Searching for specific prompts for each need is a common practice, but it can result in a significant waste of time. Currently, ways to optimize the use of prompts in ChatGPT and other AI chatbots have been identified through a prompt structure adaptable to any situation. AI chatbots, such as OpenAI's ChatGPT, Google Gemini, Perplexity, or Microsoft Copilot, have become essential tools for millions of users worldwide. Since the arrival of ChatGPT, the search for specific prompts for each task has become common, although not always efficient. An expert has shared the key to creating a universal prompt capable of addressing any query. Success in interacting with a chatbot largely depends on how the request is formulated. An inadequate structure can lead to inaccurate or unsatisfactory responses. Therefore, prompt engineering, which involves designing custom commands to achieve specific results, becomes particularly relevant. However, the abundance of available prompts can make it difficult to find the right one for each case, leading to wasted time and potential errors. The solution lies in understanding the basic principles of prompts and applying a universal structure. Although there are numerous guides and examples online that claim to be the best option, the reality is that there is no perfect prompt for everything. Many popular prompts are well-designed but do not always adapt to specific needs and can limit the quality of responses. To make the most of artificial intelligence, it is essential to provide context, define intent, and offer detailed information. These three pillars allow the chatbot to better understand the request and generate more precise and useful responses, without relying on rigid formulas. Extensive training is not necessary to create good prompts. It is enough to follow a clear structure and practice. It is important to remember that each chatbot has its own limitations and rules, so the same prompt may produce different results depending on the platform. The recommended structure for a universal prompt includes several steps: first, assign a role to the AI, such as an expert in a specific area; second, define the objective of the query; third, provide relevant context; fourth, specify the format of the response (list, table, summary, etc.); and finally, allow for iteration, inviting the AI to request clarifications if necessary before responding. In summary, to create an effective and versatile prompt, it is essential to select the appropriate AI model, clearly define the objective, provide all relevant details, indicate the desired format, and establish limits or restrictions as needed. By following these steps, a universal prompt adaptable to any need can be built, overcoming the reliance on copying and pasting predefined commands. Adopting this structure allows for more precise and personalized responses, and while specific prompts can be useful for concrete tasks, mastering the creation of universal prompts is key to maximizing the potential of artificial intelligence. Source: que.es