How to use LLMs effectively in your daily work — a practical tutorial
The article provides practical guidance on effectively using large language models (LLMs) in software development. It emphasizes the importance of focused prompts and task decomposition to achieve better results. Various prompt patterns are suggested to enhance the quality of outputs from LLMs.
- ▪LLMs excel at transforming and iterating on artifacts like requirements, design, and code.
- ▪Using small, focused prompts yields better results than broad requests for entire systems.
- ▪Task decomposition and specific prompt patterns can significantly improve the quality of AI-generated outputs.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3468139) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Rizwan Saleem Posted on May 29 How to use LLMs effectively in your daily work — a practical tutorial #ai #frontend #typescript #webdev How to use LLMs effectively in your daily work — a practical tutorial 1. Core principles for dev work LLMs are best at transforming and iterating on artifacts (requirements → design, design → code, code → tests, code → docs). You get better results from small, focused prompts than from “build my whole system” requests.
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