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…
That article is from January. This space moves too fast. It’s not worth reading. I thought things still sucked in Jan too. But they’re impressive af now.
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.
AI code is pretty unusably bad for long term use anyway https://medium.com/@dumaysacha/i-saw-the-horror-of-ai-and-coderabbit-ai-did-too-a09622ac85de so best solution is to just to handwrite proper code as before. It’s not like we ever had much of an output problem in most coding industries, it was always a quality and bugs problem.
Can you maybe post the text.
That article is from January. This space moves too fast. It’s not worth reading. I thought things still sucked in Jan too. But they’re impressive af now.
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.
It’s impressive until it isn’t because it decided to “fix” an issue by simply ignoring an exception.