# Kevin Simler’s Melting Asphalt Leads Today’s High-Conviction Resource Picks

*By Recommended Reading from Tech Founders • May 31, 2026*

Patrick O'Shaughnessy gave the strongest recommendation of the day by pointing readers to Kevin Simler's Melting Asphalt posts as an all-time favorite. Bill Gurley added two practical reads on Chinese AI commercialization, while Marc Andreessen flagged a SemiAnalysis article on AI's economic surplus with a clear caution.

## Most compelling recommendation

### Kevin Simler’s *Melting Asphalt* posts
- **Content type:** Blog posts
- **Author/creator:** Kevin Simler [^1]
- **Link/URL:**
  - [Mr. Jaynes' Wild Ride](https://meltingasphalt.com/mr-jaynes-wild-ride/) — first entry in a four-part Julian Jaynes series [^1]
  - [Social Status: Down the Rabbit Hole](https://meltingasphalt.com/social-status-down-the-rabbit-hole/) [^1]
  - [Honesty and the Human Body](https://meltingasphalt.com/honesty-and-the-human-body/) [^1]
- **Who recommended it:** Patrick O'Shaughnessy [^1]
- **Key takeaway:** O'Shaughnessy described Simler's work as an all-time favorite and named these three starting points [^1]
- **Why it matters:** This was the strongest endorsement in the set because it paired a clear personal favorite with specific places to begin [^1]

> "An all time favorite was that of @kevinsimler. Some of my favorites" [^1]

## Two Bill Gurley reads on China AI commercialization

### *Who Has the Hardest Fist in China's LLM Ring?*
- **Content type:** Article (Substack) [^2]
- **Author/creator:** not specified in the extracted note
- **Link/URL:** [https://crossingriver.substack.com/p/who-has-the-hardest-fist-in-chinas](https://crossingriver.substack.com/p/who-has-the-hardest-fist-in-chinas) [^2]
- **Who recommended it:** Bill Gurley [^2]
- **Key takeaway:** Gurley said it is a quick summary of what is happening with LLM model companies in China: there is more VC funding available for open-weights than many think, and these companies are generating real revenue [^2]
- **Why it matters:** It highlights two concrete business signals—funding and revenue generation—rather than treating the space only as a model race [^2]

### *The Commercialization Moment for...*
- **Content type:** Article [^3]
- **Author/creator:** not specified in the extracted note
- **Link/URL:** [https://crossingriver.substack.com/p/the-commercialization-moment-for](https://crossingriver.substack.com/p/the-commercialization-moment-for) [^3]
- **Who recommended it:** Bill Gurley [^3]
- **Key takeaway:** Gurley described it as an article summary about Chinese AI companies monetizing outside China with enterprises, and noted that it covers an AWS event in Shanghai [^3]
- **Why it matters:** It extends the commercialization theme from domestic funding and revenue to enterprise adoption outside China [^3]

## One theory piece Marc Andreessen thought was worth engaging with

### *AI Dark Output: The Visible Cost of*
- **Content type:** Newsletter article
- **Author/creator:** SemiAnalysis [^4]
- **Link/URL:** [https://newsletter.semianalysis.com/p/ai-dark-output-the-visible-cost-of](https://newsletter.semianalysis.com/p/ai-dark-output-the-visible-cost-of) [^4]
- **Who recommended it:** Marc Andreessen [^4]
- **Key takeaway:** Andreessen called it an interesting theory, while warning that inefficient and broken sectors of the economy may absorb any dark economic surplus, as he says happened during the computer revolution [^4]
- **Why it matters:** The recommendation is useful because it comes with the main reservation attached, giving readers both the thesis and the pressure test [^4]

> "This is an interesting theory, but one may worry that the inefficient and broken sectors of the economy will simply eat up any dark economic surplus, the same way they did during the computer revolution." [^4]

## Pattern from today

The clearest signal was Patrick O'Shaughnessy's high-conviction endorsement of Kevin Simler's writing. The rest of the day's strongest links clustered around AI economics and commercialization: Bill Gurley shared two reads on Chinese AI revenue and enterprise adoption, while Marc Andreessen highlighted a theory piece on where AI's economic gains may go [^1][^2][^3][^4]

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### Sources

[^1]: [𝕏 post by @patrick_oshag](https://x.com/patrick_oshag/status/2060779274320183340)
[^2]: [𝕏 post by @bgurley](https://x.com/bgurley/status/2060809820454719744)
[^3]: [𝕏 post by @bgurley](https://x.com/bgurley/status/2060825036886249760)
[^4]: [𝕏 post by @pmarca](https://x.com/pmarca/status/2060927737913843720)