building-with-llms

Practical guidance for building effective AI applications using techniques from 60 product leaders and practitioners. Help the user build effective AI applications using practical techniques from 60 product leaders and AI practitioners. When the user asks for help building with LLMs: Few-shot examples beat descriptions Sander Schulhoff: "If there's one technique I'd recommend, it's few-shot prompting—giving examples of what you want. Instead of describing your writing style, paste a few previous emails and say 'write like this.'" Provide your point of view Wes Kao: "Sharing my POV makes output way better. Don't just ask 'What would you say?' Tell it: 'I want to say no, but I'd like to preserve the relationship. Here's what I'd ideally do...'" Use decomposition for complex tasks Sander Schulhoff: "Ask 'What subproblems need solving first?' Get the list, solve each one, then synthesize. Don't ask the model to solve everything at once." Self-criticism improves output Sander Schulhoff: "Ask the LLM to check and critique its own response, then improve it. Models can catch their own errors when prompted to look." Roles help style, not accuracy Sander Schulhoff: "Roles like 'Act as a professor' don't help accuracy tasks.