I find it strange to see people writing articles like this as if everyone has used AI for decades. I've programmed for decades. I thought I retired three years ago but got an offer I couldn't refuse. Already there were little things I'd forgotten how to use.
Over the past six months I tried using Claude, chatgpt, Grok and Gemini. At best I got reminders of how things worked. People online say they use them to write their code. The code they supplied to me has NEVER worked or was so convoluted that I threw it away and did it myself.
At most, I use these tools as search engines. Even then some references are poor.
I'm starting to think this is becoming a sad, sad world and AI is just the new TV of the programming world.
> The code they supplied to me has NEVER worked or was so convoluted that I threw it away and did it myself.
For me, it's like reading prose with "Not X, not Y, just Z": it's technically correct, but grates like fingernails on a chalkboard.
I have real trouble sometimes, reading what SOTA (Fable, etc) generate - no isolation or partitioning at all.
The worst was the planning an AI does. When I plan something, it'll be split according to data structures "An object to hold this, an intermediary for the obejct to talk to ORM, a serialiser for it that does this", etc.
The "plans" from SOTA are sometimes just hilarious. It'll go "phase one, implement these user-facing features. Phase two, implement those user-facing features", etc.
That's not a plan, it's an aspiration! A roadmap maybe. A plan, in my way of working, is a blueprint of where all the data goes, with algorithms connecting them. With AI, the data is incidental, the algorithms are incidental, only the goal (in the form of tests) remain. It'll work out some spur-of-the-moment idea around data at the time of writing.
So yeah, I do what you do and throw their stuff away. Currently having more success laying down a skeleton manually and then asking them to add a single feature at a time.
That's with SOTA models as of September-26-2026.
I think part of the problem -- answering all of why people are somehow OK with this, and even why the AI does this in the first place -- is that the majority of software developers never got to the point of understanding any of this: the lack of understanding how to carefully structure data surrounds a question they don't even know how to pose, much less answer, and so "write some tests then incrementally try to make them work without breaking any of the existing tests" is the only way they know how to develop at all. In the end, that means that, with the current state of the art (which might change, of course... potentially quickly), your strategy of treating the AI as a junior engineer who fundamentally isn't ready to do your senior-level architecture job makes a lot of sense.
assimpleaspossi · · focus · HN ↗
Over the past six months I tried using Claude, chatgpt, Grok and Gemini. At best I got reminders of how things worked. People online say they use them to write their code. The code they supplied to me has NEVER worked or was so convoluted that I threw it away and did it myself.
At most, I use these tools as search engines. Even then some references are poor.
I'm starting to think this is becoming a sad, sad world and AI is just the new TV of the programming world.
lelanthran · · focus · HN ↗
For me, it's like reading prose with "Not X, not Y, just Z": it's technically correct, but grates like fingernails on a chalkboard.
I have real trouble sometimes, reading what SOTA (Fable, etc) generate - no isolation or partitioning at all.
The worst was the planning an AI does. When I plan something, it'll be split according to data structures "An object to hold this, an intermediary for the obejct to talk to ORM, a serialiser for it that does this", etc.
The "plans" from SOTA are sometimes just hilarious. It'll go "phase one, implement these user-facing features. Phase two, implement those user-facing features", etc.
That's not a plan, it's an aspiration! A roadmap maybe. A plan, in my way of working, is a blueprint of where all the data goes, with algorithms connecting them. With AI, the data is incidental, the algorithms are incidental, only the goal (in the form of tests) remain. It'll work out some spur-of-the-moment idea around data at the time of writing.
So yeah, I do what you do and throw their stuff away. Currently having more success laying down a skeleton manually and then asking them to add a single feature at a time.
That's with SOTA models as of September-26-2026.
saurik · · focus · HN ↗