Unleash the Power of AI in eDiscovery: Mastering the Art of Prompt Engineering
Prompt engineering is crucial for getting the most out of generative AI in eDiscovery. By carefully crafting prompts, you can ensure that the AI generates accurate, relevant, and helpful results.
Summary
- What is prompt engineering? It is the process of crafting prompts that tell a large language model (LLM) what to generate or how to respond.
- Tips for crafting effective prompts:
- Know your AI: Understand the AI's strengths and limitations.
- Avoid hallucinations: Verify the factual accuracy of the response.
- From broad to specific: Start with broad prompts and then refine them.
- Assign a role: Specify what role the AI should have or what tone to set.
- Context is king: Provide the AI with as much context as possible.
- Iterative approach: Continuously refine your prompts.
- Control parameters at play: Adjust the verbosity, length, and format of the response.
- Avoid leading the AI: Avoid prompts that express opinions or lead the AI to a specific answer.
- Direct the format: Specify the format of the response (e.g., list, bullet points).
- Break down complex queries: Break down complex questions into a series of simpler prompts.
- Challenges of prompt engineering:
- Vagueness: Prompts that are too vague will lead to broad or off-topic responses.
- Overly specific prompts: Prompts that are too specific may miss relevant results.