Photo by Nastuh Abootalebi on Unsplash

From Shipping Features to Shaping Narratives

Not long ago, over lunch with my fellow tech leader and friend Albert Alabau, we discussed the idea of a program to help promising tech leaders make the leap to Tech Executive. It’s a bigger shift than most would expect.

As engineering leaders, we’re used to living in execution: shipping, unblocking, optimizing. We’re excellent at moving from problem to solution. But at the executive level, that instinct can become a blind spot. The higher you go, the less it’s about how the system works and more about why it matters.

As a Tech Exec, your job is less about how the system works and more about how the story holds together, to connect the dots between engineering reality and business direction. You are expected to translate the engineering reality into a language that resonates with CEOs, boards, and cross-functional peers — clarity, risk, and direction.

Board meetings, where attention is scarce and stakes are high, are a completely different world from an all-hands team meeting or a roadmap review. Many brilliant leaders can run a tight sprint review yet still feel exposed when asked a deceptively simple question:

“So — are we on the right things, with the right team, and will it hold?”.

This series is about helping you answer that question — confidently, consistently, and without drowning your organization in vanity metrics. It’s not a magic formula; contexts vary by stage (Seed vs. Series D vs. IPO), by strategy (new product vs. modernization), and by moment (certifications, M&A, incidents, audits), but there is a repeatable set of questions that, when answered cleanly, signal competence, build trust, and guide decisions.

The Backbone of Board Confidence

Across companies and stages, a few questions always define board-level confidence:

• Do we have the right team? — Talent density and capability health

• Are we getting the best from them? — Execution leverage and productivity.

• Are we working on the right things? — Strategic alignment and resource focus.

• Are we reliable? — Operational maturity, quality, and risk management.

• Are we getting better? — Learning and leverage over time

It’s not about tracking everything. It’s about measuring what matters, with intent and clarity, so leadership can read the pulse at a glance and understand how engineering supports the business.

This article kicks off Part 1 of a three-part series on reporting to the board. In this first part, we’ll go deep into the key questions and signals every tech executive should be able to answer. Later, in Part 2, we’ll explore how to translate those signals into a clear board narrative; and in Part 3, how to keep them alive through your operating rhythm and decision cadence.

Before diving into frameworks or dashboards, let’s start from the basics.

Every board conversation eventually circles back to a few essential questions. They might phrase them differently — some will ask about execution, others about hiring or technical debt — but underneath, they’re assessing confidence in the same key areas:

• Team / Talent

• Productivity

• Focus / Strategic Alignment

• Reliability

• and Improvement

If you can answer these questions clearly, you already have the foundation for every future metric or slide. So let’s start with the first one — and probably the hardest to answer with confidence.

Series Part 1: Do We Have the Right Team?

Photo by Annie Spratt on Unsplash

Why it matters

Every board knows people are the biggest multiplier… or the biggest bottleneck. Especially in tech, where competition for talent has been fierce in the last years. If you don’t have the right skills, motivation, or balance, nothing else scales.

Signals / metrics to track

Here’s what healthy team dynamics look like when measured with intent:

• Hiring velocity and coverage: open roles filled vs. forecast. You can track this with most modern HR Ops or Talent Acquisition tools such as Greenhouse, Ashby, or others.

• Engagement & retention: eNPS, regrettable churn, or internal mobility. Engagement data typically comes from periodic surveys (CultureAmp, 15Five), while retention and mobility metrics rely on broader HR Ops tools like HiBob, BambooHR, or Workday.

• Manager load: span of control and leadership coverage. It’s often useful to monitor the manager-to-report ratio to ensure sustainable leadership capacity.

• Onboarding success: time to first contribution. I’ve seen as many definitions as organizations for what “onboarded” means — so this metric often requires some degree of manual tracking.

• Talent density: distribution of performance or contribution vs. company baseline.

As mentioned earlier, some of these questions are easier to answer with the right HR partners or HR Ops tools. Different moments call for different metrics — expansion vs. stabilization, hypergrowth vs. stabilization. But the question remains: how do you measure talent density and prove your team is truly strong?

Measuring Talent Density — Beyond the Résumé

Many leaders default to easy proxies: company logos, years of experience, or where someone worked before. But those signals rarely capture real performance. There’s no universal scoreboard for engineering talent — no transparent ratings, no speed, defense, or attack scores like in a video game

At Pensero, we provide different baselines so you can see how your team members perform across multiple dimensions — compared to peers at the same level, their teammates, and even across the broader engineering community.

These baselines answer a simple question:

What percentage of your engineers are performing in the top third globally across all Pensero users?

This allows you to see a fair, objective approximation of your true talent density — not by reputation, but by contribution. Pretty cool, right?

And when you start measuring talent impact more objectively, the concept of regrettable churn takes on a whole new dimension. You’re no longer relying on gut feeling or reputation to decide which departures truly hurt the organization — you can see their real performance footprint, and act before it’s too late.

Onboarding deserves its own article, but it’s worth noting how much this area has changed in the last few years. Before, it could take two to three months for a new hire to reach their normal pace of contribution, and maybe five to six months before they felt confident reviewing PRs and operating at full potential.

With the support of AI, that curve is now dramatically shorter. Codebase discovery and self-sufficiency have accelerated from months to a few weeks. This is another metric you’ll soon be able to track in Pensero — so stay tuned.

What’s next

Photo by Harper Sunday on Unsplash

Knowing you have the right team is just the start.

Even the strongest teams underperform when systems, focus, or access to the right tools hold them back. In the next article, we’ll explore the next essential question:

Are we getting the best from them?

We’ll look at productivity as leverage (not control) and how modern engineering orgs measure focus, flow, and AI adoption to amplify output without burning out in the upcoming series.

If you’ve ever tried to understand your team through data — and felt the frustration of doing it with spreadsheets, or with tools that only rely on ticket lifecycles or member surveys, without getting a holistic and factual view — stay tuned. We’re building something for you.

And if you want to join a blue-ocean opportunity — and help shape how engineering teams navigate this new technology age — check out our careers page.