# Optimal Insights

Get a complete view of how your engineering team ships — from delivery speed to AI-assisted development. Insights connects directly to GitHub, analyzes your real activity data, and turns it into actionable metrics so you can spot friction, measure progress, and ship faster.

## PR Cycle Time

Measure how fast your team moves from first commit to merge.

The PR Cycle Time dashboard shows where time is spent in your pull request workflow — from creation to review to merge. It helps you identify slowdowns and track improvements across teams, repos, or individual developers.

### Key Metrics

- **Average Cycle Time** – Total time from first commit to merge. An “Excellent” badge appears when under 24 hours.
- **Time to Open** – From first commit to PR creation.
- **Time in Review** – Duration the PR waits for review and approval.
- **Time to Merge** – From PR open to merge into the target branch.
- **Merged to Staging** – How many PRs reached staging environments.

### Filters and Views

- **Teams vs. Individuals** – Switch between team-wide or contributor-level insights.
- **Repositories** – Focus on one or multiple repos.
- **Date Range** – Analyze over 7, 14, 30, or 90-day windows to track trends.

## AI Insights

Instantly understand what changed — and why.

The AI Insights side panel automatically analyzes the page you’re on (like PR Cycle Time or Activity) and provides an executive summary.

### What It Shows

- **TL;DR Summary** – Explains what shifted (e.g., longer open times but faster merges).
- **Activity Trends** – Week-over-week % changes in each metric.
- **Notable Contributors** – Who or what drove those changes.

> **Pro tip:** Open it weekly before sprint reviews — it’s like having a built-in engineering analyst.

## Activity

Visualize your team’s engineering rhythm. The Activity view shows commits, reviews, merges, and comments across a timeline — giving you a visual heartbeat of your team’s workflow.

### How It Works

Each developer appears as a row; each bubble represents activity for that day. The bigger the bubble, the more events occurred.

Color codes:

- ⚪ Commit – Code pushed to the repository
- 🔵 PR Open – New pull request created
- 🟡 PR Review – Pull request reviewed
- 🟢 Merge Commit – Pull request merged into the main branch
- 🔴 Comment – Review comment added on a pull request

### Why It Matters

- Spot midweek review peaks and Friday slowdowns.
- Balance review load across engineers.
- Detect burnout or under-utilization patterns early.

## AI Adoption

Measure how AI tools impact your engineering workflow. The AI Adoption dashboard tracks real usage and engagement with AI coding tools like GitHub Copilot and Claude.

### Core Metrics

- **Overall Code Acceptance Rate** – % of AI-suggested code merged.
- **Average Chat Interactions per Day** – How often engineers engage AI assistants.
- **Top Performing Model by Acceptance** – The AI model producing the most accepted code.
- **Highest Acceptance by Language** – Which language benefits most.
- **Average Daily Engagement Rate** – % of developers actively using AI tools.

## Pro Tips

- Enable AI Insights on every major dashboard for context-aware summaries.
- Standardize GitHub labels to improve Distributions and Allocations data.
- Compare time windows (7-day vs 30-day) to measure process improvements.
- Encourage reviewers to spread feedback load — visible in Activity view.
- Track AI Adoption alongside PR Cycle Time to measure real ROI of Copilot.

## Troubleshooting

| Issue | Solution |
| --- | --- |
| No data yet? | Wait a few hours after connecting GitHub; Insights backfills automatically |
| Missing PRs or repos? | Verify permissions include read + metadata access |
| Empty AI Adoption view? | Ensure AI telemetry is enabled in connected IDEs or extensions |