AI

The 2026 price benchmarks for AI coding assistants, and how to turn per-seat pricing into a per-developer budget grounded in measured adoption, output, and ROI.

Codex bills through two systems that never reconcile. Learn the three export surfaces, the right API for per-user data, and how to build a reusable dataset.

Credits per developer is a spend metric, not a proficiency metric. This guide covers cost allocation, separating adoption from intensity, and benchmarking Codex spend against output and peers.

Extract Claude spend data by team, role, or function. Which Anthropic API to call, the 30-day revision window, and the HRIS join that makes it work.

Self-reported surveys measure confidence, not capability. Measure AI skills from work data across three layers: adoption, proficiency, and leverage.

Learn how to measure Claude Code productivity gains with adoption, proficiency, and hours-saved metrics, plus benchmarks engineering leaders can act on.

Most AI adoption happens quietly. Here's how to see which tasks your employees are actually automating, and what that data tells you about workflow gaps.

Step-by-step guide to exporting Claude Enterprise usage data through CSV downloads & the Analytics API, plus how to turn raw exports into insights.

Exporting ChatGPT Enterprise usage data via the Compliance API & admin console helps analyze adoption, seat utilization, and usage trends.