I don't think I would encourage my kids to get involved with programming, instead I would encourage them to become entrepreneurs who might use some coding.
I don't think I would encourage my kids to get involved with programming, instead I would encourage them to become entrepreneurs who might use some coding.
But who will maintain those features going forward?
> I also see a lot of Devs simply trusting that the code is correct, they are losing touch with the code.
My worry is that developers can't outsource their understanding to AI forever. It's a lot of risk for companies to be accumulating code faster than developers can understand them.
If necessary there is tooling to generate docs from the code itself. There is also tooling for code quality and other things. You can also use AI to help build deterministic tools for specific code quality verification you may want - all major languages have established ways to parse the code and generate easy to inspect AST and code metrics that can be used for arbitrary quality measurements.
The entire “API” (all the code objects and functions interfaces) were carefully architected so their “contracts” are well determined, with very explicitly defined types. The machine written code now can evolve it directly and it has much less impact on context, which allows using very cheap and fast models and reduce a lot of expense while producing quality and predictable code output. Just a heads up if you are still using many md files and relying too much on the big frontier models.
>1) writing and refining specs, 2) "managing" agents by answering questions, evaluating new models, new tools, etc, 3) testing and validating AI output.
A software engineer isn't going to come up with a revolutionary new mining technique or robot or something. But someone who works at a mine might. Previously those people would go find a software engineer to try and validate their idea. Now they will go to AI
I dunno. Maybe I'm wrong, but I just don't see software engineers as being the best people to generate a lot of new ideas for domains outside of software engineering
If I was going through university right now I'd want to double-major in computer science and something else.
Domain expertise is good, but coupled with software knowledge is almost a superpower, when it comes to software projects.
I have seen projects that took 6 months when done by 1 expert + 1 engineer taking mere weeks when done by a single person who were good at both, in a competitor.
We need to experience and see how the world actually works, the pain people are actually experiencing. I deeply believe we build better software that way.
Have a software engineer working for a mining company that's a good candidate to drag out into the field for a bit? Get 'em out there, encourage them to ask tons of questions.
Real example: my wife is a nurse who works for an insurance company to coordinate care for injured workers to help maximize their recoveries. I hear a ton about the stuff she has to do, and just having her tell me about how things work has given me a glut of ideas of how I could help her bypass all the administrivia so she can focus on helping the folks she's really passionate about helping. Wouldn't have had any idea about any of this, otherwise. Unfortunately for her, I don't work for her company so can do nothing about it, but the ideas!
90% of the time when you really break down the "real" problems. You learned they aren't gon a be fixed by fucking software.
Less software coupled with operational changes would have helped many organizations I've witnessed across my career, but that's not politically palatable in a lot of places.
For example, when I was working in a finance team, I'd come across all sorts of situations where someone had a task of "once a week, download this data from this application, apply the following transformations, then upload the results to this other application". Anybody reading this site would think "ah, that's like a dozen lines of code! We should automate that". But that thinking is incredibly rare outside of our field.
On the flip side of that, you'll have the people who think they can simply buy software that will solve all their problems. "No, ma'am, buying a fancy new Spend Management System will not magically make everyone know or care about the difference between 'GL 10754 - Employee Appreciation: Meals' and 'GL 10822: Employee Meals (Discretionary)'".
My take on it is that the ability to recognize automatable problems boils down to 1) having an intuitive understanding of algorithmic reasoning ( this solution comes in 4 parts, the first part can be divided into 3 separate problems, which...) 2) having an up-to-date understanding of the extant capabilities of computers. 3) having the kind of bull-headed hubris that makes someone say "Sure, we currently do it this way, but I can do it better".
And at the end of the day, those features end up meaning you need some sort of engineer.
I do think perhaps LLMs could give product-minded developers more time to think about and refine those ideas, though.
It'll be interesting to see if this is sustainable. I could see it going both ways, and I honestly don't know which is most likely.
Well, if there are, I know what I'll do over the next long weekend...
As the number of programmers decrease, the value of computer related ideas decrease.
That's what I'm hoping at least.
My team has a non-engineer vibe coder who doesn’t know how to even use git, but managed to put together a large application that serves enterprise customers better than the real SWEs we had working on the project.
We’re in the process of porting their code into the main codebase, and it’s obvious to me, not so much them, that there is an insane amount of waste. But I’m not sure whether that’s a bad trade off, the end product works and llms get whatever he needs done.
OTOH, I’m an experienced SWE who is taking a stab at writing dev tooling in rust, which I don’t know and don’t have the time rn to learn. I am very aware there is a lot of waste, the project is obviously moving slower than if I was more involved with design. I was ok with the trade off but I’m growing antsy now.
All to say, it feels to me that vibe coded tech is a viable path so long as you accept what you’re going to get.
The one exception I see rn is when we try to do brownfield work, LLMs get very confused and simply cannot manage an old dog shit human written system with a new set of concepts floating in. Jury is out whether this will also happen with ai slop, but again maybe it just doesn’t matter
Over the past year, I've been trying to better document the equipment according to new QA standards. This also means I need a way to test the racks without production hardware. Everything goes hand-in-hand, how do you test a car without an engine? We finally got access to an approved IDE with a built-in AI model so I figured I'd try that out. I had been using our ChatGPT-equivalent tool for a few months for little scripts and questions but that's pretty ineffective for a major code base. That new IDE cranked out a slick certification application that does everything I need in about a day. I turned it back to my existing codebase for the production testing and gave it my wishlist of upgrades and features. Took about two weeks but I'm ready to push v1.0.
One of the main issues is that I'm not the one usually testing new devices, technicians are and they aren't always familiar with the software or equipment. Automating an entire test was a big effort a couple years ago and I got to the point where after a bunch of setup, you just click the GO button and sit back to watch. But now, AI has automated even more of the process so all of the stupid config files one had to setup previously are now automated. The various apps you had to run in the background are all built into one package. The silly little bugs I was dealing with for years have totally been wiped out with better error handling and monitoring of connections. It's amazing how well this new thing works and how much it actually looks like a real software engineer made it. It's even got simulators built in so we can test every part of it without needing actual equipment or the production units.
I've been wanting to find a new job for a while but this automation project has been holding me back. I've so badly wanted to complete it because I'm the one that wanted it in the first place. If I had like six months of dedicated time with the equipment (impossible, at best I get a couple weeks of downtime), I maybe could have made something similar but it would have been lousy code. With just two weeks of working with AI, I'm over the big hurdle. I've still got a few things to clean up before its ready for production but I'm basically 40 hours of work away from being at the point where I could just walk away. Hell, I just realized I could even have the AI write the manual as well.