AI×GTMThe Leverageby Evan Armstrong

AI Native or Death. Choose.

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Why I picked this

Super useful and interesting — core AI-native thesis directly relevant to STEEPWORKS positioning. Victor flagged manually.

Key takeaways

  • AI-native companies show dramatically higher revenue per employee than traditional SaaS
  • The AI-native label requires specific product characteristics, not just AI adoption
  • Financial metrics reveal a clear performance gap between genuine AI-native ventures and AI-washed incumbents

I cover AI×GTM intelligence like this every Wednesday.

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Why Hasn’t AI Made Work Easier?

  • Large-scale study (164K workers, 180-day tracking) shows AI adoption doubled time spent on email/messaging/chat and increased business software use by 94%, but reduced focused work time by 9%
  • This represents a 'productivity paradox'—AI accelerates shallow, context-switching work while cannibalizing the deep work that drives actual value creation
  • Pattern repeats historical technology adoption cycles (email, mobile, video-conferencing) where efficiency tools paradoxically increased busyness without proportional output gains
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Cursor admits its new coding model was built on top of Moonshot AI’s Kimi

  • Cursor's new coding model is built on Chinese AI company Moonshot AI's Kimi foundation model
  • This represents a significant supply chain transparency issue in a widely-adopted developer tool
  • Geopolitical tensions around Chinese AI models create regulatory and compliance risk for enterprises using Cursor
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This analysis was produced using the STEEPWORKS system — the same agents, skills, and knowledge architecture available in the GrowthOS package.