Key Moments
What Happens When Everyone Can Build Software
Y CombinatorKey Moments
Supabase's database platform is seeing explosive growth, with 70% of new activity coming from AI agents and a surge in non-technical 'builders' creating software, indicating a future where everyone can build.
Key Insights
Supabase has grown to 13 million users and manages nearly 50 million databases, up from 3 million users and 8 million databases a year ago.
Approximately 70% of Supabase's new activity is now driven by AI agents, highlighting a significant shift in how software is being built and utilized.
The company has experienced a fourfold increase in revenue this year, with over a million databases being created weekly.
Supabase has evolved through three main phases: dashboard-centric, API-centric, and now code-centric, prioritizing patterns that agents want to build with.
The open-source nature of Supabase is considered crucial for its adoption, especially by AI agents who value the ability to inspect source code.
The trend of 'builders' (non-technical individuals) creating software is accelerating, with all metrics like activation and conversion showing significant increases.
Explosive growth fueled by AI agents and new 'builders'
Supabase, a PostgreSQL platform, has experienced remarkable growth, reaching 13 million users and managing nearly 50 million databases. This surge is significantly driven by AI agents, which now account for approximately 70% of new activity on the platform. This shift indicates a fundamental change in software creation, moving beyond traditional developers. The company's revenue has quadrupled this year, with over a million databases created weekly. This growth is attributed to two main factors: developers building with absolute freedom and the influx of new 'builders'—individuals without traditional engineering backgrounds—who can now create applications on Supabase.
Supabase's strategic evolution: from dashboard to code-centric
Supabase has strategically evolved through three distinct phases to cater to its growing user base and the changing technological landscape. Initially, it was a dashboard-centric company, followed by a transition to an API-centric model. Currently, Supabase is a code-centric company, focusing on providing the patterns and tools that AI agents and builders prefer, with a strong emphasis on command-line interfaces (CLIs). This pivot ensures that the platform is well-aligned with the needs of modern development workflows, particularly those driven by automation and AI. The company's adoption as a default choice in large language models (LLMs) has been a significant factor in this evolution and its recent success.
The critical role of open source in Supabase's success
The open-source nature of Supabase has been a cornerstone of its appeal and rapid adoption. AI agents, in particular, have a strong affinity for open-source technologies. This preference stems from the ability to inspect the source code, which provides transparency and allows for troubleshooting when issues arise. For security-conscious organizations, this open approach is vital for auditing and trust. Supabase actively supports the broader open-source ecosystem, including maintaining tools like PostgreSQL, further embedding itself within developer communities. This commitment to open source not only attracts users but also fosters a sense of community and shared development.
The rise of the 'builder' and democratized software creation
The definition of a 'builder' has expanded significantly, moving beyond traditional software engineers. This new wave of creators includes individuals with deep domain expertise who can now bring their ideas to life without needing to convince a technical co-founder. This democratization of software development is a major trend observed by Y Combinator, where the profiles of accepted startups are shifting. While engineers remain a crucial segment, the growth rate of 'builders' is immense. These individuals often have unique insights into specific industry problems and can now directly address them, leading to the creation of specialized software that might not have been prioritized by traditional development teams. The ability to build is becoming more accessible than ever.
Personal databases as the future of data ownership
A key implication of this trend is the rise of personal databases. Previously, the idea of an individual owning and managing their own database seemed impractical without significant technical skill. However, with the advent of AI and accessible platforms like Supabase, individuals can now consolidate and manage their personal data—spanning finances, health, and communications—in a single, secure location. This shift empowers users by giving them ownership and control over their data, rather than relying on third-party silos. This is particularly relevant for sensitive information where privacy and control are paramount, creating a strong value proposition for platforms that facilitate such personal data management.
Scaling for the future: from prototypes to petabytes
Supabase is actively preparing for a future where billions of users might require their own databases. The company is focused on building infrastructure capable of handling this unprecedented scale, moving from supporting millions of databases to potentially billions. Their strategy involves offering solutions that cater to both early-stage prototyping and massive enterprise-level data needs. By acquiring Turso and introducing 'Supabase Spark,' they are enabling users to scale from initial prototypes to petabytes of data seamlessly. This dual focus on scalability and developer experience ensures that Supabase can accommodate the long-term growth of its users, from individual builders to large-scale enterprises.
AI agents as primary users and the evolution of developer tools
The increasing sophistication of AI agents is reshaping the landscape of software development tools. Supabase is re-architecting its platform and tools, such as its CLI, to be 'code-first' and native to these agentic workflows. Error messages are being redesigned to be actionable for agents, providing direct guidance on how to resolve issues. The company is actively testing its platform with various AI models to understand which ones build best and how to improve the agent experience. This includes optimizing for specific use cases and ensuring agents can effectively leverage Supabase's capabilities, even creating self-improving loops for optimal performance. The goal is to make Supabase not just a tool for developers, but a fundamental part of the AI agent's development toolkit.
The future of software development: accessible, empowering, and dynamic
The conversation emphasizes a future where software development is more accessible and empowering than ever before. The rise of AI agents and user-friendly platforms like Supabase is democratizing creation, enabling individuals without traditional technical backgrounds to build sophisticated applications. This shift is not only changing how software is made but also how businesses operate, potentially leading to leaner, more profitable companies. The emphasis is on adaptability, continuous learning, and leveraging new technologies like AI to build for the next wave of innovation. Supabase's journey from a small YC startup to a global platform highlights the importance of understanding user needs, embracing open source, and staying agile in a rapidly evolving technological environment. The future appears to be one where entrepreneurial spirit, augmented by powerful AI tools, can flourish on an unprecedented scale.
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Superbase is an open-source PostgreSQL platform that has seen explosive growth, partly due to its adoption as a default database in AI tools. It empowers both traditional developers and 'builders' with less engineering background to create applications.
Topics
Mentioned in this video
Amazon's Relational Database Service. Mentioned as the standard database solution before companies like Parse and MongoDB emerged.
A software company specializing in big data analytics. Mentioned in comparison to G brain's functionality.
A YC-backed startup mentioned as an example of companies integrating continuously.
A platform developed by Google, similar to Parse, which demonstrated the potential for backend services and influenced the development of companies like Superbase.
A major database software company. Mentioned as a benchmark for traditional database companies aiming for enterprise clients.
A company acquired by Superbase, specializing in infrastructure compatible with PostgreSQL and SQLite, particularly for primary workloads.
A YC-backed startup mentioned as an example of companies integrating continuously.
Acquired Firebase, a platform that influenced the backend-as-a-service market.
An open-source retrieval system that Paul Copplestone integrated his work into. It's presented as a different way of working with AI, focusing on providing data and capabilities.
A personal finance application. Superbase's personal finance features are compared favorably to Mint.
A personal finance application. Superbase's personal finance features are compared favorably to Monarch.
A financial services company known for its payment processing software. Its business model of attracting clients early and scaling with them is presented as a highly desirable model.
A company whose labs Paul Copplestone visited, discussing error messages and developer tools.
A financial services company that announced adoption of OpenUSD, a file format.
Acquired Parse, a platform that influenced the backend-as-a-service market.
A platform for version control and collaboration. Mentioned in the context of how Paul Copplestone tries to prompt AI without explicitly directing it towards GitHub.
A company mentioned as an example of those building on Superbase's platform.
An AI model. Mentioned in the context of interacting with AI as a friend and its ability to understand and build based on user intent.
A file format format. Mentioned in the context of Paul Copplestone's domain name and its adoption by major companies like Stripe and Visa.
A project Paul Copplestone worked on, described as a smart newsroom that required building a search system for RAG, policies, and papers.
An AI coding assistant. Mentioned as a platform where AI research is happening within loops.
A programming language mentioned in the context of a fintech founder's past ability to assemble some Ruby scripts.
A tool where Superbase is used as a default database.
Structured Query Language, used for managing and querying relational databases. Mentioned in the context of handling graph databases easily.
A NoSQL database company whose rise and offering of Atlas demonstrated that viable database businesses could operate independently of major cloud providers.
A cloud platform as a service (PaaS) that pioneered the 'developer experience first' approach, though it faced challenges in scaling with applications.
A chatbot from xAI. Mentioned in comparison to Cappy's 'leaders' feature.
A tool used by Paul Copplestone that has a concept of 'leaders' similar to Grok bots, used for continuous improvement and innovation.
An open-source relational database management system that Superbase is built upon. It's highlighted as a robust and well-supported technology.
A lightweight, file-based relational database management system. Highlighted as an exceptional database, particularly for initial workloads and embedded applications.
An AI model by OpenAI, mentioned as a platform where AI research is happening within loops.
A system built by Gary, designed for RAG retrieval and graph database functionalities to structure unstructured data, acting as an intermediary for AI agents.
A platform or tool used by Superbase for evaluating different AI models and their performance with PostgreSQL.
A BaaS (Backend-as-a-Service) platform acquired by Meta, which paved the way for companies like Superbase by demonstrating the viability of standalone database businesses.
A PostgreSQL extension for vector similarity search, crucial for handling large datasets and enabling efficient retrieval.
A product from Superbase that scales to petabytes, catering to larger workloads.
A cloud computing platform. Mentioned as an example of a company that grew significantly by scaling with its early startup clients.
A tool mentioned for downloading and indexing research papers in the AI field.
A tool mentioned for finding AI research papers related to RAG and graph databases.
Refers to AI agents, which are increasingly becoming the primary users of software platforms like Superbase, driving a shift in how software is built and adopted.
Inode is a data structure used by Unix-like file systems to store information about files and directories. Mentioned in the context of error messages for agents.
Software businesses that cater to a specific industry niche. Discussed in the context of current funding challenges compared to broader AI software.
A type of database that does not use the traditional table-based relational model. MongoDB's success was instrumental in promoting NoSQL databases.
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