AI Automation Levels

Level 1: Prompt Engineering Framework

1. Use the “Purpose Clarity Improvement” framework for prompt engineering.
2. Begin with stating the purpose of the task for clarity.
3. Ask for clarifying instructions if the AI doesn’t fully understand the request.
4. After receiving a response, ask the AI to critique and improve the output.

Level 2: Automating Tweet Creation

1. Automate text-to-tweet conversion using an AI language model (e.g., GPT or Claude).
2. Use a trained agent to generate tweets with specific elements:
   • Concise message.
   • Hook, explanation, question, and hashtags.
3. Ensure the tweet has the right format, within 240 characters.

Level 3: Coding in No-Code Software

1. Use no-code software like Make.com to automate workflows.
2. Integrate Python code into no-code platforms for more complex tasks.
3. Create automations that can retrieve content (e.g., YouTube transcripts) using Python.
4. Develop a system that allows you to scrape and automate processes like creating social media posts.

Level 4: Using RSS Feeds

1. Set up RSS feeds to monitor specific content from websites, YouTube channels, etc.
2. Use the RSS feed to automate content retrieval.
3. Integrate with no-code tools to filter, organize, and display the content (e.g., for newsletters).
4. Set up automation to generate social media posts or emails from RSS feed content.

Level 5: Automating Form Submissions to Email

1. Use tools like Paperform to create client-facing forms.
2. Set up Make.com to watch for form submissions and trigger automations.
3. Automate the creation of a personalized email or draft based on form submissions.
4. Include client-specific data in the emails and trigger other workflows if needed.

Level 6: Automating YouTube Transcript to Email

1. Use an RSS feed to monitor a YouTube channel.
2. Retrieve video transcripts using Python.
3. Summarize the transcript using an AI model like GPT.
4. Automatically send the summary to yourself via email.

Level 7: Bundling Multiple Creators’ Content

1. Combine multiple RSS feeds from various creators into a single bundle.
2. Automate content retrieval from those feeds and summarize them.
3. Send the summaries to a Google Doc or other desired formats for archiving or use.

Level 8: Text-to-Speech Automation

1. Use text-to-speech tools like 11 Labs to convert summarized content into audio.
2. Automate sending the generated audio file via email as an attachment.
3. Adjust speech parameters like stability and clarity to customize the output voice.

Level 9: Training a GPT on Your Data

1. Collect and organize your data (e.g., YouTube transcripts) into a document.
2. Train a GPT model on this data to answer questions related to your knowledge base.
3. Embed the GPT into a no-code tool to answer questions dynamically from users.
4. Automate answers based on the knowledge embedded in the model.

Level 10: Creating a Unique Tone of Voice

1. Break down elements of tone and writing style (micro, meso, macro levels).
2. Train AI to replicate the tone of voice based on specific vocabulary, sentence structure, and rhetorical devices.
3. Use this tone of voice for automated responses, making them sound more authentic.
4. Combine insights from previous levels (training, summaries) with personalized tone for advanced automations.

These levels provide a progression of increasingly complex AI automation techniques, starting from basic prompt engineering to training AI on personalized data and voice tones.