{"product_id":"luma-framework","title":"Luma Framework","description":"\u003ch3\u003e\u003cspan\u003e1. Problem Statement\u003c\/span\u003e\u003c\/h3\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eWhen AI is already used in SMM on a regular basis, the need shifts from ideas alone to a stable working system. Without such a system, even strong prompts can lead to materials that differ in style, depth, and tone. A person or a team may have many separate pieces: a prompt library, a topic map, categories, drafts, and editing notes, but these pieces do not always work as one mechanism. Because of this, it can be difficult to explain what the brand tone should be, how to review AI responses, which formats should be used more often, and which ones should remain for separate tasks. Luma Framework was created to help gather all previous elements into a personal working system for AI in SMM.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch3\u003e\u003cspan\u003e2. Solution\u003c\/span\u003e\u003c\/h3\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eLuma Framework shows how to build a system of rules and modules for working with AI in SMM processes. The course explains how to create personal working frames for ideas, categories, content series, short texts, learning explanations, editing, tone review, and material storage. The learner practices not only writing prompts, but also building a repeatable order of actions around them. This helps identify which prompt is needed at a specific stage, how to review the response, and what to do with the material after that. Luma Framework is suitable for learners who want to move from separate tools to a personal method for working with AI in SMM.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch3\u003e\u003cspan\u003e3. What’s Inside\u003c\/span\u003e\u003c\/h3\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eLuma Framework includes modules that help create a personal AI-SMM system for daily or regular work. The first module explains what a framework means in the Nuvrake learning context. It is not a rigid model, but a set of working rules, schemes, and decisions that help keep the process in a readable order. The learner reviews how a random set of prompts differs from a system where every element has its own place.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThe second module focuses on the base of the system. Here the learner shapes the core: brand topic, communication tasks, tone, wording boundaries, material types, repeated task rhythm, response detail level, and criteria for manual editing. This block helps describe not only “what to create,” but also “how the material should sound.”\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThe third module centers on modular SMM process building. The learner creates separate modules for different tasks: idea module, category module, planning module, draft module, editing module, tone review module, and archive module. Each module has its own role and set of AI prompts. Because of this, there is no need to mix all actions into one piece of wording every time.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThe fourth module focuses on rules for AI prompts. It explains how to create a personal rule set: add context, avoid overload, define the response format, describe tone, set boundaries, ask for several options for comparison, and treat the output as a draft that needs review. The module includes examples of weaker and stronger wording so the learner can see the difference between a general request and a thoughtful task.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThe fifth module reviews editorial boundaries. For a brand, it is important to have not only a list of preferred wording, but also a list of what should be avoided. The learner creates a personal editorial note: words that do not fit the brand tone, phrases with too much pressure, overly loud constructions, empty adjectives, extra claims, and vague calls to action. This note helps review AI responses more carefully and avoid moving raw wording into working communication.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThe sixth module focuses on framework use scenarios. For example, the learner reviews a scenario for creating a series of materials: topic choice, task description, category choice, prompt creation, response analysis, editing, and saving the material in the library. Another scenario covers updating an older topic: check whether it still fits the brand, change the angle, create a new structure, remove repetition, and prepare a shorter version for further work.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThe seventh module includes a personal Luma Framework builder. The learner fills in working fields: system name, main tasks, material types, base AI prompts, tone rules, review criteria, archive structure, frequent mistakes, editorial notes, and next actions. As a result, the learner forms not just a selection of materials, but a personal system that can be expanded after completing the course.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eA separate course block focuses on framework review. The learner takes one SMM task and moves it through the full system: from topic to finished draft. At each stage, the learner answers questions: is the task understandable, is there enough context, is the right module chosen, does the text match the tone, is editing needed, and should this prompt be saved in the library. This review helps show where the system works well and where it needs refinement.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eLuma Framework also includes a block about team work. Even when one person is taking the course, these materials help think in a wider way: how to explain personal rules to another writer, editor, or assistant. This block includes examples of short internal instructions that describe tone, the order of working with AI responses, review principles, and material storage format.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch3\u003e\u003cspan\u003e4. Who Is This For?\u003c\/span\u003e\u003c\/h3\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eLuma Framework is for learners who have already moved through the basic stages of AI in SMM and want to create a personal system. It is a fitting choice for SMM specialists, content writers, editors, learning project curators, small teams, and brand owners who want to work with understandable rules rather than disorder.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eThis tier can also be useful for learners who already have many materials and want to connect them into a personal method. Luma Framework helps show how prompts, categories, maps, libraries, and editorial notes can work together. The course does not replace the author’s thinking; it creates a working support structure around it.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch3\u003e\u003cspan\u003e5. What You’ll Learn\u003c\/span\u003e\u003c\/h3\u003e\n\u003cul data-spread=\"false\"\u003e\n\u003cli\u003e\u003cspan\u003eHow to create a personal framework for AI in SMM.\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eHow to build a system from modules, rules, and editorial boundaries.\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eHow to divide the SMM process into separate working stages.\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eHow to create modules for ideas, categories, drafts, and editing.\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eHow to describe brand tone for AI prompts.\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eHow to create a list of wording to avoid.\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eHow to review AI responses by personal criteria.\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eHow to create scenarios for repeated SMM tasks.\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eHow to connect a prompt library with a process map.\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eHow to store materials so they are convenient to revisit.\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eHow to prepare short internal instructions for working with AI.\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eHow to adapt the framework to different topics and learning tasks.\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan\u003eHow to notice weak parts in the system and refine them.\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch3\u003e\u003cspan\u003e6. 30-Day Payment Review Note\u003c\/span\u003e\u003c\/h3\u003e\n\u003cp class=\"isSelectedEnd\"\u003e\u003cspan\u003eLuma Framework includes a 30-day period for payment review requests if the materials do not match the tier description on the page or if technical issues occur when receiving the learning files. The user can contact the Nuvrake team within 30 days after checkout. We review each request separately, compare it with the tier terms, and help find an appropriate resolution. This section is created for transparent communication between the user and the brand without pressure, exaggeration, or loud claims.\u003c\/span\u003e\u003c\/p\u003e","brand":"Nuvrake","offers":[{"title":"Default Title","offer_id":58400592200005,"sku":null,"price":201.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1071\/0276\/5381\/files\/Luma_F.png?v=1782647250","url":"https:\/\/nuvrake.com\/products\/luma-framework","provider":"Nuvrake","version":"1.0","type":"link"}