Jake Heller discusses lessons learned from building Co-Counsel, an AI legal assistant, emphasizing practical prompt engineering techniques. He details the three-step process: defining the customer experience, modeling the task after how the best lawyer would perform it, and breaking down the process into micro-steps that are either code or prompts. Heller stresses the importance of rigorous evaluation, aiming for near-perfect accuracy through extensive testing and iteration, and highlights the significance of context and retrieval quality. He also shares tricks for optimizing AI responses, such as using single-token outputs and reinforcement fine-tuning, and advises experimenting with different models for each prompt to balance performance and cost.
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