I’m not worried about it…
I’m not worried about it…
As to whether that will happen, I think that risk is real. Because claude code isnt made by the generalozed capabilities of the tech but by good old non-generalozable hueristics and rule based engines. I dont think that will scale to other feilds at the factor these investments assume. Its the bitter lesson again. It scales with deliberate and specific design, not data, so it wont scale
We learnt this with ibm watson. Deepblue achieved chess supremacy but the last mile wasnt data driven, it was heiristic driven, and so watson, its successor, couldnt scale/generalize.
My prediction is that this speculation on LLMs with harnesses will collapse since they wont scale. We'll have another winter where the reasearchers will be leaft alone long wnough to come up with the next breakthrough (probably game theory based data driven agency) which might then create what this hypecycle is speculating
What you've just told me is that psychologists, just like SWEs, are prone to thinking they know how business works but in fact know fuck all.
Personally I think we are at the top of the S-curve for this technology. And I suspect a lot of what we see as major recent advances are attributable to improved harnesses as much as any improvement in the abilities of the models. My guess is we will see only minor improvements going forward in the frontier models (barring a major new discovery) and major improvements in smaller models. IMO that is where the real impact will be felt day-to-day, when we can run fairly powerful LLMs in all sorts of places without having to make API calls to huge GPU clusters in the cloud.
Meaning claude code wont be able to make a "claude video editing" or "claude accounting" with the current tech. Human experts will need to encode their knowledge into it for the last mile and that wont scale the way these speculations expect
This is speculation as well. Its well founded but speculation nonetheless. Youre speculating things will stay the way they have till now.
I do see your point but what makes me consoder the other side is that ive been building an app that reaches ~10k LOC, purely with opus, no code review at all, and it hasnt hit any tech debt issues that i havent easily been able to address. Setting up good context management meant that claude could just figure things out itself.
And for reference this is an app that manages an ethernet camera, runs vehicle detection on the stream, and surfaces the detections on an ipad for operators to inspect and annotate for cellphone usage, so not trivial. Needed good architechtong and design from my end, but it was honestly scarily easy. So idk what the threshold for tech debt crash is but it wasnt there
It is cliche at this point that HN is the place you go to hear software developers reduce all of the world's problems into simple algorithmic arguments which for some reason never actually solve anything. Not shocked that we are similarly incapable of understanding that algorithmically replacing a software developer isn't easy just because we think we know what the job is.
When did that happen?
If you can fully automate software you are fully missing the point of everything you can do with that and how valuable it is
There isn't a direct correlation between AI improvement or stagnation and whether or not the amount being spent by AI labs and the associated ecosystem will result in a financial crash.
Look into the history of railroads and the internet itself to see how massive levels of investment can result in economic crashes even when the thing being invested in produces real, widespread societal value.
One could argue that one of the nightmare economic scenarios for AI is actually that it gets too good too fast and results in a wipeout of the white collar worker that we are currently nowhere near ready to deal with given how propped up our economy is on consumer spending.
The Nasdaq took 14 years to recover, 17 once you factor in inflation.
Here’s how that plays out in the economy:
- My company spent $50 on my tokens to build this internal tool
- Anthropic spent $XXX to deliver those tokens to me.
- The company I was going to buy the tool from lost $XX,XXX per year that I would have paid them.
I dunno, kind of sounds like the economy just got smaller.
I could usually accept the idea that software getting cheaper generally increases demand for software and expands the economy surrounding it, but I’m not sure if we have precedent for what happens when software becomes positively worthless.
The company could just be happy to have better margins and be happy the stock finally went up. It might literally do nothing with them or do something economically unproductive like buy back stock.
What I can tell you with certainty is that we aren’t going to hire anyone else or launch any other product as a result. Our business just isn’t at that level of growth potential.
Perhaps we can surmise that money going to shareholders can grow the economy. They’ve got more money to reinvest in other stuff.
But then again, if everyone can shart out a SaaS app with $50 in tokens, what software companies will they want to invest in?
AI gives me that feeling of “what happens to bakers and butchers when the supermarket gets invented and they decide to sell bread and meat at or below cost?”
Every company has a list of >WACC IRR projects that it can spend saved money on. If not, it’s a cash cow company that wasn’t growing in the first place and will allow shareholders to use the saved cash for other economically expanding projects.
Otherwise it would probably be the software companies that are the most focused on last-mile details (where AI in my experience has the most trouble). I expect that as consumers are faced with more and more AI slop SaaS they will be increasingly willing and able to pay for quality.
The only path that isn’t disastrous is threading the needle of “just right” productivity gains. The people in charge aren’t smart enough to give me warm fuzzy feelings on that.
Pretty soon we're going to have to reckon with the fact that AI writes better code than us.