Get going with AI Agents. All here, readily available at w3schools.com!
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AI agents are not science fiction anymore. They’re here, and they need human partners who know how to build and guide them. If you want to work with agents, don’t start with fancy models. Start with the fundamentals. - Learn Python. Most agent frameworks are built in Python. LangChain, LangGraph and CrewAI all use it as their foundation, and even enterprise tools like Semantic Kernel support Python alongside C# and Java. Python is how you customise behaviour, manage memory and connect to data. - Learn JSON. Agents call functions and tools by outputting a JSON object with the function name and parameters. The model doesn’t run the call. Your code does. If you can’t parse and construct JSON, your agent stays mute. - Learn SQL and vector search. Agents need long‑term memory. They use SQL to retrieve structured data and vector databases to recall information in Retrieval Augmented Generation. Understanding how to query both will let you feed your agent accurate context. - Learn YAML or config scripting. Frameworks like CrewAI define agents, roles and workflows in YAML or Python files. Editing these files is how you choreograph multiple agents. - Learn APIs and schemas. Every tool the agent uses, from weather data to code execution is defined by a schema. Knowing how to design and call APIs turns a language model into an actor. These skills aren’t glamorous, but they’re the backbone of agentic AI. Get to know them and you’ll be ready for the future of work. What will you learn next?