Master AI Automation: Build Real AI Agents from Scratch

Explore the distinction between AI automation and AI agents and how five core components—specific knowledge, tools, a large language model, instructions, and memory—enable flexible problem solving.

Build ai agents and automations with no-code drag-and-drop tools like relevance ai, flow-wise ai, Make.com, and Zapier. See how these platforms connect tools and manage memory and knowledge.

Learn the essential fundamentals for building powerful ai agents, including llms, prompting, roles, goals, boundaries, and handling context, with practical guidance for beginners.

Learn essential IT basics and minimal coding concepts to describe problems, understand programming syntax, and use ChatGPT to generate Python code for powerful AI agents.

Understand data types and why code expects specific types, with examples of string, integer, boolean, and list; learn how type mismatches cause errors and how to transform data types.

Master JSON, a text-based format for storing and exchanging data via APIs and webhooks, with four valid types and strict syntax.

Identify variables as labeled containers that store data with a name and a value you can reuse or change in code, such as a username.

Translate natural language ideas into code using a boolean variable and if-else constructs in Python to express conditions and determine outputs for AI agents.

Loops let code run the same task several times until a condition is met, applying logic to each element in a JSON array, such as downloading images.

Explore how Python empowers no-code AI agent development by integrating readable Python code for calculations, data type transformations, and inter-platform communication with web apps, aided by ChatGPT-generated scripts.

Explore APIs and webhooks as data-exchange mechanisms between apps. Learn post and get API methods, and how webhooks trigger actions from new data.

Learn to instruct ChatGPT to write Python scripts by defining input and output variables and data formats, crafting precise prompts, and transforming variables into the desired form with notes.

Java is a programming language for apps and Android software, while HTML structures web pages for the browser; we'll use them in AI agent tools like Python with ChatGPT.

Review essential IT concepts from the crash course, including webhooks and APIs, to reinforce knowledge as you build powerful AI agents.

Design systems by defining input and output, using black box and top-down approaches to simplify complex ai automations and build robust ai agents.

During the planning phase, the lecture uses a relevance ai example from a vacuum company to illustrate a three-step plan—plan, build, test and improve—and the black box top-down approach.

Explore relevance AI's interface, configure projects and credits, and connect OpenAI via API key to power your first AI agent with templates, tools, and knowledge bases.

Build your first AI agent with relevance ai, wiring tools to read emails, send responses, and create calendar events, guided by a knowledge base and core instructions.

Advance your AI agent through testing and iterative improvement, uncovering actual and conceptual errors, then add functionality like handling job applications with emails, calendar events, and Zoom invites via Sapir.

Test and iterate to improve ai agents; evaluate under varied conditions, uncover real and conceptual errors, then fix and add capabilities like applicant handling, zoom scheduling, and calendar integration.

Connect your ai agent to zoom via Zapier, using webhooks and api calls to automate meetings and confirmation emails, then test and refine the workflow.

Update viewers on the updated Relevance AI interface and demonstrate building AI agents quickly with the AI Agent Builder, showing faster setup without Zapier or custom tools.

Explore the relevance ai overview, including marketplace agents, knowledge bases, tools, mcp integrations, and building agents with the ai builder on the free plan.

Build an AI agent in minutes with the Relevance AI builder, using a predefined role-based prompt, tool integrations (Gmail, Google Calendar, Zoom), and knowledge-base checks to avoid fabrication.

Build a social media content generator AI agent that converts a blog URL into seven Twitter posts and two video scripts, storing assets in Google Sheets and Drive via Zapier.

Build and automate a social media generator AI agent that processes image URLs and text posts via webhooks, storing captions, video scripts, and sources in Google Sheets and Drive.

Explore Voice Flow, a no-code AI agent platform for conversational AI, with a visual workflow builder to design and deploy chatbots and voice assistants on websites or phone numbers.

Explore the Voice Flow interface, navigate agents, templates, and billing, manage credits and phone numbers, and leverage learn and documentation resources to build powerful ai agents.

Discover Voice Flow’s core elements for building AI agents, from talking blocks (message, prompt, image, card, carousel) to capture and logic elements (button, choice, listen, condition, set).

Learn to quickly build a customer support AI agent in Voice Flow using a template, upload your knowledge base, and deploy to website and phone.

Design and customize the Voice Flow chat interface by adjusting colors, logos, header, welcome messages, and appearance, and configure modality, position, and API access for website deployment.

Publish and deploy your voiceflow agent to any website by pasting the script into the host's custom code or header, then test the chat and knowledge base responses.

Learn to deploy the Voiceflow chatbot to a phone number by replacing the button with a voice-driven choice element and configuring Twilio or Vonage telephony with development and production stages.

Design and build a downloadable voice flow powered customer support and appointment setter agent that answers questions, books calls, and generates live cost offers, integrated with relevance AI tools.

Learn to build a voice flow agent that identifies intent, confirms it, and routes to booking a zoom meeting or issuing an instant offer, with interface updates and data collection.

Learn to collect six data points in voice flow, call a relevance AI tool via API to book a Zoom meeting, and handle errors with a fallback email option.

Deploy an ai agent to a website or phone, test interactions, generate a first estimate based on chosen processes and duration, and book a free strategy call while reviewing transcripts.

Set up multiple voice flow workflows, connect them with triggers and intents, and jump between canvases to run a hungry intent across separate workflows within a single agent.

Set up a custom form that pops up in chat window to collect user data for a Voiceflow chatbot workflow, and deploy code to extract six data points into variables.

Design and customize a custom chat form with ChatGPT by editing the script's CSS and data fields, adding user age, and updating the workflow.

Explore voice flow, access ready-to-use agents and a pop-up form script, and learn to copy, adjust, and implement them in your AI automation projects.

Explore n8n, an open-source no-code and low-code AI automation platform that runs locally or in the cloud, featuring visual drag-and-drop workflows and integrations with Google Sheets and Google Docs.

Build your first ai agent with n810 to automatically research daily topics, generate a newsletter and ten video scripts, plus captions for Instagram and YouTube Shorts, stored in Google Sheets.

Build a daily newsletter and content agent with n8n, triggering automatically to fetch research from Perplexity, merge results, generate an HTML newsletter, and email via Gmail.

Build a second workflow in n8n to transform newsletter content into video scripts for social media, using GPT-4 with a defined system prompt, and store results in Google Sheets.

Builds an AI content agent workflow in n8n that creates a daily newsletter and ten video scripts, merges research outputs, and updates a Google Sheet while delivering the newsletter.

Build a personal assistant with n8n and Telegram to manage emails and calendars. Research topics live online and turn ideas into video scripts stored in Google Sheets, with voice responses.

Describe the design of a personal telegram assistant built in n8n, from telegram trigger and memory to the AI agent core, with calendar, email, knowledge base, and research workflows.

Build a personal telegram assistant by connecting a telegram bot to n8n, configuring botfather, and testing the telegram trigger to drive an AI agent.

Build a personal telegram assistant in n8n with memory for chat IDs and messages, then add calculator, Google Sheets knowledge base, and a Wikipedia and Serp research workflow.

Create a Telegram-based personal assistant that reads, summarizes, and emails your inbox, orchestrated through AI-powered workflows that also manage calendars and generate short-form video scripts stored in Google Sheets.

Learn to add a voice route to a telegram personal assistant by routing text and voice inputs, transcribing voice with OpenAI, and replying with generated audio through n8n.

Compare n8n access options including cloud, local docker, repo cloud, and own cloud server, outlining costs, setup, and suitability for learning or client work.

Run n8n locally via Docker, expose it with Ngrok, and connect to Telegram and Google Sheets.

Import the provided workflows to your local or cloud project with a simple import from file, then configure credentials for OpenAI, Telegram, Google Sheets, Google Mail, Drive, Calendar, and more.

Learn how to run n8n on Repo Cloud, deploy a new app, and connect Google services with credentials and OAuth setup for AI automation workflows.