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Clearly understand
engineering progress.

Maestro turns code, reviews, and conversations into written summaries of what your teams accomplish.

Maestro01 / 11
The question

Activity metrics miss what matters.

What do these numbers tell you?

  • 2,140pull requests mergedA renamed variable and a rebuilt billing flow each count once.
  • 860tickets closedA ticket can hold an hour of work or a month. The count can’t tell.
  • 3.4Mlines changedGenerated code and lockfiles move this more than real work does.

All true. None of it tells you what got done.

Counts measure how much happened, not what changed or why it mattered.

Maestro02 / 11
Core metrics

Maestro is different

Maestro understands your work.

It reads every change, writes up what got done, and scores it on three metrics.

  • Code Impact

    The scope, complexity, and effect of every change a person ships.

    Every merged pull request · 0–5
  • Review Impact

    The substance of the feedback a person gives their teammates.

    Every review · 0–5
  • Review Overhead

    The review effort peers spend to get a person’s work merged.

    Review points per merged pull request
Maestro03 / 11
Code Impact

Introducing Code Impact

Code Impact scores how significant a change is.

  1. Read every change

    Maestro’s AI reads the code in every merged pull request, not just its size.

  2. Understand what it does

    It works out what the change does and what kind of work it is.

  3. Score its significance

    It weighs scope, complexity, and effect on the system, then scores the change from 0 to 5. Most work lands at 1–3.

Pull requestAdd workspace check to bulk export
+214 −58 · 7 files
 export async function runExport(job) {-  const rows = await loadRows(job.query)+  assertWorkspaceScope(job.actor, job.workspace)+  const rows = await loadRows(job.query, job.workspace)   return writeArchive(rows, job.format) }
SummaryBug

Adds a workspace permission check to bulk export and applies it across the API, the shared exporter, and scheduled jobs.

Code Impact: 3Significant
  1. 0
  2. 1
  3. 2
  4. 3
  5. 4
  6. 5
Maestro04 / 11
The scale

Six levels, from negligible to transformative.

A 3 is a different kind of change, not three times better.

  1. 0NegligibleFormatting, comments, renames
  2. 1MinorA one-line fix or copy change
  3. 2IncrementalBetter error handling in one component
  4. 3SignificantA change that spans several modules
  5. 4High ImpactReworking a core service other teams rely on
  6. 5TransformativeA major architectural migration. Exceptionally uncommon.
Combining scores

Ten small fixes don’t add up to one transformative change. When scores combine across pull requests, people, and teams, bigger changes carry more weight, so combined scores can exceed 5.

Maestro05 / 11
The organization

Code Impact doubled since AI agents rolled out.

See what shipped, and how impact is trending.

AI coding agents rolled out
Code ImpactReview Impact
Jun 29Reliability fixes shipped
Sep 7Major feature release
Jun 8Sep 21
Code ImpactReview Impact
Maestro06 / 11
The work mix

Feature work grew. Bugs held steady.

See what kinds of work your teams delivered. Categorized automatically from each change.

Code Impact by categoryLast 16 weeks
Jun 8Sep 21
Maestro07 / 11
The teams

See how each team moved the work forward.

Each team’s progress in a few words, with average Code Impact per engineer so team size doesn’t skew the picture.

Data9 engineers
8.6Avg Code Impact / Eng

Validated event schemas before ingestion, documented a replay-safe recovery contract, and cut nightly pipeline reruns.

Frontend14 engineers
11.8Avg Code Impact / Eng

Standardized keyboard interactions across the product and caught focus bugs before they reached customers.

Platform17 engineers
10.9Avg Code Impact / Eng

Bounded event retries, added end-to-end delivery tracing, and moved scheduled exports onto the shared exporter.

Weekly Code Impact per engineer · 12-week average and 16-week trend · dashed line marks the AI coding agent rollout

Maestro08 / 11
The person

Recognize the contribution behind the progress.

A written account of their contribution, including reviews, read alongside role, context, and your judgment.

Frontend / Tessa R. · Q3
Tessa R.Engineer · Frontend
Last 12 weeks

Tessa R. is leading the team’s keyboard accessibility work. She shipped one interaction model for dialogs, menus, and tabs, and her reviews catch focus bugs before they reach customers.

Recent work
  • Review: nested-dialog focus trapCaught focus escaping on close and proposed a shared restore helper.
    Review Impact3Significant
  • Roving focus for menusArrow-key navigation across every menu component.
    Code Impact2Incremental
  • Shared keyboard patternsOne interaction model for dialogs, menus, and tabs.
    Code Impact3Significant
Illustrative product view · Fictional data
Maestro09 / 11
The workflow

Built on the work already happening.

No new status reports. Maestro reads the systems your teams already use.

GitHubGitLabSlackJiraLinear
  • Your data never trains AI.A contractual commitment.
  • SOC 2 Type II certified.Regular third-party audits.
  • Access stays controlled.SSO and granular permissions.
Maestro10 / 11
The walkthrough

Know what’s happening.
Lead with clarity.

See the progress, support every team, and recognize the people behind it.

Book a walkthrough →

Bring one team and one quarter. We’ll show you their work in Maestro.

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