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Video course · 15 chapters · 133 min · certificate

AI Agents Course: Build Agentic AI Workflows in 2 Hours

A complete course on AI agents: the core agent loop, the big three platforms, self-modifying prompts, skills, video-to-action pipelines, stochastic consensus, verification loops, prompt contracts, reverse prompting, Chrome automation, MCP, context compression and cost control.

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What you'll learn

  • Explain the core agent loop
  • Compare Codex, Claude Code and Antigravity
  • Use self-modifying prompts and skills
  • Run consensus and verification loops
  • Write prompt contracts and use reverse prompting
  • Manage context, tokens and multi-agent cost

Chapters

15 chapters · 133:14
  1. 4:28 01Intro Members Introduction and a multi-agent demo Why this course, and a demo of multiple agents controlling Chrome.
  2. 8:50 02Foundations Members The core agent loop How agents work: the loop of think, act, observe.
  3. 12:25 03Platforms Members The big three platforms Codex, Claude Code and Antigravity, and how they differ in performance.
  4. 9:14 04Prompts Members Self-modifying system prompts Prompts that update their own rules so error rates fall over time.
  5. 12:23 05Skills Members Skills and multi-agent orchestration Standardizing workflows with skills and orchestrating multiple agents.
  6. 8:47 06Pipelines Members Video-to-action pipeline Turning tutorial videos into actions an agent can perform.
  7. 8:37 07Consensus Members Stochastic multi-agent consensus Asking many agents the same question and aggregating their ideas.
  8. 8:41 08Consensus Members Consensus reports, chat rooms and debate Combining agent output into reports, and agents debating in chat rooms.
  9. 7:31 09Quality Members Verification loops and mixture of experts Reviewer sub-agents with fresh context and a mixture-of-experts approach.
  10. 6:44 10Prompts Members Prompt contracts Defining explicit contracts that specify what the agent must deliver.
  11. 9:54 11Prompts Members Reverse prompting and context management Letting the agent ask you questions first, and managing context.
  12. 11:15 12Automation Members Multi-agent Chrome automation Sub-agents each monitoring their own task list while automating the browser.
  13. 10:30 13Context Members MCP tools, skills and context compression How to think about MCP tools and skills, and compressing context.
  14. 7:27 14Cost Members Optimizing token usage Reading only relevant sources and other token-saving tactics.
  15. 6:28 15Cost Members Cost-efficient multi-agent strategies Using cheaper models for sub-agents and LLM pricing principles.

Jobs this course suits

Our AI checked this course against 500 jobs; these get the most out of it. Each job links to its learning path.

Automation EngineersAI EngineersFull-Stack DevelopersCompetitive Intelligence AnalystsDevOps EngineersIT ConsultantsSystems AnalystsSystems EngineersAI ConsultantsMachine Learning EngineersIndependent ConsultantsIT Specialists