AI Makes Execution Cheap. Judgment Is Getting Expensive.

For most of my career, taking a requirement and turning it into working software was one of the most valuable things an engineer could do. AI is quietly rewriting that assumption.

Developers can now explore approaches, generate code, write tests, and refine implementations far faster than before. The distance between an idea and working code is collapsing. That is a genuine advantage, and it comes with a catch that is easy to miss in the excitement: when building gets this fast, building the wrong thing gets just as fast. The cost of execution is falling, and as it does, the cost of poor judgment goes up.

Which developers matter most now?

The developers I increasingly value most are the ones who simply get it. They understand what the client is trying to achieve, what the customer experiences, how the product works, and how the business makes money. They do not treat the requirement or Jira ticket as the complete definition of the problem.

That does not mean going rogue. It means understanding the intent well enough to know when something does not add up.

Sometimes the most valuable thing an engineer can do is throw a flag on the play.

Maybe the requirement works technically but creates a poor experience. Maybe it solves the immediate request while creating a larger product problem. Maybe there is a simpler way to achieve the same outcome. A developer with agency sees that and speaks up before a lot of perfectly good code gets written in the wrong direction.

What is engineering agency?

That is what I mean by agency. It is not independence from the team. It is ownership of the outcome rather than ownership of the task.

Whose responsibility is it to create that agency?

There is a leadership responsibility here too. For years, organizations trained engineers to stay inside their lane. Product defined the requirement. Engineering implemented it. QA validated it. Then we became frustrated when someone said, "That is what the ticket said."

We created that behavior.

If we want people to exercise judgment, we have to give them the context and permission to do it. They need to understand why something matters, who it matters to, and what outcome we are trying to create.

Does this mean technical skill matters less?

Engineers still need to understand systems deeply. They still need to write reliable software, manage complexity, protect security, and maintain quality. AI does not make those responsibilities disappear.

But technical execution alone is becoming less differentiating. AI can help almost anyone produce more code. The advantage increasingly comes from knowing which code should exist in the first place. This is the same conviction that shapes how we build at Exchange Solutions, where we apply AI-powered delivery across architecture, development, QA, and operations to build intelligent, scalable loyalty platforms like ES Loyalty™. The tooling changes what is possible. The judgment about what to build is still ours.

AI makes execution cheap. Judgment is getting expensive.