“Create me a resume for [newjob]. Ensure that it is properly embellished so that my two years of superficial, directionless AI-driven learning seem equivalent to the multi-decade experience and domain expertise the company is actually hiring for”.
That is absolutely insane. Thing is I can honestly believe that it happens, which makes it even more insane.
Right now the AI marketing paradigm is to create rockstar superusers who can (supposedly) do the job of hundreds of individuals at the speed of light! Which bleeds into the design paradigm, which is trash. I’m bullish on AI that can be used more cooperatively and collectively by a company.
I'm slightly _more_ convinced (still not all that strongly) that the rising cost of memory and chips, data center construction that gets outpaced by computing demand, increasing energy costs, and low switching costs for customers will force the model labs to make changes that increase the barrier to entry (either via higher pricing, more restrictive rate limiting, etc.). or force their customers into longer term commitments.
We've also seen failures who were convinced "they would make it up in volume." I guess the bet is that infra will get that much more efficient, but it's not clear how much slack there is.
Hell, even Microsoft is having trouble paying Anthropic’s API rates.
There is a ceiling to how much people are willing to pay for work slop. Just look at the backlash to GitHub Copilot’s token based billing changes.
I don’t want to live in a world where the barrier to entry on entrepreneurship is how much you can pay Anthropic or OpenAI.
Sometimes using something well involves not using it at all.
This is literally the same with every single technological development.
yup, there are a lot of successful companies today not using the internet :)
$1m ARR in 30 days :)
I see the point of your argument when this is done by inexperienced developers, as they wouldn’t know what’s happening but for those who knows and guide what has to be done, I don’t see much difference. It’s about understanding the outcome, and evaluating the risk.
AI doesn’t really fix that or is really even that suited for it. In many cases it makes it worse.
That’s why you see software quality going down. Developers aren’t told to make better quality software even though AI does really make that easier. Instead they’re told to make more software faster for cheaper.
Cheap, Fast, Quality. Pick two. Business will pick cheap (short term) and fast every single time.
...and that time never comes in most cases. Because monies are earned in exchanged for that debt and, management cares about monies. They don't see that debt as important, or as debt at all.
Also even with agents, you can't just try and error your way out of some (most) of the problems I encounter without doing harm if the solution fails.
Might be different if used for infrastructure as code or ansible or some such. That I can see.
Having a chat with chatgpt may give you clues or ideas when you have gone throught your own checklist of what could have went wrong, but can go only as far.
Agent on the other side will decompile .dll to find out issues if needed to go deep enought.
Applying the actions is unsolved. Unless you YOLO the LLMs, taking stateful actions automatically requires a lot of protective infrastructure, solid testing infra etc.
It’s all just more code, but a “create me a shopping website” LLM is likely not going to be doing the infrastructure level thinking required to handle it for now.
Quite safe, and already a force multiplier - this would be a harness. Maybe have it be able to write to a shadow system with similar (ideally same) hardware to verify it's hypothesis on how the system works, etc...
A TON of companies are getting looted by the AI labs and AI users. Many will not survive. I think Meta will be one of them (a shell of their former selves by 2030). The ones who survive to thrive in the 2030s will be the ones that are relentlessly focused on their customers and products, not the process. If you don't regularly hear both "AI would be awesome for that" and "actually AI probably won't be good for that", your company won't make it. You'll either get lapped by the companies who find the strong use-cases, or you'll get looted by infinite and aimless tokenmaxing. The path through the middle is far more narrow than most companies realize, and some major, major companies are waking up to that harsh reality; for some, too late.
Therefore, sigh burn those tokens, but make sure your prompts are at least superficially defensible, in the unlikely event that you get audited. Use multiple models for the same prompt / task, for instance. It's well know that LLMs are prone hallucinations, so it's only prudent to double / triple cross-check the results with multiple models.
But definitely yeah, normally: be careful about these things. In his case when I said "admin dashboard" i moreso meant the general idea of admin oversight; he's said he's been complimented internally about how much he's using AI.
Thankfully the people responsible have already prepared a golden parachute to land safely to destroy something else.
What the actual quack, are we being really serious? What is even happening at this point and what have I even just read. This might be worse than burning money in a fire pit.
The sad part is the perverse incentives have made it so that these datacenters and gpu's and ram prices and energy costs are going up in price for this...
Why are people tokenmaxxing? Why are these companies literally burning (actually worse) of their money and their investors money? AI psychosis, what exact reason is the cause behind such things?