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.
Describe
one prompt
Decompose
parallel tasks
Build ×5
isolated branches
Review ×3
AI code review
PR-ready
you merge
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
Running parallel AI coding agents: branch and worktree isolation, merge strategies, review pipelines, retry policies.
Build logs
Real orchestrations on Factory Nexus — what shipped, what failed, and the numbers behind both.
Design write-ups
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 and the agents start working.