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•30d ago
Arclask — governance for AI coding at team scale
Every engineer on a team is probably already using some AI coding assistant, Claude Code, Cursor, Codex, whatever. Individually they're all fine.
But once you've got 50+ engineers all pointed at the same codebase, I don't see how anyone actually knows if the architecture is holding together. The "rules" living in a CLAUDE.md or AGENTS.md file are just instructions the model can ignore under a long session or a rushed prompt. Nobody's actually checking the output against real constraints before it merges.
Same thing on cost. A hundred engineers sending overlapping context to the same model over and over, and most teams have no idea how much of that spend is redundant.
I'm building Arclask around this, a layer that checks AI-generated changes against your actual architecture rules before they land, gives leads real visibility into what's being overridden and why, and lets a team share context instead of everyone re-sending the same repo info to the model.