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Which format do you think is the best for storing your resume as contextual data for use with LLMs?

Generation Details

Date LLM Access Method
Nov 2024 GPT-4 Web UI

For the purpose of storing and referencing your resume information for future prompting, the Markdown format is generally more useful because it is human-readable and structured in a simple and clear way, making it easier to quickly interpret and modify if needed. It also works well in most text-based environments, including those for AI models like ChatGPT.

Here’s why Markdown might be preferable:

  1. Human-Friendly: Markdown is simple to read and doesn't require specialized knowledge to understand the content.
  2. Prompt Compatibility: When you're using LLMs like ChatGPT, a Markdown format is easy for the model to interpret, and it closely mirrors how text is structured for consumption.
  3. Adjustability: You can easily adjust or update your information without needing complex syntax as in JSON.
  4. No Parsing Required: Markdown doesn’t need to be parsed like JSON, so it directly serves as input in conversation without needing conversion.

JSON, while machine-readable and structured, may not be as easily editable or interpretable in real-time, unless you're dealing with structured data processing or API integration. If your context is primarily text-based interaction, JSON might add unnecessary complexity.

Suggestion: For the use case of keeping the resume as a reference for prompting, storing it in Markdown format (or similar simple text) would likely be the most efficient choice. If you are looking to add structured data for automation purposes or API calls, then JSON might be useful, but for general LLM prompting, Markdown will likely suffice.

Would you like me to store the content in Markdown format as your resume reference for future prompts?

The above text was generated by a large language model (LLM) and its accuracy has not been validated. This page is part of 'LLMs-on-LLMs,' a Github repository by Daniel Rosehill which explores how curious humans can use LLMs to better their understanding of LLMs and AI. However, the information should not be regarded as authoritative and given the fast pace of evolution in LLM technology will eventually become deprecated. This footer was added at 16-Nov-2024.