How to Start AI Coding If You Haven’t Yet

**Nathaniel Whittemore** (0:00)
Well, friends, it is officially time. Officially time to stop acting like coding with AI is something that is just for software engineers because it is not. Now, obviously, throughout the course of the last year and a half, as tools like Lovable and Repled and then Cloud Code and Codex came online, more and more knowledge workers outside of software engineering started to figure out how to use the power of writing code and building software to solve their own problems. And this is not just about all of a sudden those non-software engineers trying to act like software engineers. It's about finding new ways to do their jobs with the aid of software that they can build themselves. And yet for so many people, this still feels so inaccessible and out of range. But it doesn't have to be. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI.
I was recently having a conversation with one of my daughter's friend's parents. And this is a person who has been using AI extensively for a couple of years. They have multiple subscriptions to multiple different services at high expensive levels and has moved a lot of their work into an AI assisted type of paradigm. And yet for them, even considering anything surrounding AI coding, still seemed totally foreign. They were, in short, living that co-work life, never venturing over into the clawed code side of the world, and I think losing quite a bit for it. With absolutely no value judgments placed on where people are, I do think not having AI coding tools in your toolkit as a non-software engineer knowledge worker does at this point leave you behind. Earlier this week, we did that episode about OpenAI's recent enterprise research that found that around the end of April, beginning of May, the percentage of tokens that were being consumed via API agentically had flipped the amount of tokens being used non-agentically through ChatGPT, and that number has done nothing but rise. We saw that the firms who were in the top 10% of enterprise users, as opposed to the average firms, were using about 8.3 times as much AI, and the use cases that they were deploying were a lot more sophisticated, getting much more into systems and overall disruption.
And putting a fine point on the idea that this is not just a thing for software engineers alone, while starting from the February baseline, engineering-related users of Codex in the enterprise had grown 5x, basically every other function had grown significantly more.
Finance and accounting was using Codex 20 times more than it had been in February, sales and accounting was using it 41 times as much, and legal was using it 108 times as much as it had been back in February.
So what the heck are all these people doing with AI coding?
One thing that they are not doing in most cases, is all of a sudden trying to become the software engineers for their organization. This I think was a misconception of the early days of Vibe coding that has still a bit stubbornly persisted with us, despite it being for a long time not really where people are. The real argument for deploying AI coding as part of your AI toolkit as a knowledge worker, is not that you're going to become the software engineer, but because we're seeing that the people who are building are compounding their gains and their advantages relative to other AI users. That 83X gap that we saw between typical firms and frontier firms, was up from a 26X gap back in January. But there's a lot more reasons that you should consider coding as well. You're already doing a lot of the activity that would be extremely well suited to being supported by software, and a lot of the barriers that you would have always assumed have kept you back are pretty much just now gone. The reason to start now is that until you do, it's extremely hard to see which of your problems in work actually have software shaped solutions, although we're going to try to do a bunch of that today.
Now, when I run across folks like this friend that I was talking about before from my town, I hear some pretty common sets of reasons why they haven't fully dived in yet.
A lot of them come down to self-perception, the idea that they're not a technical person, whatever that means. But if you're someone who's been using AI for a couple of years now and is splitting your time across multiple subscriptions, you're certainly technical enough to dive into this other field.
Some folks have a fear of breaking something. They're worried that they'll make a mistake or they'll authorize AI to do something that leads to some irredeemable error. It's not that there's no rationale here, but there are of course ways to address those types of concerns, and certainly fear shouldn't be holding you back. For a lot of folks, it's still perceived barriers to entry. If they tried to use a terminal interface first, they might have taken one look at it and turned right around. Relatedly, maybe some of the onramps were wrong. If they tried to find some tutorial online, it might have been having them try to build something that wasn't relevant for their work. I think that's the big one, that they're just not sure from where they're sitting, what building and using AI coding could actually be for, for them.