Thierry Donneau-Golencer
Thierry is Head of Product at FarosI, where he builds solutions to empower teams and drive engineering excellence. His previous roles include AI research (Stanford Research Institute), an AI startup (Tempo AI, acquired by Salesforce), and large-scale business AI (Salesforce Einstein AI).
How to measure Claude Code ROI: Developer productivity insights with Faros
Track Claude Code usage, adoption, and engineering impact using Faros AI’s observability platform.
Lines of code is a misleading metric for AI impact: What to measure instead
There's a better way to measure AI productivity than counting lines of code. Focus on outcome metrics that prove business value: cycle times, quality, and delivery velocity. Learn why lines of code fails as an AI productivity metric, what outcome-based alternatives actually work, and when tracking AI code volume matters for governance and risk management.
Claude Code token limits: Guide for engineering leaders
You can now measure Claude Code token usage, costs by model, and output metrics like commits and PRs. Learn how engineering leaders connect these inputs to leading and lagging indicators like PR review time, lead time, and CFR to evaluate the true ROI of AI coding tool and model choices.
Context engineering for developers: The complete guide
Context engineering for developers has replaced prompt engineering as the key to AI coding success. Learn the five core strategies—selection, compression, ordering, isolation, and format optimization—plus how to implement context engineering for AI agents in enterprise codebases today.
Faros AI Iwatani Release: Metrics to Measure Productivity Gains from AI Coding Tools
Get comprehensive metrics to measure productivity gains from AI coding tools. The Faros AI Iwatani Release helps engineering leaders determine which AI coding assistant offers the highest ROI through usage analytics, cost tracking, and productivity measurement frameworks.
Bain Technology Report 2025: Why AI Gains Are Stalling
The Bain Technology Report 2025 reveals why AI coding tools deliver only 10-15% productivity gains. Learn why companies aren't seeing ROI and how to fix it with lifecycle-wide transformation.
A 5th DORA Metric? Rework Rate is Here (And You Can Track It Now)
Discover the 5th DORA metric: Rework rate. Learn what it is, why it matters in the AI era, and how to start tracking it today. Get industry benchmarks, see what good looks like, and find practical tips to reduce wasted engineering effort and boost performance.
How to Measure AI Productivity in Software Engineering
Most AI tools don’t improve delivery. The GAINS framework helps engineering leaders measure real productivity impact across 10 transformation dimensions—from throughput to organizational efficiency.
