Patrick Collison on Stripe’s Early Choices, Smalltalk, and What Comes After Coding
Episode
52 min
Read time
2 min
Topics
Relationships, Startups, Fundraising & VC
AI-Generated Summary
Key Takeaways
- ✓API Design as Business Strategy: Stripe's original v1 API endpoints, prefixed with "/v1" since 2010, have endured 15 years — but with accumulated flaws. Collison argues that API and data model decisions shape organizational structure and competitive outcomes, citing iOS's superior developer ecosystem over Android as a direct result of better initial abstraction design.
- ✓Instruction-Set Migration Model for API Upgrades: Stripe's v2 API rollout, begun in 2022 and shipping now, treats backward compatibility like a chip architecture instruction-set migration. Defining new APIs is straightforward; building translation layers and customer upgrade paths alongside existing integrations is the hard part. Collison recommends designing all relationships as N-to-M from the start.
- ✓Development Environments vs. Text Editors: Collison argues the industry conflates code editors with development environments. Lisp machines, Smalltalk, and Mathematica unified runtime, debugging, and editing into one surface. He advocates overlaying live production profiling data, error logs, and common variable values directly onto code lines — capabilities modern IDEs still largely omit.
- ✓Stripe's Reliability Benchmark: Stripe achieved 99.99986% API availability in its most recent reported year — equivalent to 44 seconds of total downtime annually — using Ruby and MongoDB, technologies chosen on a couch by two founders. Collison attributes this to years of custom infrastructure built around MongoDB to meet fault-tolerance and durability requirements.
- ✓Biology's New Read-Think-Write Loop: Arc Institute is training foundation models on DNA and single-cell RNA sequencing data to build a virtual cell. Collison frames three converging technologies — improved sequencing (read), transformers (think), and CRISPR/base editing (write) — as forming a complete biological Turing loop capable of systematically attacking complex diseases like cancer and neurodegeneration for the first time.
What It Covers
Patrick Collison, CEO of Stripe, speaks with Cursor CEO Michael Truell about Stripe's foundational technical decisions — Ruby, MongoDB, and API design — their lasting consequences 15 years later, the ongoing v2 API migration, what modern development environments still lack, and Collison's biomedical work at Arc Institute.
Key Questions Answered
- •API Design as Business Strategy: Stripe's original v1 API endpoints, prefixed with "/v1" since 2010, have endured 15 years — but with accumulated flaws. Collison argues that API and data model decisions shape organizational structure and competitive outcomes, citing iOS's superior developer ecosystem over Android as a direct result of better initial abstraction design.
- •Instruction-Set Migration Model for API Upgrades: Stripe's v2 API rollout, begun in 2022 and shipping now, treats backward compatibility like a chip architecture instruction-set migration. Defining new APIs is straightforward; building translation layers and customer upgrade paths alongside existing integrations is the hard part. Collison recommends designing all relationships as N-to-M from the start.
- •Development Environments vs. Text Editors: Collison argues the industry conflates code editors with development environments. Lisp machines, Smalltalk, and Mathematica unified runtime, debugging, and editing into one surface. He advocates overlaying live production profiling data, error logs, and common variable values directly onto code lines — capabilities modern IDEs still largely omit.
- •Stripe's Reliability Benchmark: Stripe achieved 99.99986% API availability in its most recent reported year — equivalent to 44 seconds of total downtime annually — using Ruby and MongoDB, technologies chosen on a couch by two founders. Collison attributes this to years of custom infrastructure built around MongoDB to meet fault-tolerance and durability requirements.
- •Biology's New Read-Think-Write Loop: Arc Institute is training foundation models on DNA and single-cell RNA sequencing data to build a virtual cell. Collison frames three converging technologies — improved sequencing (read), transformers (think), and CRISPR/base editing (write) — as forming a complete biological Turing loop capable of systematically attacking complex diseases like cancer and neurodegeneration for the first time.
Notable Moment
Collison reveals that Stripe employees still cannot use each other's computers because both he and his brother John independently optimized their keyboard layouts using genetic algorithms — and both arrived at Dvorak, which they now use exclusively, locking out anyone else who sits down.
Episode Transcript
It's interesting to me that we haven't experimented in some sense that much with the paradigm of programming over the past twenty years. Yes. You put those together, you now have the ability to, again, at the kind of level of the individual cell, to read, think, and to write. And this starts to really feel like a new kind of Turing loop and to have its own sort of completeness. I think that's a case where the right API design, the right abstraction design, ended up having just quite significant business ramifications. I think the basic idea of as development environment and not just text editor is really the right idea, and that's something I want to see a return to. Patrick Collison wrote his first startup in small talk. Its development environment let him fix errors mid request, inspect stack frames, and resume execution. And he wanted that more than he wanted a mainstream language. He and his brother chose Ruby and MongoDB for Stripe instead. Those decisions still define the company fifteen years and forty four seconds of annual downtime later. Now Stripe is shipping v two APIs, rewriting core abstractions first designed in 2010. It's taken years. Defining the new APIs is the easy part. Making them work alongside everything already built on the old ones is, as Coulson put it, more like an instruction set migration than a product launch. This conversation previously aired on Cursors podcast also gets into why AI hasn't moved product to v numbers, what today's dev environment could steal from Lisp machines, and Collison's work at Arc on foundational models for biology. Michael Truel, CEO of Cursor, sits down with Patrick Collison, CEO of Stripe. Well, it's great to have you. Thanks for Thank you for being here. Thanks for having me. Good to be here. I've heard that your first startup was written in small talk. Please explain. I don't know what there is to explain. It's the best programming language. Well, I had I'd worked on Lisp and Lisp dialects, before that. And, actually I'd I'd worked on Lisp web frameworks. And, when we went to build our first startup, we we first wrote it in we we first implemented it in Rails. And then I found compared to Lisp that development process kind of frustrating. And, I mean, we don't need to get into full details, but I thought that continuation based web frameworks were really the right way to implement web applications. There were no continuations, in there there's no continuation based framework in in Ruby. And, I was kind of searching around. I found that there was, a good one that had just been written in Smalltalk. And so I decided to play with it a little bit. And then I found that Smalltalk is actually this extremely interesting development environment, that had a lot a lot of the aspects of Lisp that I'd really appreciated there, like, you know, and a fully interactive environment …
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Tools
“Lisp machines, Smalltalk, and Mathematica unified runtime, debugging, and editing into one surface. He advocates overlaying live production profiling data, error logs, and common variable values directly onto code lines.”
“Stripe's foundational technical decisions — Ruby, MongoDB, and API design — their lasting consequences 15 years later. Stripe achieved 99.99986% API availability in its most recent reported year using Ruby and MongoDB, technologies chosen on a couch by two founders.”
“Collison reveals that Stripe employees still cannot use each other's computers because both he and his brother John independently optimized their keyboard layouts using genetic algorithms — and both arrived at Dvorak, which they now use exclusively.”
“Lisp machines, Smalltalk, and Mathematica unified runtime, debugging, and editing into one surface.”
“Collison frames three converging technologies — improved sequencing (read), transformers (think), and CRISPR/base editing (write) — as forming a complete biological Turing loop.”
“Stripe's foundational technical decisions — Ruby, MongoDB, and API design. Stripe achieved 99.99986% API availability using Ruby and MongoDB, technologies chosen on a couch by two founders.”
“Lisp machines, Smalltalk, and Mathematica unified runtime, debugging, and editing into one surface.”
Products
company
“Arc Institute is training foundation models on DNA and single-cell RNA sequencing data to build a virtual cell.”
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