The Complete AI Agent - All Levels - Build An AI Assistant

Explore the key characteristics of AI agents and how they disrupt the workforce. Gain a practical and technical background on how they work, with automation and project management implications.

Explore the rise of AI agents and how they differ from LLMs: agents act autonomously, execute tasks, and automate workflows to function as personal assistants.

AI agents are autonomous and can decide and act independently, from choosing games to adjusting factory workflows, while data from the workflow and chocolate-to-peanut ratios illustrate when humans intervene.

Learn how AI agents pursue objectives with autonomy and adaptive behavior, such as issuing refunds for undelivered pizzas, using workflow automation and machine learning to adjust actions after analyzing outcomes.

Explore how AI agents perceive their digital environment and automate tasks to boost efficiency and accuracy in business and personal workflows.

Personalize experiences and recommendations with AI agents by using input-driven parameters and tailored outputs, even without programming experience, while highlighting fundamentals and innovation that position AI as a disruptive force.

Explore real world ai agents, including self-driving cars, chatbots, and spam filters, with calendar updates. See how to classify and automate for intelligent decisions that simplify workflows.

Explore the types of AI agents, from reactive agents that trigger and respond to current stimuli to goal-oriented and learning agents that use memory and history to improve performance.

Explore the real risks of AI agents, including job displacement and automation across sectors. Examine biases in AI systems, such as facial recognition errors due to training data.

Examine privacy concerns and data collection risks in AI agents, including facial recognition and public space surveillance with consent, and assess security threats, vulnerability management, and ethical responsibilities.

Explore future trends in AI agents, driven by hyper-personalization, 24/7 autonomy, and growing human–bot collaboration, expanding from customer service to project management and even executive decisions.

Explore how intelligent automation and AI agents revolutionize work and daily life, and learn to build powerful AI assistants as automation scales exponentially.

Discover how to build an AI agent using N810, a low-code open-source automation platform that connects apps like Gmail, Google Calendar, and Slack to automate tasks with AI-driven workflows.

Discover how n8n enables seamless integrations and ai agent workflows across finance, hr, marketing, engineering, and devops, and learn to set up a free 14-day account.

learn how n8n integrates AI services to build powerful AI agent workflows, combining chatbots, data classification, and automation of emails, calendar events, and data logging in Google Sheets.

Build and manage AI agent workflows by defining triggers—manual, app events, or schedules—within projects and personal spaces, then test inputs and outputs before activation.

Set up your first AI agent trigger by connecting your Gmail on app events, selecting on message received, and fetching test events to automate inbox tasks.

explains the data flow in n8n using a Gmail trigger, showing how to connect credentials, set poll intervals, and monitor incoming emails as events to drive the ai assistant workflow.

Turn off simplify to gain full access to fetch-triggered json data, headers, and email details, then view and manipulate json in multiple formats as you build an AI assistant workflow.

Build a text classifier within the ai agent workflow to categorize Gmail messages by subject and content into work, personal, or travel, then auto-schedule in calendar.

Create Gmail labels for our classifier, adding work, personal, tour, and other categories, then hook emails to the AI-driven classification system for automatic routing.

Understand why a text classifier is better than an LLM for labeling text into predefined categories, and how training with labeled data enables accurate label prediction.

Explore how n8n's text classifier processes email data, using JSON and JavaScript to map subject and text fields, revealing OOP under the hood without coding.

Design and define a text classifier by creating categories: work, personal, touring, other for emails, using conditional statements; set up system prompts and OpenAI credentials, and test.

Generate an OpenAI API key to enable AI agents and access LLMs for the course. Create and securely store your secret key on platform.openai.com, then enable the text classifier.

Customize test runs for a text classifier in ai augmented pipeline powered by OpenAI. Test with Gmail emails and observe outputs into work, personal, and tour pipelines with json data.

Develop and test label-based app event pipelines to drive multi-level ai agent actions, using Gmail labels like personal, work, tour, and other to route messages and trigger automatic responses.

Build a personal email assistant with labeled actions for work, tour, and others. Train a GPT-4 based model to respond to emails in casual but professional tone.

Design a supervised learning prompt model for an ai agent by creating six back-and-forth user–assistant messages using ChatGPT to train a personal email responder for a customer service workflow.

Optimize an AI personal assistant by deploying a label classifier, a supervised OpenAI workflow, and Gmail integration to draft, send, and reply to messages with a consistent data flow.

Explore a simple data flow: trigger, text classifier, and AI agents that act on labeled data. Automate extracting travel details and scheduling hotels, flights, and meetings in your calendar.

Learn to set up a google calendar action for your AI agent, define start date, end date, description, location and summary, connect credentials, and implement the AI workflow with JavaScript.

Build an OpenAI message model and a function node to format Google Calendar events in an app, then test workflow tweaks and system prompt tweaking.

Integrate the OpenAI message model to extract events from text, capturing date, time, location, and description, then test prompts and map results to Google Calendar entries.

Develop a custom node in n8n using JavaScript to convert OpenAI outputs into a structured JSON for Google Calendar, including start date, end date, summary, description, and location.

Master end-to-end workflow automation with an AI agent that combines text classification, a large language model, and calendar integration using Gmail and Google Calendar.