Before diving into any subject, set up a framework for how the conversation will progress over multiple sessions—like a syllabus for a college course. How to implement: - Outline your goals, stages, and questions for the entire topic in advance. - Ask the AI to follow this framework over multiple chats (e.g., “Day 1: Definitions, Day 2: Examples, Day 3: Advanced Techniques”). Why it helps: Keeps long-term goals visible and guides each session’s focus so the conversation builds steadily over time.

Every website has an inherent structure – leverage it to make the AI’s job easier. Using your XML sitemap or navigation menu as a guide, feed the AI content section by section in a logical order. For example, start with an overview of your site’s sections (from the sitemap), then systematically go through each section’s pages. Because you’re following the site’s architecture, the AI can maintain context within each section and gradually build a mental map of the whole site. This structured approach ensures no important area is overlooked. In effect, you’re guiding the AI through a comprehensive tour of the website, much like walking a new hire through your company’s departments one by one, resulting in a more complete understanding with minimal confusion.

When faced with a mountain of pages, divide and conquer. Split your website content into logical chunks (by topic, category, or site section) and have the AI summarize each chunk separately. Once you have these individual summaries, feed them back into the AI (or a second-stage prompt) to generate a higher-level summary or to answer questions using the summaries as context. This hierarchical summarization approach yields a top-down understanding: first the details on each page, then the big picture of the entire site. It’s a scalable technique — whether your site has 10 pages or 1000, the AI deals with bite-sized pieces at each step. The end result is a concise but comprehensive overview that overcomes token limits by processing information in stages rather than all at once.

Why feed all pages to the AI if you can pinpoint the relevant ones on the fly? This strategy uses your website’s search feature or Google’s “site:” query to find specific information, then lets the AI analyze those results. For instance, if you have a question about your site, first perform a targeted search (e.g., site:yourdomain.com keyword) to pull up the most relevant pages or sections. Copy the relevant snippets or URLs into your prompt for the AI to summarize or answer questions about. By smartly retrieving just what’s needed, you enable the model to draw on site-wide knowledge indirectly – covering the whole site via targeted pieces. It’s an easy, real-world method that uses tools at hand (search engines) to extend the AI’s reach across your content.

Unlock the full potential of your creative AI sessions by turning your AI into an expert editor. In this guide, we break down three essential prompts that will synthesize your entire chat history into a clean, final draft. Move beyond simple brainstorming and learn how to compile, structure, and even analyze your work for a flawless finish.

“Shared Wiki” Method What it is: Create a personal wiki or knowledge base to store conversation outcomes—like a private Wikipedia for your AI chats. How to implement:

• Set up a simple wiki tool (e.g., Notion, Google Sites, TiddlyWiki).

• After each chat, post key definitions, decisions, or frameworks in a dedicated wiki page.

• Before a new session, copy relevant sections and feed them back to the AI. Why it helps: A wiki centralizes information in an easily navigable format and makes retrieval of prior knowledge straightforward.

Ever open a new AI chat and feel like you’re starting from zero? A thematic outline fixes that. It’s your running map of major topics and sub-topics, so every session picks up exactly where the last one ended.

Have you ever opened a new AI chat, pasted your entire conversation history, and watched the AI get confused or overwhelmed? You’re not alone. When chats get too long, token limits kick in, and context gets fuzzy.

If you’ve ever reopened a chat and thought, “Wait… what did we decide last time?”, this prompt fixes that. It turns your AI into a friendly context assistant that reads a short “cheat sheet,” uses it to continue the work, and then hands you an updated excerpt to paste back into your doc.

Imagine clicking “publish” on a story you spent weeks researching. Readers immediately flock to social media, comment sections, and forums. Manually scanning every platform is daunting—and easy to miss critical feedback. What if AI could handle that heavy lifting, delivering a concise, sentiment-driven report and suggesting next steps?

Imagine your carefully crafted story finally reaching every corner of your audience—whether it’s in their morning newspaper, on their favorite news app, or scrolling through social media during lunch. That’s the magic of a well-coordinated, multi-channel publishing strategy: maximizing reach without duplicating effort.

Ever spent hours drafting an article only to realize it still needs that final polish? This prompt hands you a built-in senior editor—minus the coffee runs—guiding you to transform good copy into great, publication-ready prose.

Imagine your draft story as a jigsaw puzzle that’s mostly assembled but has some mismatched pieces and a few missing tiles. This prompt asks the AI to first refine each piece—ensuring every sentence fits snugly—and then go detective-mode, scouring for every factual tile to confirm it truly belongs. By combining editing with fact-checking in one seamless pass, you save precious time (no more toggling between tools) and gain confidence that your final piece will shine, polished and rock-solid.

Professional journalists follow a structured process to take a project from idea to published story. One of the most critical stages in this workflow is Writing and Drafting. At this point, reporters have already gathered interviews, data, and background information—the raw ingredients for a compelling article. Now they need to transform that material into a coherent narrative: crafting a compelling lead, organizing facts in an inverted-pyramid structure, and refining prose until it’s ready for publication.

At the “In-Depth Research and Reporting” stage, journalistic integrity depends on two pillars: asking the right questions and verifying the information. If you’re an entrepreneur writing a blog post, whitepaper, or thought leadership article, you can leverage this prompt to simulate expert interviews without immediately needing to schedule real conversations. It’s also valuable if you plan to conduct actual interviews—by providing a prebuilt questionnaire and source-verification checklist, you save hours on preliminary research. This urgency is especially true when deadlines loom, and you need reliable, well-sourced quotes or data to back your narrative.

In today’s fast-paced media landscape, securing coverage for your business or idea often starts with a well-crafted pitch. Whether you’re an entrepreneur looking to land a feature in a top-tier outlet or a small-business owner sharing a local success story, having a structured “Pitching and Assignment” framework can save you time, reduce guesswork, and boost your chances of being greenlit. In this post, we’ll share three AI-powered prompt variations—each designed to guide ChatGPT, Google Gemini, or Anthropic Claude through creating professional, polished pitches. You’ll see how to adapt each prompt to different goals, audiences, and formats so that you can hit “send” with confidence.

Generating and vetting story ideas is the heartbeat of journalism—but it can also be one of the most time-consuming and overwhelming stages, especially if you’re juggling multiple projects or trying to stand out in a crowded content landscape. In this post, we’ll walk through three AI-powered prompt variations designed to help you tackle the Idea Generation and Research stage like a pro.

Unlock the full potential of your website content by consolidating it into one unified file. When every page is in one place, the AI can retrieve context without missing details—ensuring a holistic analysis.

Consolidating content from long AI chat sessions

Ensures that the content is both appropriate and accurate for its intended readers.