I’m on the Standard plan and looking for help optimizing Julius AI for a specific use case. I’m experimenting with using my ChatGPT conversation history to support different tasks, starting with crafting job application responses. I know I could use multiple tools to create a custom solution, but I am interested in seeing if this is something Julius may help with more easily. I am not entirely sure if this is a use case suited for Julius, but it would still be fun trying.
Currently, I’m using a ChatGPT conversation export (CSV) to help generate 500-1000 word responses for education-related job applications. Specifically, I need Julius to:
- Extract education-related content from my conversation history to help generate responses.
- Make meaningful connections from relevant conversations that aren’t explicitly about education but might be useful for context (e.g., discussions on technology trends or social impact).
- Generate comprehensive responses and help refine them to fit specific word limits.
I’m looking for any advice or references that could help with:
- Model selection
- Custom instructions
- Workflow optimization
- Relevant configurations or settings changes within Julius for this task.
The file I am working with is a cleaned and structured CSV of my entire ChatGPT conversation history. I used a Python script with pandas to convert the ChatGPT JSON export file (‘conversations.json’) into a structured CSV, cleaning and flattening the nested conversation structure while preserving all messages, roles, timestamps, and relationships.
I have around five specific essay questions I’m trying to answer, and I see the ChatGPT conversation history as a resource for memory retrieval—helping me find useful ideas or connections that I might have forgotten. I want to make sure I’m approaching the setup effectively without overcomplicating the workflow.
I realize that my focus is on optimizing Julius for a practical use case, and I understand it may require some experimentation. Any guidance on setup, configuration, or best practices to make this workflow as effective as possible would be much appreciated.