prompt

The prompt engineering fashion is over. Now what is important is loop engineering

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In the last three years we have seen how if you wanted to be an advanced user of AI, you had to become a prompt engineer: The way you ask the AI ​​things was vital to achieving the best results. That idea is now becoming obsolete, because an even more promising technique is beginning to emerge to make the most of chatbos. From prompts to loops. The new paradigm that has become a viral trend among developers is that of the so-called “loop engineering” (“loop engineering”) that assumes something important: that the AI ​​is going to hallucinate or make mistakes. And with this method a feedback system is implemented: a subagent generates a response, another audits it and looks for errors, and then the system automatically reruns the process until the result meets the quality standards specified by the user. AI Gurus Recommend Loops. Boris Cherny, creator of Claude Code, explained in a recent talk how he no longer writes prompts in Claude Code, but instead writes loops. “Loops do the job. My job is to write loops.” Peter Steinberger, creator of OpenClaw, agreed and commented on X that “you should not write prompts for scheduling agents. You should design loops that create prompts for your agents.” Addy Osmani, head of Google Cloud, exactly stated same idea: “loop engineering is replacing you as the person who creates the prompts for the agent. You design the system that does that instead of you.” Implacable cycle. This type of approach is what has managed to succeed in AI agents such as Claude Code or OpenClaw. The model can run code in a safe environment, test it, read error messages if they exist, and then fix those failures to get back to the beginning. AI already “reasoned”, but now it is capable of self-assessment and self-correction autonomously and independently. Steinberger put a clear example how to design one of these loops. Goodbye to the chat window. The technique is being very popular among developers, but at the same time it poses a potential disappearance of the traditional chatbot in the browser window. The value was previously in chat with AI and experiment with promptsbut now the idea is to propose automated workflows. The user only sees the initial problem and the final solution, there are no constant questions and doubts unless the user wants to refine after that final solution. Be careful with costs. The problem with this idea is that by designing a loop one can launch several subagents that work in parallel. This implies an expenditure of tokens that can be considerable, which threatens to be very expensive. The recommendation, of course, is to use subagents and loops when it makes sense. Another stage in the evolution of AI. The passing of the prompts to loops poses a new phase in the evolution of AI. ChatGPT amazed us by creating quick poems, but the process was inefficient because talking is not always the optimal route to achieve the desired result. The profession of ‘prompt engineer’ could therefore be threatened after that initial phase in which knowing how to talk to the AI ​​was the important thing. Now the powerful thing is knowing how to design those loops that end up doing everything for the user. Image | Compagnons In Xataka | Claude Code is being the big favorite among programmers. So much so that he already signs 4% of everything that is uploaded to GitHub

How to create presentations in Gemini from a document using a single prompt

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Let’s tell you how to create presentations with a single prompt wearing Gemini. This is a function with which you only have to add a document, and then ask the artificial intelligence to make the presentation based on the content of the file you are using. This feature is available to all users, both for free and paid. Of course, the result will always depend on the content of the document, its structure and its quality. The more complete and longer the document, the better the result will be. Create presentations with Gemini The first thing you should do is upload the file you want to use as a reference to create the presentation. You can do this by uploading the file from your computer or mobile, or linking it directly from Google Drive. Now, having the simple document, you have to add a prompt asking you to generate the presentation. You will then send this command along with the attached file. The one you can use is the following: “I am giving you this document. I want you to make a presentation to me with it.” Gemini will now take a few minutes to extract the information from the document, and will generate a presentation with several slides. The images will depend on the ones you have in the document, as well as all the content. Once you have the presentation created, you will have options to export or download it. If you export the document, it will go to your Drive as a Slides document, which is Google’s PowerPoint. And if you download it you will do so in a compatible format. In Xataka Basics | The best prompts to save hours of work and do your tasks with ChatGPT, Gemini, Copilot or other artificial intelligence

Google’s new AI generates interactive worlds from a prompt. Deepmind believes it is a step to get the AGI

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The Google Deepmind team has announced its new AI model to generate interactive worlds. At the end of last year We were surprised with what Genie could do 2 And the new version is an important leap, one that for Google is an advance in the creation of the General Artificial Intelligence or AGIthat which can match the abilities of the best human. Genie 3. It is the new World Model o Deepmind world model. Allows to create interactive worlds for which we can explore, all from a Prompt of text. The previous model was very limited and could only be used for a few seconds, but with Genie 3 Deepmind promises that it can be explored for “several minutes.” In addition, the resolution has improved at 720p to 24FPS. The model is based on Genie 2 and I see 3. It has memory. It is the most important improvement of the new model. The world is generated through ia as we explore it, but if we turn around and look at something we had already seen, it remains the same. We can also change something, such as painting on a wall, and that is kept as we leave it all the time. This did not happen in previous versions and its creators say they did not explicitly schedule it to do that. As explained in an article in TechcrunchGenie 3 is able to remember what he has already generated to train himself, in this way he learns how the world and his physical works. Interactive. It also emphasizes that events can be added with Prompts additional In his article, Deepmind puts several interactive examples such as a meadow in which we can choose if a tractor, a bear, a horse or hot air balloons will appear. They call it “promptable World Events” and also allows you to change aspects such as weather. Why is it important. Worlds models are useful in different scenarios such as the creation of scenarios for real -time games, in education or in the training of AI agents. Google points to it in its blog as a key step to reach the AGI, that upper artificial intelligence that so many companies are trying to get as soon as possible. These worlds can be used as a training field for other AI, also including robots, cases in which simulating real scenarios is a challenge. In the presentation, the Deepmind team explained how they put an agent in a stage that simulated a warehouse and asked him to approach certain elements, such as a green garbage cube. In all the tests he achieved, according to the Deepmind team “the fact that (the agent) is able to achieve this is because Genie 3 remains coherent.” The competition. The largest IA competition, at least at the level of products for the end user, we see it in the chatbots and, to a lesser extent, in video or audio generators. The world models are less popular among the public and there is not a great competition. Nvidia presented cosmos at the beginning of the year And there are some companies like World Labs They offer similar proposals. We would like to finish this text with a link so you can try it, but Genie 3 is only available in Beta for a very limited group of academics. Image | Deepmind In Xataka | Some researchers created a company where all employees were AI agents. They did not make a quarter of the work

If the question is “How to make a good prompt for AI”, Anthropic has just given us his guide

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Anthropic, the creator of Claude, has published its definitive guide of Prompt Engineering. A free Bible that synthesizes years of research in practical techniques to get the most out of Claude. Why is it important. The majority of users barely scratch on the surface of what the generative AI can do, leaving below even what could benefit in their day to day, even if they are not engineering uses. The panoramic. The guide covers from the foundations to the most sophisticated. From how to be clear and direct in a request to advanced techniques such as Multishot Prompting or the chains of thought. Culminates with strategies such as the chain of Prompts complex And all enlightened with real examples of Claude. In detail. The nine central techniques of this guide function as a ladder: Clarity and direction. Say exactly what you want. Prompts Vagos produce vague results. Various examples. It shows Claude how to think with several cases of use. Thought chains. Ask Claude to think step by step before answering. XML Tags. Structure the answers with greater precision. System roles. The classic “You are a lawyer”, “You are a data analyst”, etc. To change the chatbot perspective. Prellenate of answers. Guide the tone and format starting the answer. The context. Anthropic explains that many of the problems with generative AI are solved with better Promptsnot necessarily with more powerful models. This is an attempt to democratize techniques that they only knew somewhat more advanced developers. Open the guts of what they know it works. For example. The guide includes concrete examples: Instead of ‘Create a Dashboard’, he writes ‘creates a complete analytical analytical dashboard with interactive graphics and filters’. For code Frontendadds specific modifiers: “Includes soft transitions, micro -interctions and visual effects that demonstrate advanced web development capabilities.” And for complex tasks, the guide recommends using XML labels as to structure Claude’s thought. The difference is in specificity: say exactly what you want produces much better than vague instructions. The AI ​​returns you what you give. Yes, but. There is an important nuance: this guide assumes that you already have clear success criteria and ways to evaluate results. Without that base, even the best Prompt It is a shot in the air. And now what. For developers, this is gold. For the user something else casual, It is worth dominating at least the first techniques for minimizing hallucinations and improving the results. He Prompt Engineeringthat some time ago it seemed a kind of black magic to invoke in a mystical way, it is every time a skill that can be learned, measured and better perfect. Outstanding image | Xataka with Mockuuuups Studio In Xataka | Chatgpt has been a tool. If you start remembering all our conversations, it will be something else: a relationship

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