In a recent LinkedIn post, Andrew Bolis explores a novel approach to optimizing professional profiles on the platform by leveraging the capabilities of ChatGPT. Bolis presents a detailed prompt designed to act as an expert LinkedIn profile consultant, aiming to significantly increase recruiter visibility, enhance keyword searchability, and establish a cohesive personal brand identity. He emphasizes that this AI-driven method can streamline the optimization process, making it accessible within minutes.
A Structured Approach to Profile Enhancement
Andrew Bolis outlines a comprehensive, step-by-step workflow within his prompt, designed to dissect and improve every facet of a LinkedIn profile. This structured method ensures a thorough audit and strategic enhancement. As Bolis notes in his post, the objective is to create a detailed, section-by-section improvement strategy.
“You will analyze my LinkedIn profile (screenshots plus text excerpts I share) and create a detailed, section-by-section improvement strategy that increases recruiter visibility, enhances keyword searchability, and establishes a unified personal brand identity.”
Bolis’s strategy begins with a high-level profile audit, focusing on first impressions, tone, brand alignment, and positioning. He identifies key gaps that hinder recruiter engagement. Following this, the prompt guides ChatGPT through specific profile sections, including the headline, About/Summary, Experience, Skills & Endorsements, and Recommendations.
Key Strategies for Impactful Profiles
For each section, Bolis’s prompt specifies actionable advice. For instance, when it comes to the headline, the AI is instructed to assess the current version and suggest alternatives that highlight outcomes and adhere to character limits. In the About/Summary section, the goal is to rewrite it as a story, incorporating key accomplishments, primary skills, and a clear call to action.
Bolis further details the approach for the Experience section, emphasizing the need for impact-driven bullet points formatted as Action → Task → Result. He also suggests reordering roles based on relevance rather than strict chronology.
“For each role: highlight missing details (KPIs, scope, budgets, team size). Write 3–5 impact-driven bullets in the format Action → Task → Result.”
The prompt also addresses the critical Skills & Endorsements section, aiming to identify and suggest the most recruiter-targeted skills for a specific industry, while also flagging weak or overlapping skills for removal. According to Bolis, this meticulous approach ensures that the profile is not just populated with information but is strategically curated for maximum professional impact.
Beyond the Basics: Engagement and Benchmarking
Andrew Bolis doesn’t stop at profile content; his prompt also includes strategies for broader LinkedIn engagement and benchmarking. The AI is tasked with suggesting industry benchmarks by listing standout profiles and explaining their excellence. Furthermore, it is expected to develop an engagement and content plan.
“Develop a 30-day content plan (one theme + engaging hook per week). Recommend 5 niche LinkedIn Groups and 10 industry leaders for engagement.”
Bolis highlights the importance of not only optimizing the static elements of a profile but also actively participating in the LinkedIn ecosystem. This includes recommending specific niche groups and industry leaders to follow and engage with, fostering a proactive approach to networking and visibility.
To maximize the effectiveness of this AI-driven optimization, Bolis advises users to provide context and background information, utilize advanced AI features, and engage in follow-up questions with ChatGPT. He frames this as a powerful tool for professionals looking to refine their online presence efficiently.
📝 About This Content
This article is based on insights shared by Andrew Bolis on LinkedIn.
📅 Originally posted on December 14, 2025 | View original post on LinkedIn →