Report Methodology

Last updated: December 24, 2025

How we build reports

Tying.ai reports synthesize publicly available signals with a structured editorial framework. We prioritize clear definitions, evidence-backed claims, and practical recommendations that readers can verify.

What we evaluate

• Hiring signals and role scope changes
• Skill expectations and interview focus areas
• Compensation ranges and leveling patterns
• Market risks and near-term outlooks

Common data sources

Sources vary by report. When a report cites specific sources, the links appear in that report. These are common references we rely on:

• BLS / OES / JOLTS for employment and compensation signals
• Levels.fyi for role leveling benchmarks
• EEOC for policy and compliance references
• NIST AI RMF for AI risk guidance
• WCAG for accessibility considerations

Updates & revisions

We update reports when market conditions shift or when source data changes materially. The “Updated” date on each report reflects the latest revision.

Transparency

We avoid fabricating data. When precise figures are unavailable, we explain the range, the drivers behind it, and how readers can validate with their own sources.