1
Wide-reading curation
Frequent recommendations of essays, papers, books across domains. Reading list IS the content. Earned through demonstrating breadth.
Style guide · Wide-reading curation
How to write like Patrick Collison
Patrick Collison's X presence draws from extreme breadth of reading — economics, science, technology history, philosophy. The patterns reflect a polymath voice: careful claims, reading-driven curation, link amplification. Here are the 5 patterns.
Public X handle: @patrickc · Co-founder of Stripe. Public posts on technology, economics, science, and reading.
The 5 observable writing patterns
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Careful unhedged claims
Claims are precise + unhedged but verifiably correct. Not bold for boldness's sake — bold because the position is well-considered.
3
Technology-history threads
Long-form threads on the history of inventions, scientific breakthroughs, economic patterns. Historical depth applied to current questions.
4
Link-amplification with brief context
Frequent posts that are essentially "read this" with a one-line frame. The link is the content; the frame is the curation.
5
Cross-domain analogies
Connects patterns across fields (biology, economics, manufacturing, software). The analogies do real intellectual work.
Pattern shapes (NOT verbatim quotes)
These are illustrative structural templates derived from public writing patterns. Use them as scaffolds for your own specifics — the structure is universal, the words should be yours.
[Specific essay/book/paper recommendation] + [1-line context for why it matters now]
Why this works
Curation + frame. The reader gets a recommendation AND the reason to act on it.
[Cross-domain analogy]. [Implication for current question].
Why this works
Analogy-as-argument. The analogy IS the structure of the claim.
[Historical fact] [Current observation]. The pattern: [synthesized lesson].
Why this works
Historical anchor + current observation + synthesis. Three-beat structure.
[Unhedged specific claim]. [Verifiable supporting fact or source].
Why this works
Strong claim + immediate support. The support pre-empts the "source?" reply.
Do this
- +Read very widely across domains — the breadth IS the substance
- +Make claims precisely; don't hedge but be willing to revise
- +Find cross-domain analogies that do real intellectual work
- +Curate ruthlessly — only share things you've actually read
- +Add brief context to every link share
Avoid this
- -Recommending things you haven't read — readers will catch you
- -Cross-domain analogies that don't survive scrutiny
- -Long threads without payoff
- -Imitating breadth without actually having it — sounds like name-dropping
Common questions
How do I imitate wide-reading curation without being widely read?+
You can't fake it. The honest version: read deeply in your specific domain first; build curation authority there; expand from there. Patrick's breadth is decades in the making. Start narrow, get specifically known, widen later.
What's the difference between careful claims and hedged claims?+
Careful claims are specific + defensible ("This paper's central finding has been replicated in 4 independent studies"). Hedged claims are vague + non-committal ("This paper might have some interesting findings, maybe"). Both stop short of bravado, but careful claims commit; hedged claims don't.
Can I do cross-domain analogies if I'm not a polymath?+
Yes if the analogies survive scrutiny. Test: does the analogy do real intellectual work, or is it decorative? "Software development is like manufacturing" — useful if you carry through specific structural similarities. Less useful as a one-liner.
Can AutoTweet generate Collison-style content?+
Partially. The AI handles the structural patterns (analogy-as-argument, historical-anchor framings) but the wide-reading curation requires actual reading. Use the AI for structure; provide the substance (your actual recommendations + observations) via voice samples in /dashboard/settings/voice.
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