{"id":83297,"date":"2026-01-22T11:37:13","date_gmt":"2026-01-22T10:37:13","guid":{"rendered":"https:\/\/www.humanlevel.com\/diccionario-marketing-digital\/prompt-engineering"},"modified":"2026-01-22T11:37:13","modified_gmt":"2026-01-22T10:37:13","slug":"prompt-engineering","status":"publish","type":"dicmarketing","link":"https:\/\/www.humanlevel.com\/en\/digital-marketing-dictionary\/prompt-engineering","title":{"rendered":"Prompt Engineering"},"content":{"rendered":"<p><strong>Prompt engineering<\/strong> is the art of communicating effectively with AI models to obtain precise and useful responses. In essence, it is about choosing the right words, context, and format to guide the model&#8217;s behavior toward the result you need.<\/p>\n<p>The way you phrase a question greatly influences the quality of the response. The same query posed in different ways can generate completely different results, demonstrating why it is so important to fine-tune your instructions.<\/p>\n<p>With the rise of language models, a new specialty has emerged: the <strong>prompt engineer<\/strong>. These professionals focus on finding the best ways to interact with AI\u2014not by programming it directly, but by teaching it to better understand what we want from it.<\/p>\n<p>In many projects, the challenge isn&#8217;t whether the AI can generate text, but getting it to generate <em>the right text in the right way<\/em>. A model may have extensive knowledge, but a vague or poorly focused query will produce generic, incomplete, or incorrect answers.<\/p>\n<p>This is where prompt engineering comes into play. With well-designed instructions, you provide the model with the necessary context and guidelines so that its response is useful and aligned with your needs.<\/p>\n<p>For example, asking &#8220;Explain the importance of Paris&#8221; is not the same as specifying: &#8220;Briefly explain the historical importance of Paris, using a formal tone and mentioning its cultural aspects.&#8221; This second version guides the model on what to answer and how to do it, significantly increasing the quality of the result.<\/p>\n<p>As you can see, any change in phrasing can have a major impact on the final outcome.<\/p>\n<p><img class=\"gb-media-d0fbbdce\" title=\"prompt-enigineering\" src=\"https:\/\/www.humanlevel.com\/wp-content\/uploads\/prompt-enigineering.jpg\" alt=\"Prompt engineering\" \/><\/p>\n<h2 class=\"wp-block-heading\"><strong>How to write effective prompts<\/strong><\/h2>\n<p>Although prompt engineering is a complex discipline, there are <strong>fundamental practices<\/strong> you can apply immediately to improve your results with AI.<\/p>\n<h3 class=\"wp-block-heading\"><strong>Clarity and context: the foundation of everything<\/strong><\/h3>\n<p>An effective prompt <strong>minimizes ambiguity<\/strong>. Include relevant details: what information you need, what the focus should be, and who the audience is. The more descriptive your instruction, the better the AI will understand your intent.<\/p>\n<p>For example, instead of &#8220;Summarize the document,&#8221; specify: &#8220;Summarize the conclusions of the following technical document on solar energy in one paragraph.&#8221; If a term can be interpreted in multiple ways, clarify it to avoid misunderstandings.<\/p>\n<h3 class=\"wp-block-heading\"><strong>Define the response format<\/strong><\/h3>\n<p>Explicitly indicate <strong>how you want to receive the information<\/strong>. By default, AI responds in plain text, but if you need a list, a table, code, or JSON, specify it clearly. For example: &#8220;Provide the response as a bulleted list.&#8221;<\/p>\n<p>Defining the format saves time and gives the model a clear presentation guide.<\/p>\n<h3 class=\"wp-block-heading\"><strong>Break down complex tasks<\/strong><\/h3>\n<p>If your request is very broad, <strong>break it down into manageable subtasks<\/strong>. Asking for too much at once often leads to superficial responses.<\/p>\n<p>It is much more effective to maintain a <strong>multi-turn dialogue<\/strong>, where each prompt addresses a specific aspect. For example, first ask &#8220;Generate a list of key features for X,&#8221; then &#8220;Using those features, write an introduction,&#8221; and so on.<\/p>\n<h3 class=\"wp-block-heading\"><strong>Assign a role to the model<\/strong><\/h3>\n<p>Telling the AI <strong>what role it should assume or what tone to use<\/strong> significantly improves the quality of the result. For example: &#8220;Act as an expert SEO consultant and explain&#8230;&#8221; or &#8220;Respond in a professional yet accessible tone&#8230;&#8221;.<\/p>\n<h3 class=\"wp-block-heading\"><strong>Focus on what you DO want<\/strong><\/h3>\n<p><strong>Tell the model what to do<\/strong> instead of just listing prohibitions. Instructions phrased only in the negative can confuse the model.<\/p>\n<p>Instead of &#8220;Don&#8217;t give a short answer,&#8221; indicate &#8220;Provide a detailed response of at least 4 paragraphs.&#8221; The results will be much better.<\/p>\n<h3 class=\"wp-block-heading\"><strong>Iterate and experiment<\/strong><\/h3>\n<p>The first response is rarely perfect, but that&#8217;s normal. <strong>Prompt engineering requires experimentation<\/strong>. If you&#8217;re not satisfied with the result, adjust the question, add more context, and try again.<\/p>\n<p><strong>Continuous iteration<\/strong> is key to refining your prompts and achieving optimal results.<\/p>\n<h3 class=\"wp-block-heading\"><strong>Use examples (few-shot prompting)<\/strong><\/h3>\n<p>Providing the model with <strong>concrete examples of what you expect<\/strong> is extraordinarily effective. AI responds better when it has a model to follow.<\/p>\n<p>If you want a specific headline, include a well-written example before your request. Provide one or two high-quality, relevant examples, but don&#8217;t overdo it\u2014too many examples can confuse the model.<\/p>\n<h3 class=\"wp-block-heading\"><strong>Request step-by-step reasoning<\/strong><\/h3>\n<p>For complex tasks that require logic, <strong>ask the model to reason step-by-step<\/strong>. This technique (chain-of-thought) involves instructing it to show its logical process before reaching the final conclusion.<\/p>\n<p>For example: &#8220;Think through each step before responding&#8221; or &#8220;Explain your reasoning.&#8221; This makes the model pay more attention to breaking down the problem, reducing errors.<\/p>\n<p>Keep in mind that this instruction increases tokens and cost, so use it only when accuracy is critical.<\/p>\n<h3 class=\"wp-block-heading\"><strong>Prevent hallucinations<\/strong><\/h3>\n<p>Even with good prompts, there is a risk that the AI will invent information. To mitigate this, <strong>include instructions on how to handle uncertainty<\/strong>.<\/p>\n<p>For example: &#8220;If any information is unavailable, state that you do not know it instead of making it up.&#8221; This sets boundaries on the model&#8217;s creativity where you need reliability.<\/p>\n<p>For topics requiring up-to-date data, provide the recent context yourself and require the model to limit itself to that evidence.<\/p>\n<h2 class=\"wp-block-heading\"><strong>Advanced formatting techniques<\/strong><\/h2>\n<p>A well-structured prompt gives the AI clear clues on how to respond. Let&#8217;s look at some professional techniques:<\/p>\n<h3 class=\"wp-block-heading\"><strong>Delimiters and clear structure<\/strong><\/h3>\n<p>Use symbols or tags to delimit different parts of the prompt and <strong>avoid confusion<\/strong>. These can be quotes, brackets, or symbols that clearly indicate where each piece of information begins and ends.<\/p>\n<p>For example, if you want to translate a text, isolate it with quotes. You can also divide complex prompts with subheadings like ### Instruction ###, ### Context ###, and ### Question ### to differentiate each section.<\/p>\n<h3 class=\"wp-block-heading\"><strong>Structured prompts (JSON\/XML)<\/strong><\/h3>\n<p>An advanced technique involves providing the request in JSON or XML format instead of natural language. Models have seen a lot of structured code during their training and tend to respect it.<\/p>\n<p>For example, instead of &#8220;Summarize the customer&#8217;s opinion on the shipping,&#8221; you could use:<\/p>\n<pre>{\n   \"task\": \"summarize\",\n   \"topic\": \"customer_opinion\",\n   \"focus\": \"shipping\"\n}<\/pre>\n<p>The main advantage is that it <strong>reduces ambiguity<\/strong> and can force responses into a predictable format, which is especially useful when you need to process the output automatically.<\/p>\n<p>However, writing the prompt in JSON does not guarantee better responses on its own. It primarily adds value when you need structured outputs or format validation.<\/p>\n<h3 class=\"wp-block-heading\"><strong>Emphasis with capitalization<\/strong><\/h3>\n<p>Highlighting important instructions with capitalization can help them stand out. For example: &#8220;You MUST respond only with verified information.&#8221;<\/p>\n<p>Using all caps is useful for separating key elements, but remember that:<\/p>\n<ul class=\"wp-block-list\">\n<li>It does not guarantee absolute obedience<\/li>\n<li>It does not automatically prioritize that instruction over others<\/li>\n<li>On its own, it is not enough<\/li>\n<\/ul>\n<h2 class=\"wp-block-heading\"><strong>Conclusion<\/strong><\/h2>\n<p>Prompt engineering has become an essential skill for making the most of the potential of AI models. Mastering this discipline does not require programming knowledge, but rather developing a strategic mindset on <strong>how to communicate effectively<\/strong> with these systems.<\/p>\n<p>The techniques we have explored\u2014from clarity and context to the use of examples and advanced structuring\u2014are tools that anyone can apply immediately. The key lies in <strong>experimenting, iterating, and learning<\/strong> from each interaction.<\/p>\n<p>As AI models continue to evolve, the ability to formulate effective prompts becomes increasingly valuable. It is not just about getting answers, but about getting <em>the right answers<\/em>, tailored to your specific needs and presented in the most useful way possible.<\/p>\n<p>Remember that prompt engineering is both a science and an art. Apply these fundamental practices, but don&#8217;t be afraid to experiment and develop your own style. With time and practice, you will achieve increasingly precise and valuable results in your interactions with AI.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>What is prompt engineering and how to create effective prompts. Learn key techniques with practical examples&#8230;<\/p>\n","protected":false},"author":54,"featured_media":82983,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"area":[461],"letra":[397],"class_list":["post-83297","dicmarketing","type-dicmarketing","status-publish","format-standard","has-post-thumbnail","hentry","area-ai","letra-p"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.6 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>What is Prompt Engineering? | Human Level<\/title>\n<meta name=\"description\" content=\"What is prompt engineering and how to create effective prompts. 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