How It Works

An AI agent that does what 40 hours of LinkedIn scrolling would do - in 8 hours, for under $6, while you sleep.

01

Agent searches across 4 providers

The AI agent runs search queries across Provider 1 (LinkedIn's own index), Provider 2 (neural search), Provider 3 (keyword search), and Provider 4 (web search). Each provider finds posts the others miss - Provider 1 gets company-specific results, Provider 2 finds semantically similar posts, Provider 3 catches keyword patterns.

148+ query iterations, each testing a different search strategy. Company-specific queries like "product manager hiring at Coinbase", role-level queries like "staff PM hiring my team", and person-led queries like "just posted a new PM role, DM me".
02

AI classifies and scores each post

Every discovered post goes through a multi-factor scoring pipeline. Is this a real hiring signal or career advice? Is it PM-specific? Is it US-based? Does the post have a named company? Each factor contributes to a quality score.

Five scoring factors: hiring language strength, role specificity, application evidence, geographic relevance, and company attribution. Each contributes a weighted percentage to the final confidence score. Posts below our retention threshold are filtered. Posts above our verification threshold are surfaced.
03

You get the person behind the job

What surfaces is not another job listing - it's the name, title, and LinkedIn profile of someone who is actively hiring. You can DM them directly and reference their own post. That's a warm lead, not a cold application.

Example: Adrienne Wong at Coinbase posted about hiring a PM II for Payments & Trust Network. The agent found her post, verified the company match, and surfaced it - 3 days before the role appeared on any job board.

Discovery Progress

Posts discovered across 148+ autonomous iterations. Each bar represents a checkpoint.

Provider Breakdown

Provider 1
808
LinkedIn's own search index
Provider 2
988
Neural semantic search
Provider 4
101
Web search
Provider 3
172
Keyword search

Total Cost

$5.90

Less than a latte. 148+ iterations, 4 providers, 2,000+ posts discovered. That's roughly $0.003 per post - cheaper than any recruiter, job board, or LinkedIn Premium subscription.

The honest story

The first approach failed. We started with a company-feed correlation strategy - search for LinkedIn posts about each company and match them to job listings. The precision was 5%. Out of 50 evaluated signals, only 2 were useful. We shelved it.

Then we pivoted. Instead of starting from companies, we started from people. We searched for LinkedIn posts where someone is clearly hiring for a PM role - the language patterns are different from career advice or job reshares. We built a classifier to detect hiring language, PM-family roles, company evidence, and geographic signals.

The new approach worked. Discovery went from 6 posts to 1,721 across 70 iterations. We added 376 more across two additional sessions with date-filtered queries. The system now reliably surfaces real hiring managers posting about real PM roles.

Trackly finds the job. Signals finds the person behind the job.