Optimize for generation.
Agents finish bounded tasks quickly. The team gets more work than it can review and own.
Why software factories fail
Agents make implementation cheap. The team still has to review, understand, and own the work.
The opening chart starts with generated work outrunning review. The main chart lets you move decisions earlier.
The review-capacity model
The chart opens with fast generation and slow review. Advance the scrubber or adjust both rates.
Agents finish bounded tasks quickly. The team gets more work than it can review and own.
Small vertical slices keep the backlog small and keep review close to generation.
Product intent, architecture, and program design constrain the agent before it adds to the backlog.
The team still uses agents. It chooses a rate that people can review and redirects work while changes remain cheap.
An agent builds the ticket. The team still has to review, test, understand, and own the generated work.
Automated checks can catch a local defect in seconds. Maintainability appears when someone changes the system again, often weeks, months, or years later.
HumanLayer kept the agents. The team moved its decisions back into product intent, architecture, program design, and small slices.
Name the user, outcome, and reason.
Set boundaries and ownership before implementation.
Choose interfaces, data flow, and failure behavior.
Generate less work before the next decision.
Review while the team still shares the context.
Select a decision below. The useful split is not human versus agent. It is durable judgment versus bounded execution.
“The lights-off factory did not remove humans. It moved them to review and flooded the backlog.”
The useful gain is faster implementation inside a system the team still understands.