Everyone's Obsessed with Prompts. But Prompts Are Step 2.

You probably heard it a thousand times: "The edition is only as good as your request." Most beginners are obsessed with writing the perfect request. They share quick templates, quick formulas and quick technical tips. But here is what I learned after countless hours who worked with AI: we have it backwards. The true truth? Your input request can only be as good as your context. Let me explain. I wrote this for beginners who are involved in quick formulas and templates. I see them everywhere, in forums and for this perfect prompt. But here is the real change in thinking that separates those who fight from those who make AI work for them: it is not about the request. The shift about which nobody talks to experience. They develop a deeper understanding of how these systems actually work. You can see that the leverage is not in the command prompt itself. I mean, you can literally ask AI to write a request for you, "give me a request for X" and one will create one. However, the quality of this input request depends entirely on one thing: the context that you have built up. You see, we do not build any commands. We create a context to create input requests. I recently saw two colleagues from the same company who tackled identical customer proposals. One spent three hours to perfect a detailed command prompt with background, sound instructions and examples. The other guided "draft of the implementation section" in her project. She achieved better results in seconds. The difference? She had 12 context files, customer industry, company methodology, common objections and solutions. Her colleague tried to push all of this into a single request. The prompt was not the leverage. The context was. If I live in the artifact these days, I mainly use terminal -based tools with which I can work directly with files and organize all of my files in my work area. What is important for you is the following: I almost always work in the regular chatt or Claude interface with your features for canvas or artifacts. I live in these persistent documents, not in the back and forth chat. The dialogue is temporary. But the files I create? These are permanent. They think that my thinking has been made real. Every conversation is about perfecting a file that becomes part of my growing context library. The e-mail example: Before and after the old path (promptly focused) You are an administrator who responds to an angry customer complaint. You write: "Write a professional answer to these annoyed customers -e email about a delayed program. Be apologizing, but professional." Result: Generic customer stream that could come from every company. The new way (context -oriented) that you work in a project. Fast explanation: Projects in Chatgpt and Claude are dedicated work areas in which you upload files that the AI ​​remembers throughout her conversation. Gemini called something similar. It is like giving the AI ​​a registration cabinet with information about their specific work. Your project contains: Identity.MD: Your role and communication style Company_info.md: guidelines, values, offers tone_guide.md: How to communicate with different customers, escalation_procedures.md: When and how to do Customer_history.MD: Notes about regular customers Now tell me to react. " The AI ​​knows its specific guidelines, its tone, the history of this customer. The answer is exactly what you would write with perfect memory and infinite time. Your focus should be files, there is no tasks here is the mental shift: stop thinking about input requests. Think about files. Ask yourself: "Which collection of files do I need for this project?" Imagine this: If someone had to do this task for you, what should you know? Every knowledge becomes a file. For a Student Research Project: "Write to me a literature overview of the effects of climate change" → General Academic Academic Writing of your professor after creating project files (assignment requirements, research questions, source summaries, Professor preferences): "Check my sources and help me to connect you." The transformation: from Generia to exactly what your professor wants. The file types that are important through experience to appear: Identity files: Who they are, their goals, restrictions context files: background information, domain knowledge process files: workflows, methods, methods: sound, format presentations, sample examples made decisions and why sample files: What does not work. Rolle, experience, goals, restrictions what_im_doing.md: Project goals, success criteria Context.MD: Essential background information Style_guide.md: How to have things, the next_session.md: What you have achieved, what is the next start here. Each file is a living document, updated as you learn. Why this works: The deeper truth, when you create files, she externalizes her thinking. Each file frees the mental space, becomes a reference point, can be versioned. I never edit files, I create new versions. Approach.md becomes an approach_v2.md approach_v3.md. This is a deliberate methodology. This brilliant idea in V1, which is abandoned in V2? It could be relevant again in V5. The trip is as important as the goal. Files are not a documentation. They are permanently made. Do not only be a better spormpter, but a better file device of experienced users are not only better in writing to commitment requests. You are better in creating context via files. If your context is rich enough, you can use the simplest input requests: "What should I do next?" "Is it good?" "Fix this" the input requests are simple because the context is refined. They no longer push everything into an entry request. They build an environment in which the AI ​​already knows everything they need. The practical reality that I understand why beginners hesitate. This seems to be a lot of work. But here is what actually happens: WEEK 1: Creating files slowly feels about week 2: The reuse of context speeds up things. Week 3: Ki answers are extremely accurate, month 2: You cannot imagine working in a different way, as Mathematics: Project 1 5 Files requires. Project 2 Reuse 2 Plus adds 3 new ones. With project 10 you use 60% of the existing context. With project 20 you work faster 5x because 80% of your context already exist. Each file is an investment. In contrast to requests that disappear, the files are put together. "But what if I only need a quick answer?" Sometimes a simple entry request is sufficient. If you ask about the capital of France or format a date in Python, you do not need context files. The file approach applies to work that is important, projects to which you return, problems that you repeatedly solve, outputs that have to be exactly right. Use simple input requests for simple questions. Use the context for real work. Don't start rethinking today. Create a file: who_i_am.md. Write three sentences about yourself and what you try to do. Then create what_im_doing.md. Describe your current project. Use this with your next AI interaction. See the difference. Before you know it, you have built something powerful: a context environment in which AI is really useful and not just impressive. The real message here first creates its context. Call your files. Create this base of knowledge. Then, yes, absolutely, concentrate on writing the perfect input. But now this perfect prompt has a perfect context with which you can work. Then the magic happens. Context plus command prompt. Not one or the other. Both in the correct order. P.S.S. - I will write an extended version for those who are ready to get deeper into terminal -based workflows. But master that first. Create your files. Create your context. The rest follows, of course. Remember: Each expert was once a beginner who decided to think differently. Your journey from the prompt-focused on context-oriented start begins with her first file.