At the Redgate Summit in London, I ran a panel talking about Platform Engineering and how we can make developers more productive. One of the questions from our audience revolved around AI (Artificial Intelligence) technologies and how they might assist. As a note, AI tech includes a lot of different things, like machine learning (ML) among other things, but a lot of people seeing the media and hype around LLMs (large language models)  think those are AI. They see AI as what is implemented in ChatGPT and Copilot, which is correct, but incomplete.

One of the panelists, Jeff Smith of Redgate, said that he views the output from AI as a first draft, something that bootstraps further work by a human. This can save time and can help someone be more productive, but it's a starting point and a boost, not a final product.

I had not thought of AI this way, even though I expect to have to test, refine, and edit the results I've gotten from various assistants. While it might be possible for me to keep refining my prompt and perhaps generate better results (code and/or text), I don't know that it's often worth the time to do so. It's much easier to take the result of AI as a first draft and then make it fit my requirements.

In much the same way I use Stack Overflow or SQL Server Central for code snippets. They often give me a starting point and something I can then adapt to my needs without all of the time and effort spent on reading an API or SDK, experimenting with the syntax, and then actually using this in some code I'm writing. Similarly, I can get a head start on writing a summary or a pitch, though I'll admit I've found it less useful there. In fact, for many of my editorials, I've tried to use it to summarize an article or web link, and it does a very poor job (IMHO).

Some of you might be concerned or worried about this, and some might not. To me, the average-to-poor code produced isn't any different than the legions of Stack Overflow developers or SQL Server Central DBAs who take code from an online forum and fail to test it. Anyone using any code (or prose) should test (proof) it and verify it works appropriately in their situation. We have a lot of people who don't do that now and AI might exacerbate that with more code, but I don't know if we are in a worse situation. We certainly seem to be able to produce lots of average tech professionals now who turn out plenty of average code.

Ultimately AI is a tool that does exist in the world and will continue to exist. We have to learn to work with it and use it to our advantage. Good developers and DBAs will do that. I'd like to think that many organizations will look to hire and use those people as their staff and use fewer of the people who don't bother to test and improve the results from their tools.