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.
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.
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.
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.
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.