Ron Meldiner

Your AI session logs capture vital intent, execution, and reaction signals. Learn to retain useful context, run automated retrospectives, and turn daily interaction data into powerful workflow improvements.

Evidence from 211 real engineering tasks shows why AI coding performance depends on the full route: model, harness, repository context, and task.

Open AI models matched frontier quality at half the cost in Faros's 211-task coding experiment. See the results and build your own model routing policy.

Token intelligence turns raw AI usage into operational context for engineering, finance, and leadership. Here's what it is, why it matters, and how to build it.

Dive into leading developer productivity research to uncover the multidimensional drivers shaping engineering efficiency.

AI generates 25% of Google’s new code. Other organizations seek similar insights to mitigate the risks of this new age of AI-driven development.

Bridge the Gap Between Engineering and Business with Engineering Data Unification

Is the Build Time metric the right measure to demonstrate the ROI of Developer Productivity investments? Does it stand up in court? We examine through real-life trial and error.

A guide to measuring continuous integration metrics, such as CI Speed and CI Reliability, and an introduction to the most important developer productivity metric you never knew existed.