Insights for Engineering Leaders
Practical strategies for building high-performing engineering teams, powered by data and AI.
Connecting GitHub to Acticly: App Install or PAT Setup in 5 Minutes
The GitHub App is the fastest path — one click, zero maintenance. But if your org needs a Personal Access Token instead, here's exactly which two scopes to check and why fine-grained tokens are the wrong choice.
Your Team Is Using AI Coding Agents. You Have No Idea How Much.
Claude Code and Codex ship with built-in OpenTelemetry support. Here's how to start collecting that data, what it tells you, and the cross-domain insights you unlock when AI usage meets your git history.
Your Best Reviewers Are Your Biggest Bottleneck: What AI Reveals About Code Review
Pull requests sitting in review for days. Top reviewers drowning in notifications. Inconsistent feedback across the team. Here's what your PR data actually says about your review process — and how AI-assisted review is changing the math.
Who Hasn't Taken PTO in 60 Days? The Question That Prevents Quiet Burnout
Burnout doesn't announce itself. It builds invisibly over weeks. Here's how to use your existing GitHub and Jira data to spot engineers who are overdue for a break — before they burn out or leave.
How Much Time Has AI Saved My Team This Month?
Your team is using AI coding tools every day — but can you actually quantify the ROI? Here's how to measure real time savings, spot quality risks, and build a data-backed case for leadership.
How AI-Powered Analytics Can Tell You When It's Time to Hire
Stop guessing about headcount. Learn how real-time developer productivity data can reveal exactly when your team needs reinforcements — and what roles to prioritize.
Beyond Gut Feeling: Using Developer Productivity Data to Close Skill Gaps
Your team's skill gaps are hiding in plain sight. Here's how to use GitHub and Jira data to find them, measure them, and build a plan to close them — before they become blockers.