Job Sourcing and Application Workflow Redesign
The Result: Daily job hunting time cut by 95% (from about 2 hours to under 5 minutes). Skills extract in under 3 seconds. Records stay schema-validated. Application drafting capacity rises about 5x.
The Problem: Finding relevant jobs across sites took 2 to 3 hours a day of searching, reading long posts, and copy-pasting notes.
What we did: We replaced manual multi-site searching with an automated collect, extract, and draft workflow, that sends only odd posts to a review list.
2. Before
3. After
How job hunting worked before: slow, manual, and hard to keep consistent.
The new path: collect posts, extract skills, draft outreach, people only on odd cases.
- Hunting across multiple job sites every day
- Slow reading of long posts to pull out skills and salary
- Copy-paste notes into spreadsheets or docs
- Inconsistent tracking of what was applied to and what was left open
- Posts are collected automatically from the sources you set
- AI extracts skills and salary into a clean, validated record
- Outreach drafts are generated so applications can move faster
- Odd or unclear posts land on an exception queue for quick review
4. How it works
Automation handles collect, extract, and draft. You stay in control of odd posts and final send decisions.
System decides
- Collect new posts from the configured job sources
- Extract skills, salary, and role fields into a schema-validated record
- Draft outreach text from the extracted role details
- Flag odd or incomplete posts for the exception queue
- Keep every record in a consistent format for later reuse
People decide
- Set which sources and roles matter
- Review odd posts on the exception list
- Edit a draft before sending
- Choose which roles to apply to first
- Confirm the final send or skip
