Rebuild YouTube with AI, taught by a former YouTube engineer, kicks off on Saturday, September 26. Enrollment closes in 24 hours.
What you will learn
Scope a realistic MVP. Decide which YouTube features to build and break the work into manageable tasks.
Work with agents. Plan changes, review generated code, and recover from bad diffs or sessions that go off track.
Build across the stack. Turn mockups into React pages and build a backend with Postgres, authentication, and video uploads.
Add semantic search and related videos. Use multimodal embeddings and understand how this approach differs from production recommendation systems.
Test and deploy your app. Check features with Playwright, deploy to Vercel, and track watch time in an admin dashboard.
This course is part of ByteByteGo Live, giving you 12 full months of access to all current and upcoming courses.
More live courses we offer:
AI Evals in Practice for Engineers and PMs: Six weeks with Manjeet Singh, Senior Director at Salesforce.
AI Cost Optimization: Four weeks with Jeremy Hintz, Engineering Lead at Meta.
AI Engineering Fundamentals: Four weeks with Ali Aminian (Google, bestselling author).
Build with Claude Code: Two day intensive with John Kim, Senior Staff Engineer at Meta.
Build Production Grade AI Systems: Six weeks with Tanya Roosta, Director at AMD, with a PhD from UC Berkeley.
Trust optimized AI Development: Two day intensive with Kent Beck, creator of TDD.
Scoping the MVP is the actual hard part of rebuilding something like YouTube, the coding is almost secondary. Video systems force you to make encoding, storage, and recommendation tradeoffs on day one that most CRUD apps let you defer for months. Curious whether they treat the transcoding pipeline as a black box or make students actually reason about it, since that's usually where the realistic complexity lives.