Artificial intelligence has brought the cost of producing text, images and prototypes close to zero. As a result, companies now generate large volumes of things that would never have made anyone's task list, simply because nobody needed them. The speed gain is real. The question left behind is whether that work should exist at all.<\/p>\n
A consulting firm receives a research assignment. In the past, the deliverable would have been a focused synthesis, as long as the problem required. Today, with a few prompts, the same assignment becomes a document dozens of pages long, because producing volume has become easy and volume still looks like effort.<\/p>\n
On the receiving end, the reader has no time to go through it all. So they ask another AI to summarize it. The cycle closes in a curious way: one machine expands the content, another compresses it, and the decision that motivated the research ends up diluted somewhere in between. The attention cost of the reader has become the most contested resource in the operation. custo de aten\u00e7\u00e3o<\/strong> de quem recebe passou a ser o recurso mais disputado da opera\u00e7\u00e3o.<\/p>\n The second example comes from clients themselves. In the past, anyone arriving with a product idea brought a conceptual summary of what they wanted. Today, many arrive with a rough wireframe, a preview of screens generated with the help of AI.<\/p>\n It looks like progress, and in part it is. Yet to get to that wireframe, the person spent two hours interacting with an assistant, adjusting buttons, colors and copy, barely noticing the time invested. It is worth asking: what level of clarity could that same person reach in two hours spent structuring a brief? Who the user is, what problem they face, what result the business expects. The tool pulls attention toward form before the substance is settled.<\/p>\n Every step taken with AI feels cheap because it is fast. Added together, those steps consume hours across entire teams and generate material that someone has to review, validate or discard. Productivity measured by the number of deliverables goes up, while productivity measured by better decisions may stand still. In large teams the effect multiplies: everyone produces more, and everyone also receives more to read, comment on and approve.<\/p>\n AI amplifies the intent of whoever uses it. When intent is clear, it speeds up the path to results. When intent is vague, it speeds up the production of drafts, versions and variations nobody asked for.<\/p>\n That is why discovery now carries even more weight. In PoC Design, the Action Labs methodology, the Immersion, Ideation and Prioritization phases exist precisely to answer, before any prototype, who will use it, for which decision and with what expected impact. Only then does prototyping come in, with AI as an ally to move faster on what is already known to matter.<\/p>\n A good rule of thumb for any team is to ask, before generating a new document, screen or report: who will use this, and what will change once they do? If the answer is unclear, the best use of AI at that moment may be to help think the problem through.<\/p>\n Artificial intelligence has made production abundant. What remains scarce is clarity about what deserves to be produced. Companies that invest time in understanding the problem before reaching for the tool get the best of both: the speed of AI and the relevance of what gets delivered.<\/p>","protected":false},"excerpt":{"rendered":" AI has reduced the cost of producing text and prototypes. The article explores what companies have started producing unnecessarily and why discovery has become more important.<\/p>","protected":false},"author":1,"featured_media":11437,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":"","two_page_speed":[]},"categories":[1],"tags":[],"acf":[],"yoast_head":"\nTwo hours of prompting instead of a brief<\/h2>\n
Why speed hides the cost<\/h2>\n
Discovery as a filter for what is worth producing<\/h2>\n
Producing less to decide better<\/h2>\n