In February 2021, I wrote Robotic Pair Programmers, which is my description of what I would want out of an AI coding assistant. I am pretty sure I was unaware of any “good” AI coding assistants, but a month later I took a look at Kite, which was an early attempt. I think there must have been something in the air. Copilot was released that June. ChatGPT would be released the next year.

It is now more than five years later, and we’re Approaching Infinity, where the doublings of computing are on a much larger base. We are past the bend in the exponential curve. But, still, there might be things that are constant (or at least aren’t immediately obsolete) in the three doublings we had since I wrote it.

The main thing I got wrong is that I thought the main way to use AI would be as a pair programmer, which was true for the first iteration. Now, it’s more as an independent co-worker that you manage. I still do a lot of pair programming with AI, but this won’t be true in the industry five years from now.

Here are sentences that I think still apply after five years.

Let’s say I index every Xcode project in GitHub, every iOS tutorial, every iOS question in Stack Overflow. Could that be distilled somehow and then shown to me at the right time?

Yup. And distilling is exactly the right word for this. This is how it works now, but that wasn’t clear to me then.

Whatever we do, we need to make sure that nearly every suggestion is useful.

I still think this is important. The ever increasing percentage of times that the agent is exactly correct has been the main thing driving usefulness in the last six months. It used to be true that you had to weigh whether it was better to correct wrong code versus writing it yourself. That ratio has tipped in AI’s favor.

Conserving flow should be the driver for how this works.

This is definitely true when you are coding with suggestions or doing smaller changes. It feels less important when doing a long agent run (or dark factory/loop engineering style systems). But, you see memes about how programmers are watching reels while agents do work, and it makes me sad. Part of the reason I make programs is to make me into someone that is better at making programs. This is true for the way I use AI, but I am not under pressure to be faster. Productivity is a goal, but not at the expense of my enjoyment.