# Karaza > Become an AI Champion and learn how to create Claude Skills, AI Agents, and automate boring tasks. Public Ghost content for AI and LLM tooling. This file includes a bounded export of public pages first, then recent public posts. Append `.md` to any post or page URL to get the content in Markdown (for example, `/example-post.md`). ## Pages ### About Karaza URL: https://www.karaza.ai/about/ Last updated: 2026-07-19T10:13:25.000Z AI is becoming part of how we think, work, learn, and create. But having access to AI doesn't mean knowing how to use it well. Most people are still figuring things out through trial and error—collecting prompts, testing new tools, and wondering whether they're getting as much value from AI as they should. We aim to help close that gap. Our focus is on AI Fluency: understanding what the tools can do, communicating with them effectively, evaluating their output, and integrating workflows into the way they already work. The goal isn't to turn everyone into an AI expert. It's to give people the confidence, judgment, and practical skills to work effectively in a world where AI is increasingly part of everything we do. --- ## About the founder Hi, I'm Mahmoud A business owner based in the UAE. My educational background is in BCom in Management and a Master's in International Business. Before AI education, I ran a laundromat, launched a podcast, and built a merchandise brand. Every one of those taught me something about building with limited resources. My goal is to help you become AI-fluent so you can turn your ideas into a meaningful body of work. --- ### Proudly supporting independent builders Ghost is the leading platform for independent publishers and writers. Get started for free and set up your very own internet business using [Ghost](https://ghost.org/?ref=karaza.ai), the same platform that powers this website. ### About Karaza URL: https://www.karaza.ai/about-2/ Last updated: 2026-01-12T11:00:50.000Z You're trying to learn AI. You've watched the tutorials, joined the groups, and servers, bookmarked the threads. And still, something isn't clicking. That's because learning AI alone, through a screen, can be overwhelming. ## What if you had an in-person community instead? A space where you show up twice a week with a task. A proposal you need to write. A workflow you want to build. Content you need to create. And you leave with it done. That's Karaza. An in-person AI community in the UAE, Sharjah and Dubai, where professionals who sell their expertise come to actually use these tools, not just learn about them. ## How it works You bring a task. We work through it together using a simple framework: find what matters right now, think through how it applies to your work, then do it before you leave. ## Who this is for If your income depends on what you know (freelancing, consulting, marketing, building) this is your space. ## Join the founding members We're shaping what Karaza becomes right now. No payment required. Just your commitment to show up. [Join →](https://luma.com/karaza?ref=karaza.ai) ### Official Karaza AI Links URL: https://www.karaza.ai/official-karaza-ai-links/ Last updated: 2026-01-15T11:10:40.000Z ****Events Calender** [Karaza · Events CalendarView and subscribe to events from Karaza on Luma. Karaza AI is your local AI club in the UAE. A community where professionals learn and keep up with AI. Workshops, experiments, and the space to give your ideas momentum.![](https://storage.ghost.io/c/9e/ab/9eab2e0e-d29b-47f9-bdba-5daac64e7df1/content/images/icon/apple-touch-icon.png)![](https://storage.ghost.io/c/9e/ab/9eab2e0e-d29b-47f9-bdba-5daac64e7df1/content/images/thumbnail/e383f394-1700-4a18-91e6-59a37f27a661.png)](https://luma.com/karaza?ref=karaza.ai) ****Main Links** Socials 1. [Linkedin](https://www.linkedin.com/company/karaza-ai/?ref=karaza.ai) 2. [X](https://x.com/thekaraza?ref=karaza.ai) Other links 1. [Learn More About Karaza](https://www.karaza.ai/about/) 2. [For LLMS](https://www.karaza.ai/llms.txt) 3. [For Robots.txt](https://www.karaza.ai/robots.txt) 4. [About the Founder](https://www.linkedin.com/in/mahmoudaljuaidi/?ref=karaza.ai) 5. [Main Events Calendar](https://luma.com/karaza?ref=karaza.ai) ## Sign up for Karaza Newsletter A space to give your ideas momentum, with the help of modern AI tools. Subscribe Email sent! Check your inbox to complete your signup. No spam. Unsubscribe anytime. ### Community URL: https://www.karaza.ai/community/ Last updated: 2026-01-12T11:01:22.000Z Looking to join our next event, help shape up the content we focus on. [Register your interest ](https://forms.reform.app/community/ai-operators-pc?ref=karaza.ai) ## Sign up for Karaza A space to give your ideas momentum, with the help of modern AI tools. From the UAE to the world. Subscribe Email sent! Check your inbox to complete your signup. No spam. Unsubscribe anytime. ### Gmail’s 2026 Gemini update URL: https://www.karaza.ai/gmails-2026-gemini-update/ Last updated: 2026-01-12T12:15:54.000Z ## What actually changed in Gmail Google describes this move as Gmail “entering the Gemini era,” where AI steps in to summarize, prioritize, and even act on your messages instead of just displaying them chronologically. According to the official [Gmail is entering the Gemini era](https://blog.google/products-and-platforms/products/gmail/gmail-is-entering-the-gemini-era/?ref=karaza.ai) announcement, the update focuses on reducing the time users spend digging through long threads or searching for old details. When you open a long conversation with dozens of replies, Gmail can now generate a concise AI overview of the key points, letting you catch up in seconds instead of scrolling line by line. This same Gemini-powered intelligence also enhances the way you search your inbox. Rather than typing keywords and scanning results, you can ask natural-language questions like “Who was the plumber who quoted for my bathroom renovation last year?”, and Gemini will reason across your emails to surface a direct answer with the relevant details. In practice, that means less hunting through labels and more immediate, decision-ready information. ## AI Inbox: Gmail as a briefing The most visible shift is the new AI Inbox, a view that restructures your emails into to-dos and topics rather than a simple list. As outlined in Google’s launch materials and early coverage like [Gmail’s Gemini makeover looks absolutely amazing](https://chromeunboxed.com/gmails-gemini-makeover-looks-absolutely-amazing/?ref=karaza.ai), AI Inbox highlights actionable items such as bills, upcoming appointments, and messages waiting for your reply at the top. Below that, it groups related conversations into themes so you can review a project or topic in one place. This AI Inbox is initially being tested with a limited group of “trusted testers” before expanding more widely, and it uses signals like who you correspond with frequently and what kind of content appears in a message to infer importance. Google stresses that this analysis happens with the same privacy protections as existing Gmail features, with data kept under user control and used to prioritise what genuinely matters, such as urgent reminders or time-sensitive tasks. ## Smarter writing with Help Me Write and Suggested Replies On the composition side, Gemini brings a major upgrade to Gmail’s writing tools. Features that previously felt experimental—like AI-assisted drafting—are now moving into the mainstream. Google has made the “Help Me Write” feature broadly available so that anyone can ask Gmail to draft a message from scratch or improve a rough first version, as detailed in the [Gmail is entering the Gemini era](https://blog.google/products-and-platforms/products/gmail/gmail-is-entering-the-gemini-era/?ref=karaza.ai) blog. You can specify the tone you want, from more formal to more casual, and refine the output before sending. Alongside this, the old Smart Reply feature has evolved into more context-aware “Suggested Replies.” These suggestions do more than offer generic “Sounds good” or “Thanks!” responses; they use the context of the thread and your own writing style to propose fuller, more natural replies. Coverage in outlets like [CNBC’s overview of the Gemini features in Gmail](https://www.cnbc.com/2026/01/08/google-adds-gemini-features-to-gmail-message-summaries-proofreading-.html?ref=karaza.ai) notes that this can save time when dealing with routine responses, while still giving you full control to edit before sending. ## Inline AI instead of side panels Another subtle but important change is where these tools live in the Gmail interface. Instead of relying on a separate Gemini side panel, many AI capabilities are now integrated directly into messages and compose windows. Reporting in [Gulf News on the phasing out of the Gemini side panel](https://gulfnews.com/technology/gemini-side-panel-phased-out-as-gmail-rolls-out-in-line-ai-1.500403819?ref=karaza.ai) explains that the goal is to make AI feel like a native part of the email experience. For many users, the “Ask Gemini” option in the side panel is being replaced by inline options such as “Help me write,” “Summarize,” or “Proofread” right where you are working. Proofreading itself is more powerful in this update, with Gemini offering deeper suggestions on spelling, grammar, clarity, and tone. Instead of just catching obvious errors, it can suggest tighter phrasing, adjust formality, and help align your message with your intent, whether you are emailing a client, a manager, or a family member. That makes Gmail feel less like a static text box and more like a live editing partner. ## Rollout, pricing, and what to watch The Gemini update is not arriving everywhere at once, and not every feature is free. As explained in analyses like [Gmail Is Entering the Gemini Era (2026): What’s New, Who Gets It, and Why It Matters](https://www.abzglobal.net/web-development-blog/gmail-is-entering-the-gemini-era-2026-whats-new-who-gets-it-and-why-it-matters?ref=karaza.ai), the rollout starts with English-speaking users in the United States, with other regions and languages to follow. Many core features—such as thread summaries, Help Me Write, and basic Suggested Replies—are available to personal Gmail users at no extra cost. More advanced capabilities, especially those that rely on heavier reasoning or more nuanced stylistic control, are tied to paid AI tiers such as Google’s AI Pro or Ultra subscriptions. Workspace users will see a slightly different path, with enterprise controls and gradual enablement across business accounts. For everyday Gmail users, the key decision over the coming months will be how much AI they want in their inbox: some features are enabled by default, and those who prefer a more traditional experience may need to opt out in settings as they become available. --- *Source Links:* 1. [https://blog.google/products-and-platforms/products/gmail/gmail-is-entering-the-gemini-era/](https://blog.google/products-and-platforms/products/gmail/gmail-is-entering-the-gemini-era/?ref=karaza.ai) 2. [https://www.forbes.com/sites/zakdoffman/2026/01/11/googles-free-offer-for-2-billion-gmail-users-should-you-upgrade/](https://www.forbes.com/sites/zakdoffman/2026/01/11/googles-free-offer-for-2-billion-gmail-users-should-you-upgrade/?ref=karaza.ai) 3. [https://www.wam.ae/en/article/by53m31-new-gmail-features-replacing-gemini-side-panel-for](https://www.wam.ae/en/article/by53m31-new-gmail-features-replacing-gemini-side-panel-for?ref=karaza.ai) 4. [https://www.cnbc.com/2026/01/08/google-adds-gemini-features-to-gmail-message-summaries-proofreading-.html](https://www.cnbc.com/2026/01/08/google-adds-gemini-features-to-gmail-message-summaries-proofreading-.html?ref=karaza.ai) 5. [https://gulfnews.com/technology/gemini-side-panel-phased-out-as-gmail-rolls-out-in-line-ai-1.500403819](https://gulfnews.com/technology/gemini-side-panel-phased-out-as-gmail-rolls-out-in-line-ai-1.500403819?ref=karaza.ai) 6. [https://www.linkedin.com/news/story/google-enhances-gmail-with-ai-8138218/](https://www.linkedin.com/news/story/google-enhances-gmail-with-ai-8138218/?ref=karaza.ai) 7. [https://www.abzglobal.net/web-development-blog/gmail-is-entering-the-gemini-era-2026-whats-new-who-gets-it-and-why-it-matters](https://www.abzglobal.net/web-development-blog/gmail-is-entering-the-gemini-era-2026-whats-new-who-gets-it-and-why-it-matters?ref=karaza.ai) 8. [https://chromeunboxed.com/gmails-gemini-makeover-looks-absolutely-amazing/](https://chromeunboxed.com/gmails-gemini-makeover-looks-absolutely-amazing/?ref=karaza.ai) 9. [https://www.youtube.com/watch?v=mp0KGyzD9DI](https://www.youtube.com/watch?v=mp0KGyzD9DI&ref=karaza.ai) 10. [https://gulfnews.com/technology/media/gmail-overhaul-gemini-ai-turns-your-inbox-into-a-smarter-assistant-1.500402308](https://gulfnews.com/technology/media/gmail-overhaul-gemini-ai-turns-your-inbox-into-a-smarter-assistant-1.500402308?ref=karaza.ai) 11. [https://support.google.com/gemini/thread/396052272/here%E2%80%99s-an-update-on-our-work-to-upgrade-mobile-assistant-devices-to-gemini?hl=en](https://support.google.com/gemini/thread/396052272/here%E2%80%99s-an-update-on-our-work-to-upgrade-mobile-assistant-devices-to-gemini?hl=en&ref=karaza.ai) 12. [https://www.forbes.com/sites/zakdoffman/2026/01/08/google-changes-gmail-after-20-years-2-billion-users-must-now-decide/](https://www.forbes.com/sites/zakdoffman/2026/01/08/google-changes-gmail-after-20-years-2-billion-users-must-now-decide/?ref=karaza.ai) 13. [https://www.linkedin.com/news/story/google-enhances-gmail-with-new-ai-features-8117962/](https://www.linkedin.com/news/story/google-enhances-gmail-with-new-ai-features-8117962/?ref=karaza.ai) 14. [https://www.youtube.com/watch?v=RrHSIC7Sey8](https://www.youtube.com/watch?v=RrHSIC7Sey8&ref=karaza.ai) 15. [https://support.google.com/mail/answer/13952129?hl=en&co=DASHER.\_Family%3DBusiness-Enterprise](https://support.google.com/mail/answer/13952129?hl=en&co=DASHER.%5FFamily%3DBusiness-Enterprise&ref=karaza.ai) ### Turn Questions Into Structured Inputs With One Simple Form URL: https://www.karaza.ai/creating-forms-with-tally-so/ Last updated: 2026-01-15T10:57:24.000Z ## How to create a simple Lead generation form with Tally.so The easiest form builder for every Tally form builder works just like a text document — just start typing on the page to insert blocks. From simple contact forms to complex surveys with conditional logic and calculation, [Tally’s](https://tally.cello.so/25W9JJ0dKQ6?ref=karaza.ai) editor makes building forms intuitive and effortless. At the end of this post, you'll find a full demo on how to create your first form. # Turn Questions Into Structured Inputs With One Simple Form [Tally](https://tally.cello.so/25W9JJ0dKQ6?ref=karaza.ai) # ![](https://storage.ghost.io/c/9e/ab/9eab2e0e-d29b-47f9-bdba-5daac64e7df1/content/images/2026/01/image-cf585f17-f6ea-4d52-b917-2f5d32c3fb0c-2.png) Forms are one of those tools most people use without ever learning properly. Newsletter signups. Event registrations. Feedback requests. Contact forms. They’re everywhere — yet most of them feel confusing, too long, or unnecessary. This guide is **Forms 101**. By the end, you'll be able to create simple forms that work. ## **What is a form?** At its simplest, a form is a structured way to ask questions and collect answers. **Instead of:** - Back-and-forth emails - Lost DMs - Notes spread across apps **A form gives you:** - Clear questions - Consistent responses - Everything in one place Think of a form as **the front door** to your workflow. ## **When should you use a form?** ![](https://storage.ghost.io/c/9e/ab/9eab2e0e-d29b-47f9-bdba-5daac64e7df1/content/images/2026/01/image-da261ef3-1a57-42f2-b2d8-f08db79932c6.png) You don’t need a form for everything. But forms are especially useful when: - You’re asking the **same questions repeatedly** - You want answers in a **consistent format** - You need to **save or reuse responses later** **Common beginner use cases:** - Newsletter signup - Workshop or event registration - Feedback after an event - “Request access” or “Work with me” inquiries If you’re collecting information more than once → use a form. ## **Why start with Tally?** Tally is a good beginner tool because it removes friction: - Easy setup - Clean, text-based editor - Generous free plan - Works well for simple and advanced use cases You don’t need to “learn software” to use it. You just start writing questions. So how does it work? ## **Step 1: Create your first form** When you [open Tally](https://tally.cello.so/25W9JJ0dKQ6?ref=karaza.ai), you’ll see a blank form with a simple editor. ![](https://storage.ghost.io/c/9e/ab/9eab2e0e-d29b-47f9-bdba-5daac64e7df1/content/images/2026/01/image-9ea3ae62-ed10-4396-9d3d-b86d6c056e75.png) Start with three parts: 1. **Introduction** One or two sentences explaining why you’re asking these questions. Example: > “This short form helps me understand what you’re looking for.” 1. **Questions** Ask only what you truly need. 1. **Ending message** Thank people and set expectations. Example: > “Thanks for sharing. I’ll review responses and get back to you.” That’s it. You don’t need anything more to start for your first form. --- ## **Step 2: Choose the right questions** Most beginner forms fail because they ask **too many** or **poorly worded** questions. ### **Simple guidelines:** - Aim for **5–7 questions maximum** - Ask one thing per question - Avoid jargon or unclear language ### **Example (newsletter signup):** - Email address - What are you hoping to learn? - How did you find this? That’s enough. The point is to make the process as frictionless as possible to get the visitor to take action on your form. --- ## **Step 3: Use the right question types** Tally gives you multiple question options. Start simple: - **Short answer** → names, emails, short replies - **Multiple choice** → structured answers - **Long answer** → feedback or context If you’re unsure, default to: - Short answer for logistics - Long answer for opinions Avoid mixing too many types in one form. --- ## **Step 4: Preview before sharing** Before publishing: - Preview your form - Read it as if you’re answering it - Check it on mobile Ask yourself: - Is it clear *why* I’m asking this? - Does anything feel repetitive? - Could someone finish this in under 2 minutes? If yes — you’re ready. --- ## **Step 5: Share or embed your form** Tally lets you: - Share a direct link - Embed it on a website - Use it as a standalone page For beginners, **a link is enough**. Paste it in: - Your website - A link-in-bio - Email newsletters - Event pages Don’t overthink distribution early. --- ## **What happens to responses?** ![](https://storage.ghost.io/c/9e/ab/9eab2e0e-d29b-47f9-bdba-5daac64e7df1/content/images/2026/01/image-4f0a5b93-d3fb-46b2-92df-ab1aca40441c.png) All responses are saved automatically inside Tally. From there, you can: - View them directly - Export them - Send them to other tools later You don’t need integrations on day one. Just start collecting clean data. --- ## **When forms become workflows** ![](https://storage.ghost.io/c/9e/ab/9eab2e0e-d29b-47f9-bdba-5daac64e7df1/content/images/2026/01/Lead-generation-form--1-.gif) Once you’re comfortable, forms can trigger actions: - Send responses to Google Sheets - Notify you in Slack/email - Add emails to a mailing list - Create rows in tools like Notion or Airtable This is where forms stop being “just forms” and become a neat infrastructure to inform decisions. If you add Make automations on top of your forms, then the options are limitless to what you can do with [Tally](https://tally.cello.so/25W9JJ0dKQ6?ref=karaza.ai). You don’t need this immediately — but it’s helpful to know what’s possible. --- ## **Beginner mistakes to avoid** - Starting with “Name” instead of context - Asking everything “just in case” - Writing vague questions - Never testing the form - Over-automating too early Simple forms that get completed are better than advanced forms that get abandoned. --- ## **A good first goal** Your first milestone isn’t building a perfect form. It’s building **one form that replaces friction**: - Fewer messages - Clearer inputs - Better decisions Once that clicks, forms won’t feel boring anymore — they’ll feel useful. --- ## **What’s next?** If this is your first form: - Build one real use-case this week - Share it - Review the responses - Improve one question next time Form responses start to give you better insight over time. The most underrated skill you'll learn is (and this sounds simple enough), is to ask better questions. Start small — and let submissions inform future questions later. ## [Access the full tutorial here. ](https://www.karaza.ai/tally-lead-generation-form-tutorial/) [](https://tally.so/help/create-a-form?ref=karaza.ai#4a0784238bcd42e5aa7c4827314ba0eb) --- If you found this useful, explore how you can use [Claude to build artifacts](https://www.karaza.ai/claude-projects-your-ai-workspace-in-2-minutes/), remix these [10 prompt styles](https://www.karaza.ai/10-claude-prompts-every-professional-should-know/) for your form, or go deeper into [tool stacks here.](https://www.karaza.ai/the-2026-solopreneur-tech-stack-guide-for-digital-product-businesses/) ### URL Generator For LLM Chats in Website Footers URL: https://www.karaza.ai/url-generator-for-llm-chats/ Last updated: 2026-01-20T11:34:47.000Z ## POV: how do I add a request for AI summary of my business in my website footer? I saw this post on X > Spotted in a website footer. > > Every site should have this. [pic.twitter.com/pjvj7uIT7B](https://t.co/pjvj7uIT7B?ref=karaza.ai) > > — Ben Lang (@benln) [January 14, 2026](https://twitter.com/benln/status/2011458564024680957?ref%5Fsrc=twsrc%5Etfw&ref=karaza.ai) So naturally, I was intrigued. 20 mins later I made the below artifact on Claude that easily lets you create a **URL** with a **prompt** that you can **link** with each separate icon, that lets **your website visitor** go to the AI interface of their choice with the prompt you made. > note: Gemini, and X did not work for me and I would assume said platforms have disabled this method of linking. ### Start here Enter your prompt: Important: Add the brand name, and the website domain in the prompt. Generate Links ChatGPT Copy Open Claude Copy Open Perplexity Copy Open Built by [Karaza](https://www.karaza.ai/) [ ](https://linkedin.com/in/mahmoudaljuaidi?ref=karaza.ai "Connect on LinkedIn") This Artifact is made with Claude Opus 4.5, Extended Thinking ## Frequently Asked Questions ### What is this tool for? This tool generates shareable URLs that open AI chatbots (ChatGPT, Claude, or Perplexity) with your prompt already pre-filled. It's useful for businesses that want to add "Ask AI about us" buttons to their websites, letting visitors instantly get AI-generated summaries of their services. ### How does it work? When you enter a prompt, the tool URL-encodes your text and appends it to each AI platform's URL using their `?q=` parameter. When someone clicks the link, the AI chatbot opens with your prompt ready to submit, and the AI will search the web to answer it. ### Why should I include my brand name and domain in the prompt? AI chatbots use web search to answer questions. By including your brand name and website domain (e.g., "Karaza" and "karaza.ai"), you ensure the AI searches for and references your actual website content when generating its response, rather than guessing or providing generic information. ### Where can I use these links? You can add these links anywhere: your website footer, contact page, landing pages, email signatures, QR codes, or social media bios. Some businesses display small AI chatbot icons that link directly to these URLs, letting visitors "Ask AI" about their services with one click. ### Do visitors need an account to use the links? It depends on the platform. ChatGPT and Claude typically require users to sign in or create a free account. Perplexity often works without an account for basic queries. The AI platforms control these requirements, not the generated links. ### Will the AI always give accurate information about my business? AI responses depend on what information is publicly available about your business online. If your website is well-structured with clear information about your services, pricing, and offerings, the AI will have better source material to work with. Keep your website updated and SEO-friendly for best results. ### Is there a character limit for prompts? While there's no strict limit in this tool, very long URLs can cause issues in some browsers or when shared on certain platforms. Keep your prompts concise but specific—usually 2-4 sentences work best. Focus on exactly what you want the AI to explain about your business. ### Can I customize the prompt for different pages on my website? Yes! You can generate different links for different purposes. For example, create one link asking about your services for the homepage, another about pricing for your pricing page, and another about your team for your about page. Each page can have its own tailored AI prompt. ### Is this tool free to use? Yes, this tool is completely free. Generate as many links as you need. The AI platforms themselves may have their own usage limits or premium tiers, but the link generation is unlimited. ### Contact URL: https://www.karaza.ai/contact/ Last updated: 2026-02-22T13:24:01.000Z _No content available._ ## Posts ### How to Build Your First Claude Skill: A Step-by-Step Guide URL: https://www.karaza.ai/how-to-build-your-first-claude-skill-a-step-by-step-guide/ Last updated: 2026-07-25T08:08:38.000Z Building a Claude Skill isn't really a technical job. In practical terms, the file itself is a folder and a short Markdown document. The tricky part of building a skill is judgment: deciding which task deserves to be a skill and describing it so the agent reaches for it at the right moment. So, you probably already have a skill written somewhere in your AI chats. Depending on the task, you might find yourself repeating the instructions frequently, when you could package them once and have AI execute the same guidelines every time. ## Key takeaways - **A skill is task-scoped onboarding**, something that's not a persona or a role, and not knowledge the agent needs on every request. - **SKILL.md requires only two fields to trigger:** `name` and `description`. Everything else is additional and makes the skills more powerful. 💡 Today, you can type in Claude a simple prompt, and it will teach you how to do so: **Prompt: Teach me skills by building one in front of me. Draft a small example now — turning rough notes into a tidy one-page summary — and show exactly what the skill captures: the steps, the format, the rules you’ll follow the same way every time. Then ask which task I actually repeat each week, rewrite the skill for that, and test it with me on one real example before saving it.* - **The description is the trigger.** If it doesn't match the request, the skill never loads (though extended thinking modes and models might reason to search skills anyway) - **Skills come in two shapes:** workflow (a procedure to run) and reference (knowledge to consult). - **Keep SKILL.md short.** Push depth into referenced files that load only when the task requires them, so you can preserve context. - **One skill, one job.** The skills you decide *not* to write matter as much as the ones you do. --- ## What is a Claude Skill, and what tasks should you make one for? A skill teaches an agent something it can't handle from general training alone. Before you write one, the useful question is whether the task is a *sometimes, specific* need, because that's the best kind of task a skill is for. The section below on writing the description explains why that distinction matters. - **A skill is a small folder** named after one task, holding a `SKILL.md` file and any references, scripts, or templates that task needs. - **A skill is not a persona.** "Be a helpful assistant" isn't a skill; skills are scoped to a single job, not a general character. - **A skill is not always-on knowledge.** Anything that must appear in *every* response—brand colors, a default language—belongs in project-level knowledge instead. However, if your main usage with Claude is to generate artifacts such as docs, reports, slides, dashboards, or tools with your branding and design systems, then a SKILL is necessary! It does become more helpful when the knowledge files support or reinforce the skills. - **The retrieval test decides existence.** A skill is surfaced by matching its description to the request. If the two wouldn't cleanly match, the skill will rarely load. - **Good candidates are tasks that repeat:** internal workflows unique to your business, proprietary schemas the agent can't guess, patterns you find yourself correcting frequently. - **Poor candidates waste the format:** things the base model already does well, one-off tasks you'll never repeat, or a group of unrelated tips that should be separate skills. ## How do you write the SKILL.md file correctly? The whole file opens with a short block of YAML frontmatter, and two lines in that block carry most of the weight. Get the naming and the description right and the rest of the file has room to be simple. - **Start with frontmatter.** A few lines of YAML at the top, holding `name` and `description` — the main two required fields. - **Treat the description as the highest-leverage line in the file.** It has one job: say what the skill does *and* when to use it. - **Write triggers, not adjectives.** Include the concrete phrases a user might actually say: "when the user uploads a PDF," "when a request mentions refunds," because those are what the matcher catches. - **Aim for roughly 20 to 300 characters** and name the real nouns of the domain. ## How do you structure the body? After the frontmatter, the body is plain markdown, and you're writing it for a future agent. Short sections, and concrete rules keep the agent on-task. - **Decide what type of skill is it.** A skill either captures a procedure to run (workflow) or knowledge to consult (reference). Many are both, and that's fine, as long as the headings make the direction clear to the agent. - **For a workflow skill, write ordered steps.** Number them, add checkpoints, and keep the sequence explicit: create the record, send the email. - **For a reference skill, write what the agent can't guess:** schemas, naming conventions, approved legal language, the vocabulary specific to your desired output. - **Show, don't just tell.** One short, complete example of the correct output is worth more than a paragraph describing it. ## How do you test your skill and put it to work? Testing a skill means checking two different things: that it *loads* when it should, and that its instructions deliver on its instructions. The output of an agent using different models varies, so a skill that looks right on the page can still misfire in practice, which is why you discern outputs regularly. - **Draft against a checklist:** name follows the regex, description names both what-it-does and when-to-use, the body has a clear "When to use" section. - **Test the description across varied phrasings.** Create a new Project with Haiku as the model and test the triggers in separate chats to see how they trigger. - **Read the skill body for AI slop.** Every instruction should earn its place. - **Run a structural check before shipping.** A rule-based grader or a plain checklist catches the common gaps. - **Treat the first version as a draft.** Ship it, watch it meet real requests, and refine the description and rules from what you see. - **Own the result.** The skill is yours to review and correct. The agent runs it; the judgment behind it stays with you. ## Conclusion The mechanics of a Claude Skill are genuinely small—a folder, a file, and a set of references it can rely on when producing the output. Ultimately, your judgment is everything: deciding what deserves to be a skill, and describing it precisely enough that the agent reaches for it at the right moment. So start where the work already is. Notice the task you keep re-explaining to your AI—the instructions you paste again and again. Write that down as a `name`, a `description`, and a short body, and you've built your first skill. You could also using this prompt to ask Claude to teach you how **Teach me skills by building one in front of me. Draft a small example now — turning rough notes into a tidy one-page summary — and show exactly what the skill captures: the steps, the format, the rules you’ll follow the same way every time. Then ask which task I actually repeat each week, rewrite the skill for that, and test it with me on one real example before saving it.* --- ## Related - For a deeper dive into SKILLS, I recommend reading [https://agentskills.io/home](https://agentskills.io/home?ref=karaza.ai) - [Introduction to Agent Skills](https://claude.com/blog/skills?ref=karaza.ai) - [Claude Skills Course by Anthropic](https://anthropic.skilljar.com/introduction-to-agent-skills?ref=karaza.ai) --- ## FAQ **What exactly is a Claude Skill?** A small folder holding a `SKILL.md` file that teaches an agent how to handle one specific task. It's surfaced when its description matches what you're asking for — think of it as onboarding for a single job, not a plugin or an app. **Do I need to be a developer to write one?** No. A skill is mostly plain writing — a name, a description, and a short set of instructions in markdown. You can ask Claude in Chat to teach you how, or to write one for you using the trigger "skill-creator" **What actually goes in SKILL.md?** YAML frontmatter with two required fields, `name` and `description`, followed by a markdown body. The body holds your rules, steps, or reference material, structured for an agent to read quickly. **How is a skill different from just giving instructions every time?** Instructions you repeat on every request belong in always-on project knowledge. A skill is for expertise the agent needs only *sometimes*, for a *specific* kind of task — loaded when it's relevant, out of the way when it isn't. **Workflow or reference — which do I need?** If the agent needs to *do* a sequence of steps, it's a workflow skill. If it needs to *know* facts, schemas, or vocabulary, it's a reference skill. Some skills are both; clear headings keep the two parts separate. **How do I know if my skill is any good?** Check that the name follows the rules, the description names both what it does and when to use it, and the body carries no filler. Then say your request a few different ways and confirm the skill loads when it should. Refine from there. --- ### What is the 4D Framework for AI Fluency URL: https://www.karaza.ai/what-is-the-4d-framework-for-ai-fluency/ Last updated: 2026-07-19T10:21:06.000Z Most people think getting better at AI means learning to write better prompts. It doesn't. Prompting is one skill inside a much larger competency set — and if you only develop that one skill, you'll hit a ceiling fast. You'll write clever prompts that produce mediocre results because you skipped the thinking that should have happened before and after the prompt. The [4D Framework](https://aifluencyframework.org/?ref=karaza.ai) developed by Prof Rick Dakan (Ringling College of Art and Design) and Prof Joseph Feller (University College Cork), identifies the **four core competencies** that determine how effective someone is with AI: 1. Delegation 2. Description 3. Discernment 4. Diligence Each one addresses a different phase of the human-AI work cycle, and weakness in any single area undermines the others. Here's the framework, what each competency involves, and how to develop all four. --- ## First: What AI Fluency Actually Means Before we get into the competencies, we need to define what we're building toward. AI Fluency is the ability to work with AI systems in ways that are effective (producing quality outcomes), efficient (optimizing time and resources), ethical (maintaining responsible practices), and safe (avoiding harm to yourself and others). Notice that "fast" isn't on the list. Neither is "impressive." AI fluency isn't about generating more output faster. It's about consistently producing work you'd stake your professional reputation on, work that happens to involve AI as part of the process. The [4D Framework](https://ringling.libguides.com/ai/framework?ref=karaza.ai) maps the four competencies required to achieve that standard. --- ## Competency 1: Delegation - Deciding Who Does What The first competency isn't about AI at all. It's about deciding whether AI should be involved in the first place. Delegation means determining what work should be done by humans, what by AI, and how to distribute tasks between them. The critical habit here: answer "What" and "Why" before "Who" and "How." Most people skip straight to opening ChatGPT, Gemini, Claude, or the AI tool of choice. They have a vague sense of needing "help with a presentation" and start typing. The AI-fluent professional stops and asks three questions first. 1. **Problem and Goal Awareness** is the foundation. Before engaging any AI tool, you need clarity on what you're actually trying to accomplish. "Help me with my presentation" is not a goal. "Create a 10-minute investor pitch that explains our Q3 growth trajectory and asks for Series B funding" is a goal. The sharper your objective, the better your delegation decisions. 1. **Platform Awareness** means understanding what different AI tools can and cannot do. A professional who knows that Claude excels at structured analysis but requires clear context to match your brand voice will make different delegation choices than someone who treats every AI tool as interchangeable. Capabilities and limitations vary across tools, across tasks, and across how you configure them. 1. **Task Delegation** is the actual distribution. The principle is straightforward: delegate the repetitive, keep the relationship. AI handles first drafts, data structuring, research synthesis, and pattern recognition exceptionally well. Humans handle nuance, judgment calls, relationship management, and anything requiring taste or contextual sensitivity. The best outcomes come from splitting tasks along these natural lines rather than handing entire jobs to either side. **Here's what this looks like in practice**. A real estate agent in Dubai needs to respond to 30 international buyer inquiries. **Poor delegation:** paste all 30 emails into AI and say "generate a reply to these inquiries, and make them feel personalized." **Strong delegation:** have AI draft responses using your property inventory and past examples of your top-performing reply style, then personally review and adjust each one for the specific buyer relationship. The AI does the heavy lifting on structure and data. You add the judgment that closes deals. --- ## Competency 2: Description - Communicating with AI This is where most AI training starts and stops; aka the "prompting" skill. But within [the 4D Framework](https://ringling.libguides.com/ai/framework?ref=karaza.ai), description is specifically about how you articulate three things: 1. What you want produced. 2. How you want it approached. 3. How the AI should behave during the interaction. These questions form the 3Ps. 1. **Product Description** means defining your output with specificity. Format, audience, style, length, tone. The more precisely you describe the finished product, the closer the first output will be to what you actually need. "Write a professional email for person X that wants to do Y" gives AI almost nothing to work with. "Write a 150-word email to an international property buyer that warmly acknowledges their interest, answers their specific question about payment plans, suggests 2-3 relevant properties from our portfolio, and ends with a clear next step" gives AI everything it needs. 1. **Process Description** guides how the AI approaches the task. This is the difference between getting a generic answer and getting a thoughtful one. You might instruct the AI to analyze a problem from multiple angles before recommending a solution, to consider counterarguments, or to break a complex task into stages. Process description shapes the thinking, not just the output. 1. **Performance Description** defines how the AI should behave during your interaction. Should it ask clarifying questions before starting? Should it be concise or thorough? Should it push back on your assumptions or simply execute? These behavioral parameters matter more than most people realize, especially in longer collaborative sessions. The underlying principle of all three: vague input produces vague output. Always. If you find yourself frustrated with AI responses, the first place to look is at what you actually asked for. In most cases, the problem isn't the AI model or tool itself, it's the description. --- ## Competency 3: Discernment - Evaluating What Comes Back This is the competency that separates professionals from everyone else, and it's the one most people skip entirely. AI produces confident-sounding output regardless of whether that output is accurate, appropriate, or well-reasoned. - A financial summary can be presented with perfect formatting and professional language while containing a calculation error that would cost your client money. - A market analysis can read beautifully while relying on outdated data. Discernment is your ability to catch these problems before they reach anyone else. 1. **Product Discernment** is the most visible layer: assessing accuracy, appropriateness, and coherence. Does the output contain factual errors? Is it suitable for the intended audience? Does it hold together logically from start to finish? This requires you to actually know your subject, because you can't evaluate quality in a domain where you have no expertise. 1. **Process Discernment** goes deeper. It evaluates the reasoning and logical steps behind the output. Did the AI approach the problem sensibly, or did it take shortcuts? If you asked for an analysis, did it actually analyze: weighing evidence, considering alternatives — or did it just organize information into a professional-looking structure? Strong process discernment catches the outputs that look right but were built on flawed logic. 1. **Performance Discernment** evaluates the communication itself. Was the AI's response actually helpful for your workflow? Did its tone match what the situation required? Is its level of detail appropriate, or did it over-explain simple things while glossing over complex ones? This feedback loop of evaluating how the AI performed as a collaborator, is what drives improvement in outputs over time. The core habit to develop: read every AI output as if a competitor wrote it. Skeptically. Don't read it looking for what's right. Read it looking for what might be wrong. If you'd put your name on the output, you need to earn that signature through genuine evaluation. --- ## Competency 4: Diligence - Taking Responsibility for the Final Product The last competency addresses the question most people avoid: now that AI helped create this, who is responsible for it? **You are. Always.** Diligence encompasses the ethical considerations, transparency practices, and accountability structures that surround AI-assisted work. It's the competency that keeps you honest and keeps your work trustworthy over time. 1. **Creation Diligence** means making thoughtful choices about which AI systems you use and how. Not every tool is appropriate for every task. Handling sensitive client data through an AI platform with unclear data policies is a **creation diligence failure**, regardless of how good the output is. Choosing the right tool for the right job (including choosing not to use AI) at all is a professional obligation. 1. **Transparency Diligence** is the honest disclosure of AI's role in your work. This doesn't mean stamping "MADE WITH AI" on everything you produce. It means being straightforward when it matters. If a client asks how you produced a report, you don't hide the AI involvement. If your organization has policies about AI use, you follow them. Transparency builds trust; concealment destroys it. 1. **Deployment Diligence** means taking full responsibility for outputs that reach other people. The fact that AI generated the first draft does not reduce your accountability for the final product. If an AI-assisted email contains an error, that's your error. If an AI-drafted contract has a problematic clause, that's your oversight. Deployment diligence means every output passes through your judgment before it reaches anyone else, and you stand behind it completely. The habit to build here: review and refine your AI systems regularly, not just your individual outputs. **Save prompts** that work well. **Document** the edge cases where AI fails you. **Update your knowledge** bases when information changes. Diligence isn't a one-time checkpoint. It's an **ongoing practice.** --- ## How the Four Competencies Work Together The 4D Framework isn't a sequence you follow once. It's a cycle that repeats with every task. 1. You delegate (deciding what AI should handle) 2. You describe (communicating what you need) 3. You discern (evaluating what comes back) 4. You practice diligence (taking responsibility for the final product). Weakness at any point breaks the chain. - Perfect prompts can't save poor delegation decisions. - Brilliant delegation produces nothing without clear description. - And the most accurate AI output in the world is potentially unethical without discernment and diligence. The framework also maps to three distinct modes of working with AI. ## The 3 Modes of AI 1. In **Automation mode**, you define a task and AI executes it. Think of standardized processes: formatting data, generating routine responses, converting document formats. Delegation and Description carry the heaviest weight here. 1. In **Augmentation mode**, you and AI collaborate as thinking partners with iterative back-and-forth. This is where most professional knowledge work happens: drafting, analyzing, refining, strategizing. All four competencies are active simultaneously. 1. In **Agency mode**, you configure AI to work independently, including interacting with other systems or people. This is the most demanding mode because it requires exceptional **Delegation** (trusting AI with autonomous decisions), **Description** (configuring behavior for scenarios you can't predict), **Discernment** (evaluating outcomes after the fact), and **Diligence** (maintaining accountability for actions you didn't directly control). As AI capabilities grow, more work shifts from Automation toward Agency. Professionals who've developed all four competencies are ready for that shift. Those who only learned to write prompts are not. --- ## Where to Start If you're assessing your own AI fluency, ask yourself four honest questions. 1. Do you think carefully about what to delegate before opening an AI tool, or do you default to asking AI for everything? That's your Delegation competency. 1. Can you describe what you want with enough specificity that the first output is close to usable, or do you spend five rounds of revision getting there? That's your Description competency. 1. Do you critically evaluate every AI output before using it, or do you accept well-formatted responses at face value? That's your Discernment competency. 1. Do you have systems for maintaining quality, transparency, and accountability in your AI-assisted work, or do you handle each task ad hoc? That's your Diligence competency. Wherever your honest answer is weakest: start there. --- *The 4D Framework developed by Prof Rick Dakan (Ringling College of Art and Design) and Prof Joseph Feller (University College Cork), structures AI Fluency as four interdependent competencies: Delegation (deciding what AI should handle), Description (communicating requirements clearly), Discernment (evaluating outputs critically), and Diligence (maintaining ethical responsibility).* **Bonus Resources:** [AI Fluency: Framework & FoundationsLearn to collaborate with AI systems effectively, efficiently, ethically, and safely![](https://storage.ghost.io/c/9e/ab/9eab2e0e-d29b-47f9-bdba-5daac64e7df1/content/images/icon/favicon.1749519148.ico)Anthropic![](https://storage.ghost.io/c/9e/ab/9eab2e0e-d29b-47f9-bdba-5daac64e7df1/content/images/thumbnail/promo-image.1753132690.svg)](https://anthropic.skilljar.com/ai-fluency-framework-foundations?ref=karaza.ai) [LibGuides: Artificial Intelligence at Ringling: Framework for AI FluencyRingling College’s Recommended AI Tools, Press Releases, and Policies Regarding AI and the AI Certificate Program![](https://storage.ghost.io/c/9e/ab/9eab2e0e-d29b-47f9-bdba-5daac64e7df1/content/images/icon/apple-touch-icon-2.png)Ringling College library Remy logo![](https://storage.ghost.io/c/9e/ab/9eab2e0e-d29b-47f9-bdba-5daac64e7df1/content/images/thumbnail/Screenshot_2025-01-14_at_11.07.35_AM.png)](https://ringling.libguides.com/ai/framework?ref=karaza.ai) [AI Fluency Framework | Documentation, papers, presentations, and OER related to the AI Fluency Framework![](https://static.ghost.org/v5.0.0/images/link-icon.svg)Documentation, papers, presentations, and OER related to the AI Fluency FrameworkSkip to primary content![](https://storage.ghost.io/c/9e/ab/9eab2e0e-d29b-47f9-bdba-5daac64e7df1/content/images/thumbnail/4d-1-1024x576.jpg)](https://aifluencyframework.org/?ref=karaza.ai) > [Karaza](https://linkedin.com/company/thekaraza?ref=karaza.ai), [Karaza AI](https://linkedin.com/company/thekaraza?ref=karaza.ai), [Karaza AI Consulting](https://linkedin.com/company/thekaraza?ref=karaza.ai) is founded by [Mahmoud Al Juaidi](https://www.linkedin.com/in/mahmoudaljuaidi/?ref=karaza.ai), Anthropic-Certified AI Fluency Educator based in the UAE. These resources are designed for professionals looking to adapt their AI practices in efficient, effective, and responsible ways. ### Stop Planning. Start Prototyping. URL: https://www.karaza.ai/stop-planning-start-prototyping/ Last updated: 2026-02-20T14:52:29.000Z Planning feels like progress. It has the structure of work, the spreadsheets, the timelines, the strategy documents that accumulate in your Notion workspace while the idea waits. But for most founder-operators, over-planning without building anything testable is just sophisticated procrastination. It's how smart people spend time avoiding the moment when the idea meets reality. There's a better sequence. It doesn't skip thinking, but it changes when the thinking happens. ## The Planning Trap Here's what planning actually does: 1. It optimizes an idea in your head. 2. You take your assumptions and refine them. 3. You take your best guesses and arrange them into a coherent narrative. 4. You stress-test the idea against other ideas: but not against the world. The plan gets cleaner and more persuasive. The idea stays untested. And the cycle could be destructive in the sense that you never truly figure out whether what you're thinking of has merit. When you're a one or two person business, the thing you can't afford to waste is time. A large company can absorb six months of planning that leads nowhere. You cannot. And yet the planning instinct is strong; because planning feels safe. You stay in control of the idea while you plan. The moment you prototype something, reality gets to vote. ## What Happens When You Prototype First Prototyping forces specificity. The moment you try to build even a rough version of an idea — an offer, a product, a workflow — you immediately encounter decisions you hadn't made yet. You find out that the thing you were planning doesn't actually have a clear first step. Or that two parts of the idea conflict with each other. Or that the customer you were imagining wouldn't phrase the problem the way you've been framing it. These are exactly the things that planning would have smoothed over. Planning is good at producing coherent narratives. It's bad at surfacing the gaps inside them. A prototype surfaces the gaps on the first day instead of the last. ## How AI Collapses the Cost of Prototyping The traditional objection to prototyping early is cost. Building even a rough version of something takes time and usually money. Design, development, at minimum a conversation with someone who can challenge your thinking. AI changes this calculation significantly. With Claude, you can take a new idea and do genuinely useful prototype work in a single session. You can draft the offer and ask Claude to identify the objections a real customer would raise. You can describe the product and ask it to play back what you've built, and see immediately if the description holds together. You can write the first version of the sales copy and watch where it falls flat. **None of that replaces talking to real customers.** But it replaces the long planning phase that most founder-operators use as a buffer between having the idea and testing it. **Three hours of planning** typically produces a strategy document. Well organized. Hard to argue with. Untested. **Three hours of AI-assisted prototyping** typically produces a rough offer, a set of real objections, a clearer sense of who the customer is and what they're actually trying to solve, and usually at least one assumption you didn't know you were making. One of those outputs moves you forward. The other makes you feel like you did. ## The Objection Worth Addressing The most common pushback on this is: "I need a plan before I start building anything." This is true: but the plan doesn't need to come first. It needs to come before you commit resources at scale. That's a different threshold. The sequence that works for founder-operators: have the idea, spend thirty minutes on rough thinking, then go straight into a prototype session. Use what you learn from the prototype to inform a lightweight plan. Use the plan to guide the real build. Planning after prototyping is planning informed by evidence. Planning before prototyping is planning based on assumptions. The quality of the plan is better when it comes second. ## Where to Start Your next idea gets thirty minutes of thinking. Then it goes into a Claude session: 1. Describe the idea. 2. Ask Claude to surface the gaps. 3. Ask it to write the one-paragraph pitch and tell you where it's weak. 4. Ask it to articulate the strongest objection a customer would raise and how you'd answer it. That's your prototype. Plan from there. --- *In the next piece: exactly how to run that Claude session — the specific prompts that turn a fuzzy idea into a testable offer.* ### Validate Your Ideas With Thinking Tests URL: https://www.karaza.ai/validate-your-ideas-with-thinking-tests/ Last updated: 2026-02-20T14:46:23.000Z Here's a test worth running on your next business idea: describe it to Claude and ask it to summarize what you said. If the summary sounds like your idea, you're in good shape. If it sounds vague, generic, or subtly off, the problem is most likely that the idea wasn't clear enough in the first place. This is one of the most useful things AI can do for a founder-operator. The ability to reflect ideas back clearly enough that you can see what's actually there. ## The Clarity Problem Most founder-operators carry ideas in their heads that feel complete. You've been thinking about a new offer, a new product angle, a new way of positioning what you do, and in your own mind, it makes total sense. The moment you try to explain it to someone else, the cracks appear. You stumble on a sentence. You catch yourself using words that sound good but don't mean much. You realise the person you're explaining it to isn't getting it, and you're not sure if that's because they're not the right audience or because you haven't got the idea straight yet. That gap between what you understand internally and what you can communicate externally is where most business ideas make it or break it. ## Using AI as a mirror Claude can't tell you whether your idea will sell. It doesn't know your market, your customers, or your specific context well enough to validate anything in that sense. But it can do something arguably more useful at an early stage: it can reframe and restructure the idea back to you in a different way, and you can use that reframe to point out the missing pieces. When you describe an idea to Claude and ask it to play it back, you get an external representation of your thinking, or in other words: what you communicated. And those two things are often different. A sharp reflection means your idea is coherent. A fuzzy reflection means there are gaps you haven't consciously registered yet, assumptions you're making, terms you're using loosely, parts of the offer you haven't actually decided yet. ## How to Run the Test The process is simple: **Step one:** Describe your idea to Claude as if you were explaining it to a friend who doesn't know your industry. Keep it conversational. **Step two:** Ask Claude to summarize back what you described in two to three sentences. Read it carefully. **Step three:** Ask Claude to identify the gaps and assumptions in what you described. What did you not explain? What is it having to assume on your behalf? **Step four:** Look at what it surfaces. Not to outsource your thinking, but to see where your own thinking hasn't landed yet. You don't need to take every gap as a problem to solve immediately. Some gaps are fine to leave open at an early stage. But you should know they're there. ## What a Sharp Reflection Looks Like A clear idea produces a summary that you'd be comfortable sharing. Claude's playback sounds like *your* thinking in words, captures the essence without distorting it, and leaves you feeling like something got understood. A fuzzy idea produces a summary that's technically accurate but somehow hollow. The words are right but the thing feels thin. Or Claude emphasizes something you didn't mean to lead with. Or it asks you clarifying questions that you realize you don't have answers to. Both outcomes are useful. The reflection gives you confidence to move forward. The fuzzy one saves you from committing to an underbaked idea. ## Clarity Is a Prerequisite You can't sell what you can't explain. You can't build what you haven't defined. And you can't refine what you can't see clearly. AI doesn't shortcut the thinking. But it can accelerate the moment when your thinking moves from internal to external, from the idea that lives in your head to the version that has to hold up under scrutiny. That moment used to happen in a conversation with a trusted advisor, mentor, or in the process of writing a business plan, or after you'd already built something and gotten **feedback**. Now you can get there in thirty minutes with a Claude session, before you've committed to anything. The idea isn't real until someone outside your head can describe it back to you accurately. Start there. --- *Next: how to go from a clear idea to a testable offer — using Claude to pressure-test your positioning before anyone sees it.* ### The Prototype Mindset: Why Founder-Operators Should Build Before They Commit URL: https://www.karaza.ai/the-prototype-mindset-why-founder-operators-should-build-before-they-commit/ Last updated: 2026-02-20T14:37:46.000Z Most founder-operators don't fail because they had bad ideas. They fail because they committed to those ideas before testing them. The course that took 3 months to build before anyone told you they didn't need it. The service offer you spent weeks designing a sales page for before realizing the positioning was off. The tool you learned to use obsessively before finding out your clients weren't asking for that outcome. Commitment is the expensive part. And most of us commit too early. ## What Prototyping Means When most people hear "prototype," they think design mockups or working code. That's the tech industry definition. For founder-operators: people running one to five person businesses without a product team or a runway, prototyping means something different. It means making your thinking visible fast enough to test it before you've invested real time and energy into it. A prototype isn't a finished product. It's a rough, external version of an idea that you can look at, poke at, and get a reaction to. It's the difference between carrying an idea in your head (where it always sounds good) and putting it out in the world where reality can push back. Prototyping is a thinking discipline, not a technical skill. ## Why Commitment Is So Expensive Here's what commitment actually costs a founder-operator: You commit to an idea, which means you stop exploring alternatives. You start building, which means you start spending time. You tell people about it, which means your identity gets attached. By the time you find out the idea needed a different shape, you've got sunk cost, lost time, and a small amount of ego wrapped up in something that isn't working. None of that is fatal to your work. But it eventually compounds. Especially when you're a one or two person operation where every week matters. The antidote isn't better planning. Planning optimizes an idea in your head. It doesn't tell you whether the idea holds up when it meets the world. ## How AI Changed the Equation Prototyping used to require resources. You needed a designer to mock something up, a developer to build a rough version, or a team to run a workshop and map out the concept. Time, money, or both. AI collapses that cost dramatically. Using a tool like Claude, you can take a fuzzy idea and do something useful with it inside thirty minutes. You can ask it to play back what you've described and identify what's missing. You can ask it to articulate the offer as if it were writing a sales page, and see immediately whether the idea is coherent. You can ask it to surface the obvious objections a customer would raise, and watch which ones you have good answers to. None of that is the same as real market validation. But it's a genuine thinking tool, one that's available to a solo founder in a way it never was before. ## The Mindset Shift The prototype mindset asks one question before committing to anything: *what's the cheapest way I can test whether this holds up?* Not cheapest in terms of corners cut. Cheapest in terms of time and energy spent before you get useful signal back. For founder-operators, that usually means: 1. Before you build it, describe it. 2. Before you describe it publicly, describe it to Claude. 3. Use the AI session to find the gaps, sharpen the language, and stress-test the logic, before any of that work happens in the open. Building before committing isn't about being uncertain. It's about being smart with your energy. The people who build the right things are simply able to test faster. --- *Ready to run a prototype session on your next offer? The next piece walks you through exactly how to do it with Claude in one sitting.* ### Map Your Business in 60 Minutes URL: https://www.karaza.ai/map-your-business-in-60-minutes/ Last updated: 2026-07-31T10:32:30.000Z **Time:** 60 minutes **Tool:** Any document tool (Notion, Google Docs) ## How to Use This Guide - Follow the four layers in order: each one builds context for the next - Fill in each layer as you go. Reading without doing won't help - "What you should see" after each step tells you if you're on track - Save your finished map: it becomes the foundation for every AI tool you use --- **Common practice:** You open an AI tool, type a question, and get a response that could apply to any business on earth. So you try tweaking the prompt. You add more detail. You paste in random context. Sometimes it works. Mostly, you waste 20 minutes getting output you could've written faster yourself. The root problem isn't your prompting. It's that the AI knows nothing about your business. Imagine handing any AI tool a structured map of your business which includes: your role, your projects, your team, your operations, and the output sounds like it came from someone who actually works with you and is part of your team. Customer emails match your voice. SOPs reflect how your team operates. Proposals reference your services. This tutorial walks you through **Context OS** \- a 4-layer system for organizing everything AI needs to know about your business. **You'll build one layer at a time:** 1. Personal 2. Project 3. Team 4. Business. By the end, you'll have a single reference document that makes every AI interaction sharper. --- ## Core Concepts **Context OS** is a way to organize your business knowledge into four layers, from individual to organizational. Think of it like an onboarding manual, except the new hire is an AI tool. **The four layers:** 🎯 ****Personal:** Your role, expertise, communication style 💼 ****Project**: Active work, goals, timelines, deliverables 🤝 ****Team**: Who does what, how you collaborate, decision rights 🏦 ****Business**: Services, audience, brand voice, operations Each layer feeds the next. - Personal context shapes project context - Project context shapes team context - All of it rolls up into business context. --- ## Step-by-Step Walkthrough ### Step 1: The Personal Layer This is the foundation. AI needs to know who it's helping before it can help well. **What to do:** Open a blank document and create a section called **"Personal Context."** Answer these questions in 2-3 sentences each: 1. **What's your role?** In addition to your job title, what you spend your time doing at work. 2. **What's your expertise?** The domains where you make judgment calls confidently. 3. **How do you communicate?** Direct or diplomatic? Formal or conversational? Give an example. 4. **What are your current priorities?** The 2-3 things that matter most this month. 5. **What do you struggle with?** The tasks that drain your energy or take too long. **What you should see:** A half-page document that reads like a briefing note. If someone read it, they'd know how to work with you: what to bring you, how to frame it, and what to avoid. --- ### Step 2: The Project Layer Projects are where AI delivers the most immediate value, but only if it knows what you're working on and why. **What to do:** Add a section called "Active Projects." For each of your current projects (start with the top 3), capture: 1. **Project name and one-line goal:** What does "done" look like? 2. **Current phase:** Are you planning, executing, or wrapping up? 3. **Key deliverables:** What are you producing? 4. **Stakeholders:** Who cares about this project and what do they need from you? 5. **Constraints:** Budget, timeline, tools, or dependencies that shape decisions Keep each project to 5-8 sentences total. You're capturing important context. **What you should see:** A section where each project has a clear goal, a sense of where things stand, and enough detail that an AI tool could draft a status update or suggest next steps without asking you repeating clarifying questions. --- ### Step 3: The Team Layer Even if you're a solo operator, you have collaborators that include: freelancers, clients, vendors, partners. AI needs to know the cast of characters. **What to do:** Add a section called "Team Context." Document: 1. **Who's on the team?** Name, role, and what they're responsible for (2-3 sentences each) 2. **How do you collaborate?** Weekly meetings? Async messages? Shared docs? What's the rhythm? 3. **Decision rights:** Who approves what? Where do bottlenecks happen? 4. **Communication norms:** Is your team formal or casual? What channels do you use? For solo operators: document your key client relationships and any contractors or tools that function as "team members." **What you should see:** Someone reading this section could draft a message to any team member in the right tone, assign the right task to the right person, and know who to loop in on decisions. --- ### Step 4: The Business Layer This is the big picture thinking, and the context that shapes everything else. **What to do:** Add a section called "Business Context." Cover: 1. **What do you sell?** Services or products, described the way you'd explain them to a friend/colleagues. 2. **Who do you serve?** Your actual customers, with enough detail to picture them. 3. **Brand voice:** How does your business sound? Paste 2-3 examples of real communications (emails, social posts, proposals) that represent your voice. 4. **Key processes:** The 3-5 workflows that keep your business running (sales, delivery, support, etc.) described in plain language. 5. **What makes you different?** Why do customers choose you over alternatives? **What you should see:** A section that could serve as a briefing doc for a new business partner. They'd understand what you do, who you do it for, how you sound, and how you operate — in under 5 minutes. --- ### Step 5: The Full Map The real utility isn't in any single layer, it's in how they relate to each other. **What to do:** Review your complete document and add a short "Connections" section at the top. Note: 1. How your personal priorities connect to active projects 2. Which team members are involved in which projects 3. Which business processes each project touches 4. Any gaps between the layers where you wrote very little or felt unsure These gaps are your highest-leverage areas for improvement. Mark them. **What you should see:** A 2-3 page document with four clear layers plus a connections summary at the top. It reads like a comprehensive briefing. Although not perfect and polished, it should be complete enough that handing it to any AI tool would immediately improve the output you get. --- ## A short demo **Scenario:** Marcus is a solo consultant with 12 active clients. He spends his days writing proposals, managing deliverables, and fielding client requests. He's tried using AI for proposal drafts, but the output always sounds generic. **The poor approach:** Marcus opens Claude and types: "Help me write a proposal for a new consulting engagement." He gets a perfectly structured, utterly forgettable proposal that could belong to any consultant in any industry. **The Context OS approach:** Marcus spends 60 minutes mapping his business: ****Personal**: I'm a supply chain consultant. I communicate directly, and clients hire me because I don't sugarcoat. My priority this month is closing 2 new engagements while delivering the Al-Futtaim project. ****Project**: For his top 3 clients: project goals, current phase, what's due this week, key contacts ****Team**: His VA handles scheduling and first-draft research. His accountant handles invoicing. He makes all client-facing decisions. ****Business**: I serve mid-market logistics companies in the GCC. My engagements are 6-12 weeks. I differentiate on speed: I audit in week 1 and recommend by week 2\. My proposals are blunt and numbers-heavy, not polished and vague." Plus 2 real proposal excerpts. Now when Marcus asks Claude to draft a proposal, he pastes his business map as context. The output matches his voice, references his methodology, and emulates his methodology. **The result:** Marcus went from spending 45 minutes editing AI drafts to spending 10 minutes refining them. The 60-minute mapping investment pays for itself within a week. --- ## Common Issues & Fixes #### ****I don't know what to write for brand voice.** Don't describe it: show it. Go to your sent emails or social posts. Find 3 messages that sound most like "you" and paste them in. AI learns more from examples than descriptions. #### ****My business is too simple for four layers.** If you have customers and do work, you have four layers. A bakery owner with 3 staff still has personal context (their role), projects (catering orders, new menu items), team dynamics, and business operations. Simple businesses still benefit from structured context. #### ****I got stuck on the Team layer because I work alone.** You're not truly solo. Document your clients (they're collaborators), your tools (they have capabilities and limits), and your contractors or vendors. If you outsource bookkeeping, that's team context. #### ****This feels like a lot of writing for something I already know.** You know it. The AI doesn't. This exercise ****externalizes the knowledge** that lives in your head/digital folders so AI tools can access it. The writing is for every AI interaction you'll have from now on. --- ## **What you now know:** You can organize any business — including yours — into 4 structured layers that give AI tools the context they need to produce relevant, specific output. This map is a foundation that makes every other AI implementation more effective. **Test it now:** > Take your completed map and paste it into any AI tool as context. Ask it to draft a client email or a social post for your business. Compare the output to what you'd get without the map. The difference should be immediate and obvious. **Next step:** Your map is a first draft. In the next tutorial we will discuss how to *Write Your First AI Instructions Page,* which shows you how to turn this raw map into a structured instructions document that any AI tool can use consistently. **Your Challenge:** Share your business map with a colleague or friend and ask: "Does this sound like my business?" If they say yes, your context is strong. If they're confused, the gaps they identify are exactly what you need to fix. --- ## Definitions #### Context OS A 4-layer system for organizing business knowledge (Personal, Project, Team, Business) so AI tools can access it. Developed by Karaza AI. #### CIK Framework Context, Instructions, Knowledge: three elements that shape every effective AI interaction. #### Business Map The document you create in this tutorial. A structured reference that captures your business across all four Context OS layers. --- ## Struggling to put together your map? Use the below AI prompt in ChatGPT/Claude and it will interview you to develop your own Context map Copy/paste the below prompt ### The Prompt You are a Context OS Architect, a senior business consultant trained in the Context OS methodology developed by Karaza AI. Your job is to interview me and build my complete Business Map: a structured document covering four layers (Personal, Project, Team, Business) that I can use as persistent context with any AI tool. ## YOUR APPROACH You are warm, direct, and efficient. You ask one focused question at a time. You never dump a list of 10 questions — that overwhelms people and produces shallow answers. Instead, you conduct a real conversation: ask, listen, dig deeper where it matters, then move on. You think like a consultant. When I give you a surface-level answer, you probe. When I give you a rich answer, you extract what matters and keep moving. You notice gaps I don't see and flag them without being annoying about it. ## THE INTERVIEW STRUCTURE Run this interview in five phases. At the start, briefly explain what we're doing and why it matters (2-3 sentences max). Then move through each phase: ### Phase 1: Personal Layer Goal: Capture who I am professionally — so AI writes *as* me, not *for* me. Extract these components through natural conversation (do NOT present this as a checklist): - **Professional Identity:** My actual role and what I spend my time doing (not my job title) - **Expertise & Domain:** Where I make confident judgment calls - **Communication Style:** How I sound (direct/diplomatic, formal/casual, use of analogies, jargon tolerance). Ask me to share a real example — a message I've sent that sounds like "me" - **Values & Principles:** What I stand for, how I make decisions when trade-offs arise - **Current Priorities:** The 2-3 things that matter most this month - **Working Preferences:** How I like to receive information (bullets vs prose, detail level, format preferences) - **Energy Drains:** Tasks that take too long or drain my energy After this phase, show me a draft of my Personal Context section and ask me to confirm or correct it before moving on. ### Phase 2: Project Layer Goal: Map my active work so AI can be a useful collaborator on real initiatives. Start by asking how many active projects or workstreams I'm managing. Then for the top 3 (or fewer if that's all there are), extract: - **Project name + one-line goal:** What does "done" look like? - **Current phase:** Planning, executing, or wrapping up? - **Key deliverables:** What am I actually producing? - **Stakeholders:** Who cares about this and what do they need from me? - **Constraints:** Budget, timeline, tools, dependencies that shape decisions - **Blockers or friction:** Where things are stuck or slow Keep each project to 5-8 sentences. We're capturing context, not writing a project plan. After this phase, show me a draft of my Project Context section and ask me to confirm or correct. ### Phase 3: Team Layer (≈10 minutes) Goal: Map the people I work with so AI can draft communications, assign context to the right person, and understand decision flows. **Important:** If I'm a solo operator, don't skip this layer. Reframe it: my clients, contractors, vendors, and tools all function as "team members." Probe for those. Extract: - **Cast of characters** — Name, role, what they're responsible for (2-3 sentences each) - **Collaboration rhythm** — How we work together (meetings, async, shared docs) - **Decision rights** — Who approves what? Where do bottlenecks happen? - **Communication norms** — Formal vs casual? What channels? What's the unwritten rules? - **Shared terminology** — Any internal language, acronyms, or shorthand that outsiders wouldn't know After this phase, show me a draft of my Team Context section and ask me to confirm or correct. ### Phase 4: Business Layer (≈15 minutes) Goal: Capture the institutional knowledge that lives in my head — so AI can represent my business accurately. This is the deepest layer. Take your time here. Extract: - **What I sell** — Services or products, described the way I'd explain them to a friend (not marketing copy) - **Who I serve** — My actual customers, with enough detail to picture them - **Brand voice** — How my business sounds. Ask me to paste 2-3 real examples (emails, social posts, proposals) that represent my voice. If I can't, help me articulate it through comparison ("more like X or Y?") - **Key processes** — The 3-5 workflows that keep my business running (sales, delivery, support, etc.) in plain language - **What makes me different** — The honest version. Why do customers choose me over alternatives? - **Pricing logic** — Not just prices, but why they're set that way (if comfortable sharing) - **Common questions & objections** — What customers always ask and how I answer - **What would break if I disappeared for a month** — The knowledge that only I hold After this phase, show me a draft of my Business Context section and ask me to confirm or correct. ### Phase 5: Connections & Assembly (≈10 minutes) Goal: Tie the layers together and produce the final document. Review all four layers and surface: - How my personal priorities connect to active projects - Which team members are involved in which projects - Which business processes each project touches - **Gaps** — Layers where I gave thin answers or seemed uncertain. Flag these honestly as "areas to develop" rather than glossing over them Then assemble the complete Context OS Map as a single, clean document with this structure: --- # \[My Name\]'s Context OS Map *Generated \[Date\] — Living document, update quarterly* ## Connections Summary \[2-3 sentences linking the layers + flagged gaps\] ## Layer 1: Personal Context \[Formatted content from Phase 1\] ## Layer 2: Project Context \[Formatted content from Phase 2\] ## Layer 3: Team Context \[Formatted content from Phase 3\] ## Layer 4: Business Context \[Formatted content from Phase 4\] ## Appendix: Voice Examples \[Any real writing samples I shared during the interview\] ## Gaps & Next Steps \[Areas flagged for development + suggestion to revisit in 30 days\] --- ## INTERVIEW RULES 1. **One question at a time.** Never list multiple questions in a single message. 2. **Follow the energy.** If I'm giving rich, detailed answers on a topic, go deeper. If I'm giving one-word answers, don't force it — note the gap and move on. 3. **Use my own words.** When you draft each section, use my actual language wherever possible. Don't sanitize my voice into consultant-speak. 4. **Show, don't describe.** When asking about communication style or brand voice, always ask for real examples. Descriptions of voice are unreliable — samples are gold. 5. **Name the layer.** At each transition, briefly tell me which layer we're moving to and why it matters (one sentence). 6. **Flag what's missing.** If I skip something important, note it gently: "I noticed we didn't cover X — worth capturing now, or flag it for later?" 7. **Keep it moving.** The whole interview should take 45-60 minutes of my time. Don't let any single question turn into a 15-minute tangent unless I'm clearly finding it valuable. 8. **No jargon dumps.** Don't explain the CIK Framework, hermeneutic circles, or methodology theory. Just run the interview. The methodology is invisible — the output speaks for itself. 9. **Be honest about thin spots.** If a section feels underdeveloped, say so in the final document. "This section would benefit from..." is more useful than pretending it's complete. 10. **End with a test.** After delivering the final map, suggest I paste it into a new conversation and ask AI to draft something specific (a client email, a social post, a proposal intro). The before/after difference is the proof. ## BEGIN Start the interview now. Introduce yourself briefly (2 sentences max), explain what we're building and why it matters (2-3 sentences), then ask your first question. --- What do you think of the Context mapping approach for your business? Comment below 👇 ### Friction Debt: Why Most Creators Stall Before They Start URL: https://www.karaza.ai/friction-debt-creator-stack/ Last updated: 2026-07-18T09:10:31.000Z Every January, the same advice floods the internet: pick your niche, be consistent, build your personal brand. It's not wrong. But it ignores context entirely and ends up useless. I've watched a lot of people try to "become creators" over the past few years. The ones who stalled didn't lack ideas or talent. They stalled in **decision-fatigue**. Which platform? What format? How do I even publish this thing? The creator economy crossed [$200 billion recently](https://www.snsinsider.com/reports/creator-economy-market-8072?ref=karaza.ai). There's never been more opportunity, or more garbage. And the garbage isn't just bad content. It's the overwhelming noise of options, tools, and strategies that bury new creators before they publish a single piece. Here's what I've learned: the creators who ship consistently aren't more disciplined than everyone else. They've engineered lower resistance. They removed friction from their process until publishing became **the path of least resistance.** Removing friction enables momentum. And momentum is what you need to start from zero today. --- ## How Friction Compounds Most people think of friction as inconvenience. A small annoyance. Something you push through with enough motivation. That's not how friction actually works. Friction compounds. Each small decision you haven't made sits in working memory, creating cognitive load that makes the next decision harder. So you're not only facing one obstacle, you're facing a stack of them, and they multiply rather than add. Psychologist [Barry Schwartz](https://en.wikipedia.org/wiki/Barry%5FSchwartz%5F%28psychologist%29?ref=karaza.ai) documented this in his research on [the paradox of choice](https://www.amazon.com/Paradox-Choice-Why-More-Less/dp/0060005688?ref=karaza.ai). More options don't create freedom. They create paralysis. When faced with too many possibilities, people either choose poorly, choose nothing, or choose and immediately regret it. The mental energy spent evaluating options depletes the energy available for action. Now map this to the creator journey. Before you write a single word, you face a sequence of unmade decisions. ### Platform choice: Should I start a blog? A newsletter? Post on social media? All three? Each option has advocates swearing it's the only path that works. ### Tool selection: If a blog, which platform? WordPress? Ghost? Webflow? Squarespace? If a newsletter, Substack or Beehiiv or ConvertKit? Each tool has tradeoffs you'd need to research to understand. ### Format decision: Long-form or short-form? Written or video? Polished or raw? The "right" answer depends on factors you can't know until you've already started. ### Publishing logistics: Once you've written something, how do you actually get it live? Where does it go? How do you make it look decent? Four unmade decisions. But they don't add to 4x friction. They multiply. You're carrying all four in your head while trying to write your first sentence. The weight of the unmade choices presses down on the work itself. I call this: ### Friction Debt. Like [technical debt](https://agilealliance.org/introduction-to-the-technical-debt-concept/?ref=karaza.ai) in software; where shortcuts today create compounding problems tomorrow – friction debt accumulates interest. The longer decisions stay unmade, the heavier they feel. The more you research, the more options you discover, and the more the debt grows. Eventually, the backlog becomes so daunting that abandoning the whole project feels easier than facing it. This is why so many creator journeys end before they begin. As a result of friction debt that was never acknowledged, never audited, and never paid down. --- ## Why "Just Start" Fails The standard advice for new creators is simple: **just start.** It sounds empowering. Stop overthinking. Stop planning. Take action. But this advice assumes a clear starting line. It assumes you know where to stand, which direction to face, and that someone has already fired the gun. For most new creators, none of that is true. ### Creator mediums in 2026 - You could write a blog. - Or a newsletter. - Or post threads on X. - Or write an X Article, like this one. - Or make TikToks. - Or try live shopping. - Or start a podcast. - Or do all of them and "repurpose." Each platform has its own rules. Each format has its own learning curve. And every guru has a different opinion on which one matters most. "Just start" becomes "just decide everything first, then start." The starting line itself requires fifteen preliminary decisions. You can't take action until you've resolved them, but resolving them feels like its own massive project. The guru advice **compounds the problem**. Every creator educator has a different stack recommendation, a different "best platform for 2026," a different content strategy that definitely works. Consuming this advice doesn't reduce friction – it adds options. More options means more friction. You finish a YouTube video about the best newsletter platforms and you're further from publishing than when you started. So what happens? You spend 3 weeks researching platforms. You set up accounts on 4 of them. You publish once, get minimal response, and quietly abandon the whole thing by February. A predictable outcome of high-friction systems. You burned your motivation on decisions, not creation. By the time you sat down to write, you had nothing left. The creators who make it past this phase had less to **decide**. --- ## The Friction Audit Before I tell you what tools to use, I want to give you a way to diagnose your own friction. ### The 3 Friction Audit Questions **1): Where did you last stop?** The point where you stalled reveals the friction type. If you stalled before writing anything, you have ideation friction – too many possibilities, no clear angle. If you stalled with a draft sitting in a Google Doc, you have publishing friction – the logistics of getting it live felt like a separate project. If you stalled after publishing once or twice, you have distribution friction – the work went out but nothing came back, and the silence killed your momentum. Each friction type has different solutions. Knowing which one stopped you matters more than generic advice about consistency. **2): What decision are you avoiding?** There's usually one unmade choice blocking everything downstream. Maybe you haven't committed to a platform. Maybe you haven't decided whether you're building a personal brand or a company presence. Maybe you haven't chosen a format. Name the decision. Avoiding it only makes it grow. **3): What would you need to publish something in 20 minutes?** It doesn't have to be perfect. An idea you've been thinking about, turned into a published piece, in twenty minutes or less. The gap between your current setup and that answer is = friction debt. If the answer is "I'd need to figure out where to post it, how to format it, whether to include images, how to make it not look terrible..." then your friction debt is **high.** If the answer is "I'd open my editor and start typing," your friction debt is **low.** This reframes the problem, and instead of thinking you lack discipline or focus, you realize it's: a **systems problem**, and systems problems have systems solutions. --- ## The Minimum Viable Creator Stack With your friction diagnosed, here's the stack I'd recommend for starting from scratch. 3 layers. Each one chosen specifically because it eliminates decisions rather than adding them. ### Layer 1: A home you own ([Ghost](https://ghost.io/?ref=karaza.ai)) Before you post anywhere, you need a place that belongs to you. Social profiles are rented real estate. Eventually, you'll want to own. [Ghost](https://ghost.io/?ref=karaza.ai) is where I'd start. It's an independent publishing platform – open source, built specifically for **creators** and **writers**. You can run a **blog**, a **newsletter**, or **both** from the same place. The free tier lets you publish and send emails without paying anything until you're ready to grow. Why this matters for friction: **Ghost removes 3 decisions at once.** 1. You don't need to choose between a blog platform and an email platform – it's both. 2. You don't need to evaluate landing page builders – Ghost pages work fine. 3. You don't need to figure out how your pieces will look – the default themes are clean enough to start. I can't remember how much time I've spent evaluating "landing page" builders, "funnel" makers, and no-code website tools. For one reason or another, I kept coming back to Ghost because it's simple. The editor is intuitive, almost like a focus mode. Any page you create feels clean by default. And emails are built in, which means one less integration to configure. Setup takes about 15 minutes. 1. Pick a subdomain 2. Choose a theme 3. You have a live publication. One decision, made once, and publishing friction drops dramatically. ### Layer 2: A way to capture interest ([Tally](https://tally.cello.so/25W9JJ0dKQ6?ref=karaza.ai)) Once you're publishing, you need a way to turn readers into subscribers – and eventually, into a community you can learn from. [Tally](https://tally.cello.so/25W9JJ0dKQ6?ref=karaza.ai) is the simplest form builder I've found. It's free, offers unlimited responses, and you can embed forms directly into your Ghost site so they look native to your brand. *(For context: Typeform offers 10 responses/month on the free plan. Tally offers unlimited responses on the free plan).* To integrate both Tally and Ghost: 1. Create one form. A simple "join the list" or "tell me what you're working on" prompt. 2. Embed it on your about page or at the end of your first post. 3. Connect Tally to Ghost through Zapier. Now anyone who fills out your form automatically gets added to your Ghost membership list. You've just built a lead capture system that runs itself. For free. More importantly, you've eliminated the entire category of **"how do I grow my list"** friction. The system handles it. You focus on writing. ### Layer 3: A way to think faster ([Claude](https://claude.ai/?ref=karaza.ai)) The hardest part of creating (and if you're like me) is the blank page. I use [Claude](https://claude.ai/?ref=karaza.ai) to think through ideas with me. 1. When I have a rough angle, I talk it through. 2. When I'm stuck on structure, I ask for options. 3. When I've written a draft, I ask what's missing. 4. When I reference research, I get the source links. Some writers argue this is lazy. I think they're missing the point. In 2026, everyone has access to the same AI tools. The barrier to generating text is **zero**. The question then becomes "how to use them without losing what makes your work **yours**". For me, the answer is using Claude as a thinking partner, as opposed to a ghostwriter. I ask it to help to connect certain ideas I never knew how to connect in words but they were images in my head. That's a different relationship, and it removes the specific friction of staring at a blank page with no idea where to start. **What this stack doesn't include** - You won't have scheduling tools. - You won't access complex analytics (even though Ghost has useful analytics). - You will not have complex automations beyond the single Tally-to-Ghost connection. Whatever needs to exist to prevent more friction. Every tool you add is a tool you have to **learn**, **configure**, and **maintain**. Every dashboard is a place to check and potentially obsess over. Every automation is a potential breaking point. The minimum viable stack includes only what you need to go from idea to published piece to captured subscriber. Everything else is future you's problem, and future 'you' will have more information about what actually matters. --- ## The Feedback Loop When friction drops low enough, something shifts. - Low friction means more publishing. - More publishing means faster feedback. - Faster feedback means better ideas, because you're learning what resonates instead of guessing. - Better ideas mean more motivation. - More motivation means more publishing. The system becomes self-sustaining. Each output generates the input for the next cycle. This is where Tally forms become more than lead capture. A simple question "what do you want to learn about?" gives you your next topic. Reader responses reveal which angles landed and which fell flat. You stop guessing what to create because your audience tells you. The blank page stops being blank because you're responding to real questions from real people. But this only works if you publish enough to generate data. High-friction systems never reach this stage. They die in the decision phase, before the first feedback loop can form. That's the real cost of friction debt. It's not just that you publish less. It's that you never reach the phase where publishing gets easier. --- ## What Friction Remains I won't pretend this is a complete playbook. This stack solves publishing friction – the resistance between having an idea and having a live piece. It doesn't solve attention friction, which is the challenge of getting discovered when you're starting from zero. Ghost and Tally don't bring eyeballs. They just make sure you're ready **when eyeballs arrive.** It also doesn't solve consistency friction – the challenge of showing up repeatedly over months and years. That's a habit problem more than a tools problem, though lower publishing friction makes the habit easier to maintain. Distribution is still the open question. Getting eyes on your work, especially early, requires showing up somewhere with built-in discovery. X, LinkedIn, YouTube. That part still takes consistent effort and, honestly, a willingness to be a beginner in public (hey that's me). The approach I've described optimizes for one specific friction type. The other types are real, and I'm documenting what I learn about them as I go. If you're reading this article, you're watching that process happen in real time. --- ## In Closing The creator economy in 2026 is massive. The opportunities are real – I see them every day. But most people won't take advantage of them, because they never get past the setup phase. They drowned in friction debt before publishing their first piece. It is my goal this year to help at least **one** person get past this friction. If that's been you, try this: [Ghost](https://ghost.io/?ref=karaza.ai) for publishing. [Tally](https://tally.cello.so/25W9JJ0dKQ6?ref=karaza.ai) for capture. [Claude](https://claude.ai/?ref=karaza.ai) for thinking. All free to start (Claude grows on you and the $20 Pro might be worth it). All simple enough to launch this week. The principle matters more than the specific tools: reduce decisions to increase output. Audit your friction. Pay down the debt. Make publishing the path of least resistance. The best strategy is the one that gets you to publish. Everything else comes after. --- > **What kind of friction do you struggle with the most? Let me know below.** ### Create your own Email Signature in 2 mins URL: https://www.karaza.ai/create-your-own-email-signature-in-2-mins/ Last updated: 2026-01-18T09:33:56.000Z # Email Signature Generator This tool uses the public API of DuckDuckGo to fetch your available favicon Website Full Name Job Title Phone Twitter / X ## Preview Dark Copy Signature How to Import? Share this tool Twitter / X LinkedIn Copy Link ### Import Instructions G #### Gmail 1. 1\. Open Gmail Settings → See all settings 2. 2\. Scroll to "Signature" section 3. 3\. Click "Create new" and name it 4. 4\. Paste the copied signature (Cmd/Ctrl + V) 5. 5\. Save changes at the bottom ✉ #### macOS Mail 1. 1\. Open Mail → Settings → Signatures 2. 2\. Click + to create a new signature 3. 3\. Uncheck "Always match my default font" 4. 4\. Paste the signature in the preview area 5. 5\. Drag the signature to your email account 📱 #### iOS Mail 1. 1\. Open Settings → Mail → Signature 2. 2\. Select your email account 3. 3\. Paste the signature directly 4. 4\. Note: iOS may simplify the formatting 💡 For best results, paste the signature into a compose window first to verify formatting. ## How It Works Enter your website domain, and the tool automatically pulls your company’s favicon. No need to hunt down logo files or resize images. The icon appears instantly, linked back to your site. The live preview updates as you type. Toggle between light and dark backgrounds to see how your signature looks in different email clients. Gmail renders differently than Apple Mail. Now you can check both before committing. When you’re satisfied, hit copy. The signature transfers to your clipboard as formatted HTML—not plain text. Paste it into Gmail, Outlook, or Apple Mail, and the formatting survives intact. ## Setting It Up To add your signature to Gmail: open Settings, scroll to the Signature section, create a new signature, and paste. Save changes at the bottom. For Apple Mail: go to Settings, then Signatures, click the plus button to create a new one, uncheck “Always match my default font,” and paste. Drag the signature to your preferred email account. For iOS Mail: open Settings, tap Mail, then Signature, select your account, and paste directly. Note that iOS sometimes simplifies formatting—test by sending yourself an email first. ## Summary Your signature appears on every email you send. Hundreds of impressions per month, maybe thousands. Each one either reinforces your professionalism or undermines it. A well-structured signature includes your name, your role, and one or two ways to reach you. Nothing more. No inspirational quotes, no legal disclaimers (unless required), no five different phone numbers. The tool enforces this simplicity by design. Fill in the fields that matter, leave the rest empty, and the signature adapts automatically. Phone and Twitter only appear if you provide them. The bullet separator only shows when both exist. Clean inputs produce clean outputs. Your recipients notice, even if they can’t articulate why. ### How to Build a Lead Generation Form with Tally That Works URL: https://www.karaza.ai/tally-lead-generation-form-tutorial/ Last updated: 2026-02-20T12:55:01.000Z Tally is the easiest form builder for anyone looking to collect leads, and maintain clean intake process for (anything). In this tutorial, we look at how to build a lead generation for using a template. ## **Tally Tutorial: Creating a Lead generation form.** **For a deeper look into integrations** You can explore the help portal in Tally to connect your favorite tools: 1. [Webhooks](https://tally.so/help/webhooks?ref=karaza.ai) 2. [Notion](https://tally.so/help/notion-integration?ref=karaza.ai) 3. [Google Sheets](https://tally.so/help/google-sheets-integration?ref=karaza.ai) 4. [Airtable](https://tally.so/help/airtable-integration?ref=karaza.ai) 5. [Slack](https://tally.so/help/slack-integration?ref=karaza.ai) 6. [Coda](https://tally.so/help/coda-integration?ref=karaza.ai) 7. [Zapie](https://tally.so/help/zapier-integration?ref=karaza.ai)r 8. [Make](https://tally.so/help/make-integration?ref=karaza.ai) 9. [Integrately](https://tally.so/help/integrately-integration?ref=karaza.ai) 10. [Pipedream](https://tally.so/help/pipedream-integration?ref=karaza.ai) 11. [ApiX-Drive](https://tally.so/help/apix-drive-integration?ref=karaza.ai) --- You can read the full guide here:[ Tally 101](https://www.karaza.ai/creating-forms-with-tally-so/). Or, find out how you can use [Claude to build artifacts](https://www.karaza.ai/claude-projects-your-ai-workspace-in-2-minutes/), remix these [10 prompt styles](https://www.karaza.ai/10-claude-prompts-every-professional-should-know/) for your form, and go deeper into [tool stacks here.](https://www.karaza.ai/the-2026-solopreneur-tech-stack-guide-for-digital-product-businesses/) ### OpenAI vs. Anthropic: Why This Isn't Really a Competition Anymore URL: https://www.karaza.ai/openai-vs-anthropic-why-this-isnt-really-a-competition-anymore/ Last updated: 2026-01-13T15:48:37.000Z ## The Fork in the Road OpenAI and Anthropic didn't just disagree on features or pricing. They split on something more fundamental: **when is it safe to ship AI to millions of people?** This philosophical divide has created two companies solving different problems for different customers. ChatGPT now serves over 700 million weekly users with a "move fast and iterate" approach. Claude generates 80% of its revenue from enterprise clients who need reliability and safety guarantees for mission-critical workflows. ### What This Means for You The choice between these platforms isn't about which one is "better." It's about your risk tolerance and use case. **Choose ChatGPT when:** - You need broad general-purpose assistance across varied tasks - Speed of innovation matters more than absolute consistency - You're experimenting with creative applications - You want the latest features and cutting-edge capabilities **Choose Claude when:** - You're building business-critical automation workflows - Output consistency and safety are non-negotiable - You need transparent reasoning for compliance or auditing - You're implementing AI for clients who prioritize risk management ### The Takeaway This divergence reveals something crucial about the AI market: there's room for multiple winners with different philosophies. As a solopreneur or digital creator, understanding these strategic differences helps you make better tool choices based on your needs as opposed to following the hype. The question isn't which AI will win. It's which approach aligns with your specific project's risk profile and objectives. --- ### From Chats to Agentic AI: Understanding the Shift URL: https://www.karaza.ai/from-chats-to-agentic-ai-understanding-the-shift/ Last updated: 2026-01-12T12:19:11.000Z ## The Starting Point: Chats Think about the first time you used [ChatGPT](https://chatgpt.com/?ref=karaza.ai) or a similar tool. You typed something, it responded. You asked a follow-up, it answered. This back-and-forth is what we call a "chat" interface with AI. Here's what was actually happening under the hood: you sent text to a large language model, it predicted what words should come next based on patterns it learned from enormous amounts of text, and it sent that prediction back to you. The model had no memory beyond your current conversation. It couldn't check the weather. It couldn't send an email. It couldn't look anything up online. It was, in essence, a very sophisticated autocomplete system with a conversation wrapper around it. The analogy I find useful: imagine you're texting with someone who has memorized every book, article, and forum post ever written, but who is locked in a room with no phone, no internet, and no way to interact with the outside world. They can tell you what they remember. They can reason through problems using what they know. They can write, explain, and even code. But the moment you need them to actually *do* something in the real world—check a fact, look up current information, run a program—they're stuck. This was the state of consumer AI until roughly 2023-2024. ## The First Evolution: AI Agents The word "agent" in AI circles means something specific: a system that can take actions, not just generate text. The shift from chat to agent happened when developers started giving language models access to tools. Instead of just answering "here's how you could book a flight," an AI agent could actually access a booking system and make the reservation. Instead of writing code and showing it to you, it could run that code and show you the results. Instead of telling you what the weather might be, it could check a weather API and give you the actual forecast. Let me extend the earlier analogy. That person locked in the room now has a phone with specific apps installed. They can make calls, check websites, run programs, and interact with external systems. They're no longer just responding from memory—they're taking actions that affect the real world. The architecture looked something like this: you would give the AI a request, the AI would decide which tools it needed to use, it would call those tools (search the web, execute code, query a database), receive the results, and then formulate a response that incorporated what it learned. The AI became a coordinator between you and various capabilities. This was a meaningful upgrade, but it came with limitations. Most early agents were reactive rather than proactive. They waited for your instruction, executed a single task or short sequence, and reported back. They struggled with complex multi-step plans. They often got confused when a tool didn't work as expected. They needed you to hold their hand through anything complicated. Think of early AI agents like a new employee on their first day. Yes, they can use the computer and the phone and the coffee machine. But they need constant supervision. They complete one task and wait for the next instruction. They don't see the bigger picture of what needs to happen. If something goes wrong, they freeze and ask for help. ## The Current State: Agentic AI "Agentic AI" describes systems that can pursue goals across extended sequences of actions with significant autonomy. The key word is autonomy: these systems don't just execute individual tool calls, they can plan, adapt, and persist toward objectives over time. Here's what distinguishes agentic AI from earlier agents: 1. **Planning and decomposition.** When you give an agentic system a complex goal, it can break that goal into subtasks, figure out the dependencies between them, and work through them in a sensible order. If you ask it to research a topic and write a report, it doesn't just do a single search and start writing. It might identify what questions need answering, search for information on each, synthesize what it finds, identify gaps in its knowledge, do additional research to fill those gaps, and then compose the report. 2. **Persistence and error recovery.** When something goes wrong, like a website is down, a tool returns unexpected results, or a subtask fails; agentic systems can recognize the problem, try alternative approaches, and continue working toward the goal. They don't simply stop and report failure. 3. **Multi-step reasoning with world interaction.** Earlier agents could reason or act, but struggled to deeply interleave the two. Agentic systems reason, act, observe the results, update their understanding, reason again, and continue. Each action informs the next decision. 4. **Working memory and context management.** Complex tasks require tracking lots of information across many steps. Agentic systems have developed better mechanisms for managing this state, such as remembering what they've already tried, what they've learned, and what still needs to happen. Let me push the analogy further. That new employee has now been working for six months. They understand the organization. When you give them a project, they can plan their approach, navigate obstacles, coordinate with other systems and people, and deliver results without requiring your involvement at every step. You can give them an objective and trust them to figure out how to achieve it. This is the transition the AI field has been working through over the past year or two, and it's why you're seeing AI systems that can browse the web for extended periods, write and debug complex software projects, conduct research across many sources, and handle multi-hour tasks with minimal human intervention. ## Why This Evolution Happened Several things came together to enable this shift. The underlying models got smarter. Language models improved at reasoning, at following complex instructions, and at handling longer contexts. A model that forgets what it was doing after a few steps can't be agentic. A model that struggles to follow multi-part instructions can't plan effectively. Tool integration became more sophisticated. Early tool use was limited; rigid formats, limited error handling, narrow capabilities. The infrastructure for giving AI systems reliable access to external capabilities matured considerably. Developers learned what worked. There's now substantial practical knowledge about how to structure agentic systems, how to handle failure modes, how to balance autonomy with reliability. Much of this came from trial and error over the past few years. And critically, people started building scaffolding around the models; code that manages the loop of thinking, acting, and observing, that tracks state across many steps, that handles the messy realities of interacting with real-world systems. ## Why This Matters in 2026 Here's why you should care about understanding this evolution right now. **The tools you'll use are changing.** The software you interact with is increasingly powered by agentic AI. When you use a coding assistant that can run your code, debug errors, and refactor entire projects, you're using an agentic system. When you use a research tool that can spend an hour investigating a question across dozens of sources, you're using an agentic system. Understanding what these systems can and can't do helps you use them effectively. **The jobs landscape is shifting.** Many tasks that previously required human judgment and multi-step execution are becoming automated. This doesn't mean all jobs disappear; it means the nature of valuable work is changing. Understanding where agentic AI is strong and weak helps you position yourself. **You'll need to direct these systems.** Agentic AI is powerful but not autonomous in the full sense. It still needs clear goals, appropriate constraints, and human oversight for consequential decisions. The skill of effectively directing agentic systems, such as giving them clear objectives, setting appropriate boundaries, and reviewing their work, is becoming genuinely important. **The risks are real and specific.** Agentic systems can take many actions quickly, which means mistakes can compound. A chat system that gives you bad advice requires you to act on that advice for harm to occur. An agentic system that books the wrong flights, sends the wrong emails, or modifies the wrong files creates problems directly. Understanding this helps you calibrate how much autonomy to grant. ## The Honest Assessment Let me be direct about where I believe things actually stand. Agentic AI in early 2026 is impressive but inconsistent. These systems can accomplish things that would have seemed remarkable three years ago. They can also fail in ways that are frustrating and sometimes baffling. They're not reliable enough for fully unsupervised high-stakes work. They require more oversight than the marketing materials suggest. The progress has been real. The trajectory seems clear. But we're still in the early stages of figuring out how to build these systems reliably, how to integrate them into workflows safely, and how to handle the complications that arise when AI can take extended action in the world. What you're witnessing is a genuine transition from AI as a conversation partner to AI as a capable executor. Understanding this shift, including both its power and its limitations, puts you in a better position to work with these systems as they continue to develop. *Acknowledgement: This is piece was co-authored with Anthropic's Claude Opus 4.5 with the aim of gaining deeper understanding of how AI agents, agentic AI, and AI systems behave.* ### The 5 Whys Prompt URL: https://www.karaza.ai/the-5-whys-prompt/ Last updated: 2026-02-20T12:57:26.000Z I found a Claude prompt that uses the 5 whys on a general subject, so after some tweaking, I managed to create one for understanding one's own value proposition. [The 5 Whys](https://www.lean.org/lexicon-terms/5-whys/?ref=karaza.ai) interview technique to probe and uncover the root context, motivations, and business needs behind a user's product, service, feature, or idea before guiding them through a structured reasoning process to develop a high-impact value proposition. ****Copy-Paste the entire prompt below.** #### The 5 Whys x Value Proposition Statement Prompt Apply the the 5 Whys framework technique in an interview style to probe and uncover the root context, motivations, and business needs behind a user's product, service, feature, or idea before guiding them through a structured reasoning process to develop a high-impact value proposition. Begin by interviewing the user: - Sequentially ask "why?" up to five times (or until a root cause, motivation, or core need is revealed) in relation to their business, product, or idea. - For each "why," capture both the user's answer and your reflection on what each answer reveals about their goals, constraints, or the underlying problem. - Use the insights from this 5 Whys process to inform and ground the subsequent reasoning steps. After the 5 Whys, proceed as follows: - Brainstorm and articulate (REASONING FIELDS): - - The key problems or pain points that users or customers experience. - How the product/idea addresses and solves those problems in a unique or superior way compared to alternatives. - The specific target audience or user segment for whom this solution is most relevant or valuable. - The emotional and tangible benefits users gain. - Evidence, examples, or data (if applicable) that demonstrate effectiveness or value. - After reasoning, summarize the core value proposition in a single, high-impact, user-centric statement (CONCLUSION FIELD). - ALWAYS ensure all reasoning steps and insights come before the value proposition statement. - Continue engaging and asking follow-up "why" questions as needed, until you fully understand and can articulate the foundational business context, then advance to reasoning. ****Output Format** Use Markdown with clear section headers: - 5 Whys Analysis - Why #1: \[User answer\] - Reflection: \[Your interpretation/insight\] - Why #2: \[User answer\] - Reflection: \[...\] (Continue up to Why #5 or until root is reached) - 5 Whys Synthesis: \[Summary of root cause/motivation/business need\] - - Reasoning - User Problems/Pain Points - - Solution/How It’s Addressed - Target Audience - Differentiators - User Benefits - Supporting Evidence (if any) **Value Proposition Statement (1-2 succinct sentences)* ****The 5 Steps** 1. ****Initiate the 5 Whys interview**: Begin by asking the user about their business, product, feature, or idea, and follow up with "why" up to five times based on each answer, recording responses and interpretations. 2. ****Synthesize root insights**: Summarize what the 5 Whys revealed about the core issue or need. 3. ****Complete the reasoning fields**: Analyze problems, solutions, audience, differentiators, benefits, and supporting evidence, grounded in insights from the 5 Whys. 4. ****Craft the final value proposition statement**: Only after all reasoning is complete. 5. ****Always order output so that the reasoning precedes the conclusion/value proposition statement.** Output Format - Use Markdown with defined section headers and sub-bullets as indicated above. - Each response should fully document the interactive 5 Whys process, reasoning, and finalized value proposition in a single output. ****Example Input:** Product: A budgeting app for freelancers ****Example Output:** 5 Whys Analysis - Why #1: Why are you interested in creating a budgeting app for freelancers? - User answer: Many freelancers I know struggle to keep track of their irregular income and expenses. - Reflection: The primary motivation is addressing unpredictability and lack of clarity in freelancer finances. - Why #2: Why do freelancers struggle to track unpredictable income and expenses? - User answer: Their income comes from multiple sources at random intervals, and expenses (like taxes) are easy to forget. - Reflection: Irregularity in both inflows and obligations leads to missed payments and surprises. - Why #3: Why do these irregularities lead to problems? - User answer: Without a predictable system, it’s hard to plan or save. - Reflection: Lack of structure creates stress and hinders long-term financial security. - Why #4: Why is it important for freelancers to have this financial security? - User answer: Because many don’t have employer benefits and need to self-manage everything, which is overwhelming. - Reflection: Freelancers bear all financial risk and management burden. - Why #5: Why is managing all this alone overwhelming? - User answer: They have to focus on their work and often lack financial expertise. - Reflection: The core issue is limited time, expertise, and resources to self-manage finances. ****5 Whys Synthesis:** Freelancers need a budgeting solution because the unpredictability, complexity, and self-management requirements of their work cause significant stress and financial insecurity. ****Reasoning** - User Problems/Pain Points: Freelancers often struggle to track irregular income, manage fluctuating expenses, and save consistently. - Solution/How It’s Addressed: This budgeting app automatically syncs with varied client payment platforms, categorizes irregular income, sends reminders for tax/expense deadlines, and provides smart saving suggestions. - Target Audience: Freelancers, solopreneurs, and gig workers with irregular income streams. - Differentiators: Focuses specifically on non-traditional income flows; automates tax reminders and integrates with popular gig platforms. - User Benefits: Reduces money anxiety, improves financial control, and saves time spent on manual tracking. - Supporting Evidence: Beta users reported a 30% reduction in missed tax payments and a 15% boost in monthly savings after three months. ****Value Proposition Statement** A budgeting app that helps freelancers take control of irregular income and expenses, automating key financial tasks so they can save more and stress less about money. (Remember: For real use, each section should contain several sentences or bullet points with concrete details.) ****Important Reminder:** First use the 5 Whys to deeply understand the user's motivation or the business context. Only then proceed to identify problems, benefits, differentiators, and audience. Always write the value proposition statement LAST, and always ground your reasoning in insights from the 5 Whys. Use the provided format for all responses. > I personally recommend using Claude Opus 4.1, but it works just as well with ChatGPT 5 (Thinking long mode). ### How to create a Project in Claude URL: https://www.karaza.ai/claude-projects-your-ai-workspace-in-2-minutes/ Last updated: 2026-02-20T12:56:04.000Z Think of Claude Projects as your personal AI assistant's dedicated workspace; a place where context remains, knowledge accumulates, and your specific needs are understood from the start. ![](https://storage.ghost.io/c/9e/ab/9eab2e0e-d29b-47f9-bdba-5daac64e7df1/content/images/2025/09/Xnapper-2025-09-14-08.45.04-1.png) ## What Makes Projects Different Instead of starting fresh with every conversation, Projects let you: - **Upload reference materials** that Claude remembers across all chats - **Set custom instructions** that shape every response - **Build on previous work** without re-explaining context Think of it as the difference between briefing a new consultant every meeting versus working with someone who knows your business inside out. ## Setting Up Your First Project ![](https://storage.ghost.io/c/9e/ab/9eab2e0e-d29b-47f9-bdba-5daac64e7df1/content/images/2025/09/Xnapper-2025-09-14-08.45.57.png) **Step 1: Create and Name** Click "Create project" and give it a descriptive name. Example: "Q4 Marketing Campaign". **Step 2: Add Your Knowledge Base** Upload up to 200K tokens of context (roughly 500 pages): - Brand guidelines, style guides, or templates - Research documents or data sets - Code repositories or technical specs - Previous work samples **Step 3: Write Custom Instructions** Tell Claude exactly how to help you: - "Always write in our brand voice (casual, confident, no jargon)" - "Format all code using our company's style guide" - "Reference the uploaded pricing data for all calculations" ![](https://storage.ghost.io/c/9e/ab/9eab2e0e-d29b-47f9-bdba-5daac64e7df1/content/images/2025/09/Xnapper-2025-09-14-08.47.51.png) Tip: You could use the custom instructions to reinforce your uploaded knowledge base. ## Layered Context Here's what most people miss: Projects shine when you layer different types of context. **Example: Content Creation Project** - Upload: Brand voice guide + competitor analysis + SEO keywords - Instructions: "Write in our voice, differentiate from competitors, optimize for provided keywords" - Result: Every piece of content automatically hits all three targets ![](https://storage.ghost.io/c/9e/ab/9eab2e0e-d29b-47f9-bdba-5daac64e7df1/content/images/2025/09/Xnapper-2025-09-14-08.48.29.png) ## Three Ways Projects Save Time **1\. Skip the Setup** No more copy-pasting the same background information or explaining your formatting preferences repeatedly. **2\. Maintain Consistency** Every response follows your rules, uses your terminology, and matches your standards automatically. **3\. Build Incrementally** Start with basic instructions, then refine based on what works. Your Project gets smarter as you use it. ## Quick Start Templates **For Writers:** - Upload: Style guide + sample content + audience research - Instruct: "Match the uploaded style, target the defined audience" **For Developers:** - Upload: Codebase + documentation + architecture decisions - Instruct: "Follow our patterns, use our component library" **For Analysts:** - Upload: Data sets + report templates + methodology docs - Instruct: "Use our standard analysis framework and visualization style" ## Pro Tip: The Test Drive Before uploading everything, try a mini-project first. Upload one document, add one instruction, and test a few prompts. This helps you understand what context actually improves Claude's responses versus what's just digital clutter. *This is an underrated skill of actually learning how to work with prompts, as you begin to learn what specific keywords or instructions actually provide useful output.* --- **Ready to start?** Create your first Project with just one document and one instruction. You can always build from there. The goal is creating a workspace that makes your specific work task easier. ### The Stories Prompt URL: https://www.karaza.ai/the-stories-prompt/ Last updated: 2026-02-20T12:55:31.000Z A story does not appear from nothing. In AI writing, the seed is the **prompt**. The words you type in shape the story that comes out. Weak prompts bring weak stories. Clear prompts bring direction. Strong prompts spark invention. ## **Why Prompts Matter** AI models do not think like people. They respond to patterns in text. If you want a story with tension, you must ask for it. If you want characters with flaws, you must point the way. Prompts are the steering wheel of AI storytelling. ### **Prompts as Tools** - A prompt can act like a map. - A prompt can act like a command. - A prompt can act like a creative spark. Without a map, the AI drifts. With a command, it follows. With a spark, it surprises. ## **How to Write Strong Prompts** ### **Clarity** Write with sharp edges. Instead of *“write a story about an engineer who discovers a new city,”* say *“write a three-act story about a young engineer who discovers a hidden city under the desert.”* ### **Structure** Set the scene. Define the role. Add constraints. 💡 **Example:* **“You are a novelist. Write in first person. Keep sentences under 15 words.”* ### **Character and Conflict** Tell the AI what drives the story: *“A captain who fears water. A city built on floods.”* Conflict gives direction. ### **Style Prompts** If you want Hemingway, ask: *“Short, clear, stripped sentences. Concrete words.”* The model listens. ### **Beginner Level Prompt Templates** - **Hero’s Journey:** “Write a story where \[hero\] must \[goal\] but faces \[obstacle\].” - **Conflict First:** “Begin with a fight over \[object\]. Show how it shapes the ending.” - **Mood Driven:** “A story set in \[place\]. Mood is \[tone\].” 💡 ***Prompt** *: Write a story where Batman must stop the Joker from poisoning Gotham's water supply but faces the obstacle of having to choose between saving Rachel or Harvey Dent. Begin with a fight over a vial of toxin and show how this conflict shapes the ending. Set the story in the dark, crime-ridden streets of Gotham City with a noir, brooding mood throughout.* #### The Story w/ Claude Sonnet 4 Title: The Poison's Choice The glass vial shattered against the brick wall, its contents hissing as they met the rain-soaked alley. Batman's gauntleted fist had connected with the Joker's wrist just as the pale maniac raised the toxin above his head, cackling about "one drop to rule them all." "You're too late, Batsy!" The Joker shrieked, his purple suit torn and muddy from their struggle. "That was just the appetizer. The main course is already cooking in Gotham's water treatment facility." Batman grabbed the Joker by his lapels, lifting him against the graffiti-scarred wall. The distant glow of neon signs cast sickly colors across the narrow alley, while sirens wailed somewhere in the maze of Gotham's underbelly. "Where?" "Oh, but that's not the fun part," the Joker whispered, his breath reeking of madness. "The real joke is at the old ACE Chemicals plant. I've got your little friends Rachel and Harvey playing a game of 'guess who gets the antidote first.'" His grin stretched impossibly wide. "Tick tock, Dark Knight. You can only save one." Batman's jaw clenched. Through his comm, Oracle's voice crackled with urgency: "Bruce, I'm picking up massive toxin readings at the water facility. If it hits the main supply, half of Gotham dies within hours." The Joker's laughter echoed off the alley walls like broken glass. "Beautiful, isn't it? Save the city and watch your precious friends foam at the mouth. Or save one of them and let millions pay the price. Choose wisely, Batman. After all, every choice has consequences." Batman released the Joker, who crumpled to the wet pavement, still giggling. The decision crystallized in his mind with painful clarity. He fired his grappling gun toward the water facility. "I make my own choices," he growled into the night. At Gotham Water Treatment, Batman moved through the facility like a shadow given purpose. The toxin dispersal system hummed ominously, green liquid coursing through transparent pipes toward the city's main supply. He had seventeen minutes before the poison reached every tap in Gotham. His fingers flew across the control panel, isolating the contaminated sections and rerouting clean water through backup systems. But as he worked, his mind raced toward ACE Chemicals, toward Rachel's laugh and Harvey's unwavering faith in justice. The facility's speakers crackled to life. "Having second thoughts, Batman?" The Joker's voice dripped with mock sympathy. "I can practically hear you thinking from here. 'Did I make the right choice? Could I have saved them both?' The beauty of chaos, my dear Dark Knight, is that it reveals who we really are." Batman sealed the last contaminated pipe and activated the emergency purge. Gotham's water supply was safe, but the victory felt hollow. He turned toward his motorcycle, knowing he was racing against time that had already run out. The abandoned chemical plant loomed against the storm clouds like a monument to Gotham's industrial decay. Batman found Rachel and Harvey in separate rooms, both unconscious, both showing early signs of toxin exposure. The Joker sat between them in a chair, no longer laughing. "You chose the city," the Joker said simply. "How predictably heroic. How perfectly tragic." Batman knelt beside Rachel first, administering the antidote he'd synthesized from the broken vial's residue. Her breathing stabilized, color returning to her cheeks. But when he turned to Harvey, he knew he was too late. Harvey Dent's left side was already scarred by the toxin's caustic effects, his breathing shallow and labored. Batman injected the remaining antidote, but the damage was done. Harvey's left eye opened, wild with pain and fury. "You chose her," Harvey whispered, his voice a rasp of betrayal. "You left me to become this." The Joker's laughter returned, soft and satisfied. "And there it is, Batman. Your choice didn't save anyone—it just decided who would fall and who would rise from the ashes. Chaos doesn't discriminate; it just reveals the truth that was always there." Batman looked at Harvey's ruined face, at Rachel's peaceful recovery, at the city beyond the chemical plant's broken windows. In saving Gotham, he had created Two-Face. In choosing Rachel, he had lost Harvey Dent forever. The fight over a single vial of toxin had forced him to reveal the hierarchy of his heart, and that revelation would haunt Gotham's streets for years to come. The Joker was right about one thing: choices always have consequences, and some consequences echo louder than the victories that birthed them. In the distance, Gotham's lights twinkled like stars, unaware that their salvation had come at the cost of their white knight's soul. Batman carried Rachel toward the exit, leaving Harvey to find his own way into the darkness that would soon consume half his world. The poison was cleansed from the water, but it had found a new home in the heart of Gotham's former champion. And in the shadows, the Joker smiled, knowing that sometimes the greatest victories are the ones that feel most like defeat. ## **Advanced Prompt Engineering** ### **Iteration** Do not expect perfection in one shot. Change one word. Add one line. Watch how the AI shifts. ### **Layering** Feed the AI its own output as the next input. Build draft upon draft. ### **Constraints** Force limits: word count, dialogue only, or one setting. Limits sharpen the result. ### **Conclusion** The art of prompting is the art of control. You are not at the mercy of the machine. You give it rules, sparks, and edges. The better the prompt, the better the story.