Amazon workers are gaming the AI leaderboard. HR built it.

The episode is not merely a Silicon Valley curiosity. For HR leaders who are currently designing, implementing, or being asked to justify AI adoption programs — which is to say, most of them — it is a live demonstration of a failure mode that is easy to build and hard to reverse.

What Amazon Built, and What Went Wrong

Amazon had been widely deploying MeshClaw, an in-house agentic AI product that allows employees to create software agents capable of connecting to workplace tools and completing tasks on a user’s behalf. The bot can initiate code deployments, triage emails, and interact with applications including Slack, according to the Financial Times. An internal memo described it in terms that will be familiar to anyone who has sat through an AI all-hands: it “dreams overnight to consolidate what it learned, monitors your deployments while you’re in meetings and triages your email before you wake up.”

More than three dozen Amazon engineers worked on the tool. The company positioned it as empowering “thousands of Amazonians to automate repetitive tasks each day.”

But Amazon had also introduced targets requiring more than 80 percent of its developer workforce to use AI tools each week, and had begun tracking token consumption — the units of data processed by AI models, essentially a meter of how much the tools are being run — on internal leaderboards. Team-wide statistics were initially visible to all staff before being restricted so only employees and their managers could view them.

The result was predictable to anyone who has studied organisational behaviour. “There is just so much pressure to use these tools,” one Amazon employee told the Financial Times. “Some people are just using MeshClaw to maximise their token usage.” Another said the data was being watched regardless of official policy: “Managers are looking at it. When they track usage it creates perverse incentives and some people are very competitive about it.”