We cut middle managers across the organization because AI allows us to have more direct reports per manager while still measuring and mentoring our teams effectively. – Matthew Prince, How I Choose…
I’m sorry to say this is a garbage take.
I have been told “6 months ago things sucked, but they are amazing now” for like 2 years.
When chatgpt4 came out I was told it was amazing and that 6 months old models sucked.
Nowadays I use chatgpt4 and it produces garbage and I get told “yeah but chatgpt4 is garbage”. Well, it was supposedly amazing 6 months ago and my work is still the same and the codebase is mostly the same.
This is called bullshitting. This stuff isn’t amazing now and it wasn’t amazing 6 months ago.
I realize you aren’t happy about it. But it’s true.
I was basically born behind a computer in 1978. Been a fulltime software dev since 1998.
What the latest models are doing is nothing short of incredible. And in 6 months the current models will suck compared to the latest.
Somewhere around Feb is when things really shifted for me personally. I can do all home sys and net admin tasks now by just asking a bot, running a LOCAL model. Frontier models can whip up apps in minutes.
It does require dev/architect knowledge to get quality. You have to understand the broad solution, then just get ai to do the grunt work.
I wrote all 4 of these this week, 100% ai code. I wouldn’t have had the time to write the first three, but it (opus 4.6 I think) oneshot them all in a couple mins:
Do these repos have bugs? Yep probably. But they’re working today for me solving my problems.
The same applies on large repos where I do work. When properly guided by a high skill dev/architect, the results are profound. Even non code stuff like terraform and ansible.
Given proper direction, an LLM allows you to perform at a much higher level.
Are you asking me to reject my professional daily reality?!
You can provide sources all day, but it won’t change my reality of this being the most productivity enhancing tool since MS introduced intellisense in 1996.
If I wanted to shit on AI I could absolutely provide data to make it look like it sucks and laugh at it. It can do some really stupid shit.
In the hands of an expert, this technology is a productivity multiplier. In the hands of a beginner, this technology is a security and code quality problem. If you’re having problems controlling it, look inward.
Are you asking me to reject my professional daily reality?!
Can you point me to a single field study that shows programmers become faster and not just feel faster, and that doesn’t come with some caveat like they haven’t tested AI coders vs non-AI coders, or coders without significant AI exposure before (since otherwise it won’t rule out simply becoming dependent)?
Even if you could find one, and I was unable to so far, it doesn’t change that:
you are probably faster by verbatim plagiarizing somebody’s other project at a large scale, and
by encouraging the environmental destruction brought on in particular by the training of new models.
Two caveats:
Keep in mind more lines of code is not a useful metric for faster project completion and faster maintenance task completion, especially for code bases that are already large.
I’m merely speaking about using LLM code in your project, so for example LLM auto completion or copy&pasting code from a chatbot. I’m mot talking about LLM code reviews that point out issues in natural language.
I’m sorry to say this is a garbage take. I have been told “6 months ago things sucked, but they are amazing now” for like 2 years.
When chatgpt4 came out I was told it was amazing and that 6 months old models sucked.
Nowadays I use chatgpt4 and it produces garbage and I get told “yeah but chatgpt4 is garbage”. Well, it was supposedly amazing 6 months ago and my work is still the same and the codebase is mostly the same.
This is called bullshitting. This stuff isn’t amazing now and it wasn’t amazing 6 months ago.
I realize you aren’t happy about it. But it’s true.
I was basically born behind a computer in 1978. Been a fulltime software dev since 1998.
What the latest models are doing is nothing short of incredible. And in 6 months the current models will suck compared to the latest.
Somewhere around Feb is when things really shifted for me personally. I can do all home sys and net admin tasks now by just asking a bot, running a LOCAL model. Frontier models can whip up apps in minutes.
It does require dev/architect knowledge to get quality. You have to understand the broad solution, then just get ai to do the grunt work.
I wrote all 4 of these this week, 100% ai code. I wouldn’t have had the time to write the first three, but it (opus 4.6 I think) oneshot them all in a couple mins:
Homey apps:
Other:
Do these repos have bugs? Yep probably. But they’re working today for me solving my problems.
The same applies on large repos where I do work. When properly guided by a high skill dev/architect, the results are profound. Even non code stuff like terraform and ansible.
Given proper direction, an LLM allows you to perform at a much higher level.
LLMs seem to be inherently dumb: https://machinelearning.apple.com/research/illusion-of-thinking
And from what I can find in recent studies, no, they didn’t suddenly get smart. They just plagiarize slightly better: https://www.sciencedirect.com/science/article/pii/S2949719123000213#b7
Are you asking me to reject my professional daily reality?!
You can provide sources all day, but it won’t change my reality of this being the most productivity enhancing tool since MS introduced intellisense in 1996.
If I wanted to shit on AI I could absolutely provide data to make it look like it sucks and laugh at it. It can do some really stupid shit.
In the hands of an expert, this technology is a productivity multiplier. In the hands of a beginner, this technology is a security and code quality problem. If you’re having problems controlling it, look inward.
Can you point me to a single field study that shows programmers become faster and not just feel faster, and that doesn’t come with some caveat like they haven’t tested AI coders vs non-AI coders, or coders without significant AI exposure before (since otherwise it won’t rule out simply becoming dependent)?
Even if you could find one, and I was unable to so far, it doesn’t change that:
you are probably faster by verbatim plagiarizing somebody’s other project at a large scale, and
by making yourself addicted and reliant on the AI where your own skill is eroding: https://www.404media.co/software-developers-say-ai-is-rotting-their-brains/ (if you get a paywall: https://archive.is/tHq80 ) and
by having a higher rate of bugs in your code no matter how carefully you review it https://www.coderabbit.ai/blog/state-of-ai-vs-human-code-generation-report which especially for security sensitive projects may have dire long term consequences, and
by encouraging the environmental destruction brought on in particular by the training of new models.
Two caveats:
Keep in mind more lines of code is not a useful metric for faster project completion and faster maintenance task completion, especially for code bases that are already large.
I’m merely speaking about using LLM code in your project, so for example LLM auto completion or copy&pasting code from a chatbot. I’m mot talking about LLM code reviews that point out issues in natural language.