Merging, Not Writing, Is the New Bottleneck for AI Coding

The real bottleneck in AI-assisted development isn't code generation—it's safely merging hundreds of agent-created PRs. When teams run 10+ agents in parallel, local testing breaks: shared databases, port conflicts, and resource contention make isolation impossible.

Crabbox, a new tool from the OpenClaw creator, spins up per-agent cloud sandboxes with Docker, syncs uncommitted changes, runs tests, and returns evidence like screenshots. This moves verification from a fragile local setup to isolated, on-demand environments, enabling true parallel agent testing without conflicts.

The setup isn't trivial—teams must define Dockerfiles, YAML configs, setup scripts, and integrate with a sandbox provider like Daytona. However, once configured, agents can invoke `crapbox warm up`, test, and clean up automatically, drastically reducing the human review burden.

Evidence is early; only the creator's team uses it. The immediate lesson is that the merge and test pipeline, not model capability, will gate AI development speed. Most teams should watch this trend, not necessarily adopt the tool today.