The latest articles on DEV Community by mathew_woo (@mathew_woo). https://dev.to/mathew_woo https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F4040938%2F28e5d058-a4bf-4036-aca4-c0dd8d5bdfb7.png https://dev.to/mathew_woo en mathew_woo Wed, 22 Jul 2026 02:29:20 +0000 https://dev.to/mathew_woo/anyone-know-prior-research-on-rewriting-a-rough-prompt-per-model-n9f https://dev.to/mathew_woo/anyone-know-prior-research-on-rewriting-a-rough-prompt-per-model-n9f <p>I've been kicking around an idea and want to read up before I build it. </p> <p>The idea: you type a rough, half-formed prompt, an LLM works out what you actually mean, and then rewrites it into a specific, optimized prompt tuned for each target model (Claude, GPT, Gemini, etc.). </p> <div class="crayons-card c-embed"> <br> <strong>The Core Insight:</strong> The same instruction lands differently on different models. I don't want a single generic "cleaned-up" prompt—I want one explicitly tailored <strong>per model</strong>.<br> </div> <h2> What I'm Looking For </h2> <p>Before I start building, I'd love to find prior work. Specifically, I'm looking for:</p> <ul> <li>Automatic prompt optimization or prompt rewriting techniques.</li> <li>Research on adapting a prompt to a specific target model's quirks and strengths rather than producing a generically better prompt.</li> </ul> <p>Is this already well-studied and I'm just searching the wrong terms? </p> <p>If you've run across papers, GitHub repositories, or blog posts tackling model-specific prompt adaptation, please drop them in the comments below! What keywords should I actually be searching for?</p> ai llm machinelearning opensource