Not because you are not capable. Not because you are not using AI. But because you are using AI the same way you did when it first appeared.

A year ago, we talked how much faster AI could make engineering teams. At that time, speed was the headline. Write a requirement, generate code, move faster than before. The improvement was obvious.

After a year of working with AI every day, I’ve realized something more important.

Speed is no longer the advantage. Workflow discipline is.

Today I see two types of engineers.

Both use AI. Both move faster than before.

One uses AI as an upgraded autocomplete. Prompt, review the diff, merge, move to the next task.

The other treats AI as a system component. Before coding, they let the agent clarify the requirement. They separate planning, implementation, and review into explicit phases. They generate tests and extend them with edge cases. They validate critical constraints, the parts of the system where small mistakes create long-term consequences.

The difference may look small in the first few months. Over time, it compounds.

One engineer can only focus on one problem at a time because their workflow is still single-threaded. Prompt, wait, review, merge, repeat.

The other can scale the number of things they build by increasing the number of agents they can clearly define, coordinate, and control.

The difference is not just productivity. It is leverage.