AI自动撰写您所有的邮件！

AI自动撰写您所有的邮件！

Table of Contents

1. Introduction
2. The Need for Automated Outbound Messages
3. The Build Process
   1. Back End
      1. Terraform for Cloud Infrastructure
      2. Using GCP and Functions
      3. Creating Models and Data Points
      4. Creating Prompts
   2. Front End
      1. Gallery View
      2. Create New Button
      3. Chat Box
4. Overcoming Challenges
   1. Optimization with Conversation Buffer
   2. Utilizing Knowledge Graphs and Pinecone Vector Database
5. Workflow of the Chaotic Good Creation
   1. Signing in and Naming the Model
   2. Training Data and Prompts
   3. Adding Company Information and Successful Examples
   4. Iterating with the AI Assistant
6. Conclusion

Automating Outbound Messages: A Breakdown of the Chaotic Good Creation

Have You ever found yourself spending hours crafting outbound messages for potential clients as part of business development or sales? The process can be time-consuming, especially when considering the different platforms and tones required in various sectors. In this episode of Chaotic Good Creations, we Delve into a fascinating project where we aim to automate the creation of outbound messages tailored to different platforms and highly effective in capturing potential clients' Attention.

Introduction

In the world of business development and sales, reaching out to potential clients through outbound messages is a common practice. However, this task can be arduous, requiring personalized messages for different platforms and sectors. To address this challenge, we set out to create a product that streamlines the process of generating highly effective outbound messages across various platforms.

The Need for Automated Outbound Messages

In today's fast-paced business environment, time is of the essence. As professionals in business development and sales, we understand the value of automating repetitive tasks. The idea of automating outbound messages came about when a friend approached us with a two-month-long conversation he had with Chang JBT. He wanted to transform the insights gained from these conversations into a product that could potentially replace his job. Intrigued by the concept, we took on the challenge and envisioned a solution that would generate outbound messages matching the style and effectiveness of the user.

The Build Process

To bring this unique product to life, we divided the development process into two main components: the back end and the front end.

Back End

In the back end, we utilized Terraform, a powerful tool for programmatically configuring cloud infrastructure, to Interact with the Google Cloud Platform (GCP). Within GCP, we employed various functions, including creating models, data points, and prompts.

Terraform for Cloud Infrastructure

By leveraging Terraform, we could seamlessly configure our cloud infrastructure. This allowed us to focus on the essential aspects of our product's functionality.

Using GCP and Functions

Within the Google Cloud Platform, we employed functions to handle specific tasks, such as creating and retrieving models, data points, and prompts. These functions formed the backbone of our automated outbound messaging system.

Creating Models and Data Points

The creation of models was a pivotal step in our product's development. Models enabled users to specify the desired AI behavior, such as tonal and conversational rules. Additionally, we created data points Based on training data, which included examples of effective outbound messages.

Creating Prompts

Prompts played a crucial role in guiding the AI to generate appropriate outbound messages. We fine-tuned our prompts to ensure accurate and contextually Relevant responses.

Front End

While the back end handled the technical aspects, the front end provided a user-friendly interface for users to interact with our product.

Gallery View

The gallery view component allowed users to have a comprehensive overview of their outbound message templates. They could easily manage and access different templates in a visually appealing manner.

Create New Button

The "create new" button served as a gateway for users to add new outbound message templates. With a simple click, users could initiate the creation of custom templates tailored to their unique requirements.

Chat Box

The chat box feature was an exciting addition to our product. We sought to incorporate a chat box into the product's front end to enable seamless communication between users and the AI-powered assistant.

Overcoming Challenges

During the development process, we encountered challenges that required innovative solutions to ensure optimal performance and user experience.

Optimization with Conversation Buffer

In our Quest for optimization, we explored various approaches to preserve memory while still retaining the most recent conversational Context. The solution came in the form of a conversation buffer, which allowed us to selectively access and utilize only the most recent information.

Utilizing Knowledge Graphs and Pinecone Vector Database

To maintain the specificity and Detail-oriented nature of our AI responses, we employed knowledge graphs and Pinecone Vector Database. These memory architectures enabled us to retain essential details and enhance the accuracy of the generated outbound messages.

Workflow of the Chaotic Good Creation

The workflow of our automated outbound message generation system comprises several key steps, each contributing to the overall user experience and effectiveness of the AI assistant.

Signing in and Naming the Model

Users begin by signing in to the Website and naming their model. This step ensures personalized and efficient interactions with the AI assistant.

Training Data and Prompts

Training data and prompts form the foundation of our AI assistant's abilities. Users provide relevant training data, including successful email templates and messaging examples. These data points serve as references for the AI's outbound message generation.

Adding Company Information and Successful Examples

To further customize the AI assistant's responses, users can provide specific information about their company and product. This additional context empowers the AI assistant to craft highly relevant and engaging outbound messages.

Iterating with the AI Assistant

Once the AI assistant generates an outbound message, users have the opportunity to fine-tune and iterate their requirements. They can provide feedback and request adjustments, effectively collaborating with the AI assistant to achieve optimal outcomes.

Conclusion

Automating outbound messages can revolutionize the efficiency and productivity of business development and sales professionals. With the chaotic good creation of our AI-powered assistant, users can now streamline the process of generating personalized, platform-specific outbound messages. We have overcome challenges, utilized innovative memory architectures, and designed a seamless workflow that empowers users to create highly effective outbound messages with ease. Embrace the power of automation and embark on a Journey of increased productivity and success in your outbound messaging endeavors.

Highlights:

• Streamline the process of generating outbound messages
• Automate personalized messages for different platforms
• Utilize Terraform and GCP for efficient cloud infrastructure
• Fine-tune AI models with tonal and conversational rules
• Preserve memory with conversation buffer optimization
• Enhance accuracy with knowledge graphs and vector database
• User-friendly front end with gallery view and chat box
• Workflow from signing in to iterating with the AI assistant

FAQ

Q: Can I use this product for any industry? A: Yes, our product is designed to cater to various sectors, allowing you to tailor your outbound messages based on the specific requirements and tone of your industry.

Q: How accurate are the generated outbound messages? A: The accuracy of the generated outbound messages heavily relies on the quality of the training data provided by the user. Garbage in, garbage out. By ensuring high-quality training data, you can expect highly effective outbound messages.

Q: Can I collaborate with the AI assistant to iterate on my outbound messages? A: Absolutely! Our AI assistant allows for iterative feedback and adjustments. You can engage in a collaboration-like process with the AI assistant to achieve the desired outcomes for your outbound messages.

Q: Can I personalize the AI assistant's responses based on my company's information? A: Yes, our product enables you to add specific information about your company and product. This additional context empowers the AI assistant to create highly relevant and engaging outbound messages tailored to your company's needs.