Hamel Husain says elite AI teams spend 60% of their effort on error analysis, not writing code. They examine execution traces, annotate failures, and cluster them to find the most frequent problems. This data-driven approach to fixing errors beats spending most of your time coding.
The best AI teams spend at least 60% of their time doing this one task, and it's not coding. It's actually looking at data. And this process of looking at data is called error analysis. Error analysis is where you look at your traces individually and you write notes on what you see that's wrong. And then after you're done, you categorize those notes into buckets or clusters, and then you can do things like count them to prioritize what's wrong. And that simple technique could take you very far.
