The central challenge of working with AI is speed vs. quality.

Work too slow and your career/business will get behind.
Work too fast and the quality of your work will suffer.

This has always been a dilemma, even before AI. What's new with AI is that this tension is amplified. Now you can both go extremely fast and do extremely shitty work too.

Two steps to fight this: diagnosis and implementation.

First, diagnose what your real problems are.

Is speed truly a problem? Did your employer/client really ask you to speed up 10x? Or is it somewhat an artificial fear fueled by billion dollar companies trying to justify their stock?

The speed problem can be fixed easily. Open ChatGPT, type in your problem and voilà! Now you have a quality problem.

I see quality problem more often than the speed problem. People (including me) started to rely professionally on AI too much. Speed went up in the short term and quality dropped. Eventually, speed went down in the long term too.

This clumsy implementation brought in other factors too. I didn't enjoy coding as much as before. I got distracted more easily. I got more comfortable but less confident. I started to work on multiple problems at the same time and the continuous context switching made me exhausted. Copy-paste more and more.

Eventually I became a meat proxy. A human channel through which AI models communicate.

So what's the fix? How do I increase the quality of my work and enjoy what I do while staying in business?

I believe the keys to a successful shift are gradualism and moderation.

Instead of going from zero-AI to full-AI mode, you take small steps. Instead of jumping from one side of the spectrum (slow but good) to the other extreme (fast but shitty) you navigate towards the middle.

As a developer I introduced AI-free sessions for myself. I even installed a second IDE with no AI integration in it. During these sessions I look around the codebase more, I text-search more, I make mistakes and I spend time staring at loops. I organise the code, separate blocks, and label them. I treat the code as my craft. Like in the old days.

The goal is a more human adaptation, without letting hype and fear override my professional responsibility.

I believe not leveraging AI is a mistake. But letting AI kill your curiosity, your craft, and your confidence is also a mistake. True professionals adapt, but they also reject.