agent-displacement

To track weekly AI agent workforce displacement signals, this skill discovers and verifies named companies, roles, and headcount reductions from the last 7 days. It searches web sources, scores the evidence, and updates a maintained ledger for recurring research workflows.

Finding verified AI headcount analytics for a newsletter requires evidence-first extraction. This skill fetches articles and press releases to capture specific role displacement data, deduplicates against prior baselines, and categorizes signals for downstream digests.

Signal scoring for AI agent substitution evidence works by evaluating discovered web research data to filter and deduplicate claims. It reads prior state from memory topics, scores new findings, and maintains an evolving displacement topic file.

Yes, you can use this skill for recurring company announcements research. It applies to maintained ledger workflows, targeting web searches for recent AI deployment events and conditionally sending notifications and logs when new displacement signals are verified.

Yes, you need prior memory topics to run AI workforce displacement tracking effectively. The skill reads prior state from memory to deduplicate new signals against previous baselines, ensuring the displacement ledger evolves without repeating old data.

Categorized AI displacement signals are organized into practical groups like ops, code/dev, creative, and legal/finance. This grouping structures the verified headcount analytics and role specifics, providing structured angles for downstream articles and digests.