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News of the day
1. Amazon has shut down its internal AI leaderboard after employees exploited it by completing pointless tasks, increasing cloud costs. → Read more
2. EU institutions lack access to Anthropic's advanced cybersecurity AI, Claude Mythos, unlike the US Fed and Bank of England, raising significant concerns about a growing cyber defense gap. → Read more
3. Anthropic raises $65B at $965B valuation, fueling AI research, Claude expansion, and product scaling. New Claude Opus 4.8 model launched. → Read more
4. Anthropic's run-rate revenue hits $47 billion, a massive increase from previous months, highlighting rapid enterprise AI adoption. → Read more
Our take
Hi Dotikers!
Amazon just unplugged KiroRank, the internal leaderboard that scored developers based on how much they used AI. The reason ? Employees did exactly what you would expect : they pointed agents at pointless tasks just to climb the rankings. The behavior even has a name now, tokenmaxxing, and it drove up the cloud bill before management called time on the whole thing with a very diplomatic "please don't use AI just for the sake of using AI".
This is a textbook case of Goodhart's law : the moment a measure becomes a target, it stops being a good measure. Amazon set a goal of 80 percent of developers using AI every week, turned token consumption into a competition, and got plenty of token consumption. Not value. Meta and Microsoft lived through the same movie a few weeks earlier. When the boss of Nvidia explains that an engineer paid 500,000 dollars should be burning at least 250,000 dollars in tokens, you start to see where the confusion comes from.
The real question was never how much AI gets consumed, but what comes out of it. Amazon figured that out too, swapping raw tokens for normalized deployments, meaning code that is actually useful. An adoption KPI that ignores the output only measures one thing : our talent for looking busy in front of the manager.
Nice timing with the calendar, by the way. The day before, Anthropic was selling Opus 4.8 on its honesty, a model trained to say "I'm not sure" rather than to bluff. In the end, machines and humans alike, real productivity starts the day you stop pretending.
Alex.
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