Building AI Agent Loops: Foundational Workflows and Tool Integration

AI agents are transforming how we interact with technology by executing complex multi-step tasks autonomously. To build these systems, you must understand how to orchestrate the core agent loop that processes user input, calls external tools, and maintains state. In this text-based course, you will learn the foundational mechanics of agentic workflows. You will transition from basic concepts to practical implementation, discovering how to manage conversation history, execute sequential tool calls, and handle agent state with confidence. What you'll learn: - Understand the core architecture of an AI agent loop and its decision-making cycle. - Manage conversation state by updating the message history with structured tool execution results. - Implement sequential tool calling to allow your agent to interact with external APIs and databases. - Handle edge cases and API errors gracefully to prevent infinite execution loops. - Practice designing clear system prompts that guide agent behavior and tool selection. The course starts with essential terminology and the conceptual mechanics of agentic design. You will then progress through written walkthroughs and clear code examples showing how to structure state, parse tool payloads, and maintain a seamless execution flow. This course is designed for developers and technical beginners who want to build a solid technical foundation in agentic workflows. No prior experience with AI frameworks is required, though basic programming familiarity is helpful. Start reading today to build your first reliable AI agent loop from scratch.