Michael Truell: Building Cursor at 23, Taking on GitHub Copilot,...
Y Combinator Startup PodcastFull Title
Michael Truell: Building Cursor at 23, Taking on GitHub Copilot, and Advice to Engineering Students
Summary
The episode details Michael Truell's journey building Cursor, an AI-powered code editor, from early AI interests and failed projects to its current success in transforming software development.
It highlights the strategic pivot to focus on AI in coding, even against giants like GitHub Copilot, and the subsequent rapid growth driven by product improvement and word-of-mouth.
Key Points
- Truell's entrepreneurial journey began in middle school, inspired by Y Combinator essays, and his early programming experience involved building a viral mobile app and exploring AI through projects like a robotic dog, which taught him fundamental programming and AI concepts.
- The founding of Cursor was fueled by the belief that AI would fundamentally change coding, aiming to build the best AI coding experience rather than just incrementally improving existing tools, despite the competitive landscape dominated by GitHub Copilot.
- Initial projects after graduating MIT, including a co-pilot for mechanical engineers and an end-to-end encrypted messaging system, failed to gain traction, leading to a pivot towards Cursor's core focus on AI-assisted coding.
- The development of Cursor involved building its own editor from scratch, a challenging endeavor that was later refactored to be based on VS Code to focus on AI features and faster iteration.
- Early growth was driven by word-of-mouth and consistent public engagement with AI research by the founding team, with a significant acceleration in adoption seen in 2024 as the product matured.
- The company prioritized product improvement, making AI features like prediction, code suggestion, and AI-driven actions more accurate and faster, which directly correlated with user growth.
- Truell advises aspiring entrepreneurs to focus on what they are genuinely interested in and to work with people they respect and enjoy collaborating with, emphasizing the importance of deep engagement over simply checking boxes.
Conclusion
Focusing on genuine interest and working with respected collaborators is crucial for entrepreneurial success.
Continuous product improvement, especially in rapidly evolving fields like AI, directly drives user growth and adoption.
Foundational programming and computer science skills remain valuable, even as AI transforms the landscape of software development.
Discussion Topics
- How do you balance pursuing groundbreaking AI capabilities with the practical realities of user adoption and existing technology limitations?
- What core skills for software engineers will remain essential in an era of increasingly capable AI coding assistants?
- How can founders navigate early-stage product development and pivot effectively when initial ideas don't gain traction?
Key Terms
- Objective-C
- A general-purpose, object-oriented programming language that is a common language for macOS and iOS development.
- Xcode
- An integrated development environment (IDE) for macOS, iOS, iPadOS, tvOS, and watchOS.
- AI
- Artificial Intelligence, the simulation of human intelligence processes by computer systems.
- Reinforcement Learning (RL)
- A type of machine learning where an agent learns to make a sequence of decisions by trying to maximize a reward it receives for its actions.
- Neural Network
- A computing system inspired by the structure and function of the human brain.
- Torch
- An open-source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing.
- TensorFlow
- An open-source software library for data processing and large-scale numerical computation, often used for machine learning and artificial intelligence.
- Microcontrollers
- Small computers built into a single integrated circuit that contain a processor, memory, and input/output peripherals.
- VS Code
- Visual Studio Code, a free source-code editor made by Microsoft which runs on the desktop and is available for Windows, macOS and Linux.
- Codex
- A descendant of GPT-3 focused on code generation and understanding, used to power GitHub Copilot.
- GitHub Copilot
- An AI pair programmer that suggests code and entire functions in real-time, right inside the editor.
- AGI
- Artificial General Intelligence, a hypothetical type of AI that possesses the ability to understand or learn any intellectual task that a human being can.
- YC
- Y Combinator, an American seed accelerator that has been described as one of the most powerful startup accelerators in the world.
- CVE
- Common Vulnerabilities and Exposures, a list of standardized names for publicly known information security vulnerabilities.
- Flynn T5
- A fine-tuned version of the T5 language model, known for its strong performance on various NLP tasks.
Timeline
Truell recounts his origin story as a founder, starting with his early interest in programming and entrepreneurship in middle school.
Truell describes his first encounter with programming and the creation of a viral mobile app with his brother.
Truell details his early AI exploration, including a project to build a robotic dog that could be taught without programming, leading him into learning about genetic algorithms and reinforcement learning.
Truell explains the experience of implementing a neural network from scratch for a robotics project due to limited hardware resources.
Truell discusses the genesis of Cursor, beginning with his co-founders' shared interest in AI and their decision to start their own company.
Truell talks about the initial hackathon that explored AI's impact on knowledge work, leading to an initial focus on mechanical engineering.
Truell elaborates on the challenges faced during the mechanical engineering AI project, including data scraping and infrastructure development.
Truell mentions a concurrent project on an end-to-end encrypted messaging system.
Truell describes the lack of user traction for these initial projects and the moment of realization that they needed to pivot.
Truell explains the team's initial hesitation to enter the AI coding space due to competition and their eventual pivot to focus on AI-driven coding.
Truell discusses the conviction and excitement for the vision of transforming coding with AI, leading to the decision to focus on Cursor.
Truell details the rapid development and launch of Cursor's first version, including building a custom editor.
Truell shares lessons learned from the initial version of Cursor, particularly regarding the form factor of AI features and the realization that a fully functional editor would take longer than anticipated.
Truell explains the strategic decision to base Cursor on VS Code to concentrate on AI capabilities.
Truell discusses the initial inspiration from Codex and the team's approach to model development and funding.
Truell reflects on the challenges and debates within the team during 2023 about whether to continue pursuing Cursor.
Truell describes the process of identifying the need to build their own models for improving AI capabilities.
Truell highlights the rapid growth of Cursor in 2024, driven by a 10% week-over-week compounding effect.
Truell explains that product improvements, such as making AI predictions faster and more ambitious, directly led to user growth.
Truell notes the dramatic shift in Y Combinator batches, with Cursor adoption increasing from single digits in 2023 to 80% in 2024.
Truell discusses the role of social media and early community engagement in Cursor's initial adoption.
Truell describes how one co-founder built a following by consistently posting about AI research, which helped gain early visibility.
Truell explains that Cursor's growth in 2023 was primarily driven by word-of-mouth due to a strong focus on product development.
Truell mentions that the company remained small in 2023, with the core team of four handling much of the development.
Truell discusses the market's perception of AI work in 2022 and the differing views on pursuing AGI versus practical AI applications.
Truell expresses a long-term view on AI as a transformative technology and the industry-wide effort required to realize its full potential.
Truell believes that in the near term, AI will act as a "colleague" or advanced compiler for professional engineers, requiring human oversight.
Truell advises that programming and computer science fundamentals remain valuable skills, emphasizing continuous learning.
Truell offers advice to aspiring entrepreneurs, encouraging them to pursue their interests with passionate collaborators.
Episode Details
- Podcast
- Y Combinator Startup Podcast
- Episode
- Michael Truell: Building Cursor at 23, Taking on GitHub Copilot, and Advice to Engineering Students
- Official Link
- https://www.ycombinator.com/
- Published
- September 3, 2025