I Built A Custom AI Email Assistant with ChatGPT! | Make Automations 101 Tutorial
TLDRSimon shares his experience of creating a custom AI email assistant using Gmail and Chat GPT to streamline his email management. The tutorial demonstrates how to automate email classification and response with Make, a no-code automation tool, and a custom Chat GPT model trained to categorize and process inquiries. Simon also introduces Make's features, templates, and the cost-effectiveness of using the AI assistant for small businesses, encouraging viewers to explore automation for their workflow needs.
Takeaways
- 😀 Simon created a custom AI email assistant to manage his increased email workload due to the success of his Notion template business.
- 🔧 The AI assistant was developed with the help of a generalist company and uses Gmail and Chat GPT for email classification and response automation.
- 📧 The aim is to identify different types of emails and train the AI to classify and respond to them, reducing manual email management.
- 🤖 The AI assistant is trained to classify emails into various categories like partnership offers, discount clarifications, and delivery issues.
- 🛠️ Make, a no-code automation tool, is used to create workflows that automatically process and respond to emails based on their classification.
- 📚 Make offers pre-built templates and integrations with various apps, including Notion and Gmail, to facilitate easy workflow creation.
- 📊 Simon used FigJam, a flowchart tool, to plan and visualize the email classification process before building the automation.
- 🔗 The automation workflow involves Gmail, the custom Chat GPT assistant, and routing based on email classification to apply appropriate labels or actions.
- 💡 Custom GPT assistants are created in Open AI's platform, where they can be trained with specific instructions and examples for the task at hand.
- 📈 The custom AI assistant is cost-effective, running on a pay-as-you-go basis with minimal expenses for a large number of operations.
- 🚀 The next steps include refining the AI's ability to draft responses based on previous replies, further automating the email handling process.
Q & A
What problem was Simon trying to solve with his custom AI email assistant?
-Simon was overwhelmed with managing his emails, especially after his notion template business took off. He created a custom AI email assistant to automate his email responses and streamline his workflow.
What is the purpose of using Make and Chat GPT in the automation process described in the video?
-Make is a no-code automation tool that helps create workflows across various apps. Chat GPT is used to train a custom AI assistant that can classify emails and potentially respond to them, adding AI intelligence to the automation process.
How does Simon plan to train the custom Chat GPT assistant for his email classification?
-Simon plans to train the Chat GPT assistant by providing it with examples of emails and their corresponding categories. This training helps the assistant to classify incoming emails accurately.
What is the role of Fig Jam in Simon's workflow planning?
-Fig Jam is used by Simon to create a flowchart that visualizes the email classification process. It helps him to clarify the categories for email classification and plan the automated workflow.
How does Make's Gmail integration work in the automation?
-Make's Gmail integration allows new emails to be fed into the Chat GPT assistant. Based on the assistant's classification, the email is then routed through a series of conditional statements to take appropriate actions, such as labeling the email.
What is the significance of using a custom GPT assistant instead of a standard Chat GPT interface?
-A custom GPT assistant is an interface designed for bots, allowing for automation and API integration. It can be trained specifically for tasks like email classification, making it more efficient and tailored to the user's needs compared to a standard Chat GPT interface.
What are the cost implications of using different versions of the GPT model in the custom assistant?
-The cost of running the custom assistant depends on the version of the GPT model used. The 3.5 model is relatively cheap to run, but if higher accuracy is needed, upgrading to a more advanced model like GPT-4 might be considered, which could have cost implications.
How does Simon ensure that the custom GPT assistant's output aligns with the expected email categories?
-Simon aligns the output of the custom GPT assistant with the email categories by providing specific instructions and examples during the training process. This ensures that the assistant classifies emails into the correct categories as defined by Simon.
What is the next step Simon plans to take after setting up the email classification automation?
-The next step Simon plans to take is to match his pre-drafted responses to the questions and see if the bot can start drafting responses automatically, further enhancing the automation process.
How does Simon ensure that the automation system is cost-effective and efficient?
-Simon ensures cost-effectiveness by using the GPT 3.5 model, which is relatively inexpensive to run. He also optimizes the system by keeping instructions concise to use fewer tokens and by leveraging the power of no-code automation with Make.
Outlines
📧 Email Overwhelm and AI Assistant Integration
Simon discusses the challenges of managing a surge in emails following the success of his Notion template business. To address this, he collaborates with a generalist company to develop a custom AI email assistant for his Gmail. He provides an overview of how to set up automations using Make, a no-code automation tool, and aims to demonstrate the integration of Gmail with Chat GPT. Simon's goal is to classify emails, train an AI assistant to respond, and automate the process using Make. He also highlights the partnership with Make for the tutorial and mentions the limitations of traditional email filters compared to the AI intelligence offered by Chat GPT.
🤖 Building an AI-Powered Email Workflow with Make
In this paragraph, Simon details the process of building an automated workflow for email classification using Make and a custom Chat GPT assistant. He explains the top-down approach where new emails are fed into the Chat GPT agent for classification into predefined categories. Simon then demonstrates the setup of the workflow in Make, including the integration of Gmail and Open AI, filtering out replies, and routing classified emails to appropriate actions. He emphasizes the cost-effectiveness of using the 3.5 turbo model for the task and shows how to build the workflow step by step, including setting up a router for conditional actions based on the email classification.
🛠 Creating a Custom GPT Assistant for Email Classification
Simon outlines the steps for creating a custom GPT assistant tailored for email classification. He starts by creating a new project in the GPT platform and defining the bot's purpose and instructions. The assistant is trained to classify emails into specific categories based on the subject and body content. Simon provides examples of the input and desired output for the assistant, emphasizing the importance of aligning the instructions with the workflow setup in Make. He also discusses the cost implications of using different GPT models and the benefits of using the assistant API for integration with Make. Finally, Simon shares insights on the effectiveness of the automation and the next steps for refining the system to draft responses based on previous replies.
Mindmap
Keywords
💡AI Email Assistant
💡Automation
💡Make
💡Chat GPT
💡Notion
💡Custom AI Assistant
💡Workflow
💡Fig Jam
💡Email Classification
💡API Key
Highlights
Simon created a custom AI email assistant for his Gmail account to manage his email workload.
The AI assistant is designed to identify and process various email inquiries related to Notion templates and community questions.
Simon uses 'Make', a no-code automation tool, to connect Gmail with Chat GPT for customized email responses.
The AI assistant is trained to classify emails into eight different categories based on the content.
Make's visual interface allows for easy workflow creation across various apps.
Make offers pre-built templates for workflows, such as syncing Notion databases with Google Calendar.
Simon used Fig Jam, a flowchart tool, to plan the email classification process.
The email classification bot is built using the GPT model and is trained with specific instructions for categorizing emails.
Custom GPT assistants can be created with different tones and expertise, such as copywriting.
The custom GPT assistant can analyze and label new emails automatically based on their content.
Make automations are cost-effective, with the assistant running for thousands of instances at a minimal cost.
The automation process includes filtering out replies and only processing new emails.
Simon's tutorial provides a starting point for using Make and connecting Gmail with Chat GPT.
The custom GPT assistant can be linked to Make using an API key for seamless integration.
The tutorial covers the setup of a Make automation from watching emails to classifying and labeling them.
Simon suggests that automating work is most effective when paired with the right systems and personal productivity habits.
The video concludes with a teaser for Simon's productivity tips and a tour of his Notion second brain template.
