Has it been released to the public yet? Genuine question. Because if you didn't try it yourself, you have to rely on others' reports. And different people who tried it on different projects got different results, leading to different conclusions.
You can scaffold out a simple app pretty easily. Anything large or complex things break down. If you don’t know what you’re doing you end up leaking secrets like the dozens of examples we’ve seen so far.
On one side, it means that a certain amount of business will just use it even if you think its not safe/good enough and they will throw out people and will still succeed.
And on the other side: yes because they will also use LLM review or other tooling and will be fine whatever the 'security llm agent' tells them.
Before gen code killed the freelance business model, there were hoards of people on Upwork/Fiverr willing to fuck other freelancers over and underpay themselves to make whatever barely-working slop you wanted.
Hell, before managers got the idea of AI layoffs, they had been off-shoring to low-quality code sweatshops for years. That was supposed to kill software engineering in the States 20 years ago. And it was just as frustrating (if not moreso) to get them to actually fulfill the project requirements.
There is almost no maintenance work for bespoke apps apart from infrequent updates to keep OS and hardware compatibility as the environment slowly changes.
Keep in mind, these are not products in the endless feature treadmill promoted by scrum.
I don't particularly doubt your experience. But if you have struggled to maintain an app that is effectively complete upon inception, it means that changes in your environment are so common that it's a surprise you get anything at all done.
I'm happy to have a discussion with you if you bring any argument.
Before GPT what would have been your choise of architecture, setup, alogorithm if someone comes to you and says "write a tool/system which can generate code" "what do you mean generate code? How do i control it?" "by writing what you want in natural language" "puh 50 years of development, 100 billion, top tier team of linguists and software engineers perhaps?"
Ask StackOverflow if they think it didn't change anything for them.
Programming is the reification of decision-making processes. If you don't understand the decision-making process that you want, you get a different one, which at best approximates the one you want but couldn't articulate.
If you do this with COBOL or Python, at least you get consistent operation and errors when you're wrong. If you do this with any LLM, consistency is dropped in favor of obsequiousness.
The base problem is that people aren't equipped naturally to think about all the details of their problems.
It’s mind-boggling that anyone could deny this in mid-2026. Virtually every software engineer I know is no longer writing the majority of their code. Many are not writing any code, myself included. And I’m a staff engineer with 20 yoe, formerly at big tech, and now building a (profitable) SaaS of my own. The way I work is wildly different from a year ago.
For starters it makes you able to bypass having to go on Reddit to find incomplete trace of solution to some niche problem and acts as a sophisticated (but sometimes wrong) search engine. This already is worth every penny and improved my mental health immensely.