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Meta drops AI usage from engineer performance reviews after "tokenmaxxing" backfires

Meta removed AI-tool usage from engineer performance reviews after 'tokenmaxxing' inflated metrics, with internal AI costs heading toward billions in 2026.

Executives Maher Saba and Santosh Janardhan said in an internal memo, seen by The Information, that AI dashboards and token counters will no longer factor into performance reviews; quality, speed, and complexity of work will count instead. The change follows 'tokenmaxxing,' where employees burned AI tokens in bulk to rank on internal leaderboards. Internal AI use is projected to cost billions in 2026, prompting Meta to introduce budgets and a central dashboard starting in 2027. Separately, Meta is testing its AI agent tool Hatch for autonomous computer tasks, though some employees resist linking it to personal accounts over privacy concerns.

The Decoder · 7d agoAI industry

[AINews] Andrew Ng gets into AI Engineering

Andrew Ng relaunches DeepLearning.AI around AI Engineering, defining four core skills from an analysis of 10,000+ job postings and expert interviews.

Andrew Ng, cofounder of Google Brain and Coursera, relaunched DeepLearning.AI with a focus on AI Engineering, basing the curriculum direction on an analysis of over 10,000 job postings plus interviews and surveys. He identifies four key skills: building and deploying AI applications, software engineering fundamentals, effective use of coding agents, and shaping the build with product sense. The Latent Space AI News issue also recaps agent ecosystem developments, including NVIDIA's 'Skill Lift' evaluation proposal showing skill scan scores correlate only weakly (Spearman rho = 0.14) with judged quality, and Konwinski's open-source persistent-agent 'microharness' Headlong, which achieved an unattended self-debugging repair in 48 minutes.

Latent Space · 21d agoAI industry1