The software factory is already here.

The person who gets AI working first is useful. The company that keeps needing that person has not adopted anything yet.

An agent cannot take responsibility for a system it cannot see. Give it half the environment and you get half the autonomy, no matter how capable the model is.

If an agent can make ten consequential moves before a person finishes reviewing the first one, adding another approval meeting is not governance. It is a queue the machine will outrun.

A coding agent is not cheap because its meter is low. It is cheap when the work it produces survives without sending the rest of the bill to somebody else.

Put the same model inside two different coding systems and you do not have the same worker. You have two different factories pretending to share an engine.

An agent that has to rediscover who it is, what it may do, and whether the system around it is telling the truth will spend your budget answering questions the factory should have settled already.

One clean agent run proves that the agent can finish a task. The second run, after the context changed and nobody stayed late to rescue it, tells you whether you built a factory.

The agent can write the code. It should not be the only place that knows what the product is, how the work gets done, or why the result is allowed to ship.

The dangerous thing about cheap code is not that agents will write bad features. It is that they will make every feature feel too inexpensive to refuse and too established to remove.

You can spend months deciding whether a model is safe, then give it a harness that turns one bad decision into a thousand fast, repeatable actions. The model is only one part of the threat surface.

Giving a coding agent another agent to test its work is a real advance. It is also the start of a verification system, not the end of one. Two agents can still share the same blind spot, reward the same shortcut, and agree on a result that should never ship.

Code written by an agent should face a higher bar before it reaches production. Not because a person is automatically better, but because automation can repeat one bad assumption across a codebase before a human team finishes discussing the first pull request.