I don’t know if it even helps with productivity that much. A lot of bosses think developers’ entire job is just churning out code when it’s actually like 50% coding and 50% listening to stakeholders, planning, collaborating with designers, etc. I mean, it’s fine for a quick Python script or whatever but that might save an experienced developer 20 minutes max.

And if you “write” me an email using Chat GPT and I just read a summary, what is the fucking point? All the nuance is lost. Specialized A.I. is great! I’m all for it combing through giant astronomy data sets or protein folding and stuff like that. But I don’t know that I’ve seen generative A.I. without a specific focus increase productivity very much.

Yesterday it tried to tell me Duration.TotalYears() and Number.IsNaN() were M functions in the first few interactions. I immediately called it out and for the first time ever, it doubled-down.

I think I'm at a level where, for most cases, what I ask of LLMs for coding is too advanced, else I just do it myself. This results in a very high counts of bullshit. But even for the most basic stuff, I have to take the time to read all of it and fix or optimise mistakes.

As someone who has been a consultant/freelance dev for over 20 years now this is true. Lately I've been getting offers and contacts from places to essentially clean up the mess from LLMs/AI.

A lot of is pretty bad. It's a mess. But like I said I've been at it for awhile and I've seen this before when companies were offshoring anything and everything to India and surprise, surprise, they didn't learn anything. It's literally the exact same thing. Instead of an Indian guy that claims they know everything and will work for peanuts, it's AI pretty much stating the same shit.

I've been getting so many requests for gigs I've been hitting up random out of work devs on linkedin in my city and referring the jobs to them. I've burned through all my contacts that now I'm just reaching out to absolute strangers to get them work.

yes it's that bad (well bad for companies, it's fantastic for developers.)

EDIT: Since my comment has gained a lot of traction I've marked down peoples user names and portfolios/emails to my dev list. If something more comes up (and trust me, it will) I'll shoot you an email or msg on here. Currently I've already shoved off a bunch of stuff to others and have nothing as of now but I imagine that will change by next week so if more stuff comes up I'll shoot you an email or DM.

Retired dev here, I'm curious about the nature of "the mess". Is it buggy AI-generated code that got into production? I know an active dev who uses ChatGTP every day, says it saves him a hell of a lot of work. What he does sounds like "vibe coding". If you're using AI for grunt work and keep a human is in the workflow to verify the code, I don't see how it would differ from junior devs working under a senior. Have some companies been using poorly managed all-AI tools or what? Sorry for the long question.

I imagine you aren't talking about large companies that just let ai loose in their code base. Are these like companies that fired half their staff and realized llms couldn't make up for the difference, or small companies that tried to make new apps without a proper team and came up short?

Same thing happened during the outsourcing craze of early 2000s. Everything and I mean everything moved to India or Philippines. There's even a movie about it because it was so common. I and everyone else lost our jobs. about a year later the contracts expired and we all got jobs back and outsourcing is used in balance. Eventually ai use will be balanced I hope. It cannot replace us. Not yet anyways.

essentially, from what I've been dealing with, most if it is their offshore people using the AI to completely do the job from start to finish and no one is verifying anything. So it's not even vibe coding, it's "here's a prompt, build it, i'm pushing it to production" coding.

To be fair, 0.2 + 0.1 = 0.30000000000000004

AI as it exists today is only effective if used sparingly and cautiously by someone with domain knowledge who can identify the tasks (usually menial ones) that don't need a human touch.

AI as it exists today is only effective if used sparingly and cautiously by someone with domain knowledge who can identify the tasks (usually menial ones) that don't need a human touch.

The biggest point is that you must be an expert in the field you are using it in. I rarely get fooled by hallucinations and stupid bugs because they are glaringly obvious to me. The best use case is having the llm write code for using a library that has poor documentation, that am going to use once, and I am too lazy to learn.
These tools are scary when used by juniors, they are creating more work for everyone by using llms to code. I just imagine myself using this when I was a fresh grad, it is terrifying. It would have only been one step up from vibe coding.

This is the best description of current AI I've seen so far.

The biggest point is that you must be an expert in the field you are using it in. I rarely get fooled by hallucinations and stupid bugs because they are glaringly obvious to me. The best use case is having the llm write code for using a library that has poor documentation, that am going to use once, and I am too lazy to learn.
These tools are scary when used by juniors, they are creating more work for everyone by using llms to code. I just imagine myself using this when I was a fresh grad, it is terrifying. It would have only been one step up from vibe coding.