Insights
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The AI Industry is Financing Itself and Calling It Demand
A $100 billion deal disappeared overnight. The question isn’t whether it was real—it’s who’s building trillion-dollar infrastructure on deals just like it, and who ends up paying when the numbers don’t add up. Spoiler: it won’t be the companies making the deals.
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Why AI Assistance Destroys the Skills You Need to Supervise AI
Developers using AI assistants scored lower on skill assessments with zero productivity gain. They shipped code they couldn’t explain, bypassed errors where learning happens, and built dependency instead of capability. Research reveals six interaction patterns—three that preserve learning, three that destroy it. We’re training people to supervise AI while undermining the exact skills supervision requires.
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Organizations Drawing the Hardest Lines Around AI Protect the Smallest Territory
Award eligibility, exhibition space, platform curation—prestigious institutions banned AI content throughout 2025. But most creators make their living in the commercial middle: stock imagery, background music, copywriting, design templates. Bans protect the showcase while displacement happens in the warehouse. Here’s where durable protections are actually coming from—and why they look nothing like categorical prohibition.
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The Company That Ignored Genocide Is Building Your AI
Meta’s Reality Labs burned $73B. But that’s not the real cost. Internal researchers documented genocide amplification, teen mental health crises, and sex trafficking—then watched leadership ignore the warnings. The AI pivot changes the technology, not the incentives.
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Why the Companies Building AI Can’t Use It in Their Own Codebases
Meta and Google can’t effectively use standard AI coding tools in their own codebases. A recent study showed experienced developers predicted 24% gains but got 19% slower instead. The gap between AI marketing and enterprise reality reveals something important about deployment strategies.
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The Uncomfortable Truth About Where Your AI Capabilities Come From
NVIDIA charges $30,000 for a GPU that costs $6,400 to make. But the 80% margin is just the start. Their partnerships reveal something darker: when monopolistic pricing meets authoritarian regimes, the cost isn’t just economic—it’s measured in excluded nations and empowered surveillance states.
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What 100 Trillion Tokens Tell Us About What People Actually Want from AI
Open-source AI usage is 52% creative roleplay, not productivity. The industry is building for the wrong problem. Analysis of 100 trillion tokens reveals a massive gap between stated priorities and actual behavior. Here’s what users really want from AI—and what it means for your product strategy.
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Why Are Teams Using AI Tools They Fundamentally Don’t Trust?
Teams adopt AI at record rates but trust it at half that speed. Uncover the hidden “shadow work,” backlash patterns, and what separates lasting implementations from failed experiments.
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The AI Bubble is About to Burst—Here’s What Survives
Billions are at stake as AI giants race toward a cliff few acknowledge. Discover how open source, shifting infrastructure, and hard economic realities reveal what survives when the AI bubble bursts—no monopoly, just a new balance.
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Colossal Disorder Inside a Paradox of Success, Technical Debt, and Broken Trust
300,000 expected sales. 300,000 sold in 24 hours. Ten years later, experimental tech, quarterly targets, and a $10 DLC turned colossal success into paradoxical failure. How a fifteen-year partnership imploded under its own ambition.