Factory Nexus is an AI software factory: you describe a feature, and a team of up to five AI coding agents decomposes it into tasks, builds each task in parallel on its own isolated git branch, runs the result through a multi-reviewer AI code review pipeline, and merges approved work into a PR-ready branch.
Building that system has forced us to answer questions that most teams running AI coding agents eventually hit:
- How do you keep five agents from stepping on each other's changes? (Branch isolation plus file-level ownership grants.)
- What do you do when an agent's work fails review — retry blindly, or re-review with focus on what actually changed?
- How much of a diff can a reviewer model meaningfully see before its context budget runs out, and what should you cut first?
- When an agent and a reviewer disagree, who adjudicates?
This blog is where we write those answers down, including the ones we got wrong the first time.
What to expect
- Practical guides on running parallel AI coding agents: branch and worktree isolation, merge strategies, review pipelines, retry policies.
- Build logs from real orchestrations on Factory Nexus — what shipped, what failed, and the numbers behind both.
- Design write-ups on the platform itself: task decomposition, agent capacity queues, review dialogue between agents and reviewers.
No fluff pieces, no "10 prompts that will change your life." If a post exists, it's because we hit the problem ourselves.
Try it
You can watch a swarm build a feature without signing up — describe an idea on the homepage and the agents start working. If you're sizing up a bigger project first, the Idea Estimator is free and doesn't require an account either.