Prompt Techniques, Frameworks and Formulas for LLMs: A Practical Guide

Técnicas, Frameworks y Fórmulas de Prompts para LLMs: Guía Práctica

If you’ve ever interacted with an artificial intelligence like ChatGPT, Claude, Gemini or Grok, you know these tools have incredible potential — but they don’t always understand exactly what you want on the first try.

In 2025, with language models (LLMs) more advanced than ever, the real game-changer lies in how we structure our prompts. That’s where techniques, frameworks, and prompt formulas come into play: they serve as strategic shortcuts for getting clearer, more useful, and more aligned responses.

Whether you’re optimizing workflows, generating creative ideas, solving technical challenges, structuring projects, or simply getting more on-point answers, this guide brings together the right tools to help you unlock the full power of LLMs.

Discover the Best Prompt Techniques, Frameworks, and Formulas for LLMs

Now’s the time to explore the tools that will revolutionize how you interact with LLMs! Here, we’ve compiled a collection of techniques, frameworks, and prompt formulas — from simple structures to more strategic approaches — all tested and ready to use.

Each card below leads to a detailed post: click to explore explanations and practical examples that work with models like ChatGPT, Claude, DeepSeek, or Perplexity. Whatever your goal, you’ll find something that fits perfectly. Check them out and start experimenting!

Frameworks

The frameworks presented below were either specifically developed for interactions with LLMs or adapted from other fields of knowledge. Each post explores their foundations and proposes practical steps to help you craft more structured prompts and achieve smarter, more strategic results with AI.

Techniques

Check out some prompt engineering techniques to enhance your interaction with LLMs.

Important: some of the techniques listed below originate from technical studies focused on direct application in language models. In this guide, we aim to explore the context of each technique, understand its principles and lessons, and adapt them for use by end users. In practice, we use this knowledge to improve prompt creation and make AI interactions more accessible, effective, strategic, and intelligent.

What’s the Difference Between Formulas, Frameworks, and Techniques?

Understanding how these approaches differ helps you pick the most appropriate one for each situation:

  • Prompt Formulas: Simple, straightforward, and reusable structures. Perfect for quick tasks like generating lists, explaining concepts, or asking for something specific.
  • Prompt Frameworks: More complete approaches that organize the prompt into multiple blocks: context, intention, role, action, outcome… Ideal for strategic projects, plans, and more elaborate analyses.
  • Prompt Engineering Techniques: Specific strategies to explore the AI’s reasoning or control the output. Examples: Chain-of-Thought, Zero-Shot, ReAct, among others. Great for boosting logic, creativity, or depth.

Each of these categories contributes in its own way to improving interactions with language models — and they can all be creatively combined.

Test, Adapt, Experiment

Every structure presented here — whether it’s a direct formula, a robust framework, or a refined technique — can produce different results depending on the AI model you’re using. That’s why, more than sticking to a fixed formula, the key is to test and tweak based on the context.

Here are a few practical tips:

  • Try the same structure on different LLMs (ChatGPT, Claude, Gemini, etc.) and observe how each interprets your prompt.
  • Adjust tone, detail level, and response style to see which variation gives you the most useful result.
  • Experiment by mixing approaches — for example, apply a formula like RTF inside a technique like Chain-of-Thought, or adapt a framework like ROSES with the narrative focus of the ReAct technique.

💬 Exploration is part of the process. By adapting and blending these strategies, you’ll discover your own style of dialoguing with AI — and unlock increasingly relevant results.

Useful Resources

The field of prompt engineering is constantly evolving — new models, techniques, and discoveries emerge every month. That’s why it’s essential to rely on solid sources and stay up to date.

Here are a few trusted references that support this guide and that you can explore to go deeper:

Fabio Vivas
Fabio Vivas

Daily user and AI enthusiast who gathers in-depth insights from artificial intelligence tools and shares them in a simple and practical way. On fvivas.com, I focus on useful knowledge and straightforward tutorials you can apply right now — no jargon, just what really works. Let's explore AI together?

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