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.
1) The size of task the AI has been given to do appears to be too big, which is why it looks like a roadmap/aspiration. You can ask it to implement a single feature or even a single part of a feature. Just keep cutting the size of the tasks until you become comfortable with it.
2) You like plans in a particular way following data structures/data etc. have you actually told the models this. It doesn't magically know. For the record the fact that the models focus on the end behaviour covered with tests is the way to to it imo. The actual implementation is less important and can be refactored as you wish fairly easily with the AI with the tests ensuring the feature still works.
I do agree though that the current SOTA models are very keen to just implement absolutely everything straight away without explaining/exploring properly. You can customise it fairly easily by using the various skills/agent/claude files to remember your preferred workflow, imo the agents adhere to theses better than they used to even just a few months ago.
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.
jpleyden98 · · focus · HN ↗
1) The size of task the AI has been given to do appears to be too big, which is why it looks like a roadmap/aspiration. You can ask it to implement a single feature or even a single part of a feature. Just keep cutting the size of the tasks until you become comfortable with it.
2) You like plans in a particular way following data structures/data etc. have you actually told the models this. It doesn't magically know. For the record the fact that the models focus on the end behaviour covered with tests is the way to to it imo. The actual implementation is less important and can be refactored as you wish fairly easily with the AI with the tests ensuring the feature still works.
I do agree though that the current SOTA models are very keen to just implement absolutely everything straight away without explaining/exploring properly. You can customise it fairly easily by using the various skills/agent/claude files to remember your preferred workflow, imo the agents adhere to theses better than they used to even just a few months ago.