Tag: QBRs vs OKRs

Mastering 30,000-Foot Vision and Ground-Level Execution: Systems That Decide Without You

Executive function, for me, is the art and discipline of building systems that make high-quality decisions without my constant involvement. The real unlock isn’t personal heroics; it’s institutionalizing judgment. When I do my job well, teams move faster, ambiguity shrinks, and the organization compounds learning even when I’m not in the room.

Operating simultaneously at 30,000 feet and ground level is the defining muscle of executive leadership. I deliberately switch altitudes. At 30,000 feet, I obsess over strategy, architecture, and resourcing. On the ground, I validate core assumptions with firsthand data, listen for weak signals, and spot process cracks before they widen. Altitude changes are not random; they’re triggered by variance from plan, critical customer moments, or leading indicators that deviate from expected ranges.

The leap from frontline manager to manager of managers is where many rising leaders stall. As a manager of managers, my primary value shifts from personal execution to system design. I move from answering questions to installing mechanisms that ensure questions get answered well by others. This includes clear decision rights, shared metrics, and repeatable, lightweight rituals that scale across teams.

What is an executive actually accountable for? Outcomes over output, talent density, and the clarity of the operating system. That means defining strategy, aligning resources, creating a cadence of review that exposes truth, and ensuring incentives reward the behaviors we want. My barometer: if I step away, do priorities hold, do metrics behave as expected, and do tradeoffs land where I would have landed?

Knowing when to dive deep versus when to step back is a craft. I dive deep when risks are existential, when metrics have no credible owner, or when narrative and numbers diverge. I step back when leaders demonstrate consistent judgment, metrics sit inside control limits, and learnings are documented. The principle I return to again and again: context is everything. Senior leaders operate on context, not control.

To scale judgment, I teach people how I think. I externalize my mental models: how I construct decision trees, how I stress-test assumptions, and how I weigh time horizons. I rely heavily on driver trees for metrics because they force causal clarity. If we can’t map how a top-line goal decomposes into controllable levers, we’re managing by hope, not design.

Creating a shared language across the business is a force multiplier. I standardize definitions for our core metrics, codify what “good” looks like, and make it easy to repeat the system. We align around outcomes versus output, and we use cadences like MBRs and QBRs to unify narrative and numbers. Shared language makes decisions legible across functions and reduces rework.

My COO playbook emphasizes owning the full customer experience end to end. When marketing rolls up under a COO in certain stages, the upside is coherence: one narrative from awareness to activation to expansion, one set of metrics, one growth engine. The point isn’t org charts; it’s removing seams customers can feel.

Demanding and supportive is not a contradiction. I set ambitious, unambiguous bars and back them with coaching, resourcing, and fast feedback. The combination builds trust: expectations are clear, and help is immediate. I expect leaders to bring problems paired with proposed solutions and to escalate early, not perfectly.

Inside my executive interview process, I’m assessing altitude agility, operating cadence, and taste in metrics. I use structured interviews and live case workshops to see how candidates frame ambiguous problems, build driver trees, and prioritize tradeoffs. The best prompts are simple and revealing: design the operating system for a 3x scale scenario; diagnose a broken funnel with incomplete data; align two teams with conflicting incentives. The workshop prompts that reveal everything surface thinking speed, humility, and the instinct to make context legible.

The common thread in failed executive hires is a mismatch between the company’s operating system and the leader’s default mode. Some leaders can’t stop doing the work themselves. Others stay too abstract and never build mechanisms. I look for demonstrated ability to change systems, not just run them—leaders who can both author and evolve the playbook.

On metrics, I practice the driver tree philosophy. I begin with the North Star, decompose it into controllable levers, instrument each node, and assign single-threaded owners. We design review cadences where deviations trigger targeted diagnostics, not thrash. Each tree has documented assumptions, data sources, and thresholds that prompt action. This is how teams learn to anticipate, not react.

High-functioning executive teams are visibly collaborative. We clarify decision rights, disagree and commit quickly, and conduct post-decisions to harvest learnings without blame. My favorite litmus test is simple: can 30 people operate as one team when it matters? When we get this right, information flows, execution accelerates, and customers feel consistency.

One of the most counterintuitive leadership lessons is working yourself out of a job. If the system cannot run without you, you have a key-man risk, not a leadership strength. I aim to build successors, codify judgment, and design mechanisms that make good decisions the default state. That’s how you create durable, compounding advantage.

And the review feedback you can’t unhear? Mine was brutally honest: my bar was high, but my mechanisms were implicit. Once I wrote them down—how I decide, what I expect, where I dive deep—the organization moved faster, and I actually became less central. If there’s a throughline to extraordinary leadership, it’s this: make your judgment teachable and your systems inevitable.

February 5, 2026
Playing the 25-Year Game: Rethinking Networking, Ditching OKRs, and Owning the Full Stack

I’m drawn to builders who choose decades over exits. The story behind Meter—providing full-stack networking infrastructure as a service for businesses—captures that ethos with unusual clarity. From day one, the strategy hinged on vertical integration, business model innovation, and committing to a multi-decade horizon. As a product leader, I see this as the rare combination that compounds: patient R&D, an earned right to own the stack, and a commercial model aligned with customer outcomes.

Why think in 25-year horizons? In entrenched, often monopolistic markets like networking, short-term optimization simply doesn’t move the needle. Incumbents such as Cisco and Meraki shape expectations around procurement, installation, and support. If you want to reset the standard, you can’t iterate around the edges—you have to re-architect the experience end-to-end and give yourself the time to do it right. That’s the difference between building a product and building a company.

I also share the contrarian stance on planning. Rituals can easily masquerade as rigor. “We don’t do OKRs” doesn’t mean don’t align; it means don’t confuse activity with progress. I prefer crisp narratives, simple success metrics, and a cadence that keeps teams close to customers. Planning without over-planning lets you steer with first principles: what problem are we solving, for whom, and how do we know it’s working?

On that note, I relentlessly track unhappy customers. Satisfaction scores and dashboards are lagging indicators; the real signal is in the gaps, escalations, and stuck use cases. Building a habit of surfacing and resolving those moments creates the operational muscle you need later when you scale. It’s also how you find “seller-market fit” and sharpen your go-to-market motion.

The origin story matters. Meter spent four-plus years in heads-down R&D, even scrapping a year of OS work during the process. That discipline—killing good work to unlock great work—is the hallmark of teams that play the long game. Shenzhen accelerated progress by compressing feedback loops between design, manufacturing, and iteration, a reminder that sometimes geography itself is a strategy choice.

Getting to a sales-ready product requires intentional sequencing. Own the interfaces, the telemetry, the install experience, and the service envelope—not just the code. In networking, that means controlling the full stack so performance, reliability, and support converge into one promise. The surprising thing you should innovate isn’t only the feature set—it’s the business model. Turning networking into a service aligns incentives, reduces complexity for customers, and creates durable revenue with clear SLAs.

Avoiding the one-trick pony trap is also central. The best teams design for adjacent expansion from day one: new sites, new form factors, new service layers. The secret to finding an excellent market is to look where switching costs and frustration are both high; that’s where a superior end-to-end experience can pry open demand. That’s also why Meter didn’t sell via traditional channels—a direct motion builds intimacy with the customer problem, strengthens pricing power, and helps validate “seller-market fit.”

Resilience is the throughline: surviving COVID, Apple’s M1 transition, and “a thousand bad days.” In those stretches, pace and patience matter more than theatrics. I’ve learned to decouple management from authority, reduce meta-work, and tackle performance issues quickly—“when the person is the problem,” clarity and speed are an act of care for the whole team. There’s inherent value in going slowly when it preserves quality, trust, and optionality.

For founders and product leaders, the takeaway is simple: build a company you’ll want to run for as long as possible. Focus on first principles decision making, empower product teams, and choose the few metrics that truly reflect customer value. Resist the comfort of templates; adopt only the practices that raise your odds of learning faster than the market evolves. Owning the full stack, rethinking the model, and extending your time horizon can transform even the most entrenched categories.

This is how I aim to run product: fewer rituals, tighter feedback loops, and a relentless bias toward long-term compounding. When you commit to decades, you earn the right to define the category—one thoughtful release, one delighted customer, and one resolved escalation at a time.

December 10, 2025
Unify Your Analytics to Accelerate Growth: Cut Costs, Move Faster, and Decide in Real Time

I’ve learned that the fastest way to stall growth is to scatter your data across a maze of dashboards and point solutions. My guiding principle is simple: Escape fragmented tools with a unified analytics platform that accelerates growth, reduces costs, and empowers smarter, real-time decision-making. When every team can trust a single source of truth, momentum compounds.

By “unified analytics,” I mean a single platform that integrates product, marketing, sales, support, and finance data with consistent definitions, shared metrics, and strong governance. The right foundation pairs real-time instrumentation and event streaming with standardized taxonomies and role-based access. This is what transforms raw data into reliable insight that product managers and executives can act on with confidence.

Growth accelerates when hypotheses move faster from discovery to delivery. A unified analytics platform tightens the experimentation loop, informs product discovery, and aligns product roadmapping and sprint planning with measurable outcomes. It anchors outcomes vs output OKRs in trustworthy metrics, so QBRs and executive reviews focus on impact, not anecdotes. The result is clearer prioritization, sharper bets, and faster compounding wins.

Costs come down just as decisively. Consolidating analytics reduces redundant SaaS, manual reporting, and bespoke pipelines that are expensive to build and maintain. With one data model, we cut duplication, improve data quality, and negotiate smarter under consumption SaaS pricing. Teams spend less time wrangling CSVs and more time shipping value.

Real-time decision-making is where unified analytics truly pays off. Proactive alerts and cohort insights surface anomalies before they become churn. LTV, funnel, and retention forecasts inform pricing and packaging moves. Layering gen ai on top of clean, unified data speeds synthesis and narrative insight, while a thoughtful customer support AI strategy connects voice-of-customer signals directly to the roadmap.

Implementation starts with clarity. Identify the highest-impact decisions you want to improve, map KPIs to events, and instrument end-to-end tracking with quality SLAs. Establish governance early, align stakeholders across data, engineering, RevOps, and finance, and empower product trios to own their metrics. With disciplined stakeholder management and empowered product teams, the platform becomes a force multiplier rather than another tool to maintain.

The payoff is strategic agility: faster learning cycles, lower operating costs, and confident calls made in the moment, not after the fact. If you’re ready to break free from fractured dashboards and lagging reports, commit to a unified analytics platform and let your data become a competitive advantage.

Inspired by this post on Amplitude – Best Practices.

October 23, 2025
Build Scalable Startup Systems: My Take on Kevin Fishner’s Writing-First, KPI-Driven Playbook

When I think about building enduring startups, one principle guides my approach: treat the company itself as the product. That mindset came into sharp focus as I studied the operating systems behind Kevin Fishner, Chief of Staff at HashiCorp. The rigor and clarity of his approach offer a blueprint any product management leader can adapt to scale with speed and integrity.

As the first business hire at the cloud infrastructure automation company, he previously built out the sales, marketing and product management teams. That trajectory matters: it’s rare to see one leader connect go-to-market, product management, and operational cadence so cohesively. The result is a system that aligns strategy, execution, and learning loops without creating organizational drag.

Now as chief of staff, he’s focused on building a strong foundation of company-wide systems, now that the team has grown to over 1000 people. This is where great product management leadership shines—codifying how decisions are made, how work moves, and how teams align around outcomes as headcount and complexity expand.

In today’s conversation, Kevin shares a detailed look at how they run meetings, set and track progress toward goals, and make decisions through writing at HashiCorp. I’m a strong proponent of a writing-first culture as the backbone of a scalable operating cadence: crisp memos reduce meetings, strengthen decision quality, and preserve context. Combined with clear meeting charters, owner-defined agendas, and time-boxed decision-making, this turns process into a lever for speed—without sacrificing rigor.

He also shares incredibly tactical advice for making annual planning more effective, including the unique business simulation they run, their scorecard system, and the weekly and quarterly meetings that help them stay focused on important KPIs. My lens: anchor annual planning in outcomes vs output OKRs, then connect those outcomes directly to product roadmapping and sprint planning. Use QBRs vs OKRs thoughtfully—QBRs to pressure-test business performance and assumptions, OKRs to lock in the next set of measurable bets. The scorecard becomes the single source of truth for progress and trade-offs, while the business simulation stress-tests priorities before they hit roadmaps.

Whether you’re a chief of staff, a founder spinning up a company from scratch, or a manager scaling a team, you’ll find practical takeaways here to make your organization more effective. I’ve distilled templates, prompts, and visuals to help you adopt a writing-first decision model, stand up a repeatable meeting rhythm, and operationalize goal tracking so KPIs stay front and center—not buried in dashboards.

If you’re serious about building startup systems that scale, adapt these practices: align on a few critical outcomes, document decisions in writing, instrument scorecards that ladder to KPIs, and commit to weekly and quarterly cadences that turn strategy into execution. That’s how you build an organization that learns faster than it grows.

Inspired by this post on First Round.

October 22, 2025
Inside Tido Carriero’s Playbook: Build World-Class Engineering Orgs and Nail Product/Market Fit

I’m drawn to leaders who’ve built both high-performing engineering organizations and durable products. Tido Carriero, the Chief Product Officer at Segment, a customer data platform which was recently acquired by Twilio, exemplifies that trajectory. Before that, he built out the engineering teams that worked on the core product and the initial business product at Dropbox. Tido started out his career in 2008 as an early member of the Facebook ads engineering team, and went on to become an eng manager on the Pages team — a pivotal IC to leadership transition that resonates with many of us in product and engineering.
What stands out in his journey are pragmatic lessons on building engineering orgs and launching new product lines at several top tech companies. His reflections on the pros and cons of single threaded leadership and the black box analogy for assessing a team’s performance offer concrete ways to interrogate how work actually gets done. In my own practice, I pair these lenses with outcomes vs output OKRs, tight product roadmapping and sprint planning, and a clean operating cadence that links QBRs vs OKRs. Together, these mechanisms create clarity in org design, planning, and execution — and make performance visible without micromanaging.
For new engineering managers and new managers-of-managers, I appreciated the practical “gems of advice.” That IC to manager transition is rarely linear; success hinges on shifting from personal velocity to organizational throughput. I coach first-time managers to build credible operating systems early: explicit decision rights, transparent prioritization, and lightweight feedback loops. One simple ritual I rely on is a weekly narrative update that forces crisp, outcome-focused thinking — a habit that complements any try do consider framework a team may use.
We also explored the path to product/market fit, especially for multi-product strategies — an area where many B2B teams struggle. Tido shares his advice for going from zero to one in a new product, including the simple milestone his teams have to hit before he’ll greenlight a new project, why he prefers iterative approaches over “big bang launches,” and his thoughts on why Dropbox struggled here. My own playbook mirrors this: invest in fast product discovery, define a clear gate tied to must-have user behavior, and resist vanity launches until repeatable pull exists. Small, well-instrumented bets compound; “big bang launches” rarely do.
If you want to go deeper on finding product/market fit in the context of multi-product strategies, Tido shares more of his thinking here: https://segment.com/blog/finding-product-market-fit-again/. It’s a useful companion for leaders calibrating zero-to-one efforts alongside an at-scale core business.
The through line across these lessons is disciplined simplicity. Whether you’re architecting engineering orgs, coaching the IC to manager transition, or charting zero to one in a new product, choose mechanisms that surface reality quickly, reward learning, and keep teams focused on outcomes. That’s how world-class organizations build, ship, and iterate their way to enduring product/market fit.

Inspired by this post on First Round.

October 22, 2025
From Zero Customers to IPO: Eric Berg’s Hard-Won Playbook for the Messy Middle

I’ve been revisiting the hard-won lessons behind durable product companies, and Eric Berg’s journey is a masterclass. Eric Berg is the CEO of Fauna, which is an adaptive operational database platform. In joining Fauna as its CEO in the summer of 2020, he brought a wealth of experience as a product leader. Most recently, he was the Chief Product Officer at Okta, scaling the company from 10 employees and zero customers to its eventual IPO in 2017. He started his career in product at Intel, working under the legendary Andy Grove, as well as a five-year stint as a product leader at Microsoft.

From a product management leadership lens, the earliest chapters at Okta are a blueprint for zero to one B2B marketing and founder-led GTM. I break down his early go-to-market lessons and the keys to honing in on an ICP to get Okta off the ground, highlighting how tight product discovery, crisp problem statements, and ruthless prioritization turn ambiguity into product-market fit.

What stands out is the often-maligned “messy middle” — the stretch when traction exists but entropy expands. Eric’s moves on “moving upmarket” and evolving a “pricing and packaging model” are reminders that, when done well, takes a company to new heights. For SaaS pricing, I lean on value metrics tied to critical jobs-to-be-done, clear guardrails for discounting, and a win–loss feedback loop owned jointly by product and sales.

We then switch gears to team building and company building. The cultural patterns that stick with me: hire “folks up and down the org chart with the right ego to talent ratio” and operationalize a “disagree and commit” value so it’s not just a long-forgotten team motto. Practically, that means defining decision types (one-way vs. two-way doors), naming a DRI and approver for every call, time-boxing debate, and documenting the rationale so execution never stalls.

On execution mechanics, I’ve found that outcomes vs output OKRs paired with QBRs vs OKRs alignment creates a healthy cadence from strategy to delivery. When you layer in forward deployed engineers and structured customer advisory boards, feedback cycles compress without sacrificing focus — a powerful pattern in both product roadmapping and sprint planning.

Finally, the perspective shifts “as he approaches one year of sitting in the CEO seat” underscore the difference between building products and building a business. Capital strategy, talent density, and narrative become first-class product surfaces. As a product creator, I translate this into designing org APIs, setting explicit burn-to-learn budgets, and treating pricing, packaging, and GTM as core parts of the product.

If you’re navigating product-market fit lessons, wrestling with “moving upmarket,” or recalibrating SaaS pricing, this playbook maps the trade-offs from 0 customers through the “messy middle” and beyond. It’s a grounded field guide for product folks and operators who want to scale with clarity, strengthen culture, and accelerate learning without losing the thread.

Inspired by this post on First Round.

October 22, 2025
My Proven Product Strategy Playbook: From Mission to NCTs That Align Teams and Drive Growth

I’ve spent years building and scaling products, and I continue to see one pattern derail even the most talented teams: a disconnect between product strategy and what product teams actually work on day-to-day. In this deep dive, I share how I bridge that gap with a practical, battle-tested playbook I’ve used to align teams, accelerate impact, and power growth at scale.

I start by getting brutally clear on the real work my teams are doing versus the outcomes we’re aiming for. Too often, teams are busy shipping features that don’t ladder up to strategy. The fix isn’t more process—it’s sharpening the connective tissue between strategy, planning, and execution so every sprint advances a clear, long-term narrative.

At the core of my approach is the product strategy stack: company mission, company strategy, product strategy, product roadmap, and product goals. When each layer is explicit and connected, prioritization becomes straightforward, trade-offs are defensible, and the team understands not only what we’re doing—but why it matters. I treat this stack as a system, not a document, and I revisit it frequently with my leads to ensure decisions remain aligned.

Here’s how I operationalize it. I anchor every planning cycle in the company mission and company strategy, then translate that into a crisp product strategy that defines where we will play and how we will win. From there, the product roadmap becomes a sequencing tool for outcomes, not a wishlist of features. Finally, I define product goals that are specific, measurable, and clearly tied back to the strategy—so everyone can see the throughline from mission to metrics.

When it comes to goal-setting, I prefer an alternative to traditional OKRs: NCTs. Outlining narratives, commitments, and tasks sidesteps some of the most common headaches when it comes to OKRs. The narrative clarifies the why, the commitments define the measurable outcomes we’re on the hook to achieve, and the tasks capture the critical work we believe will get us there. To implement NCTs, I pilot them with a single squad, ensure each narrative maps to the product strategy, pressure-test commitments against leading indicators, and keep tasks flexible as we learn.

Strategy is often misunderstood and has come to mean all sorts of different things. I’ve found that clarity around terms like “mission” and “vision” changes everything. Mission is enduring and customer-centered; vision is a vivid, time-bound picture of the future we’re building. When teams grasp the difference, alignment snaps into place. I’ve seen this playbook resonate across industries and company stages—from category leaders like Tinder and TripAdvisor to fast-growing startups—because it turns abstract strategy into concrete choices and accountable execution.

If you’re looking to uplevel product management leadership and bring more focus to product discovery and delivery, start by assessing your product strategy stack, then pilot NCTs in your next quarterly planning cycle. Tie every roadmap item to a narrative, stress-test commitments with real metrics, and empower teams to adapt tasks as insights emerge. The result is a more resilient roadmap, tighter alignment, and a team that consistently ships what moves the needle.

October 21, 2025
From Roadmaps to Sprints: Proven Tactics to Ship Software at Scale Without Chaos

I recently sat down with Snir Kodesh, Head of Engineering at Retool, a development platform for building custom business tools. Before joining Retool, he spent six years as a Senior Director of Engineering at Lyft. Coming from my vantage point leading product at HighLevel, I was eager to compare notes on what it really takes to ship software at scale without losing clarity, customer focus, or team morale.

We dug into the biggest differences between leading engineering teams for a consumer product versus an enterprise platform — and the patterns that hold true across both. Consumer surfaces demand rapid iteration loops and relentless UX polish; enterprise platforms demand configurability, security, reliability, and stakeholder alignment across buyers and users. In my experience, the constant across both worlds is crisp product management leadership: clear problem definition, tight feedback loops, and unambiguous ownership.

We pulled back the curtain on the software development cycle, starting with setting the product roadmap while balancing a diverse set of customer needs. On roadmapping, I ensure we explicitly identify who’s in the room to represent product, engineering and design, as well as customer-facing teams like support and solutions. The most effective sessions make trade-offs visible: we quantify impact, risk, and effort; we surface dependencies; and we align on outcomes before timelines. The result is not just a list of features, but a sequenced narrative that earns the right to build.

From there, we discussed how engineering takes that product roadmap and turns it into a concrete plan of action using the “try, do, consider” framework. I’ve found this framing incredibly practical: “try” creates space for low-risk experiments, “do” commits to high-confidence work, and “consider” tracks explorations that need more discovery. When sprint planning inherits this taxonomy, teams retain momentum without overcommitting — and leaders get a transparent view into where learning versus delivery is happening.

He makes the case for leaning on QBRs instead of OKRs. I agree that quarterly business reviews calibrate teams on real outcomes, not vanity metrics, and they naturally force prioritization around customer value. When we do use OKRs, we emphasize outcomes vs output OKRs so teams aren’t incentivized to ship volume over impact. In practice, QBRs keep us honest: what shipped, what moved the needle, and what needs to change next quarter.

We also tackled why scope creep gets a bad rap. In my experience, what’s labeled as “scope creep” is often legitimate learning uncovered through product discovery. The key is disciplined change management: time-box discovery, explicitly re-baseline when new information emerges, and separate must-haves from nice-to-haves. When done well, this turns surprises into strategic clarity rather than delivery risk.

On estimation, we shared practical tactics for getting better at estimating how long a feature will actually take to complete. I lean on reference-class forecasting (compare to similar past work), risk burndown charts, explicit buffers for integration and QA, and a habit of capturing deltas between estimate and actuals. Over time, this creates a trustworthy velocity signal and sharpens intuition across both product and engineering.

Translating the roadmap to sprint planning is where execution quality shows. We align on definitions of ready and done, maintain code review SLAs, budget a percentage for tech debt, and instrument everything so we can spot drift early. The “try, do, consider” framework maps cleanly to backlog hygiene, keeping discovery visible without derailing delivery. This is how we sustain speed and quality at scale.

Finally, we zoomed out to essential advice for engineering leaders — especially folks scaling quickly from leading a small team to a much bigger one. Shift from direct control to leverage: clarify decision rights, invest in Staff+ ICs, and scale communication through operating cadences, decision logs, and crisp narratives. Pair autonomy with accountability using QBRs, and keep product discovery tight to preserve customer empathy as you add layers. The goal is the same at ten people or a thousand: ship valuable software predictably, learn fast, and keep the team energized.

If you’re navigating the leap from product roadmapping to sprint planning, these patterns are battle-tested. Anchor on outcomes, use the “try, do, consider” lens to manage ambiguity, and treat scope as a living artifact informed by discovery. With the right rituals and metrics, you can ship software at scale — without chaos.

October 21, 2025