If you sell "AI" maybe, if you sell products that happen to use LLMs to provide services previously not possible, the money still exists in my experience.

When I first heard of tokenmaxxing, I thought it had to be a joke. But no, it turned out to be a widespread phenomenon. I still cannot believe that was a thing.

What I keep saying in internal meetings is: "I am so glad these people are this bad at deploying these tools." It really leaves the door open for folks like us.

▲

skippyfish 6 hours ago | parent | next [-]

There's very little that wasn't possible before LLMs, because, well, you still had humans. There are many things that the models promise to make a lot cheaper, if you're willing to accept trade-offs, but these trade-offs can be quite severe.

Many of the most successful applications of LLMs are fields that were already terrible. For example, LLMs are a natural fit for customer support. And somehow, it's also a natural fit for software engineering, which I suppose is an indictment of our field... who cares if a model comes up with a bad architecture or a product that only kinda-works, that's how we always rolled.

	▲	consumer451 6 hours ago \| parent [-]
		> There's very little that wasn't possible before LLMs, because, well, you still had humans. Agree, but only partially. When I said "provide services previously not possible," it was just due to the fact that finding and allocating the talent to do analysis on Topic X, would have previously made many products too expensive and non-tech complex to provide. Even if you just consider LLMs + harnesses to be an improved search tool, there is a lot you can make with a better search tool.

▲

Spooky23 6 hours ago | parent | prev [-]

It’s a forcing function. If you are running a company you need to be in control. Some engineers dngaf or will sandbag everything.

We did a 90 day push and identified where we found value and where we didn’t. Our tools teams really upped their game, more than expected, and it would have been unlikely to have been funded if they tried to justify the budget as an individual initiative.

There’s a spectrum of people - some folks are building rando apps for fun with LLMs, and many don’t really know what’s possible becuase they don’t or can’t invest in the subscription to really use the tools at home.

▲

satvikpendem 6 hours ago | parent [-]

Exactly. People misunderstand the point of the tokenmaxxing time period, it was to force people to use AI so as to not have them stuck in their way, as some people are, and then to evaluate how it can help the company.

	▲	vehemenz 6 hours ago \| parent \| next [-]
		This is a good point. You need to immerse yourself in a Max plan for at least a month, ideally much longer, to understand where the benefits are. If you don't have the flexibility to regularly push your context to 1M, or do elaborate xhigh planning sessions, your opinion won't reflect reality.
	▲	consumer451 6 hours ago \| parent \| prev [-]
		OK, that is an interesting take I had not considered. Thanks to both of you.