AI Agents & Automation

Module 1

Tools & real-life automation

Explore how AI and no-code tools can be applied to everyday business processes. Through practical use cases, you'll learn how to streamline repetitive tasks, improve information flows, and deliver quick operational improvements while understanding where tool-based automation is most effective.

• Design linear workflows using AI and no-code automation tools
• Automate data collection, reporting, and routine business processes
• Apply AI tools to support basic analysis and decision-making tasks
• Evaluate when a process requires more advanced automation approaches

• Zapier
• Make
• Google Sheets
• LLMs

Project: automate a simple business workflow (e.g., customer feedback processing or reporting automation).

Module 2

Integrations: Webhooks, APIs & Data

Learn how systems exchange information through APIs, webhooks, and structured data. Explore the foundations of reliable automation and build workflows that connect AI tools with business applications.

• Connect business applications using APIs and webhooks
• Structure and validate data to support reliable automation workflows
• Manage errors and system constraints in automated processes
• Integrate AI tools into API-driven workflows

• Webhooks
• REST APIs
• Postman
• Make
• Zapier

Project: build an API-driven automation workflow designed as a reusable building block for future agents.

Module 3

AI agents

Explore how AI agents can support decision-making within automation workflows. Learn how agents evaluate inputs, select actions, and coordinate tools and integrations to handle more complex business processes.

• Differentiate AI agents from chatbots and other AI-powered tools
• Design automation workflows that incorporate decision-making logic
• Connect AI agents with external tools and integrations
• Evaluate when AI agents are appropriate for a business process

• Zapier
• n8n
• LLMs

Project: Design an AI agent that manages multiple decision paths and API calls without relying on long-term memory or autonomous responsibility.

Module 4

AI assistants: Orchestrated automation systems

Explore how AI assistants coordinate workflows, tools, and human input across complex business processes. Learn how orchestrated systems operate over time to deliver reliable and scalable automation.

• Design AI assistants that coordinate multiple workflows, tools, and data sources
• Manage state, context, and task progression across long-running processes
• Implement escalation rules and human-in-the-loop decision points
• Evaluate the reliability and operational requirements of AI assistant systems

• LLMs
• orchestration platforms
• state stores

Capstone Project: Design a B2B onboarding concierge that reacts to events, manages state, coordinates tools, and escalates decisions to human stakeholders when required.