Gitlights Blog

Insights, tutorials and product updates to help you get the most out of Gitlights.

How to Use Software Development Metrics to Make Better Engineering Decisions

Metrics are decision tools, not performance scores. Learn how to use signals from your repositories to make better decisions about technical debt, staffing, and team structure.

Collaboration and Code-Quality Metrics: Signals That Predict Team Health (2025)

High-performing teams don't fail from bad commits, but from degrading collaboration. Learn which Git-based metrics reveal how your team collaborates and the true health of your codebase.

How to Measure the Real Productivity of Your Development Team: Key Metrics Guide (2025)

What are the best metrics to track team productivity? This guide explains core engineering metrics like lead time, PR cycle time, and change failure rate, and how to interpret them safely.

The Best Productivity Tools for Engineering Teams with Advanced Analytics (2025)

Modern engineering teams have outgrown simple velocity charts. Understand what developer productivity means in 2025 and how tools like GitLights, Code Climate Velocity, LinearB, and Jellyfish approach analytics.

2025 Comparison: Gitlights vs. Leading Developer Productivity Platforms

A structured comparison of Gitlights, LinearB, Code Climate Velocity, Hatica, and Jellyfish. Find the right developer productivity platform for your team size and goals.

Top Tools to Improve Developer Collaboration in 2025

Discover the best developer collaboration tools for 2025. Compare GitHub, Linear, Notion, Slack, and Gitlights to boost team velocity, code reviews, and reduce technical debt.

AI-Assisted Code Reviews: Enhancing Your Git Workflow Without Losing Human Oversight

Discover how AI tools can accelerate code reviews while maintaining quality standards—from automated PR summaries to intelligent issue detection.

Inside GitLights' Developer Performance Model

Learn how GitLights builds a multi-dimensional performance profile for each developer using GitHub data, and how to interpret the Developer Detail dashboard responsibly.

Pull Request Analytics: Collaboration, Conversations, and Time to Merge

Deep-dive into GitLights Pull Requests dashboard: understand collaboration depth, conversations, and time to merge using EMA, RSI, and benchmarking across developers and repositories.

GitHub Commit Analytics in GitLights: Volume, Lines of Code and Temporal Patterns

See how GitLights transforms raw GitHub commits into trends, line-level analytics, and benchmarks across developers, repositories, and organizations.

Engineering Investment Balance with NLP and AI

Understand how GitLights classifies every commit into clear investment categories using NLP, AI and code metrics, and how to guide the model with explicit hashtags.

Mapping Individual vs Collective Contribution in Software Teams: Inside GitLights' Developer Contribution Map (2025)

Learn how GitLights' Developer Contribution Map visualizes individual vs collective impact for every engineer, using rich GitHub signals instead of a single productivity score.

Benchmarking GitHub Teams with Normalized Cross‑Organization Metrics

Understand how GitLights compares your commits and pull requests to other organizations using normalized, per-developer, per-time-unit indicators instead of raw counts.

Executive GitHub Activity Dashboard: Activity Analytics in GitLights

See how GitLights Default Activity Analytics dashboard turns raw GitHub events into an executive view of commits, PRs, reviews, investment balance, and codebase structure.

Review Comment Analytics in GitLights: Sentiment, Type, Urgency and Technical Depth

Discover how GitLights transforms raw review comments into structured analytics across sentiment, types, urgency and technical depth to measure review quality and collaboration.

GitHub Actions Analytics in GitLights: CI/CD Metrics and Pipeline Health

Learn how GitLights turns GitHub Actions runs into clear CI/CD metrics for execution time, reliability, cost hotspots and workflow, author and repository health.

GitHub Insights, Not Guesswork: See Real Development Signals

Turn raw GitHub activity into clear engineering insights with visual dashboards—no individual metrics, just actionable team context.

Why Individual GitHub Metrics Fail & What Teams Should Track

Measuring developers alone backfires. Learn better ways to leverage GitHub analytics for healthy, effective team performance.

Measuring Technical Investment with GitHub Insights

See the balance of new code, fixes, and refactoring in GitHub to guide strategy and align engineering with business goals.

Building Technical Transparency with Visual GitHub Data

Visualizing GitHub activity in Gitlights nurtures openness, healthy discussions, and stronger alignment—without micromanaging developers.

Better Technical Decisions with GitHub Data

Use GitHub insights to replace gut feelings with evidence when planning and making trade-offs—while preserving team autonomy.

Smarter PR & Branch Management with Real GitHub Data

Improve branches, pull requests, and collaboration using Gitlights dashboards that surface real development patterns—not assumptions.

Our Mission

AI has fundamentally changed software development. Gitlights exists to help engineering leaders navigate this shift. We measure what traditional analytics can't: the real value each developer brings as an individual contributor. Because in a world where anyone can generate code, understanding who drives real impact is the new competitive advantage.

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