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A developer published HackerTube, a YouTube-style site built around videos recommended in Hacker News comments from 2007 to 2026. The creator says an AI coding assistant helped process the comments and build the site; its dataset contains 6,454 videos across 150 topics.
Developer Andrej Karpathy has published HackerTube, a YouTube-style site that collects videos recommended in Hacker News comments, offering an alternative way to browse videos without relying on YouTube’s usual recommendations. Karpathy says the project’s dataset contains 6,454 videos across 150 topics, identified from about 40,000 comments posted between 2007 and 2026.
In a post dated October 31, 2026, Karpathy said he started the project after finding YouTube’s recommendations and thumbnails a poor fit for his own viewing. He described the site as a personally useful alternative, rather than presenting it as a measured improvement for all viewers. HackerTube puts the collected videos into a familiar YouTube-style interface and includes topic browsing and custom recommendations.
Karpathy said the source material came from Hacker News comments, which were downloaded and filtered to find references recommending YouTube videos. He said an AI workflow helped remove spam and narrow the material to around 40,000 recommendation comments. The resulting collection covers videos recommended on the forum over nearly two decades; the post does not say that every video was independently checked for quality.
The creator also listed design choices including use of a 50% thumbnail rather than the uploaded thumbnail, keyboard shortcuts, and recommendations that do not require user accounts. Karpathy said the site keeps state in the browser session and makes its data exportable, so users can provide it to an AI agent to create their own version. Those are descriptions in the launch post; no independent review or audience data was provided in the supplied material.
A Forum-Based Alternative to Feeds
HackerTube’s premise is to replace one recommendation source with another: rather than ranking videos from a viewer’s YouTube activity, it draws on links that people chose to share in Hacker News discussions. That makes the site a small experiment in community-curated discovery, with a collection shaped by the interests and habits of a particular online forum.
The project also illustrates how an individual can use an AI coding assistant to assemble a working web product from existing public material. Karpathy said the process involved having the assistant process comments and build the application, while he handled a Google Cloud API key, rented server, and domain. His account is a description of this project, not evidence that the same timeline or workflow applies to other products.
For viewers, the immediate question is whether the archive’s selection and browsing tools are useful. The collection may surface older or less familiar videos, but its source also means it reflects what Hacker News users recommended, not a representative sample of YouTube or viewers’ preferences generally.
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How HackerTube Was Assembled
Karpathy’s post traces the project to a late-night decision to make a video site based on Hacker News recommendations. He said he used Claude Code, with the Opus 5.5 model at medium effort as his default, and assigned it the task of building the site. According to his account, the assistant downloaded comments, filtered them, ran another model in a workflow to remove spam, and extracted video recommendations.
He described the result as a site built in about two hours. The remaining manual steps he identified were creating a Google Cloud key to request YouTube metadata, starting a virtual private server, and purchasing the domain. He said he then gave the assistant the server’s IP address and asked it to update, deploy, secure, harden, and optimize the code. These details come from the creator’s own account, and the post does not provide a separate technical audit or a breakdown of how much work each step required.
What the Launch Post Does Not Establish
The supplied report does not include independent testing of the site, its recommendation system, or its security. It also gives no figures for visitors, usage, or uptime, and does not explain how the 150 topic categories were selected or how recommendation comments were judged beyond filtering and spam removal.
It is also unclear how often the archive will be updated, whether videos that are removed or made private will be tracked, and how the site handles changes to YouTube metadata. Karpathy’s description of the videos as quality content is a stated view, not a finding supported by published evaluation data. The project’s dataset reflects Hacker News recommendations and should not be read as a broad measure of video quality or popularity.
The Site’s Next Test Is Use
The immediate next step is for people to try HackerTube and see whether its forum-derived catalog offers a useful way to find videos. The launch post does not announce a release schedule, roadmap, or plans to expand the dataset, so it is not clear whether Karpathy intends to maintain the service or treat it as a completed experiment.
Future details that would help users assess the project include how the collection is updated, what safeguards apply to the site and its data, and whether the creator will publish usage or quality information. For now, the confirmed development is the publication of the site and Karpathy’s account of how he built it; broader claims about its usefulness remain untested.
Key Questions
What is HackerTube?
HackerTube is a YouTube-style video browsing site built from videos recommended in Hacker News comments, according to its creator, Andrej Karpathy.
How many videos are in its collection?
Karpathy says the site includes 6,454 YouTube videos across 150 topics, identified from roughly 40,000 Hacker News comments dating from 2007 to 2026.
Does HackerTube require an account?
Karpathy says its custom recommendations work without user accounts and that session state is kept in the local browser. The launch post does not provide an independent technical review of those features.
How was the site built?
Karpathy says he used Claude Code and AI models to process comments and build and deploy the site. He identified obtaining a Google Cloud key, setting up a server, and buying the domain as his manual tasks.
Is the video collection independently rated for quality?
The supplied launch report does not describe an independent quality evaluation. The claim that the collection contains quality content is Karpathy’s characterization.
Source: karpathy.bearblog.dev
