๐บ You're either Jeremy or you're cut
AI Summary
This newsletter covers major AI industry developments including DeepSeek's V4 model launch with 1M-token context at 10% the cost of competitors, Meta cutting 8,000 jobs (10%) to fund its $72B AI buildout, and Google committing up to $40B to Anthropic. It also highlights a case study of an analyst who spent $6K/day on Claude tokens and singlehandedly replaced a 100-person team, and introduces a 'Grill Me' AI prompting skill for better code planning.
Key Facts
Author Takes
Meta layoffs and AI restructuring
The Meta cuts signal that the ZIRP-era org chart is being restructured by infrastructure build rather than the CFO, and the most at-risk workers are those whose job descriptions overlap with what AI now does autonomously.
DeepSeek V4 architectural durability
DeepSeek V4's efficiency polish might be papering over architectural rot that will not hold at the next training generation.
Specs-to-code AI workflows
Writing a spec and letting AI generate code without review is vibe-coding in disguise and produces worse code with each iteration.
AI token usage strategy
The three-part rule for surviving AI restructuring: use more tokens, generate outsized value with them, and capture that value before the org chart gets rewritten around you.
Contrarian Angle
The Jeremy Play: One AI-Fluent Analyst Replaces 100-Person Team
A SemiAnalysis energy analyst spent $6,000/day on Claude tokens for three weeks and singlehandedly rebuilt a product that an incumbent's 100-person data-services team had worked on for a decade.
Conventional thinking optimizes for cost savings on AI; this approach maximizes token spend aggressively to generate outsized value before org charts restructure around the capability.
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