A Board-Ready Engineering Report in 60 Seconds

TLDR: Paste a GitHub org URL. Get a health score, key risks, velocity trends, and strategic recommendations. This replaces two days of slide deck assembly. Generate yours → intelig.ai/tools/executive-summary

Every quarter, the same ritual.

The CTO spends two days building a board deck. They pull screenshots from Jira, export some graphs from Linear, add a few bullet points about what shipped, and paste in a burndown chart that nobody fully understands.

The board nods. Asks a few surface questions. Moves on.

Nobody in that room has any real idea whether the engineering org is healthy.

The board deck problem

Board members aren’t engineers. They can’t evaluate a sprint velocity chart. They don’t know if 47 story points is good or bad. They have no frame of reference for whether your PR cycle time is competitive.

So they fall back on vibes. Does the CTO seem confident? Are customers complaining? Did anything break publicly?

That’s not governance. That’s theater.

What the board actually needs is the same kind of report they get from finance: a health score, key risk indicators, trend lines, and actionable recommendations. Numbers with context. Data with narrative.

What the Executive Summary produces

Point it at any public GitHub org. Sixty seconds later, you get:

Health Score. An overall engineering health rating based on commit velocity, contributor distribution, PR patterns, and repository activity. Not a vanity metric — a composite signal derived from actual code data.

Key Risks. Bus factor warnings. Repos with declining activity. Contributor concentration. Stale repositories consuming maintenance attention. The things that should keep a CTO up at night, surfaced automatically.

Velocity Trends. Is the org shipping more or less than last quarter? Not measured in story points — measured in actual commits, PRs, and active contributors. Real output, not estimated effort.

Strategic Recommendations. Based on the data patterns, specific actions the engineering leader should consider. Knowledge distribution. Team rebalancing. Repository consolidation.

What this replaces

Let me describe the current process at most companies:

1. CTO asks engineering managers for updates
2. EMs copy-paste from Jira/Linear dashboards
3. CTO synthesizes into slides
4. Slides go through two rounds of “feedback” (mostly cosmetic)
5. CTO presents to board
6. Board asks “are we on track?”
7. CTO says “yes, mostly”
8. Everyone moves on

Total time spent: 2-3 days of CTO time, plus EM time, plus review cycles.

Information quality: Low. Self-reported. Filtered through multiple layers. Optimistic by default.

Now compare: paste a URL, get a data-driven executive summary in 60 seconds. No self-reporting. No filtering. No optimism bias. Just what the code says.

Why git data beats Jira data

Jira tells you what people said they’d do and what they said they did.

Git tells you what actually happened.

A ticket can sit in “In Progress” for three weeks while nobody touches the code. Jira won’t flag that. Git will.

A repository can have zero commits for six months while a team “maintains” it. Jira won’t catch that. Git will.

An engineer can close 50 tickets by splitting one feature into 50 sub-tasks. Jira celebrates that. Git shows you the actual diff.

The board deserves better data than filtered self-reports. They deserve data from the source of truth: the code itself.

The real question

If an investor asked you right now — “Give me a one-page summary of your engineering org’s health” — how long would it take you to produce something credible?

If the answer is more than 60 seconds, you have a visibility problem.

Generate your executive summary now — free, no sign-up →