First Dashboard

Last updated: September 2026

Reading your first dashboard

A guided 10-minute walkthrough of /teams, the page you land on when you log in. By the end you’ll know what every column means and where to click next.

Flow and Delivery view in GitKraken Insights with the team-pulse KPI strip, cycle time by phase trend, and average changes per developer chart
Flow & Delivery — hero KPI strip with team-pulse cards, plus the Flow tab’s cycle-time-by-phase and changes-by-type charts.

Set the scope first

Before you read anything, set two filters at the top of the page:

  1. Date range. Default is the last 14 days. For weekly reviews keep it at 14 days. For a quarter-end review, switch to 90 days. Sub-7-day windows force some rates to zero, so don’t pick “yesterday” expecting full data.
  2. Department or team. Pick the slice of the org you care about. If you have a Default Department set in Settings, this comes pre-filled.

Everything below this point will reflect those two filters.

The team table — column by column

The main view is one row per team. Here’s what each column tells you:

Readiness

A composite “is this team set up to succeed with AI?” rating. Combines repository readiness (do they have AI tools wired in?), behavior (are developers actively using AI?), and outcomes (cycle time, output). Read as: green = no help needed, yellow = friction worth investigating, red = blocked.

Avg Adoption

The mean Agent Adoption Score across the team’s active developers. A team average of 50 means a healthy mix; 80+ means a high-adoption team.

→ Agent Adoption Score

Tier mix

Bars showing the team’s distribution across Power User / Regular / Explorer / Emerging. A team can have a great average and still be lopsided — e.g. half Power Users, half Emerging. The tier mix surfaces that.

Cycle Time

Average hours from a PR’s first commit to merge. Lower is generally better, but not always — see the Cycle Time section for nuance.

Output Score (per active dev)

Effort-weighted shipping rate, divided by the number of active developers on the team. A team that ships fewer but bigger PRs can have the same Output Score as a team that ships many small ones. Read this alongside the PR/DC count breakdown to know which pattern you’re seeing.

→ Output Score

Power User %

Percentage of the team’s active developers in the Power User tier. Useful for tracking “where is AI adoption already mature” at a glance.

Expand a row to drill in

Click any team row to expand it. You’ll see three tabs:

Repos

Per-repo readiness. Helpful when a team’s Readiness score is dragged down by one specific repo that needs a config update.

Developers

The full developer roster for that team with individual Adoption Scores, Output Scores, AI Tier, and a Direct Commits column. Click any developer to drill further into their profile (this navigates to /developers).

System Metrics

Cycle Time + PR Volume trends for the team. Use the dimension dropdown to break either chart down by author, AI tier, or PR category.

What to look at first

In order, every time:

  1. Tier mix bars. Are any teams disproportionately Emerging? That’s the leading edge of an adoption problem.
  2. Avg Adoption vs Output Score. A team with high adoption and low output (or vice versa) deserves a conversation.
  3. Cycle Time outliers. Anyone over 4 days? That’s almost always a review-bottleneck or WIP problem, not a coding problem.
  4. Readiness reds. A red Readiness usually means a missing integration or a stale roster — quick to fix.

Where to go next

Now that you’ve read /teams, here are the obvious follow-up pages depending on what you saw:

If you saw … Go to …
A team with low adoption /developers, filtered to that team — find the Emerging cohort
A team with slow cycle time /flow-delivery → Flow tab → switch dimension to “phase”
A team with high output but low AI /comparison → compare that team to a high-AI peer
A team you don’t recognize /settings → Teams — check the roster
An exec asking “what’s the ROI?” /ai-impact and /executive

What the dashboard won’t show you (and why)

Glossary refresher