The End of Tokenmaxxing

The tokenmaxxing era was brief. We now appear to be entering the era of token rationing.

Tokenmaxxing was the hottest trend in Silicon Valley earlier this year, with CEOs encouraging employees to push AI usage as far as it would go. Then the bill came due. Uber reportedly blew through its annual AI budget in a few months, some companies cut Claude licenses for parts of their org, and Meta killed its internal leaderboard.  This tension between […]

Tokenmaxxing was the hottest trend in Silicon Valley earlier this year, with CEOs encouraging employees to push AI usage as far as it would go. Then the bill came due. Uber reportedly blew through its annual AI budget in a few months, some companies cut Claude licenses for parts of their org, and Meta killed its internal leaderboard.  This tension between […]

I’ve been around long enough to remember when deploying an application meant copying a *.exe file from the developer’s machine right into production. I am not making this up. It was that simple, and that fraught with peril. Applications weren’t complex — they were often not anything more than that simple *.exe file — and the process around deployment didn’t need to be anything complex, but it probably should have been. Proper deployment of an application is something we’ve learned to do over the years. The process of properly building, testing, and deploying an application has grown more complex for two reasons. First, the process must ensure that every deployment succeeds. Deploying complex applications can be convoluted and challenging, and a strict deployment process ensures everything happens properly and runs correctly. Second, the process must thoroughly test the application to make sure that all the moving parts work together to create a properly functioning application.  Today’

"The whole conversation shifted from tokenmaxxing and 'go fast' to 'we need guardrails, how do we control this?'"

Tokenmaxxing highlights the potential disconnect between AI adoption metrics and actual productivity, raising concerns for investors and stakeholders. The post Amazon employees use internal AI tool to inflate usage scores in practice called ‘tokenmaxxing’ appeared first on Crypto Briefing.

It seems that the software developers at Facebook, who are all in on AI-powered coding, came up with a notion they called “Claudeonomics” to measure their all in-ness. This manifested itself as an internal dashboard/scoreboard of who was burning the most tokens with Claude Code. The race was on to see who could burn through the most tokens. Never mind whether this conflagration of Claude tokens was actually producing anything good. The chart merely gave boasting rights to the developer who cranked through the most processing power, declaring leaders as “Token Legend” and “Cache Wizard.” Similar things were going on at Microsoft and Salesforce.  This is just the latest chapter in an age-old battle, and it is a really bad idea. Maximum bad Managing software developers is hard enough. There are many reasons why managing developers is hard, but chief among them is that it is difficult (if not impossible) to measure the process of writing software.  And that isn’t from a lack of trying. We

There's a lot more code—but it's a lot more expensive and requires a lot more rewriting.