I disagree. I have a successful software product that I vibe coded using claude code starting last June. It does something novel and useful that wasn't yet offered on the App Store or any app on Android.

I am not going to say what it is because all of the AI haters will immediately flock to leave it bad reviews and overwhelm my support systems with bad faith requests (something that has already happened).

I've been writing software for 25 years, I know what I am doing. Every bug I shipped was my fault either because I didn't test well enough or I did not possess enough platform knowledge to know myself the right way to do things. "Unknown unknowns"

But I have also learned better ways to do things and fixed every bug using AI tools. I don't read the code. I may scan it to gain context and then tweak a single value myself, but beyond that I don't write or read code anymore.

Its not a magical few shot prompt then reap profits machine. I just feel like a solopreneur ditch digger who just got a lease on a new CAT excavator. I can get work done faster I can also do damage faster if I am not careful.

Beyond this concern,

haha.. I agree with the points mentioned in the article. Literally every model does this. It feels like this even with skills and other buzzword files

See also https://www.fast.ai/posts/2026-01-28-dark-flow/

I do not think "AI coding" - as distinct from the human who drives it - is gambling. More like a delayed footgun for the uneducated. I don't mean that disparagingly, but I do mean it literally.

    I’ve certainly been spending more time coding. But is it because it’s making me more efficient and smarter or is it because I’m just gambling on what I want to see? 

Is this really a difficult question to answer for oneself? If you can't tell if you're learning anything, or getting more confident describing what you want, I would suggest that you cannot be thinking that deeply about the code you're producing.

    Am I just pulling the lever until I reach jackpot?

And even then, will you know you've won?

At the very least, a gambler knows when they have hit jackpot. Here, you start off assuming you've won the jackpot every time, and maybe there'll be an unpleasant surprise down the line. Maybe that's still gambling, but it's pretty backwards.

An idea just occurred to me: why not tell AI to code in Coq? AFAIK the selling point of that language is that if it compiles, then it's guaranteed to work. It's just that it's PITA to write code in Coq, but AI won't get annoyed and quit.

I really hate when people write about the AI of the past, opus 4.6 and gpt 5.4 [not as much imo, it's really boring and uncreative] have increased in capabilities so much that it's honestly mind numbing compared to what we had LESS than a year ago.

Opus specifically from 4.1 to 4.5 was such a major leap that some take it for granted, it went from getting stuck in loops, generally getting lost constantly, needing so so much attention to keep it going to being able to get a prompt, understand it from minimal context and produce what you wanted it to do. Opus 4.6 was a slight downgrade since it has issues with respecting what the user has to say.

As always, scope the changes to no larger than you can verify. AI changes the scale, but not the strategy.

Now you have more resources to test, reduce permissions scope, to build a test bench & procedure. All of the excuses you once had for not doing the job right are now gone.

You can write 10k + lines of test code in a few minutes. What is the gamble? The old world was a bigger gamble.

So.

Is.

Life.

You've discovered probability, there was an 80% change of that. Roll a dice and do not pass go.

Again. The output from llm is a probable solution, not right, not wrong.