How a power-user built a high-velocity content flywheel with Scrunch AI
Andrew Sorensen • 
In today’s AI-powered search landscape, discoverability isn’t just about keywords, it’s about structure, format, and scale. Brands that want to stay visible must produce content that’s not only relevant, but also optimized for how large language models (LLMs) consume and surface information. Those who crack this code are pulling ahead.
One standout example is Emmett Fear, Growth Lead at Runpod and a Scrunch AI power-user. Emmett built a high-velocity, insight-driven content flywheel using Scrunch AI’s platform, turning prompt-level insights into scalable, AI-optimized content that drives real results.
Let’s break down how Emmett uses Scrunch AI’s tools to fuel programmatic content creation and continuous optimization.
Prompt Manager: The insights powering programmatic content creation at Runpod
At the core of Emmett’s strategy is Scrunch AI’s Prompt Manager, a tool that enables you to create, manage, and monitor prompts across major AI search platforms (e.g., ChatGPT, Google AI Overviews, Perplexity, etc.). This platform provides visibility into how your brand shows up in AI-generated answers and recommendations.
Here’s how Emmett uses it:
- Creates specific, niche prompts: Due to the flexible and granular nature of the tool, Emmett is able to create very specific niche prompts for his business like “How do serverless GPU platforms compare to traditional cloud infrastructure?” or “What’s the best way to manage GPU provisioning and auto scaling for AI workloads?"
- Reviews top-performing prompts: Emmett analyzes which prompts consistently surface Runpod in AI search results. These insights inspire new content titles and angles that align with what AI is already recommending.
- Exports data for programmatic content: With Scrunch’s flexible export tools, he is able to export data on prompt performance and use it to generate content at scale. He filters the data to identify key topics, personas, and search intents (based on the stage of customer journey).
- Pairs with ChatGPT’s DeepResearch: Emmett uses Deep Research to dig deeper into trending themes, audience questions, and gaps in existing content, ensuring each piece hits the mark.
- Publishes and monitors: After publishing, he monitors AI search visibility through Scrunch, doubling down on what resonates and refining what doesn’t. Using the “Star” filter he is able to flag and prioritize prompts for further refinement.
The result: A self-reinforcing content flywheel, where every insight feeds the next round of creation, accelerating visibility and relevance.
Sources: Competitive Benchmarking and Thematic Insights
Scrunch AI’s Sources module provides a detailed view of what websites (sources) that AI is going to for answers. You can analyze data across your brand, competitor, and third party sites to gain a better understanding of where your brand and competitors are being cited.
Emmett uses this module to:
- Track Runpod’s presence in AI search: He benchmarks where Runpod ranks in ChatGPT compared to competitors. He reviews the top domains cited across owned, competitor and third party to identify potential content opportunities with third party review sites and potential threats.
- Uncover thematic opportunities: With built-in insights, he identifies gaps or emerging themes in different categories where Runpod can improve or expand its content. From there he prioritizes his next optimization effort.
This competitive lens ensures Runpod isn’t just producing content, it’s producing content that outperforms the market.
Site Audit: Unlocking Technical and Content Wins
Scrunch AI’s Site Audit tool enables you to view specific web pages the way an AI bot would. It checks if a single site page is easy for ChatGPT-User, OAI-SearchBot, and/or GPTBot to access, read, and understand. The tool surfaces technical issues that may be blocking AI from accessing your page or impacting how your brand appears in AI generated answers.
Emmett leverages it to:
- Diagnose technical issues: The Site Audit identifies rendering and accessibility issues that might block LLMs from seeing or understanding the site’s content. Emmett discovered critical rendering issues, which prevented Runpod from being cited. For instance, several articles were only being partially indexed (e.g., titles but not body content). With these insights, the team quickly updated metadata, restructured pages, and fixed formatting issues.
- Reveal hidden opportunities: By addressing these technical barriers, Emmett ensures that high-value content is visible and usable by AI systems, not stuck behind code or formatting errors.
Check out our Resource Guides: Guide to AI User Agents and Top 5 Content Optimization Problems (and how to fix them) for more information.
The Takeaway
Emmett’s use of Scrunch AI illustrates how brands can build a high-velocity, insight-driven content flywheel by combining strategic prompt monitoring, competitive intelligence, and technical site optimization. By embedding Scrunch AI into his workflow, Emmett has transformed content creation from guesswork into a data-driven engine for growth.
Ready to build your own AI-optimized content engine?
Get started with Scrunch AI today.