I would prefer to replace myself, yes.

I have a 37 year work history of finding ways to replace myself and folks like me. I already offer my clients free Ai consulting on the side to help them replace me. I'm already onto the "next thing" that will replace Ai in the headlines anyway.

I don't own a computer. I am not a programmer. I do everything from my iPhone.

In the past 10 years, I have spent tens of thousands of dollars on human programmers to create 3 web apps. Zero of them ever were finished. ZERO.

I used Grok AI to create 5 web apps. 3 of them were monetized almost immediately and have paying clients. All 5 have passed security checks that look for bugs or hack entry points.

One of the 3 monetized web apps took me all of 30 minutes using Grok, on an airplane, using my iPhone. I was able to download the files and upload them to a web server and the site was live. Literally 30 minutes and that website has created thousands of dollars of passive income.

I use vibe coding DAILY to make spreadsheets better for me and clients (I am not in IT). I use vibe coding DAILY to come up with cool functions for my web apps that people pay me to use.

AIUI, your costs can't (or couldn't) generally be passed on when using the small claims system. Has that changed? It's been a while since I went through the process, so it's possible that my information here is out of date.

There is obviously a personal data angle here. There might also be a defamation angle if the system works as implied by TFS, since it appears that someone's reputation has been affected because someone else lied about them and this has demonstrably caused harm? If there was more than one relevant incident then there might also be a harassment angle.

Please be careful with that advice about requesting compensation in a Letter Before Action, though. There are fairly specific rules for what you can and can't claim under our system and just going in with claiming some arbitrary figure of a few thousand pounds in "compensation" for vague damages is far from guaranteed to get the result you're hoping for. If someone were serious about challenging this kind of behaviour, they might do better to consult with a real lawyer initially to understand what they might realistically achieve and what kinds of costs and risks would be involved.

I almost wonder if that's actually a dude who was on the flight or someone taking advantage of an opportunity to get in the news.

Seems so unlikely.

I own a tiny indie studio in Chicagoland and my peers own the some of the huge studios in Chicagoland.

Cinespace is dead right now. It has ONE show active. The other studios are so dead that they're secretly hosting bar mitzvahs and pickleball tournaments for $1500 a day just to pay property taxes.

My studio is surprisingly busy but I'm cheap and cater to non-union folks with otherwise full time jobs.

To put out a hacker prize for laid off employees to target big AI companies for data center elimination.

Only somewhat correct. Unemployed because the AI companies convinced the CEOs that they can cut headcount and be fine.

And with 50% of the software engineers in 2019 now unemployed (even among senior level developers) they'll have you reviewing that code for minimum wage.

This is a good time to remind everyone that when government fucks with markets 40 years ago, they make it hell on everyone for the next 200 years.

Some are. I work more with smaller businesses than Big Tech and I don't think we've ever had more interest in our software development services.

There is a rational concern that technical people will understand the benefits and limitations of generative AI but management and executive leadership will fall for the hype because it was in the right Gartner quad or something and that will lead to restructuring and job losses. Businesses that get that wrong will probably be making a very expensive mistake and personally I'm quite looking forward to bumping our rates very significantly when they come crying to people who actually know what they're doing to clean up the mess later. It's not nice for anyone whose livelihood is being toyed with in the meantime, obviously, but I don't buy the arguments that this isn't fundamentally an economic inevitability as the comment I replied to was implying.

Historically and economically, it is far from certain that your hypothetical 20% increase in productivity would actually result in a proportionate decrease in employment. Indeed, the opposite effect is sometimes observed. Increased efficiency makes each employee more productive/valuable, which in turn makes newer and harder problems cost-effective to solve.

Personally, I question whether any AI coding experiment I have yet performed myself resulted in as much as a 20% productivity gain anyway. I have seen plenty of first-hand evidence to support the theory that seems to be shared by most of the senior+ devs I've talked with, that AI code generators are basically performing on the level of a broadly- but shallowly-experienced junior dev and not showing much qualitative improvement over time.

Whenever yet another tech CEO trots out some random stat about how AI is now writing 105% of the new code in their org, I am reminded of the observation by another former tech CEO, Bill Gates, that measuring programming progress by lines of code is like measuring aircraft building progress by weight.

I trust Weather Underground instead- it's private citizens, not government propaganda, and it's far more accurate.

Post-COVID, I don't trust governments or corporations to do science. I saw too much statistical abuse, p-hacking, politics, and outright lying about the scientific method to trust federal funding OR corporate funding of science.

Science is best done by private citizens funding their own experiments with outside jobs, not academic peer-review cancel culture bubbles.

True in general, I agree. How well any local tools pick out context to upload seems to be a big (maybe the big) factor in how good their results are with the current generation of models, and if they're relying on a RAG approach then there's definitely scope for that to work well or not.

That said, the experiment I mentioned that collapsed horribly was explicit about adding those source files as context. Unless there was then a serious bug related to uploading that context, it looks like one of the newest models available really did just get a prompt marginally more complicated than "Call this named function and print the output" completely wrong on that occasion. Given that several other experiments using the same tool and model did not seem to suffer from that kind of total collapse, and the performance of that tool and model combination was quite inconsistent overall, such a bug seems very unlikely, though of course I can't be 100% certain.

It's also plausible that the model was confused by having too much context. If it hadn't known about the rest of the codebase, including underlying SQL that it didn't need to respond to the immediate prompt, maybe it would have done better and not hallucinated a bad implementation of a function that was already there.

That's an interesting angle, IMHO, because it's the opposite take to the usual assumption that LLMs perform better when they have more relevant context. In fact, being more selective about the context provided is something I've noticed a few people advocating recently, though usually on cost/performance grounds rather than because they expected it to improve the quality of the output. This could become an interesting subject as we move to models that can accept much more context: if it turns out that having too much information can be a real problem, the general premise that soon we'll provide LLMs with entire codebases to analyse becomes doubtful, but then the question is what we do instead.