building-with-llms

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. But they're great for controlling tone and style in creative work." Put context at the beginning Sander Schulhoff: "Place long context at the start of your prompt.