Episode 175: ChatGPT Prompt Engineering for Legal - Tips and Traps
Jul 23, 2023
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Ab Saraswat, Chief Revenue Officer, Lupl and Founder, Fringe Legal discusses ChatGPT prompt engineering for legal in this podcast. Topics include prompt engineering basics, prompt formatting, techniques and best practices, ethical considerations, and resources for prompt engineering with OpenAI API.
Effective prompt engineering involves creating specific and concise prompts to train the model and achieve desired responses.
Prompt chaining and chain of thought prompting are advanced techniques that allow for step-by-step reasoning and complex chains of prompts.
Continuous experimentation, iteration, and staying updated on resources and developments are crucial for refining prompt engineering skills and achieving better results.
Deep dives
Understanding the Art of Prompt Engineering for Chat GPT
Prompt engineering is a key methodical process for getting the best results from Chat GPT. It involves creating prompts with specific roles, context, instructions, and desired output format. By structuring prompts effectively, you can train the model to produce desired responses. It is important to be specific and concise in your prompts, avoiding fluffy or imprecise descriptions. Prompt chaining and chain of thought prompting are advanced techniques that allow you to get step-by-step reasoning or create complex chains of prompts for more elaborate tasks. Experimentation and iteration are key to refining your prompts and achieving the desired outputs.
Tips for Successful Prompt Engineering
Here are some tips for effective prompt engineering. First, be mindful of prompt slippage, as models may change over time. Experiment and adjust your prompts accordingly. Consider creating a library of frequently used prompts for efficiency. Use a consistent format to differentiate prompts from instructions, such as using colons or other symbols. Understand and leverage the specific features and capabilities of each model you use, such as Chat GPT or Claude. Finally, stay updated on the latest developments and resources to keep improving your prompt engineering skills.
Prompting Best Practices and Resources
OpenAI provides valuable resources on prompting best practices. Their Prompting Best Practices guide offers in-depth insights and tips for structuring prompts effectively. It covers concepts like fine-tuning, parameters, and tokens, and discusses the importance of being specific and avoiding fluffy descriptions. OpenAI also offers a help page on Prompt Engineering that developers can leverage. Additionally, staying updated with the latest developments and advancements in the field of large language models will help you enhance your prompt engineering skills.
Experimenting and Learning from Chat GPT
The key to successful prompt engineering is to experiment and learn from your experiences with Chat GPT. Continuously refine your prompts based on the outputs you receive, adjusting and iterating as needed. Develop a deep understanding of how to structure prompts for specific tasks and goals. As you gain more experience, your prompt engineering skills will improve, allowing you to achieve better results and harness the power of Chat GPT effectively.
The Future of Prompt Engineering and Large Language Models
Prompt engineering is a rapidly evolving field. As large language models continue to improve, there will be more specialized models catering to specific industries and tasks. It is essential to stay informed about the latest advancements and developments in the field. While Chat GPT is a widely used model, exploring other models like Claude and being open to future innovations will help you adapt and optimize your prompt engineering strategies for different use cases and requirements.
This podcast was delivered on 21 July 2023 and is the sixth session in CLI’s AI for Legal Series.
In this session Ab Saraswat, Chief Revenue Officer, Lupl and Founder, Fringe Legal discussed everything you need to know about ChatGPT Prompt Engineering for Legal …. all the tips and traps.
