
Why sourcing automation matters
Overview of automation tools and their benefits
Problems sourcing automation solves
Key concepts: Scraping, Parsing, Outreach
Differences between recruitment and sourcing automation
Key tasks solved by scraping and parsing
Tool overview and comparison
Value of data extraction for sourcing efficiency
Tasks solved by candidate contact tools
Overview of tools for outreach
Features of ATS-integrated communication tools
Saving time on messaging and follow-ups
This course contains the use of artificial intelligence
A candidate list is only useful when you can explain where every fact came from.
An AI agent's finished answer is the start of your review, not the end of your responsibility.
Recruiting work often moves through disconnected searches, profile notes, screening comments and message drafts. Copying information between these steps makes it easy to lose the source, miss a duplicate or report a draft as a completed action. A fluent AI summary can hide those gaps instead of resolving them.
The practical shift is from asking for isolated answers to commissioning a bounded piece of work. A recruiting run has a goal, permitted inputs, intermediate outputs, checkpoints and a named reviewer. Its result travels with the evidence and the record of what happened, so a correction can be traced to the step that needs attention.
Mike is the #1 HR instructor on Udemy, with 2,000,000+ students on the platform and 20 years in HR. He holds PHRi, SHRM-CP and HCI sHRBP certifications. This PapaHR course connects that HR perspective with practical recruiting work, while keeping hiring responsibility with people.
The course opens with a new five-part agent workflow. The first section establishes the task and its boundaries. The next sections follow candidate search and profile enrichment, preliminary screening, and outreach preparation. The final section brings candidate records and observed actions together in a checked funnel summary. Each part has one interactive browser tool, a complete fictional example and a practical assignment.
Live practice uses an approved agent workspace with the tools and permissions available to you. A clearly labeled simulated run supports output review when live access is unavailable. The browser tools organize task instructions, evidence, corrections and review decisions; they do not execute an AI agent themselves. Draft preparation and actual candidate contact remain distinct.
After the new core, the retained LinkedIn, Boolean search and OSINT sections provide the sourcing context behind queries, profile research and contact verification. The original sourcing automation sections then cover scraping and parsing, contact tools, browser extensions, applicant tracking systems and assessment tools. These recordings remain a foundation layer rather than a claim that every older demonstration uses an agent.
What's included
Every unreviewed recruiting run can carry a small error into the next search, shortlist or report. Putting evidence and review into the work now creates a clearer basis for the next handoff. Enroll now and start your first lesson today.