LinkedIn Automation Playbooks with OpenAI (GPT)

The people who like and comment on posts in your niche are already raising their hand, and that intent is spread across dozens of posts and buried in the feed. To work it by hand you first have to find the right posts, then open each one, scroll every reaction, read every comment, and copy profiles. It does not scale, so the warmest signals go to waste and teams keep buying cold lists instead.

Lead generationBuying / intent signalsGoogle GeminiClaude (Anthropic)Google Sheets

LinkedIn or Sales Navigator search returns hundreds of profiles, and most of them are not a fit. Teams handle this in two expensive ways. Some message everyone, which burns limited sending capacity, hurts reply rate, and trains them to blast more. Others pay to enrich and AI-score every single row in a tool like Clay, spending credits on leads that were never going to qualify. Either way you pay full price for the whole list before you know who is worth it.

Lead generationData enrichment & scoringOpenAIGoogle GeminiGoogle Sheets

When a company posts a job for a role you sell around, it is telling you it has a new priority, a fresh budget, and a pain. That is one of the strongest buying signals in B2B. The trouble is that job posts are scattered across LinkedIn, most are from recruiting agencies and staffing firms you do not want, and the person who posted is a recruiter, not the decision-maker you need to reach. Working this by hand does not scale, and by the time you get to a post it is often stale.

Lead generationBuying / intent signalsGoogle SheetsClaude (Anthropic)Google Gemini