For the people arguing that the output is the code and the faster we generate it the better..

I do wonder where all the novel products produced by 10x devs who are now 100x with LLMs, the “idea guys” who can now produce products from whole clothe without having to hire pesky engineers.. where is the one-man 10 billion dollar startups, etc? We are 3-4 years into this mania and all I see on the other end of it is the LLMs themselves.

Why hasn’t anything gotten better?

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argee 33 minutes ago | parent | next [-]

Going 100x faster is the problem. Having more people on board somewhere along the way can really help course correct, but when your first colleague arrives when you already went a million miles off course there’s a huge cost to recovery.

As they say, “slow is smooth, and smooth is fast,” when going for product market fit this is very important (and understated, in my opinion). It doesn’t help that your thread is spinning out at a hundred yards a second when what you’re doing is trying to thread the needle.

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ipaddr 4 hours ago | parent | prev | next [-]

Marketing is the moat llms haven't been able to overcome. Being able to create a Word clone is easier but the difficulty of selling it is as hard or harder than ever.

Show me an llm that can sell my product and find market fit.

In reality llms are taking away profitable tools and keeping the revenue themselves.

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steveBK123 3 hours ago | parent | next [-]

Right Very Rory Sutherland kind of thought - marketing doesn’t make sense. It is alchemy.

If I told you the drink tastes bad, is an off putting color, comes in a small bottle, and is expensive you wouldn’t believe it would work. But Red Bull made billions.

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gedy 3 hours ago | parent | prev [-]

There's definitely folks working on automatically marketing via LLMs, but I have my doubts that it wont just numb people further to marketing as we are close to saturation.

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steveBK123 3 hours ago | parent [-]

My thought/worry on a lot of the LLM agentic workflow personal assistant stuff is it is just ripe for fraud. The money is more on the adversarial side.

People think they'll just have a personal bot out there buying airline tickets, hotel rooms, jeans, new phone, etc. Meanwhile as soon as you have agents like this out in the wild, the capital will flow to bad actors creating bots to game those bots.

The world is PvP unfortunately. There is more money to be made skimming agents trying to buy stuff than there is in getting people to pay for a personal assistant agent subscription.

It's like why a lot of ad-based stuff doesn't offer a premium option for people to pay to opt out (ex Youtube). The people who can afford to pay and avoid search/social media/etc advertising are exactly the people you can make a lot of money advertising to.

	▲	nothinkjustai an hour ago \| parent \| next [-]
		Also, wtf are people doing with their lives where a significant amount of time is spent on stuff like this? It only takes a few minutes to book a flight or hotel/airbnb. Shopping for things can be fun, and if it isn’t, again, a few minutes. The amount of time that a “personal assistant” would save me is minuscule and probably actively harmful. Are people just so addicted to doomscrolling or whatever that they just can’t spend a few minutes of their day doing some type of human activity?
	▲	gedy 2 hours ago \| parent \| prev [-]
		Yes it feels a lot like the earlier internet days, when people only saw the upside/utopian view based on a high trust environment.

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maplethorpe 4 hours ago | parent | prev | next [-]

I'm waiting for Anthropic to realise they can just set a few thousand agents loose to do just that, and monopolize the entire software market overnight. I'm not sure why they haven't done this yet.

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slfnflctd 3 hours ago | parent | next [-]

You jest, but it's a good question.

When people talk about the 'plateau of ability' agents are widely expected to reach at some point, I suspect a lot of it will boil down to skyrocketing costs and plummeting accuracy past a certain point of number of agents involved. This seems to me like a much harder limit than context windows or model sizes.

Things like Gas Town are exploring this in what you might call a reckless way; I'm sure there are plenty of more careful experiments being conducted.

What I think the ultimate measure of this new tech will be is, how simple of a question can a human put to an LLM group for how complex of a result, and how much will they have to pay for it? It seems obvious to me there is a significant plateau somewhere, it's just a question of exactly where. Things will probably be in flux for a few years before we have anything close to a good answer, and it will probably vary widely between different use cases.

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steveBK123 4 hours ago | parent | prev [-]

Because a lot of valuable software is the implicit / organizational / human domain knowledge .. not the trillions of lines of code LLms all scraped and trained on.

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csomar 3 hours ago | parent [-]

There is a lot of software that is just code, though; especially at the foundational level.

	▲	steveBK123 3 hours ago \| parent [-]
		I guess the thing is - we've always had open source, frameworks, libraries, whatever for all that though, haven't we? So we can glue that together a bit faster, great. What if we also stop producing new open source, frameworks, libraries, etc. What about stories like Tailwind?

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mikeaskew4 4 hours ago | parent | prev [-]

Could be possible that the 10x devs working at 100x are just starting down the homestretch…

The 10x dev doesn’t just set out to build a hello world app, ya know.

	▲	steveBK123 3 hours ago \| parent [-]
		I think its telling that the two main places I've seen the biggest in-roads in FinTech in terms of LLMs has been: 1) Stuff that was astonishingly not automated yet. I am talking about somebody opening up excel on one screen, and a website/pdf/whatever on the other.. and type stuff in to your excel sheet. So stuff where there wasn't any code involved previously, possibly due to diminishing returns of how adhoc it was to automate, skills mismatch, organizational politics or other reasons. 2) Lot of former BigData / crypto / SaaS guys who were in product/sales roles suddenly starting AI startups to help your company AI better. The product is facilitating the doing of AI.