Effective AI Usage: AI-fu
In my last blog post I talked about the many aspects of modern AI and the importance of understanding them all. But even more important than this is what I am terming "AI-fu". So what is AI-fu?
AI
Effective AI Usage Part One
In my last blog post I talked about some lessons I've learned from using AI. I talked about a follow-up article talking about AI use at a higher level. Recent experience has reinforced my thinking on this. In this blog post we're going to focus on what AI is, the initial interaction, and training.
More AI Lessons
A little while ago I blogged on developing at speed. The obvious omission from all aspects was AI. But AI – like an IDE – is just a tool. Unless you understand what it can and can't provide, unless you use it intelligently, you will not reap the benefits. But unlike an IDE, AI doesn't come with a set of menus that hint at what it can and can't do. AI doesn't come with a marketplace of extensions that provide functionality shared by the community. And it's so new that we're all working it out. So what are my thoughts?
Using AI
As a researcher, I'm always looking to learn, to expand the toolbag I have, and find innovative ways to improve outcomes. Even when AI is not at the heart of the project I'm working on, I'm constantly looking for ways it can make my life easier and life easier for developers using what I create. And the fact that we targeted a standard IDE means the effort required to integrate AI is reduced. But as with any new tool, it's important to learn what it can do and what it can't. And work this week has shown me that this requires a diligent approach.