AI Coding Live News

Karpathy builds HackerTube in about 2 hours with Claude Code and Opus 5.5: a YouTube clone of 6,454 videos recommended on Hacker News

On Oct 31 Andrej Karpathy published HackerTube (hackertube.org) on his personal blog: a YouTube-style site that only lists the 6,454 YouTube videos recommended in Hacker News comments from 2007 to 2026, grouped into 150 topics. He says Opus 5.5 in Claude Code did the work: it downloaded every HN comment, ran Sonnet over them in a Workflow to narrow things down to about 40K comments recommending a video, wrapped the result in a YouTube UI, then deployed and hardened it on a VPS, all in about 2 hours. His only manual steps were creating a YouTube API key, booting the VPS and buying the domain. His HN submission reached the front page with about 1,005 points and 308 comments.

Key Takeaways

  • Source: Karpathy's personal blog post HackerTube (Oct 31), with the site live at hackertube.org
  • Scale: from every HN comment it narrowed things down to about 40K comments recommending a YouTube video, giving 6,454 videos across 150 topics from 2007 to 2026 (author-reported)
  • Method: Opus 5.5 ran the download and overall pipeline, used Claude Code's Workflow feature to have Sonnet filter comments and drop spam in bulk, then built a YouTube-style front end and deployed and hardened it on a VPS
  • Product details: it uses the frame at the 50% mark instead of the uploaded thumbnail, offers account-free For You picks with state kept only in the local browser, supports keyboard shortcuts, and exports the site's data so you can hand it to your own agent to build a variant
  • Workflow: Karpathy says Opus 5.5 on Medium effort is his default and he no longer reads or writes code or runs terminal commands himself; the HN post has about 1,005 points and 308 comments (public HN data as of Nov 1, 14:10 SGT)
Read full story
Linked Models & Agents:

Google previews Gemini API CLI (gemini-api), a zero-dependency Go binary that lets Claude Code, Codex, Cursor and other coding agents generate media, transcribe and run managed agents from the shell

The Google AI Studio team released an experimental preview of the Gemini API CLI (command name gemini-api). It is a stateless, zero-dependency Go binary for macOS, Linux and Windows, open source under Apache 2.0. Any coding agent with shell access and a GEMINI_API_KEY can call text reasoning, image, video, music and speech generation, file and YouTube analysis, audio and video transcription, and managed agents such as Deep Research with one command. Media is written straight to disk and only the file path goes to stdout, so base64 payloads never land in the context window. Google labels it experimental and not a supported Google product.

Google previews Gemini API CLI (gemini-api), a zero-dependency Go binary that lets Claude Code, Codex, Cursor and other coding agents generate media, transcribe and run managed agents from the shell

Key Takeaways

  • Default models (official README): gemini-3.8-flash for generate, analyze and transcribe; gemini-nano-banana-2.1 for image; gemini-omni-1.1-flash for video; lyria-3.5 for music; gemini-3.8-flash-tts for speech
  • Install with a one-line curl script on macOS/Linux, a PowerShell script on Windows, or go install; the latest GitHub release is v0.4.3 (published 2026-10-19)
  • Built for agents: --usage prints the command tree as KDL, --schema prints JSON Schema, --dry-run validates offline with credentials redacted, plus --output-format json/toon and inline --jq
  • Exit codes separate 4 cases: 0 success, 1 runtime/API failure, 2 usage or validation error, 3 auth failure; --agent-mode emits structured JSON errors
  • It also manages sandbox environments, server-side credentials, webhooks and cron triggers for managed agents; files uploaded via the Files API are kept for 48 hours
Read full story
Linked Models & Agents:
⚡ Gemini 3.8 Flash⚡ Gemini Nano Banana 2.1⚡ Gemini Omni 1.1 Flash⚡ Lyria 3.5⚡ Gemini 3.8 Flash TTS🤖 Gemini API CLI🤖 Claude Code🤖 Codex🤖 Cursor🤖 Antigravity🤖 Deep Research🌐 Google

Chubby Skills open-sources multi-platform ingest skills plus a KB MCP server

@DanKornas highlighted Chubby Skills (github.com/chubbyguan/chubbyskills, MIT, ~688★): open content-ingest and PKB skills that save Bilibili/YouTube/Douyin/Xiaohongshu/WeChat/X/podcasts as source-preserving local Markdown/JSON (subtitle-first transcription, local vault indexing) plus an MCP server so coding agents can search and manage the knowledge base.

Key Takeaways

  • Multi-platform capture into local Markdown with preserved sources (Bilibili, YouTube, Douyin, Xiaohongshu, WeChat, X, podcasts).
  • Subtitle-first video path with local transcription fallback, plus hashes and JSON records.
  • Includes a KB MCP server so Claude Code/Codex-class agents can search and manage the index.
Read full story
Linked Models & Agents:

Agent-Reach open-sources a zero-API-cost CLI for agents to read X, Reddit, YouTube, GitHub

@CamilleRoux announced Agent-Reach (github.com/Panniantong/Agent-Reach), an open-source CLI that gives AI agents read/search access to Twitter/X, Reddit, YouTube, GitHub, Bilibili, and Xiaohongshu with zero API fees and automatic backend failover when one path is blocked—handy external context for coding agents.

Key Takeaways

  • Open-source CLI covering read/search on X, Reddit, YouTube, GitHub, Bilibili, and Xiaohongshu.
  • Zero API-fee path for local/self-hosted agents that need outside context.
  • Automatic multi-backend failover when one access route is blocked.
Read full story
Linked Models & Agents:
ADSponsored

Open-source Jev Android Super: accessibility-tree phone agent, ~400ms decisions, MIT

@SomeshSampat123 released open-source Android agent jev-android-super (github.com/SomeshSampat2/jev-android-super, MIT): an accessibility service indexes tappable elements; one Jev (System One) call decides goal status and tap/type targets, then deterministic gestures run—no screenshot vision model. Demo “Open YouTube & subscribe” took ~32s / 17 steps; glowing border, notification STOP, paywall blocks, and on-device keys are called out.

Key Takeaways

  • Accessibility-tree state plus Jev decisions; no screenshot vision model.
  • Demo completed YouTube subscribe in ~32s / 17 steps; ~400ms per decision.
  • MIT open source; STOP control, paywall blocks, and on-device keys.
Read full story
Linked Models & Agents: