Best of Venture Capital — April 2026

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   Video

   Theo - t3․gg·3w

   GitHub has a fake star problem…

   A deep dive into the fake GitHub star economy, covering a peer-reviewed CMU/NC State/Socket study that identified ~6 million suspected fake stars across 18,600 repos. The investigation reveals a mature shadow market where stars sell for 3 cents to 90 cents each, with ROI of up to 117,000x when used to manufacture VC funding traction. Key findings include detection heuristics like fork-to-star and watcher-to-star ratios, analysis of specific AI and blockchain repos showing manipulation signals, how VC firms like Redpoint explicitly use star counts as sourcing benchmarks, and GitHub's reactive-only enforcement leaving the fake account infrastructure largely intact. The piece also covers legal exposure under FTC rules and SEC wire fraud precedents, and recommends alternative metrics like contributor activity and package downloads.

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   Video

   Philipp Lackner·6w

   Is the cost of AI a dead end?

   AI companies like OpenAI, Anthropic, and big tech giants are burning massive amounts of capital in a race to build ever-larger models, with no clear path to profitability. However, the cost to achieve equivalent AI performance has dropped dramatically — GPT-3.5-level performance fell from $20 to $0.07 per million tokens in just two years, a 285x reduction. The argument is that cost alone won't burst the AI bubble; instead, growth will likely slow as training costs hit a ceiling, consolidating the market to two or three dominant players. The analogy to the dot-com bubble is explored: like the internet, AI's underlying business value is real and unlikely to disappear, but the hype cycle may cool into slower, steadier growth.

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   Article

   Where's Your Ed At·6w

   Premium: AI Isn't Too Big To Fail

   Ed Zitron argues that the AI industry is not 'too big to fail,' systematically dismantling common rationalizations used to justify the AI bubble. He draws detailed parallels to the subprime mortgage crisis, showing how AI startups are subsidized by VC funding in ways that make them structurally unviable without continuous capital infusion. Key data points include: only 5GW of AI data centers actually under construction worldwide, over $600M of OpenAI shares sitting unsold on secondary markets, and the Poolside-CoreWeave deal collapsing. He argues that unlike the 2008 financial crisis — which involved trillions in securitized instruments — AI's financial footprint is comparatively small, meaning its collapse would hurt markets but would not constitute a systemic economic risk. Companies like NVIDIA, OpenAI, and Anthropic are not load-bearing to the global economy the way mortgage-backed securities were.

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