Y Combinator’s CEO says he ships 37,000 lines of AI code per day. A developer looked under the hood
We love a good ol’ social media roast, and Y Combinator CEO Garry Tan found himself on the business end of a doozie Wednesday. Tan, who in a past life worked as an engineering manager at Palantir and has more recently been a vocal proponent for AI acceleration, bragged that he and his AI coding agents have been deploying 37,000 lines of code per day across five separate projects. “Absolutely insane week for agentic engineering,” Tan wrote in an X post on Monday, adding in a follow-up post that he was on a 72-day shipping streak. Absolutely insane week for agentic engineering 37K LOC per day across 5 projects Still speeding up pic.twitter.com/VR3utsduYx — Garry Tan (@garrytan) March 30, 2026 Two days later, a Polish game developer and senior software engineer who goes by the username Gregorein decided to have a closer look at the actual results of all that shipping and took a peek at Tan’s AI-focused blog . “Here’s what 78,400 lines of AI slop code actually looks like in production,” he wrote on X . Gregorein—who has an MSc in Computer Science, a Polish engineering title, and 13 years in the industry—found numerous examples of bloat and inefficiencies in Tan’s site code, and used a single (Anthropic) Claude session to review the files he downloaded from the website to confirm his observations, which are these: Tan/AI built the website so that when a user visits, their browser makes 169 server requests for various assets totaling 6.42 megabytes
Y Combinator’s CEO, Garry Tan, recently found himself in the center of a social media roast after claiming that he and his AI coding agents have been deploying an impressive 37,000 lines of code per day across five separate projects. In a series of tweets, Tan described the week as “absolutely insane” for agentic engineering and mentioned that he was on a 72-day shipping streak. However, his assertion sparked curiosity among developers, leading one to take a closer look at the actual results of this AI-driven development.
A Polish game developer and senior software engineer, known online as Gregorein, decided to investigate the claims made by Tan. Gregorein, who holds an MSc in Computer Science, a Polish engineering title, and has over 13 years of experience in the industry, examined Tan’s AI-focused blog. In a tweet, he shared his findings, stating, “Here’s what 78,400 lines of AI slop code actually looks like in production.”
To verify his observations, Gregorein used a single session with Anthropic Claude, an AI assistant, to review the files downloaded from Tan’s website. His analysis revealed several instances of bloat and inefficiencies in the site’s code. One of the most striking examples was the number of server requests made by the website. When a user visits Tan’s site, their browser makes 169 server requests for various assets, totaling 6.42 megabytes in size. For comparison, the minimalist Hacker News homepage, also run by Y Combinator, makes just seven requests for data totaling only 12 kilobytes.
Another notable issue was the inclusion of 28 actual test files, which are typically used by developers for testing and debugging, directly shipped to every visitor’s browser. This results in an additional 300 kilobytes of developer scaffolding that users never requested. Furthermore, the website loads 78 different JavaScript controllers for features such as AI image generation, voice extraction, and video tools, none of which are visible on the homepage.
These findings highlight a potential disconnect between the impressive scale of code deployment claimed by Tan and the actual performance and efficiency of the resulting website. While Tan’s efforts to accelerate AI development through automated coding are commendable, the results of this approach need to be carefully evaluated to ensure that the benefits outweigh the drawbacks.
The incident serves as a reminder that even with the help of AI, developers must still prioritize efficiency and user experience. The case of Tan’s website demonstrates that the rush to deploy large amounts of code quickly can sometimes lead to bloated and inefficient solutions that negatively impact user performance. As AI continues to play a more significant role in software development, it is crucial to strike a balance between speed and quality to ensure that the end products meet both functional and performance standards.
In the meantime, the social media roast of Tan has underscored the importance of transparency and accountability in the tech industry. When high-profile figures make bold claims about their technological achievements, the broader community is often eager to scrutinize these assertions. Such scrutiny can lead to valuable insights and help drive improvements in the field.
As the debate continues around the potential of AI in software development, Tan’s situation offers a cautionary tale. While AI-driven coding has the potential to revolutionize the industry, it is essential to ensure that the tools and processes used are optimized for both efficiency and effectiveness. Only then can the full benefits of AI acceleration be realized without compromising on the quality and performance of the software produced.
