Technology

To quote your quote:

I got the product launched. It worked. I was proud of what I’d created. Then came the moment that validated every concern in that MIT study: I needed to make a small change and realized I wasn’t confident I could do it. My own product, built under my direction, and I’d lost confidence in my ability to modify it.

I think the author just independently rediscovered "middle management". Indeed, when you delegate the gruntwork under your responsibility, those same people are who you go to when addressing bugs and new requirements. It's not on you to effect repairs: it's on your team. I am Jack's complete lack of surprise. The idea that relying on AI to do nuanced work like this and arrive at the exact correct answer to the problem, is naive at best. I'd be sweating too.

They never actually say what "product" do they make, it's always "shipped product" like they're fucking amazon warehouse. I suspect because it's some trivial webpage that takes an afternoon for a student to ship up, that they spent three days arguing with an autocomplete to shit out.

I cannot understand and debug code written by AI. But I also cannot understand and debug code written by me.

Let's just call it even.

Great article, brave and correct. Good luck getting the same leaders who blindly believe in a magical trend for this or next quarters numbers; they don't care about things a year away let alone 10.

I work in HR and was stuck by the parallel between management jobs being gutted by major corps starting in the 80s and 90s during "downsizing" who either never replaced them or offshore them. They had the Big 4 telling them it was the future of business. Know who is now providing consultation to them on why they have poor ops, processes, high turnover, etc? Take $ on the way in, and the way out. AI is just the next in long line of smart people pretending they know your business while you abdicate knowing your business or employees.

Hope leaders can be a bit braver and wiser this go 'round so we don't get to a cliffs edge in software.

So there's actual developers who could tell you from the start that LLMs are useless for coding, and then there's this moron & similar people who first have to fuck up an ecosystem before believing the obvious. Thanks fuckhead for driving RAM prices through the ceiling... And for wasting energy and water.

Fractional CTO: Some small companies benefit from the senior experience of these kinds of executives but don't have the money or the need to hire one full time. A fraction of the time they are C suite for various companies.

The developers can’t debug code they didn’t write.

This is a bit of a stretch.

Personally I tried using LLMs for reading error logs and summarizing what's going on. I can say that even with somewhat complex errors, they were almost always right and very helpful. So basically the general consensus of using them as assistants within a narrow scope.

Though it should also be noted that I only did this at work. While it seems to work well, I think I'd still limit such use in personal projects, since I want to keep learning more, and private projects are generally much more enjoyable to work on.

Another interesting use case I can highlight is using a chatbot as documentation when the actual documentation is horrible. However, this only works within the same ecosystem, so for instance Copilot with MS software. Microsoft definitely trained Copilot on its own stuff and it's often considerably more helpful than the docs.

AI is really great for small apps. I've saved so many hours over weekends that would otherwise be spent coding a small thing I need a few times whereas now I can get an AI to spit it out for me.

But anything big and it's fucking stupid, it cannot track large projects at all.

Just ask the ai to make the change?

I think this kinda points to why AI is pretty decent for short videos, photos, and texts. It produces outputs that one applies meaning to, and humans are meaning making animals. A computer can't overlook or rationalize a coding error the same way.

Computers are too powerful and too cheap. Bring back COBOL, painfully expensive CPU time, and some sort of basic knowledge of what's actually going on.

Pain for everyone!

Same thing would happen if they were a non-coder project manager or designer for a team of actual human programmers.

Stuff done, shipped and working.

“But I can’t understand the code 😭”, yes. You were the project manager why should you?

It looks like a rigid design philosophy that must completely rebuild for any change. If the speed of production becomes fast enough, and the cost low enough, iterating the entire program for every change would become feasible and cost effective.

Just sell it to AI customers for AI cash.