In a recent LinkedIn post, Andrew Bolis highlights a novel approach to content creation, detailing how artificial intelligence can be leveraged to identify and replicate the success of viral hooks. Bolis introduces a tool called ChatGPT Atlas, designed to analyze top-performing content and extract the underlying formulas that drive engagement.
Deconstructing Viral Hooks with AI
Andrew Bolis explains that the foundation of any viral post lies in its initial hook. To assist creators in mastering this crucial element, he presents ChatGPT Atlas as a solution. The tool aims to automate the process of dissecting popular content, making the strategies behind viral success more accessible.
“Every viral post starts with a great hook. ChatGPT Atlas finds those hooks for you.”
As Bolis outlines, the process involves pointing ChatGPT Atlas at a creator’s channel. The tool then performs several key functions: it extracts top-performing hook formulas, generates customizable variations, and delivers fresh templates daily via email. This systematic breakdown, according to Bolis, allows creators to move beyond guesswork and adopt data-backed strategies.
A Step-by-Step Guide to Leveraging ChatGPT Atlas
Bolis provides a comprehensive, step-by-step guide within his post for users to implement ChatGPT Atlas effectively. The initial steps involve downloading the free browser extension (currently available for macOS) and signing in with a ChatGPT account.
Identifying and Analyzing Top Content
The core functionality, as detailed by Andrew Bolis, begins with selecting a YouTube creator and enabling the ‘Ask ChatGPT’ feature. This activates the Atlas panel, where users can then input a specific prompt designed to analyze the creator’s most successful videos.
“Analyze the top 5 highest-viewed YouTube videos on {CHANNEL_NAME} from the past 5 months. For each video, provide: 1. Exact video title + thumbnail title 2. First ~10 seconds of the opening hook (verbatim from transcript) 3. The underlying HOOK PATTERN (the formula, not the exact words) 4. Create 5 hook templates based on that pattern → include 2 different angles + 2 ways to adapt each for {YOUR_NICHE}”
This detailed prompt, shared by Bolis, instructs the AI to identify video titles, opening hooks verbatim, the underlying hook pattern, and generate multiple templates with niche-specific adaptations. It also requires the AI to provide takeaway points based on the observed patterns, emphasizing the use of verifiable data and concise, actionable outputs.
Building a Personal Content Library
Andrew Bolis further elaborates on how users can automate this process for continuous learning and content generation. By setting Atlas to run daily analyses on a chosen list of creators, users can build a personal library of effective hook formulas, templates, and angles. This proactive approach, Bolis suggests, can significantly streamline the content creation workflow.
“Stop writing posts from scratch. Start using patterns backed by real data.”
The final stage involves translating these extracted patterns and templates into LinkedIn posts. Bolis recommends pairing a chosen hook template with insights from longer-form content, ultimately crafting a clear and concise post with a single main takeaway. This method, according to Bolis, ensures that content is not only engaging but also data-driven and efficient to produce.
Bolis concludes by offering a free Advanced ChatGPT Guide and encourages readers to follow him for more AI-related insights, reinforcing his role as a thought leader in leveraging AI for content strategy.
📝 About This Content
This article is based on insights shared by Andrew Bolis on LinkedIn.
📅 Originally posted on December 10, 2025 | View original post on LinkedIn →