99% of people still don’t know how to use AI Agents

This course helps you move from simply “chatting with a model” to building and operating real AI agents that can work independently — with clear goals, planning ability, tool usage, contextual memory, and automatic completion. You’ll start by mastering the agent thinking framework (goal → plan → action via tools → observation → reflection) and core building blocks: defining tools with function/JSON schema, setting up short-term and long-term memory, designing stop conditions, and standardizing output formats to prevent infinite loops. Next, the course guides you to connect agents with real-world tools—web browsing, file reading, spreadsheets, email, calendars, CRMs, and webhooks—choosing between Zapier/Make/n8n for speed or SDK/frameworks for higher flexibility. You’ll practice through four practical scenarios: • Research Agent: collect, normalize, summarize, and compare data with citations. • Content Agent: outline, draft in brand voice, fact-check, and publish across channels. • Sales Agent: enrich leads, generate personalized emails/DMs, and auto-log to CRM. • Ops Agent: create tasks, update spreadsheets, send Slack notifications, and schedule events. The final module focuses on reliability and performance—guardrails, logging/monitoring, reproducible testing, and optimization strategies for cost and latency (hierarchical context summarization, caching, batching, and model selection by task). By the end of the course, you’ll have a minimum viable agent ready to hand off to your team, along with an operational checklist and ROI criteria to safely scale your automation.