19 minutesEvery AI Model Explained
Compare flagship, lite, mid-tier and specialized models so routing decisions are based on task fit, cost and latency instead of brand preference.
Anthropic. A two-minute Anthropic demo of Claude planning a small multi-app task — search the web, check Maps, drop a calendar invite — by driving the desktop directly. Useful contrast to the cloud-browser-only model in the Operator demo below and a good gut check on the article's point that computer-use agents work best on short, well-bounded chores rather than open-ended work.
This is a short capability demo, not a deployment recipe. Do not copy it into production without sandboxing, account isolation, logging and explicit user approval for state-changing actions.
Compare desktop computer-use behavior with browser-only agents.
Read the companion article's safety section first; the Operator demo below adds the browser-side picture.
Last reviewed: May 18, 2026
Continue through the same learning path with the next curated companion videos.
19 minutesCompare flagship, lite, mid-tier and specialized models so routing decisions are based on task fit, cost and latency instead of brand preference.
107 minutesLearn the product-builder eval loop: inspect traces, label failures, define criteria, test changes and compare against human judgment.
211 minutesUnderstand the modern LLM stack well enough to reason about tokens, training, tools and failures.
Hand-picked external courses that go deeper on this topic.
Anthropic Academy
MCP is the protocol that's quietly replacing one-off tool integrations across the AI tooling ecosystem. Learn it from the source. By the end you'll have built and deployed your own MCP server, connected an LLM client to it, and understood why this standard is the closest thing the field has to USB-C.
João Moura (Founder, CrewAI)
Doubles as our sales and customer-support vertical pick and a genuinely practical agent-building course: you build an agentic sales pipeline (lead scoring, personalized outreach) and a customer-support data-insights pipeline as two of the five hands-on projects, taught by CrewAI's own founder. Requires basic Python, so it sits with our other builder-track courses rather than the no-code picks.
Hugging Face
The clearest open-source treatment of agentic systems available. Anchored in the three frameworks engineers actually evaluate (smolagents, LlamaIndex, LangGraph) rather than one vendor's stack. Concludes with a benchmark assignment and public leaderboard — accountability your team can verify.