The Blog
Introducing Karman: Mission Control for AI-Native Engineering Teams
AI coding agents are now capable enough to write features, open PRs, and trigger deploys. The missing piece isn't better agents — it's a control plane that keeps humans in the loop. Today we're sharing what we've been building.
Why your AI agents need a mission briefing, not just a prompt
A prompt tells an agent what to do. A briefing tells it where it is, what changed, who owns what, and what failure looks like. The difference is everything.
Context is the missing layer in AI-assisted development
Most software sees inputs but not intent. Processes tasks but not history. Automates steps but not judgment. Here's how we think about closing that gap.
Why we named our product after the edge of space
The Kármán line is the boundary where Earth's atmosphere ends and space begins. For us, it's a metaphor for the point where a mission escapes the gravity of manual oversight.
Running Claude Code and Cursor on the same codebase — without chaos
Three agents, one repo, two engineers. How a small team in Singapore used Karman to keep parallel AI missions from colliding, and what we learned from watching them work.
The state machine at the heart of every Karman mission
Every mission in Karman follows a canonical lifecycle: Opened → Worktree → Agent → Tests → PR → Deploy → Verified. Here's why we modelled it as a formal state machine.
Building for AI-native teams from Singapore
Southeast Asia's engineering teams are moving fast with AI tooling. Here's what we're seeing on the ground, and why we chose Singapore as our home base.