Prompt Encadenamiento

Prompt chaining is a technique in artificial intelligence where a large task is divided into a sequence of simpler prompts. Each prompt addresses a specific part of the task, and the output from one step becomes the input for the next. This approach helps AI handle complex problems by working through them step by step, much like how people solve big challenges by tackling one piece at a time.

For example, instead of asking an AI to write a full report in one go, you might first ask for an outline, then expand each section in separate prompts. This makes the process more manageable and the results more relevant to your needs.

Understanding prompt chaining is important because it helps you get better, more accurate results from AI, especially for tasks that are too complex for a single prompt. It allows for step-by-step refinement, making the AI’s output more useful and tailored to your needs.

To use prompt chaining, start by mapping out the main goal and breaking it into smaller, logical steps. For each step, create a clear prompt for the AI. After the AI responds, review the output and use it as the basis for the next prompt. Continue this process until the final result meets your expectations.

For instance, if you want to generate a marketing plan, you could:

• Ask the AI to list key objectives.
• Use those objectives to prompt for strategies.
• Refine each strategy with follow-up prompts.
  This method allows for more control and refinement compared to a single, lengthy prompt.

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Example:
Suppose you want an AI to create a blog post.

1. First prompt: “Generate an outline for a blog post about eco-friendly travel tips.”
2. Second prompt: “Expand on the first point in the outline with practical advice.”
3. Third prompt: “Write an engaging introduction based on the outline.”
   By chaining these prompts, you guide the AI through each part of the task, resulting in a well-structured and detailed blog post.

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