Returning to the Low-Code CTO: Lessons from the AI Fast Lane

Look, I know it’s been a while since the last issue of this newsletter, and it’s not because I’ve run out of ideas or conversations. Honestly, the sheer speed and volume of what’s happening in the AI space has been eating up all my external bandwidth. But as we roll into the holiday season, I’m making a little time to get back to writing and share what’s been on my mind. So here’s a quick rundown of the insights and conversations that have been brewing both in my head and around the Launch by Lunch community.

Developer Pushback on AI

So one of the very common pushbacks I get from very technical people in my network is, “Oh, it’s really great these people are building without code, but the reality is when it breaks, they’re going to have to bring us back in, and they don’t know how to read it.” And I don’t know if I agree with that, because I no longer write legacy code. I always use an AI proxy that sits between me, because it gives me a space to think about the “why” before I decide whether any line of code needs to be changed.

And so my pushback to developers is: why do you think you actually need to come in and solve someone else’s problem? Are you expecting these founders to fail? Because these founders are not expecting to fail. They know they can build with it. They don’t want me or anyone else at Launch by Lunch to fix it for them. They want to understand where their thinking went wrong and how to fix it.

“Legacy Coding” is the name I give to how I used to code before AI and MCP.

Where do Junior Developers Sit?

Then the next thing I’ve noticed—and there have been some blog articles on LinkedIn about this—is that junior developers can build quickly, but they don’t know how to debug. We’re in this in-between time where people who were educated to value code and syntax because that was the only way to deliver value are now seeing a new tier of people who maybe don’t code everything by hand, but they get context differently. I had this happen recently with my own proof-of-concept. Instead of just coding it all myself, I asked the AI to plan and refactor as if it were a seasoned Google engineer. It wasn’t about learning to code better myself, but framing the work differently.