AI software factory / OpenFactory
Your developers got faster.Did your company?
Coding agents made code abundant.
But making coding 10× faster does not make your company ship software 10× faster.
The bottleneck moves.
OpenFactory finds what is limiting software production, attacks the constraint, measures what changed, then finds the next one.
Works with Claude Code, Codex and the agents your team already uses.
01 / The new constraint
Code got cheap. Software production did not.
Your engineers can now generate in hours what used to take days.
So they generate more.
Then something else starts breaking.
- 01
More code reaches review than humans can inspect.
- 02
Agents finish tasks that are not actually finished.
- 03
Context gets lost between tools.
- 04
QA cannot absorb the new volume.
- 05
Engineers spend their new productivity babysitting agents.
- 06
A repo built for ten humans struggles with fifty parallel workers.
Pressure map / beforeQueue rising ↑
Code inflow10×
Review capacity
The work waits here
Useful output1×
You removed the coding bottleneck. You did not remove the bottleneck.
You moved it.That is why adding another coding agent does not necessarily make the company faster.02 / The software factory
You already have the workers. Now build the factory.
Claude can build. Codex can check. Devin can take a task.
Tomorrow another agent will be better at something else.
Stable layerOpenFactoryworkflows / context / verification / history
OpenFactory sits around the agents you already use. It coordinates work between them, carries context, lets one model verify another, routes failed work back for correction, brings humans in when judgment is required, and records what happened.
But orchestration is not the goal.Throughput is.
The question is not how much code your agents generated.
How much useful software made it through the factory?03 / Independent verification
One model makes. Another checks.
A coding agent should not grade its own work. Different models fail differently. OpenFactory can use that disagreement instead of hiding it.
04 / What got through
41 verified. 12 sent back. 3 need you.
Most agent systems tell you what they completed. OpenFactory tells you what actually got through.
What passed.What failed.What was retried.Where humans intervened.How much it cost.How long it took.Where work is piling up.
Because once verification gets faster, something else becomes the constraint.That queue is your next bottleneck.
05 / The moving target
The bottleneck keeps moving.
This is the part that matters.
Every improvement exposes the next constraint.
- 01CodingMade faster
- 02ReviewQueue forms
- 03VerificationAutomate it
- 04QANext constraint
- 05DeploymentKeep looking
Make coding faster. Review becomes the bottleneck.
Improve review. Verification becomes the bottleneck.
Automate verification. QA becomes the bottleneck.
Fix QA. Now it might be deployment. Architecture. Context. Coordination. Human judgment.
Good.
That is what happens when a production system gets faster.
OpenFactory is built around a simpler ideaThere will always be a constraint. Find it.
06 / Replaceable workers
The workers will change. The factory is yours.
There will not be one magical coding agent. Today's best model will be beaten. New agents will appear. Your engineers will use several of them.
That is fine.
ClaudeCodexDevinWhatever comes next
Your software factoryYour workflowsYour verificationYour production historyYour knowledge
OpenFactory is not trying to win the coding-agent war. It is the production system around the workers you choose.
The workers will change. The factory gets better.07 / Factory memory
Every run should make the next run better.
An agent makes a mistake. Another catches it. A human corrects an assumption.
A particular model repeatedly fails at a certain kind of task. A workflow keeps getting stuck in the same place.
Those are not just failures. They are production data.
OpenFactory / ledgerappend only
08:31Claude Code
build assigned
08:38Codex
idempotency missing
08:41Claude Code
fix returned
08:44Codex
evidence verified
Today's catch → tomorrow's default
What to delegate.Who should do it.What needs independent verification.When a human should enter.Where production keeps getting stuck.
08 / The self-improving harness
How the self-improving harness gets better.
Models change. The harness keeps the evidence, corrections, routing decisions and human judgment that made the work reliable.
- 01AttemptReal work enters
- 02CheckAnother model verifies
- 03LearnEvidence becomes memory
- 04AdaptRouting and gates improve
Not a model that claims it improved. A production system that can show what changed.
Failures, corrections, accepted proof and human overrides become durable production history—not a vague chat transcript.
Future runs can choose a better worker, add an independent check, strengthen a gate or escalate sooner.
The harness proposes from observed results. Humans still own policy, risk thresholds and what is allowed to ship.
09 / The operating loop
Find the bottleneck. Solve it. Find the next one.
We do not assume your problem is coding. Or verification. Or orchestration. We measure it.
- 01Give OpenFactory a real production flow.
- 02See what gets through and what comes back.
- 03See where humans enter and where the queue forms.
- 04Attack the constraint. Measure again.
Repeat.
Run your own AI factory
Want to run it yourself?
Good.
Download OpenFactory. Point it at real work. Let one agent build and another verify. See what happens.
No sales call required.Get OpenFactoryYour real workDrop it in ↓
01BuildYour agent
→02CheckAnother agent
→03EvidenceYou decide
No rip-and-replace.Start with one flow.
One flow that matters
Want your company to ship faster?
Do not give us your whole engineering organization. Give us one production flow that matters to the business.
One production flowMeasured before + after
Something that takes weeks and should take days.
Or days and should take hours.
We will baseline where the time goes, identify the constraint, attack it with OpenFactory and measure what changed.
If we cannot materially change the economics, you will know. If we can, we will find the next bottleneck.