26 minutesFrom Zero to Your First AI Agent in 25 Minutes (No Coding)
Build a first n8n AI-agent workflow while recognizing where tool access, memory and guardrails belong.
Jack Roberts. A working automation builder names the three considerations that actually drive the choice — native AI agents, self-hosting, and the long-term roadmap of each tool — including notes from a conversation with Make's head of Applied AI on where Make is heading. Closely mirrors the article's "don't switch just because of shiny-object syndrome" framing.
Treat the specific product comparison as version-sensitive. n8n and Make are changing quickly; use this video for the decision criteria, then verify current pricing, hosting, AI-agent features and connector limits before choosing a stack.
Choose an automation platform based on hosting, AI-agent fit, integrations and maintenance tradeoffs instead of product hype.
Know the basic trigger/action model from Zapier, Make or n8n.
Last reviewed: May 18, 2026
Continue through the same learning path with the next curated companion videos.
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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.