Practical guides for teams building with AI coding agents: run tasks in parallel, isolate changes with Git worktrees, and ship through review-first workflows.
Engineering
Running agents concurrently vs sequentially isn't just faster - it fundamentally changes how teams decompose work. We break down the throughput gains and the orchestration challenges.
Architecture
Containers are heavy. Branches alone aren't enough. Worktree-based sandboxing gives each agent a clean, isolated copy of your repo without the overhead.
Workflow
Real-time diffs, inline annotations, and one-click approvals. How we built a review flow that keeps humans in control without slowing agents down.
Industry
Different models excel at different tasks. Your orchestration layer shouldn't lock you into one provider - it should let you use the best tool for each job.
If you are evaluating multi-agent coding workflows, begin with setup and architecture docs before diving into implementation guides.