Building a browser API in one shot (nolanlawson.com)

A recent experiment successfully utilized Claude Code and a Ralph loop to build an implementation of IndexedDB with a remarkable pass rate, achieving 95% of targeted Web Platform Tests (WPTs) and 77.4% on a more rigorous set. This endeavor is particularly significant for the AI/ML community as it demonstrates the potential of large language models (LLMs) to tackle complex specifications, such as browser APIs, when provided with clear guidelines and acceptance criteria. The IndexedDB API was intentionally chosen due to the author's familiarity and its intricate features, which include transactions, various key types, and scheduling. The project involved creating a plan to implement IndexedDB in TypeScript atop SQLite and running it in Node.js, all encapsulated within a Bash loop for seamless iteration. Despite minor setbacks, such as crashes during tests, the implementation showcased a unique approach, including custom serialization logic for handling JavaScript objects in SQLite. This innovative use of LLMs not only streamlines the development process but also highlights its effectiveness in creating compliant browser functionalities, thereby pushing the boundaries of what AI can achieve in programming and contributing to the evolving landscape of web technologies.