AI and Home-Cooked Software

“Every line of AI-generated code is a plausible-looking liability. It may pass basic tests, only to fail spectacularly in production with an edge case you never considered.”

Every time I read something along the lines I have to wonder whose code these people review during code reviews. It’s not like the alternative is bulletproof code.

Long-term SWEs at non-tech companies will spend much of their time reviewing vibe coded features/prototypes/scripts from non-technical employees and scaling them once they become critical infrastructure.

This'll eliminate jobs in the "develop CRUD app" industry but will create better jobs in security/scalability/quality expertise. But it'll take a few years as all these vibe coded business process scripts start to fail.

Programmers miss the human element, which is that many managers look at a software project as too risky, even if automating a business process could trivially save money. There are millions of people in the USA who spend most of their day manually transferring data from incompatible systems.

AI allows anyone to create a hacky automation that demonstrates immediate value but has obvious flaws that can be fixed by a skilled SWE. That will make it easier to justify more spending on devs.

I've been thinking in a similar way over the past year or so—we're seeing the emergence of more widespread access to custom software for use cases that previously never would have justified the investment.

There are so many situations where a little program can save one or a few people hours of work on tedious tasks, but wouldn't make sense to build or support given traditional software development overhead, but that becomes realistic with AI-assisted development. This is the idea of a sysadmin who has automated 80% of his job with a variety of shell scripts, borne out into many other roles.

We've seen the early phases of it with Replit and Lovable et al, but I think there's a big playing field for secure/constrained runtime environments for non-developers to be able to build things with AI. Low/no-code tooling increasingly seems anachronistic to me: I prefer code, just let an AI write and maintain it.

There's also a whole world of opportunity around the fact that many people who could benefit greatly from AI-built programs are simply not particularly suited to building them themselves, barring a dramatically more capable AI, where I think enterprising software engineers can likely spin out tons of useful stuff and address a client base they might never have previously been able to address.

I feel personally targeted :D

Programming classes didn't work out for me in college, so I went into sysadmin with a dash of Devops.

Now I can make small tools for things like syncing my living room PC to a big LED panel above the TV (was app-only but there's a Python reverse engineering which I vibe-coded a frontend for) or an orchestration script which generates a MAC address, assigns a DHCP reservation in OPNsense, and created the VM or CT using that MAC and a password which gets stored in my password manager.

I could have done either of these projects myself with a few weekends and tutorials. Now it's barely an evening for proof of concept and another evening to patch it up to an acceptable level. Knowing most of the stuff around coding itself definitely helped a lot.

AI tools have been so good for me for making home-cooked software. As a new-ish parent, it’s so much easier to do stuff. I don’t need to go into extra-deep focus mode to learn how to center a div for the hundredth time, I can spend that precious focus time on the problems that matter / the core motivation.

I've made this point before, and in the short to medium term, I really do think it's one of the biggest and most underrated uses of AI. If I am making a tool for myself, and only myself, and if I deeply understand both the inputs and the expected outputs, and if it's a one off script or tool designed to solve a specific problem I have, then a huge swath of the issues with AI coding go away.

It's still not perfect, but it is dramatically easier to be fast and productive, and it is a huge leap in capabilities for people who previously couldn't code anything at all, but had deep enough domain knowledge to know what tools they wanted, and approximately how they should work, what kind of information they should ingress, and what kind of information they should egress.

Ah, another "Now that we have AI, people can do [thing people could do for decades]" article. If there was something you wanted a computer to do, that it did not yet do, you programmed it. And if you didn't know how, you learned. BASIC was always there.

But the industry as a whole moved away from the idea that end users are to program computers sometime in the 80s or 90s (the glorious point and click future was not evenly distributed). So now the only tools for writing software out there are either outdated, or require considerable ceremony to get started with (even npm install). So what, we're gonna paper over the gap with acres of datacenter stealing our energy and fresh water to play token numberwang? Fuck me!

This article, and generative AI in general, is appealing to the people on Golgafrinchian Ark Fleet Ship B (aka "the managerial class") because it helps them convince themselves that they can now do all the things the folks on Golgafrinchian Ark Ship A can do (so who needs them, anyway) without having to learn anything. Now you can program without having to program! You're an Idea Person, and that's what's really important; so just idea-person into ChatGPT and all the rest will be taken care of for you. I think these folks are in for a rude awakening.