Future Ready Leadership With Jacob Morgan

Meta Launched a New AI Model and Employees Are Being Ranked by How Much AI They Use

·40 min·4 clips

Electricians on data center projects earn a 32% premium, pulling in a quarter million dollars a year with no college debt.

The episode opens with host Jacob Morgan introducing four stories for April 9, 2026. He first discusses Lowe's $250 million commitment to train 250,000 skilled tradespeople by 2035, noting CEO Marvin Ellison's quote that 'AI can't climb a ladder.' Morgan frames this as a strategic business investment, not philanthropy, due to labor scarcity in trades needed for AI infrastructure like data centers. He cites electricians on data center projects earning a 32% premium, up to $250,000 annually. The second story covers Meta's secret internal AI leaderboard called Clodonomics, which tracked token usage among 85,000 employees. The top individual used 280 billion tokens in 30 days, potentially costing Meta $1.4 million. Morgan notes the leaderboard was named after Anthropic's Claude, suggesting marketing value for Anthropic. He critiques token consumption as a flawed productivity metric, arguing it rewards volume over quality. The third story reports OpenAI is building a restricted cybersecurity AI model, echoing Anthropic's restricted Mythos model. Morgan views this as the start of a two-tier AI economy where select companies get early access to frontier models, creating a competitive moat. He also mentions the irony of AI disclaimers urging verification despite claims of advanced capabilities. The fourth story details Meta's launch of MuseSpark, a new AI model developed after Meta spent over $14 billion to acquire talent like Alexander Wang from Scale AI. MuseSpark is multimodal and includes a 'contemplating mode' with multi-agent reasoning. Morgan notes it achieves competitive benchmarks with less compute but isn't dominant. Meta frames it around personal super intelligence rather than enterprise use. Throughout, Morgan promotes his CHRO community Future of Work Leaders and his Substack on 'human prompting.' He concludes with an Albert Einstein quote on intelligence.

As heard by us

A clear look at why AI usage volume is a shaky shortcut for judging productivity.

Meta's secret AI leaderboard gives the episode a useful spine: token consumption is starting to look like a visible stand-in for employee productivity, even though the conversation keeps pressing on whether volume says much about quality or business impact.

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Why you'd press play

Want to know whether your AI usage looks productive on a leaderboard or just costly in a way you still have to justify?

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