A pool only counts if people will move. This is how you find out — the exact signals, where they live, how to read them with AI, and how to put the whole sweep on autopilot.
Two tiers. Hard signals are verifiable and public — they hold up in a leadership room. Soft signals are sentiment and chatter — earlier, noisier, and only trustworthy when they corroborate something hard.
| Signal | Where it lives | What it tells you |
|---|---|---|
| WARN Act notices | DOL / state WARN databases | US employers (100+ staff) must file 60-day notice for mass layoffs. The most underused signal there is — names the site and headcount. |
| Layoff tracker entries | layoffs.fyi | Company, date, count, % of workforce for tech layoffs. Fast aggregation, good for trend. |
| SEC 8-K filings | SEC EDGAR | Public companies disclose material restructuring and RIFs. Dry but authoritative. |
| Earnings-call language | transcripts, IR pages | "Cost discipline," hiring freeze, headcount guidance — leading indicators before formal cuts. |
| Posting-volume drop | Lightcast / LinkedIn over time | A sudden fall in a company's active reqs signals a freeze before any announcement. |
| Funding distress | Crunchbase / PitchBook | Down rounds, bridge rounds, a missed raise — layoffs at startups usually follow within a quarter. |
| Signal | Where it lives | What it tells you |
|---|---|---|
| Anonymous employee chatter | TeamBlind | Layoff rumors in tech and semi often surface here first, in company-specific channels. Early but unverified. |
| Community threads | r/chipdesign, r/ECE, r/layoffs | Affected-team detail, severance terms, timeline. Mixes real reports with speculation. |
| Review velocity + sentiment | Glassdoor | A spike in negative reviews, "layoffs" mentions, or falling CEO approval is a morale and movability tell. |
| Open-to-work surge | A cluster of #opentowork badges or "impacted" posts among one company's alumni = a wave just happened. | |
| Company-specific forums | TheLayoff.com | Dedicated per-company layoff discussion. Noisy, but sometimes ahead of the news cycle. |
| Comp erosion | Levels.fyi | RSU refresh cuts, downward comp drift, frozen bands — quiet signals that people are getting restless. |
Semis are cyclical, so movability moves with the industry, not just the company. Watch fab utilization rates and capex cuts in earnings, inventory-correction cycles (SEMI, DigiTimes, EE Times), and named restructurings (Intel, GlobalFoundries, the memory makers). A downturn can make a normally locked-in analog or process-integration pool suddenly movable across the whole sector at once.
Free and public first. You can run a credible sweep without spending a dollar; paid tools just make it faster and broader.
AI does three jobs here: real-time sentiment sweeping, multi-source hard-signal compiling, and synthesizing messy forum threads into clean intelligence. Different jobs want different tools.
Search X for posts from the last 30 days about [COMPANY] related to: layoffs, restructuring, hiring freeze, RIF, reorg, or team cuts. Tell me: 1. Volume of relevant chatter (rough count + trend vs. prior month) 2. Overall sentiment and whether it's shifting 3. Any specifics on which teams/functions are affected (I care most about [RF / analog / silicon design] roles) 4. Credibility flag: separate apparent-employee posts from outside speculation or news amplification Be concise. Lead with whether there's a real signal here or just noise.
Compile verifiable layoff and restructuring signals for [COMPANY] from the last 6 months. For each, give source, date, and a one-line summary: - WARN Act notices (check the relevant state databases) - layoffs.fyi entries - SEC 8-K filings mentioning restructuring or workforce reduction - Earnings-call language on cost reduction, hiring freezes, or headcount - Major news coverage of site or fab closures and reorgs End with: a net read on whether [COMPANY]'s [target function] talent is becoming more movable, and how confident the public record makes you.
Below are forum threads about [COMPANY] from Blind / Reddit / TheLayoff. Analyze them and extract: 1. Specific layoff signals (dates, teams, scale) 2. Which functions and levels appear affected 3. Timeline — is this rumor, announced, or already done? 4. Credibility per claim — rate each on specificity and corroboration 5. What I should verify against hard sources before acting Ignore generic venting. I only want signal. [PASTE THREADS HERE]
Three tiers. Start at Tier 1 — it takes thirty minutes a week and covers most of the value. Move up only when monitoring more companies makes the manual version painful.