This week, there are two interesting articles in the newsletter. The first is a markdown getting started article, which helps you learn how to format your documents. At first, I wasn't sure I liked markdown, but I've come to prefer it for a lot of documents. It's easy to use, and it makes using Git for docs very easy. Plus, I can mix in markdown and HTML as needed, which I really appreciate. I think most people who collaborate and update any documents in a team should learn to use markdown instead of Word, Notepad, etc.

The second one that caught me eye is one on Power Query. I don't know Power Query, but there was a piece on the 13 things John Kerski wishes he knew when he started. I didn't really do more than skim this since I am not writing any Power Query right now. What was interesting to me is that I'm not sure I'd bookmark this if I were actually writing Power Query in Power BI as part of my job.

Maybe I would, but as I start to use a GenAI more and more to get me started with different projects or requirements, I'm finding it as a way to kickstart me in learning something new. It's not perfect, and I have to test the results I get. Learning to judge the quality is part of my job, but that's different than trying to learn something new from scratch. That's a similar view to what I've heard from a few people. This podcast with Kent Beck showcases this view (starts at 6:12).

In the real world, when I wanted to learn something new, I often looked for a book or a few magazine articles that might get me some basics in a new area. In the digital world, I used to do the same thing, but in the last 20 years, I've been looking for an article or a "start in 30 days" book that might give me some basic skills. Then I could experiment and extend what I learned to get work done, likely asking friends or someone in a forum how to do the thing I need.

Now I ask a GenAI and go from there. I no longer worry about learning the specifics of a language, as I have a good idea in general of the things I need to do. What I'm using the GenAI to do is implement some details, and then I go back and check things. It's like having an intern who can do a first draft while I work on something else.

Except it's way faster.

GenAI models aren't perfect, and they make mistakes. However, the more I use them, the more I enjoy them, and I find enough small time savings that I want to use them more.