Jeff Dean's lecture breaks down the full AI engineering pipeline from building LLMs to orchestrating multi-agent systems, targeting developers who skip prompt engineering courses and need to understand how production AI actually works.

• Most developers learn AI wrong by focusing on prompt engineering instead of production systems fundamentals
• The lecture covers the complete stack: orchestration, RAG, evals, context engineering, and inference
• One person can coordinate 100 agents using proper engineering practices

Orca lets you run multiple code-generation agents (Codex, ClaudeCode, Pi, etc.) side-by-side in isolated git worktrees and compare or merge their outputs. It combines split terminals, UI scraping, remote execution, commit workflows, and real-time mobile notifications to manage and steer agents without context switching.

• Orca runs multiple AI coding agents (Codex, ClaudeCode, OpenCode, Pi, etc.) in parallel using isolated git worktrees, so you can fan out one prompt to several agents and merge the best output.
• It bundles a full dev environment—WebGL terminal, embedded VS Code with autosave, and Chromium-based UI scraping to capture HTML/CSS/screenshots directly into prompts.
• Mobile apps (iOS/Android) let you get notified when agents finish or need input, then steer them, review PRs, and comment on diffs remotely.
• It's MIT-licensed and open source, installable via Homebrew, AUR, or prebuilt binaries, with every action scriptable via CLI commands.