.

Specialists run side by side rather than in a queue. The planner drafts while the builder codes while the reviewer checks, and handovers ship the baton, not the entire context window. That parallel structure is what turns a pile of agents into something that reads like an actual team. That's the whole point.

Each run shows elapsed time, tokens used, tool calls, and lines changed, along with the files the crew touched. You can see what the agents did and how much it cost, which keeps an agent workflow from feeling like a black box. That trace matters when you're deciding which model each role should use. No mystery here.