Philip Arkcoll

How to track OpenAI Codex adoption, usage, and spend - what the native analytics dashboard, Analytics API, and Compliance API cover, and how to see Codex alongside Claude Code, Cursor, and Copilot.

How to track Claude Code usage in 2026: the analytics dashboard, contribution metrics and PR attribution, token costs via the API and OpenTelemetry, and what admins can and can't see.

AI isn't just challenging how employees work. It's challenging how organizations operate. Many companies are about to discover that the hardest part of AI adoption isn’t generating more output; it’s building organizations capable of handling it.‍

Centralized vs decentralized organizational structure: research-backed data on which model wins, when hybrid works, and how to measure org design.

AI overspending starts with daily habits. Learn how employees can write tighter prompts, pick the right tool, & cut LLM costs without engineering changes.

A practical guide to monitoring LLM token consumption and API costs across OpenAI, Anthropic, and more with code examples and best tools.

Effective feedback is more than just a performance review. Master the art of constructive criticism to lead a high-performing team.

A complete guide to advanced workplace analytics. Learn key metrics, cohort analysis, and predictive models to optimize performance & reduce burnout.

The most common assumption about AI in the workplace is that it’s a universal accelerator. If everyone works faster, the entire organization should move faster too. But in reality, that’s not what happens. Instead, we’re seeing AI dramatically improve how individuals work, but not automatically improve how work flows across teams. And those are two very different things. Let’s dig in.