Honeybook built a ChatGPT agent that logs into LinkedIn, searches for candidates based on a job description, and applies nuanced filters (e.g., tenure, location, activity). This automates a time-consuming, multi-step workflow, freeing up the hiring team for higher-value tasks.

With HR departments using AI to screen candidates, a 'brag book' serves a new purpose beyond performance reviews. It becomes a critical repository of the quantifiable wins, keywords, and specific accomplishments needed to optimize a resume for automated hiring systems.

LinkedIn's new AI-driven search moves beyond exact job titles. Prospecting now involves natural language queries, like finding founders in a specific industry who previously worked at a certain company. This allows for much more nuanced and effective lead generation for premium users.

Instead of searching for new "AI" job titles, non-coders should focus on applying AI capabilities to traditional roles like marketing or sales. Companies are prioritizing existing positions but now require AI fluency, such as building custom GPTs or using AI assistants, as a core competency.

The ability to effectively communicate with AI models through prompting is becoming a core competency for all roles. Excelling at prompt engineering is a key differentiator, enabling individuals to enhance their creativity, collaboration, and overall effectiveness, regardless of their technical background.

Traditional recruiting tools rely on keyword searches (e.g., "fintech"). Juicebox uses LLMs to semantically understand a candidate's profile. It can identify an engineer at a payroll company as a "fintech" candidate even if the keyword is absent, surfacing a hidden talent pool that competitors can't see.

Zapier's CEO uses Grok's natural language search on X to find "under-the-radar" candidates. You can specify niche interests (e.g., "fans of no-code"), modest follower counts, and geographic locations to uncover passionate individuals who aren't on typical recruiter radars.

LinkedIn now automatically profiles you using an LLM that analyzes your bio, title, and industry. Unlike the old system of self-selected keywords, you must now craft your bio with machine-readability in mind, clearly stating your ICP, industry, and credibility metrics for the algorithm to categorize you correctly.

Create a custom GPT and feed it 10 of your company's best job descriptions. It learns your format, tone, and key requirements. This allows anyone on the talent team to generate a high-quality, company-specific job description in minutes by providing a simple brief.