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IBM tripling entry-level jobs after finding the limits of AI adoption

fortune.com

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Re: IBM tripling entry-level jobs after finding the limits of AI adoption

#251

Post by smileysteve »

nunez wrote: post #223
chasd00 wrote: post #170

Earlier quoted context omitted.

I don’t know how to measure maintainability but the AI generated code I’ve seen in my projects is pretty plain vanilla standard patterns with comments. So less of a headache than a LOT of human code I’ve seen. Also, one thing the agents are good at, at least in my experience so far, is documenting existing code. This goes a long ways in maintenance, it’s not always perfect but as the saying goes documentation is like…

I find it funny that we, collectively, are now okay with comments in the code. I remember the general consensus on this _not even two years ago_ being that the code should speak for itself and that comments harm more than help. This matters less when agentic tools are doing the maintenance, I suppose, but the backslide in this practice is interesting.

In context of the thread, that's because AI fixes the key problem with comments, because it maintains them when the code is updated.

Re: IBM tripling entry-level jobs after finding the limits of AI adoption

#252

Post by lukevp »

Spooky23 wrote: post #49
notepad0x90 wrote: post #11

Earlier quoted context omitted.

Another one? What is it with IBM, they must really save lots of money in a way no one else has figured out by firing people at 50yo. This is like the 3rd or 4th one i've heard from them.

It’s not very hard. Take a guy making $200k and 30% benefit overhead and replace with two offshore people at $50k total comp.

25k TC for an engineer? From where?

Re: IBM tripling entry-level jobs after finding the limits of AI adoption

#253

Post by throwaway613746 »

bluGill wrote: post #99
throwaway613746 wrote: post #88

Earlier quoted context omitted.

> "if you're so much more productive with AI, what have you built with it" If my boss asked me a question like this my reply would be "exactly what you told me to build, check jira". If you want to know if I'm more productive - look at the metrics. Isn't that what you pay Atlassian for? Maybe you could ask their AI...

As a senior engineer sometimes the system shows I did nothing because I was helping others. sometimes I get the really hard problem -'the isn't speller teh' type bugs are more common than thread race conditions - but a lot faster to solve.

[dead]

Re: IBM tripling entry-level jobs after finding the limits of AI adoption

#254

Post by whstl »

johnnyanmac wrote: post #230
whstl wrote: post #97

Earlier quoted context omitted.

It's not luck. Customers want to save money and see projects finished. That anyone can reason with. Someone inside the company trying to climb the corporate ladder? Different story.

Okay. I'm glad you're privileged enough to where you can choose your customers. Customers that aren't abusive or otherwise out of their league thinking they know everything just because they have money. Otherwise, you never feeelanced on the cheap.

Calling me "privileged" or "lucky" feels like a cheap attack on my competence.

I am certain that I went through the same problems you did in the past, maybe I just have a different way of dealing with them, or maybe I had even worse problems than you did but I have a different frame of comparison. We never stopped to compared notes.

All I'm saying is: for me dealing with business owners, end-users, CEOs and CTOs was always way easier than dealing with proxies. That's all.

Re: IBM tripling entry-level jobs after finding the limits of AI adoption

#255

Post by fleabitdev »

nunez wrote: post #223
chasd00 wrote: post #170

Earlier quoted context omitted.

I don’t know how to measure maintainability but the AI generated code I’ve seen in my projects is pretty plain vanilla standard patterns with comments. So less of a headache than a LOT of human code I’ve seen. Also, one thing the agents are good at, at least in my experience so far, is documenting existing code. This goes a long ways in maintenance, it’s not always perfect but as the saying goes documentation is like…

I find it funny that we, collectively, are now okay with comments in the code. I remember the general consensus on this _not even two years ago_ being that the code should speak for itself and that comments harm more than help. This matters less when agentic tools are doing the maintenance, I suppose, but the backslide in this practice is interesting.

I'd describe that as a trend, rather than a consensus.

It wasn't an entirely bad idea, because comments carry a high maintenance cost. They usually need to be rewritten when nearby code is edited, and they sometimes need to be rewritten when remote code is edited - a form of coupling which can't be checked by the compiler. It's easy to squander this high cost by writing comments which are more noise than signal.

However, there's plenty of useful information which can only be communicated using prose. "Avoid unnecessary comments" is a very good suggestion, but I think a lot of people over-corrected, distorting the message into "never write comments" or "comments are a code smell".

Re: IBM tripling entry-level jobs after finding the limits of AI adoption

#257

Post by Twirrim »

Twirrim wrote: post #217
ineedasername wrote: post #209

Earlier quoted context omitted.

Same ? Not quite as good as that. But google’s Gemma 3 27B is highly similar to their last Flash model. The latest Qwen3 variants are very good, to my need at least they are the best open coders, but really— here’s the thing: There’s so many varieties, specialized to different tasks or simply different in performance. Maybe we’ll get to a one-size fits all at some point, but for now trying out a few can pay off. It a…

I get tolerable performance out of a quantized gpt-oss 20b on an old RTX3050 I have kicking around (I want to say 20-30 tokens/s, or faster when cache is effective). It's appreciably faster on the 4060. It's not quite ideal for more interactive agentic coding on the 3050, but approaching it, and fitting nicely as a "coding in the background while I fiddle on something else" territory.

Just in case anyone hasn't seen this yet:

https://github.com/ggml-org/llama.cpp/discussions/15396 a guide for running gpt-oss on llama-server, with settings for various amounts of GPU memory, from 8GB on up

Re: IBM tripling entry-level jobs after finding the limits of AI adoption

#258

Post by JumpCrisscross »

sublinear wrote: post #235
halamadrid wrote: post #150

I pay $20 for OpenAI and codex makes me incredibly productive. With very careful prompts aimed at tiny tasks, I can review, fix and get a lot of things done. I’ll happily pay up to $2k/month for it if I was left with no choice, but I don’t think it will ever get that expensive since you can run models locally and it could have the same result. That being said, my outputs are similarish in the big picture. When I get…

Bro, nobody wants to hear about the hustle anymore. We're in the second half of this decade now.

> nobody wants to hear about the hustle anymore

Plenty of people are still ambitious and being successful.

Re: IBM tripling entry-level jobs after finding the limits of AI adoption

#259

Post by giancarlostoro »

velcrovan wrote: post #160
halamadrid wrote: post #150

I pay $20 for OpenAI and codex makes me incredibly productive. With very careful prompts aimed at tiny tasks, I can review, fix and get a lot of things done. I’ll happily pay up to $2k/month for it if I was left with no choice, but I don’t think it will ever get that expensive since you can run models locally and it could have the same result. That being said, my outputs are similarish in the big picture. When I get…

I would like to know what models people are running locally that get the same results as a $20/month ChatGPT plan

Well theres an open source GPT model you can run locally. I dont think running models locally is all that cheap considering top of the line GPUs used to be $300 now you are lucky if you get the best GPU for under $2000. The better models require a lot more VRAM. Macs can run them pretty decently but now you are spending $5000 plus you could have just bought a rig with a 5090 with mediocre desktop ram because Sam Altman has ruined the RAM pricing market.

Re: IBM tripling entry-level jobs after finding the limits of AI adoption

#260

Post by everforward »

velcrovan wrote: post #160
halamadrid wrote: post #150

I pay $20 for OpenAI and codex makes me incredibly productive. With very careful prompts aimed at tiny tasks, I can review, fix and get a lot of things done. I’ll happily pay up to $2k/month for it if I was left with no choice, but I don’t think it will ever get that expensive since you can run models locally and it could have the same result. That being said, my outputs are similarish in the big picture. When I get…

I would like to know what models people are running locally that get the same results as a $20/month ChatGPT plan

I got some decent mileage out of aider and Gemma 27B. The one shot output was a little less good, but I don’t have to worry about paying per token or hitting plan limits so I felt more free to let it devise a plan, run it in a loop, etc.

Not having to worry about token limits is surprisingly cognitively freeing. I don’t have to worry about having a perfect prompt.

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