Thoughts from a Thirsty Bear

 I noticed this throwaway comment recently: " Whenever I use AI to probe a topic I know something about, it seems to make a number of errors; by contrast, whenever I use it to explore topics I know little about, it knows so much more! " I must admit I have noticed something similar. When I am asking about something I know about, such as software, AI generated responses tend to be at best flawed, at worst plain wrong. Yet when I ask about something I genuinely know nothing about the results are compelling and I have to rein myself in. It turns out this is a named effect, observed by Michael Crichton (yes, that  Michael Crichton !). " Gell-Mann Amnesia ". He noticed that experts reading articles in their field of expertise will tend to find them full of errors, whereas reading other articles, even in the same publication, on topics outside their expertise  are believed to be credible. That is exactly what is happening with AI. When the results are critiqued by an exp...

What makes a high performing team tick? What is it that takes a team from being medium or low performing into elite performance as defined by DORA? On demand deployments, single figure bug counts, next to no downtime. Having worked in high performing teams, as well as having built a few myself over the years, I feel that I have a unique perspective on what it is that allows a team to work effectively together. The "Secret Sauce". So what's the recipe?  It's...." complicated ". But it looks a bit like this: At the top, unsurprisingly there is Technical Excellence . Team members need to be fully aware of and skilled in the various accepted best-of-breed tools and techniques that are out there. These currently include TDD, BDD, incremental design & architecture, refactoring, pairing/mobbing and so on. No excuses, these are all proven techniques that improve both quality and delivery, and should not be dropped unless there is a provable reason to. Even then ...