In a recent LinkedIn post, Andrew Bolis discusses the strategic importance of research in achieving LinkedIn growth, arguing that success on the platform is not a matter of chance but of diligent investigation. Bolis highlights the potential of AI-powered tools, specifically Perplexity, to streamline this research process and translate findings into high-performing content.
Bolis emphasizes the need for a structured approach, outlining a step-by-step method for leveraging Perplexity to gather insights from various sources. He states:
LinkedIn growth isn’t luck ➟ it’s research.
According to Andrew Bolis, the key lies in utilizing the right prompts to extract valuable information that can be repurposed effectively.
Leveraging Perplexity for Diverse Content Insights
Andrew Bolis breaks down his research strategy into several key steps, each designed to tap into different information ecosystems. One of his primary recommendations involves combining Perplexity with YouTube.
Repurposing YouTube Content with AI
Bolis suggests using Perplexity to identify popular YouTube videos on specific topics and extract key details such as the channel name, publish date, reasons for popularity, and even specific timestamps for valuable segments. He provides a sample prompt:
“Find the top 5 most popular YouTube videos to learn ‘How to write a thesis with AI’. For each, include: channel name, publish date, why it’s popular, and the timestamp for the most valuable 2 minutes.”
As Andrew Bolis notes, this method allows users to quickly access credible video insights that can be repurposed instantly for LinkedIn content.
Mining User Sentiment and Academic Research
Beyond video content, Bolis advocates for using Perplexity to understand user sentiment and delve into academic research.
Understanding User Pain Points via Reddit
For identifying real user pain points and themes, Bolis recommends leveraging Reddit. His prompt strategy focuses on extracting short quoted snippets, thread links, and grouping findings by theme, ensuring relevance and recency.
Extracting Key Takeaways from Academic Papers
Furthermore, Andrew Bolis highlights the utility of Perplexity for academic research, enabling users to find highly cited papers on specific topics. He suggests prompts designed to yield crucial information like BibTeX entries, open-access links, and concise summaries of the main ideas, particularly for emerging fields like prompt engineering.
Advanced Research and Content Creation
Bolis also touches upon Perplexity’s advanced features, including its ‘Discover’ tab for tracking trending topics and ‘Labs’ for in-depth research, which requires a subscription. He outlines how to use these tools for creating custom reports and company insights.
The culmination of this research process, as outlined by Andrew Bolis, is the transformation of these data-backed insights into compelling LinkedIn posts. He advises users to identify patterns and trends that resonate with their audience and craft clear, story-driven narratives.
In essence, Andrew Bolis argues that by systematically employing AI tools like Perplexity for research, professionals can move beyond generic content ideation and create more impactful, data-driven posts that foster genuine LinkedIn growth.
📝 About This Content
This article is based on insights shared by Andrew Bolis on LinkedIn.
📅 Originally posted on January 27, 2026 | View original post on LinkedIn →