I’ve been talking each week with my friend and mentor Barney Cohen about AI.
Barney built and took a company public in the late ’90s, and he’s one of the clearest thinkers I know about business and management. We’ve both been trying to understand how AI will change the way businesses operate, and I thought I’d start sharing some of our conclusions. Take 'em or leave 'em.
One question we keep returning to is: When and where is AI actually useful?
As a software engineer, it’s tempting to give AI everything I used to do. It can think through architecture, write code, test it, debug it and help deploy it much faster than I can.
But it still struggles with the final polish required to get an app across the finish line. Those big little details that make something feel considered and finished.
So is it accurate to say "AI is useful for the first 90% of a project"? Not really.
Something we realized is that AI is also weak at the first 10% of a project. That original idea. Knowing what's worth pursuing and what's not.
The concept that feels accurate today is: AI is appropriate for the middle 80% of work, and poorly suited at the edges.
How do we make it?
Research, drafting, coding, testing, debugging, and iteration.
I feel "appropriate" and "poorly suited" are the right word too. It's not that AI can't come up with ideas, or push a project over the finish line, it's that the results are diminished.
Humans still matter most at the beginning, when we decide what deserves to be made, and at the end, when we decide whether it’s actually good. I’ve heard a lot about the importance of “taste” and the judgment required to refine and finish something well. But much less has been said about "discernment" and knowing what is worth making in the first place.
I suspect this pattern will appear throughout knowledge work, not just software engineering. Software is simply near the front of the wave.
I’ll keep sharing these little findings as Barney and I arrive at them, hopefully helping you find some footing, and opportunity, in your own work as we go.


