The rise of Cursor: The $300M ARR AI tool that engineers can’t stop using | Michael Truell (co-founder and CEO)

Michael Truell is the co-founder and CEO of Anysphere, the company behind Cursor—the fastest-growing AI code editor in the world, reaching $300 million in annual recurring revenue just two years after its launch. In this conversation, Michael shares his vision for the future, lessons learned, and advice for preparing for the fast-approaching AI future.

What you’ll learn:

• Cursor's early pivot from automating CAD to automating code

• Michael’s vision for “what comes after code” and how programming will evolve

• Why Cursor built their own custom AI models despite not starting there

• Key lessons from Cursor’s rapid growth

• Why “taste” and logic design will become more valuable engineering skills than technical coding ability

• Why the market for AI coding tools is much larger than people realize—and why there will likely be one dominant winner

• Michael’s advice for engineers and product teams preparing for the AI future

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Where to find Michael Truell:

• X: https://x.com/mntruell

• LinkedIn: https://www.linkedin.com/in/michael-t-5b1bbb122/

• Website: https://mntruell.com/

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In this episode, we cover:

(00:00) Introduction to Michael Truell and Cursor

(04:20) What comes after code

(08:32) The importance of taste

(12:39) Cursor’s origin story

(18:31) Why they chose to build an IDE

(22:39) Will everyone become engineering managers?

(24:31) How they decided it was time to ship

(26:45) Reflecting on Cursor's success

(32:03) Counterintuitive lessons on building AI products

(34:02) Inside Cursor's stack

(38:42) Defensibility and market dynamics in AI

(46:13) Tips for using Cursor

(51:25) Hiring and building a strong team

(59:10) Staying focused amid rapid AI advancements

(01:02:31) Final thoughts and advice for aspiring AI innovators

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Referenced:

• Cursor: https://www.cursor.com/

• Microsoft Copilot: https://copilot.microsoft.com/

• Scaling laws for neural language models: https://openai.com/index/scaling-laws-for-neural-language-models/

• MIT: https://www.mit.edu/

• Telegram: https://telegram.org/

• Signal: https://signal.org/

• WhatsApp: https://www.whatsapp.com/

• Devin: https://devin.ai/

• Visual Studio Code: https://code.visualstudio.com/

• Chromium: https://chromium.googlesource.com/chromium/src/base/

• Exploring ChatGPT (GPT) Wrappers—What They Are and How They Work: https://learnprompting.org/blog/gpt_wrappers

• OpenAI’s CPO o