Today, I sat down with Max Mullen, co-founder of Instacart, to dig into the craft of company culture with the precision it deserves. As a product leader, I’ve learned that culture is the operating system of the business—and Max’s journey from early generalist (running everything from product to payroll) to culture-focused executive offers a rare, tactical lens on how to build that OS with intent.
What struck me first was how deliberately he and the Instacart team approached company values. We unpacked the process behind defining distinctive principles—like “Every minute counts,”—and the mechanisms that ensure those values actually guide behavior. I shared how, on my own teams, we translate values into observable behaviors, interview rubrics, and operating rituals so they aren’t posters on a wall—they’re decisions in motion.
We then got practical about embedding values so employees truly feel connected to them. Max offered creative tactics that go beyond all-hands slides: narrative storytelling in onboarding, leader “value spotlights” in weekly reviews, and lightweight recognition loops that reward values-aligned choices. I added my playbook for hiring for values early on—using structured prompts, scenario-based assessments, and scorecards that map back to the behaviors we expect to see on day 30, 90, and 180.
From there, we dug into measuring culture—because what you don’t measure turns into mythology. We discussed using eNPS and pulse surveys, but also the importance of qualitative signals: skip-levels, anonymous async forms for hard feedback, and decision postmortems that reveal if incentives are aligned with stated values. I emphasized closing the loop publicly to build trust and make feedback feel consequential.
We also confronted the pitfalls that creep in as companies scale: easy-to-make founder mistakes, factions that emerge between early employees and newcomers, and the slow drift toward politics and bureaucracy. I shared a few guardrails I rely on: structured re-onboarding during hypergrowth, rotating “culture ambassadors” across functions, publishing decision logs for transparency, and codifying “how we decide” to reduce shadow politics.
The throughline is simple and powerful: founders and product leaders can and should take a deliberate role in shaping culture from day one. If you’re scaling now, run a quick audit: Are your values specific enough to create trade-offs? Do they appear in hiring, performance, and artifacts like PRDs and roadmaps? Can your newest team member explain how to live them in a tough decision? If not, you’ve found your next sprint.
You can follow Max on Twitter at @Max.
If you’re interested in learning more about how Cocoon makes employee leave easy, visit https://www.meetcocoon.com/
I was energized by the depth and clarity in this conversation. Today’s episode is with Dharmesh Shah, the co-founder and CTO of Hubspot. In today’s conversation, we deeply explore some of the marquee moments along the 15-year journey building Hubspot. From my vantage point leading product at HighLevel, Inc., I zero in on what product leaders can operationalize right away: co-founder alignment, deliberate operating systems, and engineering-driven culture.
Early in the discussion, Dharmesh unpacks the very specific way he and his co-founder Brian Halligan approached evaluating their compatibility as co-founders. As someone who has built and led cross-functional product organizations, I appreciated the rigor behind this compatibility testing—clear expectations, explicit decision rights, and pre-agreed escalation paths. My takeaway for potential founding pairs: align on values and working agreements up front to increase the likelihood of success and smoother sailing.
What keeps Dharmesh engaged after all these years are foundational building blocks that make the role intrinsically rewarding. I loved his approach to eliciting feedback through “bug reports.” Treating leadership behaviors and team processes like software defects creates a safe, systematic way to surface issues fast. Equally compelling is his decision to never take on any direct reports and remain an individual contributor as a co-founder; IC leadership can be a force multiplier when the organization designs clear ownership boundaries and high-bandwidth interfaces.
The most striking arc in the conversation is how he came to own culture at Hubspot, even as the self-described least social person at the company. He walks us through how he approached culture as an engineering exercise, which continues today in his assessment of the culture as a product. As a product creator, I resonate with this framing: culture needs a roadmap, measurable outcomes, and tight feedback loops—exactly the mechanisms we use to build world-class products.
For product leaders and founders, the practical playbook is clear: test co-founder fit early and explicitly, invite “bug reports” to de-risk blind spots, design IC leadership paths alongside managerial tracks, and engineer culture with the same rigor you bring to the product. These patterns improve product-market fit internally—within your org—long before they amplify results in the market. That’s the compounding advantage I aim to cultivate every day.
I’ve helped hundreds of early-stage startups build their positioning and brand strategy from the ground up, and certain patterns show up again and again. In this reflection, I’m sharing six early marketing missteps I see most often — plus the practical fixes I use with founders to sharpen positioning, clarify messaging, define brand personality, and orchestrate a high‑leverage launch strategy.
Early marketing can feel like changing the tires while the car is moving. You’re chasing product‑market fit while trying to define a category, articulate company purpose, and build a founder‑led GTM motion that actually converts. The good news: with a few repeatable exercises and a clear sequencing of work, you can avoid costly detours and get to traction faster.
Misstep 1: Chasing category creation too early. Defining a new category is tempting — it feels bold and visionary — but it’s often premature before you’ve nailed a sharp, undeniable problem. My fix: earn the right to a category by first winning a specific use case. Anchor your product positioning to an existing mental model customers already understand, then introduce the “newness” as a step‑change, not a wholesale reinvention. Category creation is a byproduct of repeated wins, not the starting line.
Misstep 2: Treating company purpose as a tagline instead of a true north. A purpose that doesn’t inform roadmap, pricing, brand personality, and go‑to‑market is just wall art. My fix: write a one‑sentence purpose that states who you serve, the change you enable, and why it matters — then pressure‑test every strategic decision against it. If it doesn’t help you prioritize features, target segments, or channels, it’s not actionable enough.
Misstep 3: Leading with emotional benefits while burying functional proof. Emotion matters for brand-building, but in the zero‑to‑one phase, customers buy outcomes. My fix: articulate a crisp value proposition that pairs functional benefits (time saved, errors reduced, revenue unlocked) with specific, credible proof points. Use customer‑validated messaging built from interviews, jobs‑to‑be‑done, and real usage data. Earn the right to emotion by proving the outcome first.
Misstep 4: Allowing brand personality to drift from the product and buyer. When brand voice doesn’t match the problem space or ICP, trust erodes. My fix: choose three core personality traits (for example: authoritative, pragmatic, optimistic) and define both what they are — and what they are not. Audit every touchpoint — website, onboarding, sales enablement, docs — to ensure consistency. This creates a brand people recognize and rely on across the funnel.
Misstep 5: Obsessing over other startup competitors instead of the status quo. The biggest competitor for most startups is inertia — spreadsheets, duct‑taped workflows, or “do nothing.” My fix: frame your positioning against the current workaround first. Show the switching ROI clearly, then differentiate from adjacent vendors. Use side‑by‑side comparisons that include the baseline status quo, not just other tools.
Misstep 6: Expecting PR to be a growth strategy. Launch theater can generate a spike, but it rarely produces sustained pipeline. My fix: treat launch as a process, not an event. Warm up your ICP with problem‑led content, customer stories, and social proof. Invest in owned channels (email, SEO, community) that compound. Set media expectations appropriately and measure what matters: qualified demand, activated users, and retained revenue.
To operationalize all of this, I use a simple positioning framework that keeps teams aligned: for [who], who [have this need], our [product] is a [category] that [delivers this outcome], because [proof]. Then we stress‑test with customers until the language is repeatable, the benefits are measurable, and the story is unmistakable across sales, marketing, and product.
If you want to go deeper into startup brand strategy, positioning, and messaging, I recommend these articles:
Founders who avoid these traps — and sequence brand strategy, product marketing, and go‑to‑market with discipline — build momentum faster. Do less launch theater, more customer‑validated messaging. Less category hype, more proof. That’s how you create a brand that compounds.
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.
I sat down with Steven Bartel, co-founder and CEO of Gem, to go deep on what really works when you’re making the very first critical hires in a startup. As a builder and operator, I know how much early talent decisions determine product velocity, culture, and ultimately whether the team can execute founder-led GTM with confidence.
Before building the talent acquisition platform, Steven was an early engineer at Dropbox, where he spent 5 years working on analytics, Dropbox Paper, and hiring as the company grew from 25 to 1500 people.
This experience from Dropbox, combined with his lessons from building out Gem’s own team and talking to his customer base of recruiters makes Steven the perfect person to talk to about early-stage recruiting.
In our conversation we focus on how to make those fourth, fifth, or tenth hires — those really early days when your startup has zero brand recognition or recruiting help. Here’s a preview of his tactical advice, paired with my product leadership lens on what to actually do next.
A trick for sourcing second-degree network connections. I’ve used this same approach to turn lukewarm interest into warm intros by mapping mutual connectors across former teammates, investors, advisors, and early customers. The goal is to engineer serendipity: stack-rank warm paths, ask for specific intros, and close the loop quickly with crisp role requirements and a two-sentence value proposition.
The power of sending a “break-up” message in your candidate outreach. When a candidate goes quiet, a polite, time-bounded note that gives them an easy out often re-engages the conversation. It respects their time, signals high standards, and creates a natural moment for them to opt back in—very similar to enterprise follow-ups in founder-led sales.
How Gem brought candidates on to work with them in very structured trial periods before making a full-time offer. I’ve found structured trials invaluable for de-risking early hires: define a scoped project, align on success criteria, and ensure tight feedback loops. This mirrors a product discovery sprint—short, measurable, and collaborative—while giving both sides a realistic preview of working together.
Advice for working on your recruiting pitch and nurturing passive talent. Your pitch should evolve like your product narrative: lead with the mission, the unique wedge, and the precise problems a candidate will own in the next 90 days. For passive talent, sequence lightweight touchpoints (demo the product, share a customer story, invite a technical deep dive) to build trust long before you ask for a decision.
The similarities between early-stage hiring and founder-led sales. Both require targeted prospecting, tight messaging, and rigorous follow-through. The best founders and product leaders treat recruiting pipelines like revenue pipelines—measure response rates, iterate on messaging, and run structured, time-boxed cycles to convert high-signal candidates.
If you’re navigating your first hiring wave, these principles will help you build a repeatable recruiting engine: amplify second-degree networks, use respectful “break-up” nudges, validate fit with structured trials, sharpen your pitch for passive talent, and apply founder-led sales discipline to every stage of the funnel. Do this well, and your early team becomes a durable competitive advantage.
I’ve learned that a startup’s trajectory often mirrors the strength of its co-founder relationship. With that lens, I sat down to unpack how to scale trust, decision-making, and speed between co-founders as the company itself scales.
Our guests are Manu Sharma and Brian Rieger, co-founders of Labelbox.
In this interview, I take a microscope to their co-founder DNA, exploring the ins and outs of how they’ve made the relationship work over the years.
We traced how Manu and Brian came together as co-founders and landed on the idea for Labelbox. That origin story matters: it reveals the early signals of shared conviction, complementary experience, and a clear problem thesis—foundations I look for when evaluating co-founder fit in any startup.
Before writing a line of code, they intentionally aligned their skillsets, values and responsibilities. I emphasize this step in my own product management leadership practice: make the invisible explicit. Define roles, boundaries, and how decisions get made while the stakes are low, so you can move fast when the stakes are high.
As the company grows, their rituals for spending valuable time together keep the relationship durable. They use thought-starter questions for deep discussions and even benefit from sharing an executive coach. I’ve seen this playbook consistently reduce friction: structured prompts surface misalignments early, while an external coach creates a safe container to reset, recommit, and keep momentum.
We also dug into how they run the executive team at scale and sketch out decision rights. Clear decision rights accelerate execution, prevent rework, and protect the co-founders’ relationship from getting pulled into every operational knot. In my experience, codifying who decides, who contributes, and how dissent is handled is one of the fastest ways to boost operating cadence without sacrificing trust.
Manu and Brian both offer practical advice to other founders—whether you’re in the early stages of looking for a co-founder or aiming to add a little magic to an existing partnership. If you’re building, apply their lessons: align on values early, institutionalize rituals, use an executive coach, and be explicit about decision rights. These are the simple, scalable mechanisms that preserve focus, speed, and resilience as you pursue product-market fit and scale your executive team.
You can follow Manu at @manuaero and Brian at @RiegerB on Twitter.
Founders often ask me how to navigate startup acquisitions without losing focus on product, customers, and culture. I view M&A as an extension of product strategy: it’s about creating long-term value, not just closing a deal. That’s why I study practitioners who’ve done it repeatedly and well—and few have a clearer track record than Daniel Debow.
I draw on insights from Daniel Debow, a VP of Product for Demand at Shopify. Daniel is a three-time founder and a seasoned M&A pro. Daniel oversaw the process of all three of his companies’ acquisitions and has helped continue to grow them at scale inside larger corporations. His most recent startup, Helpful, was acquired by Shopify in 2019. Before that, he co-founded Rypple which was acquired by Salesforce in 2011. His first startup, Workbrain, was acquired by Infor in 2007.
From my vantage point leading product teams, Daniel’s journey underscores a core truth: the moving parts of an M&A process as a startup demand the same rigor we apply to product discovery and go-to-market execution. When I’m advising founders, I concentrate on aligning strategy, timing, and relationships so the outcome—whether you sell now or later—remains squarely in your control.
First, I assess conditions at potential acquirers with the same discipline I’d use to qualify enterprise customers. I look for executive sponsorship, a clear product adjacency, an integration path (org and technical), and real ownership of outcomes post-close. If I don’t see resourcing commitments, aligned incentives, or a P&L that will house the asset, I assume the environment won’t be “founder-friendly.” On the flip side, established companies that want to be more founder-friendly should make the sponsor and decision-maker map explicit, publish their integration playbook, define success metrics early, and commit to retaining key builders.
Next, I differentiate between clear buying signals and the companies that are just “tire kicking.” Buying signals include rapid access to senior decision-makers, diligent technical and security deep-dives, direct discussions about deal structure and integration, and proactive work on a joint customer narrative. Anti-signals include vague interest without a timeline, refusal to share org charts or decision rights, and perpetual “one more meeting” cycles led only by corp dev. When signal strength drops, I reset expectations or pause the process to protect the team’s focus.
Relationships make or break outcomes, so I build meaningful relationships with executives of all types, not just corp dev teams. I cultivate trust with the GM who owns the P&L, the product and engineering leaders who will operate the asset, the sales leader who needs a story customers will buy, and the finance lead who models the upside. I share roadmaps, customer win stories, and integration hypotheses, then ask for honest pushback. This turns diligence into joint problem-solving and sets the tone for post-acquisition execution.
Finally, I’m deliberate about techniques for including your investors in the M&A process, as well as messaging tips when opening up about the process to the wider team. With investors, I align on valuation guardrails, role clarity in negotiations, and information sharing protocols. Internally, I limit the circle early, establish a single source of truth (a lightweight data room and weekly update), and script what we’ll tell managers if rumors surface. If and when a deal becomes likely, I plan retention, customer communication, and integration milestones concurrently so momentum carries through day one.
The through line in all of this: treat M&A like a high-stakes product launch. Validate intent, qualify the buyer, insist on ownership of outcomes, and protect your team’s energy. Drawing on Daniel’s example, you can structure an acquisition process that preserves optionality, increases deal quality, and—most importantly—sets you up to scale the impact of what you’ve built.
Culture is a company’s operating system, and documentation is the code that keeps it performant. As I lead product teams, I’ve learned that great cultures don’t just happen—they’re intentionally designed, scaled, and maintained. When founders and operators ask me which organizations model this best, Stripe reliably tops the list.
I recently sat down with Brie Wolfson to compare notes on how documentation, rituals, and communication norms shape high-velocity teams.
Brie spent nearly 5 years at Stripe, where she worked on bizops and launched Stripe Press, followed by a stint at Figma where she worked on education. She then started her consultancy, named The Kool-Aid Factory, to share her lessons on building team cultures. And now she’s operating as a first-time founder building Constellate, a new productivity and communications tool for teams.
In our conversation, we zeroed in on company culture—what it looks like when it’s working, how to codify it early, and how to scale it without diluting what makes it special. A decade ago, many teams tried to emulate the playbooks of companies like Google and Amazon. Today, a newer guard has emerged, and Stripe is often the culture benchmark that startups aim to emulate.
Brie peels back the layers into not just the cultural pillars that drove Stripe’s meteoric rise, but also how these showed up in day-to-day work.
We also zoom out beyond Stripe to talk about her work teaming up with companies with The Kool-Aid Factory, seeing culture and company-building up close. Brie shares advice on codifying your operating principles, establishing meaningful rituals, and growing this kernel of culture as the company scales.
Here’s what resonated most for me—and what I’ve seen pay dividends in product management leadership. First, treat kickoffs as the contract between intent and execution. A strong kickoff doc aligns on the problem statement, the “why now,” the DRI and decision log, risks and non-goals, and success measures tied to outcomes vs output OKRs. This single artifact becomes the source of truth for product discovery, scope decisions, and stakeholder communication.
Second, close the loop with retros that are structured and searchable. Think of retro docs as compounding assets: what worked, what didn’t, what we’ll change, and where decisions deviated from the kickoff. Over time, these narratives accelerate onboarding, reduce repeated mistakes, and strengthen operating principles.
Third, make Slack channels work like living documentation. Clarify a channel’s purpose, pin an index post, standardize naming conventions, and link to the latest kickoff and retro. When Slack is curated—not chaotic—it becomes a lightweight knowledge system that complements your docs rather than competing with them.
Finally, remember that rituals are the scaffolding for culture. Whether it’s weekly written updates, decision memos, or quarterly operating principle reviews, the goal is to make writing a team sport. Writing sharpens thinking, scales context, and reduces the cost of coordination as headcount grows.
If you’re building a product organization—or evolving from IC to manager—this playbook helps you replace ambiguity with clarity, reactive busyness with intentional outcomes, and scattered updates with a coherent, documented operating rhythm. Start with one ritual, write it down, and let the practice compound.
I recently sat down with Ben Lang, Head of Community at Notion, to unpack how a decentralized, bottom‑up community can power durable, compounding growth. In my day-to-day leading product, I’ve seen community-led growth move markets—hearing the detailed playbook behind it brought the strategy into sharp focus for operators and founders alike.
Since joining the company in 2019, Ben has had his hand in several high-impact projects at Notion that has grown its tight-knit community of passionate Notion evangelists into millions of users today.
But before he was doing this as a full-time job, Ben was already spreading his love for Notion in his free time as a voracious product user. After discovering the tool on Product Hunt, he became obsessed. He got on the company’s radar after launching his own Notion template gallery on Product Hunt and joined as one of the first 15 employees.
In our conversation today, we focus on the nuts and bolts of building a global community that drives user growth. Ben shares tactical advice on: Tackling community organically from the bottom-up, and why you shouldn’t go top-down; What companies are best suited to a centralized vs. decentralized community approach; Partnering with YouTubers and other creators; His advice to founders on finding your own first community hire.
Here’s my biggest takeaway on the bottom-up vs. top-down decision: bottom-up wins trust before it asks for anything. When you enable passionate users to teach, build, and share—then get out of their way—you unlock authentic advocacy that no paid campaign can replicate. Practically, this looks like community-led onboarding (templates, live office hours, and user-run meetups), lightweight governance (clear brand and safety guardrails), and a creator toolkit (assets, sample briefs, and success stories) that fuels developer evangelism and product discovery without stifling creativity.
On centralized vs. decentralized approaches, fit matters. Centralized communities shine when your product is compliance-heavy, your ICP requires curated expertise, or you need consistent, high-signal feedback loops. Decentralized communities thrive when your value compounds through remixing and sharing—think modular templates, integrations, and a vibrant ecosystem of product creators. My operating rule: start centralized for quality and learning, then progressively decentralize as playbooks harden and local leaders emerge. Instrument the handoff with clear roles, lightweight certifications, and community health metrics (activation, contribution velocity, and sentiment).
Creator partnerships—especially with YouTubers and niche educators—act as force multipliers. Treat creators like product partners, not channels: co-develop curricula, share early product roadmaps where appropriate, and equip them with data-backed talking points and reusable assets. Build a transparent value exchange (rev share, affiliate programs, early feature access), define success upfront (reach, engagement, and downstream activation), and keep content evergreen with updates tied to releases. The result is a repeatable growth loop that blends PLG, social proof, and zero to one B2B marketing.
For founders hiring the first community leader, optimize for a builder-operator hybrid: someone who has shipped programs, written docs, hosted events, and can close the loop from insight to iteration. Look for evidence of creator empathy, editorial judgment, lightweight product instincts, and the ability to scale through systems (templates, playbooks, and tooling). Define outcomes, not activities: measure community-led pipeline, activation lift, retention improvements, and the velocity of high-quality user feedback feeding product management leadership.
The throughline is simple: community is a product. Design it with the same rigor—clear ICPs, onboarding, retention hooks, and feedback loops—and it becomes a durable moat. Whether you lean centralized or decentralized, start bottom-up, enable your best users, and let creators help you tell the story the market actually wants to hear.
I recently sat down with Nadia Singer, Chief People Officer at Figma, to unpack what separates good interviewers from truly remarkable talent evaluators. As I reflect on my own hiring philosophy in product management leadership, her approach sharpened my lens for identifying signal over noise, eliminating bias, and scaling culture with intention.
Nadia joined Figma in 2020 and has seen explosive growth in her own career alongside the collaborative design platform’s. Before Figma, Singer was a talent expert who has hired hundreds of talented folks at places like Quora, Facebook and Google.
In our discussion, we dove into the patterns that consistently predict excellence. What resonated most was a simple yet powerful idea from her recruiter playbook: study how a candidate reaches an answer, rather than what they say. I’ve found this especially impactful when hiring PMs and cross-functional leaders. Rather than celebrating the “right” conclusion, I push candidates to narrate their reasoning, make trade-offs explicit, and surface assumptions—revealing structured thinking, customer empathy, and learning velocity.
To operationalize this, I ask candidates to walk me through ambiguous product decisions: Which constraints did you prioritize and why? Where did you seek disconfirming evidence? How did you iterate when new data emerged? I’m listening for clarity of problem framing, the ability to quantify impact, and the rigor of decision-making under uncertainty. The outcome matters, but the method matters more.
We also explored tactics interviewers can use to avoid pattern matching and other biases. In my teams, that starts with a role scorecard that defines the core competencies up front (not resume proxies), structured interviews with consistent prompts, and independent scoring before any debrief. I’m deliberate about diverse panels, rotating interviewers to reduce shared blind spots, and separating signal (evidence-backed behaviors) from story (polish, pedigree, or charisma). In debriefs, the most senior voice speaks last, we anchor on evidence tied to the scorecard, and we explicitly call out potential biases when they appear.
Another theme was learning from early missteps in recruiting. I’ve made many of the common mistakes: over-indexing on pedigree instead of proof of outcomes, letting hypotheticals outweigh real-world execution, asking leading questions that telegraph the “desired” answer, and failing to define success criteria before meeting candidates. The fix is discipline: better prompts, deeper follow-ups (“tell me about a time…” with measurable results), consistent rubrics, and a higher bar for reference checks that validate how someone collaborates under pressure.
Finally, we discussed ways that Figma tweaked its approach to culture so it could scale alongside the company. My takeaway: culture scales when it’s operationalized. Codify a few non-negotiable principles, translate them into observable behaviors, and weave them into hiring rubrics, onboarding, performance management, and rituals like product reviews. As the organization grows, refine language—without diluting standards—so new teams can apply the same principles to different contexts.
If you lead hiring for product or adjacent functions, here’s the throughline I’m taking forward: raise the bar on reasoning, not rhetoric; design interviews that produce comparable evidence; and treat culture as a living operating system, not a poster. That’s how you consistently spot high-agency, high-learning talent—and build teams that compound value over time.
I’m often asked how elite teams compress the journey to product-market fit. One story I keep returning to is Jessica McKellar, co-founder and CTO of Pilot, which is the largest accounting firm for startups. For the past six years, she’s built Pilot alongside her two co-founders, Waseem Daher and Jeff Arnold — and what makes this trio extraordinary is that they’ve stuck together across three startups.
As repeat founders, the team learned a ton from their first two ventures, K Splice and Zulip, and both netted some positive outcomes. Yet there were mistakes that prevented those products from becoming an outsized success. From a product management leadership perspective, I see a clear evolution in how they approached problem selection, product discovery, and go-to-market.
With Pilot, they prioritized picking an acute problem and a huge market to tackle. That simple but rigorous reframing matters: identify a customer segment with a painful, high-frequency workflow; quantify the market; and ensure a compelling “why now.” This is classic founder-led GTM discipline and the essence of practical product-market fit lessons.
They also embraced a deliberately tedious build process for v1: looking over Waseem and Jeff’s shoulders as they manually did the bookkeeping for early customers, while she wrote code alongside them. In my experience, this “do the job, then automate” approach functions like forward deployed engineers for founders — embed with the real workflow, capture edge cases, then translate that knowledge into the system of record.
Even going back to the earliest days, Pilot had some really strong product-market fit signals, with customers agreeing to pull out their credit card and pay for the product right away when it was just an idea on paper and eventually pulling the Pilot team into expanding their product suite. That willingness-to-pay signal, coupled with pull-based requests for adjacent capabilities, is exactly what I look for before scaling zero to one B2B marketing or hiring beyond the founding team.
My playbook from this story is straightforward: choose a narrowly defined, acute pain in a massive category; run founder-led discovery inside the customer’s workflow; ship code alongside the service until the workflow is reliable; price early to validate value; and align outcomes vs output OKRs so the team optimizes for customer impact, not feature volume. Do this, and you convert messy service learnings into a repeatable product engine.
Make no mistake about it — being a founder is incredibly difficult — but choosing the right problem to tackle can drastically smooth the path ahead of you. For product creators, that choice — and the discipline to live in the customer’s workflow early — is the difference between meandering and momentum.
Expanding from a single hero product to a resilient multi‑product portfolio is one of the most consequential moves a SaaS company can make. I’ve navigated this shift firsthand and studied how leaders approached it at companies like Stripe and Watershed. What follows is the playbook I use to assess new product ideas, structure teams for 0‑1 execution, and run rigorous product reviews without losing momentum on the core business.
I start by clarifying the type of multi‑product strategy we’re pursuing. Are we building adjacent features that deepen adoption, launching true net‑new products for new buyers, extending a platform with new primitives, or assembling a bundle that compounds customer value? That choice dictates everything else—resource allocation, hiring profiles, team topology, and the shape of our product discovery.
Stories from Stripe’s multi‑product success reinforce a principle I believe deeply: launch with small, high‑trust teams and a brutally clear problem statement, then iterate fast with real customers. When adding products like Stripe Billing and Stripe Treasury, the work required not only great execution but also adapting to new buyer profiles and purchasing motions. The lesson I apply is simple—don’t assume the new buyer is just a variant of the old one.
Resource allocation is where strategy meets courage. I protect the core product’s roadmap while ring‑fencing a few exceptional builders to pursue secondary bets. These squads operate with clear, outcome‑based goals and tight feedback loops, not sprawling OKR spreadsheets. The aim is to make small, reversible bets at first, then scale conviction with evidence—market pull, repeatable use cases, and early revenue signals.
Team structure matters even more than headcount. I form new‑product squads that behave like a startup within the company—full‑stack ownership, minimal dependencies, and direct access to customers. The early team must combine product discovery instincts with the ability to ship. Great early‑stage product thinkers show crisp problem framing, a bias for learning, and the humility to change course. One common fail‑case I watch for is hiring purely for potential over demonstrated ability to drive ambiguous work from zero to one.
Hiring the right people for 0‑1 work is its own craft. I look for signals of self‑direction, obsession with customer outcomes, and the ability to reason from first principles under uncertainty. I use five interview questions to unearth hidden talent among product candidates, all designed to reveal how they validate problems, reduce scope intelligently, earn trust with engineers, and handle the uncomfortable middle of product discovery.
Even the best teams stumble when product, packaging, and go‑to‑market are misaligned. I’ve seen what happens when an organization assumes the existing buyer will adopt the new product in the same way—pricing misses the mark, activation drops, and sales enablement lags. The fix is to revisit the buyer, refine the value proposition, and rebuild the path to value so the first‑run experience matches the new buying journey.
To keep new bets honest, I treat them with “definite optimism”—a clear, written view of what success looks like and a pragmatic path to get there. I focus on the sequence of proof: problem validation, consistent user pull, and evidence of repeatable adoption. In a new or early market, I combine a methodical approach (milestones, stages of validation) with analytical rigor (leading indicators, customer expansion patterns) to decide which products to prioritize and when to scale.
Goal‑setting for new products must be measurable yet forgiving of discovery. I favor outcome‑centric checkpoints over vanity metrics, and I evaluate bets by expected learning speed and cost of delay. This keeps us moving fast without confusing activity for progress.
My product reviews are anchored by 12 questions that force clarity on problem, user, value, and risk. I often share these questions as a pre‑read so teams can self‑diagnose and come in focused on decisions rather than updates. “The Enterprise Rent‑A‑Car Story” is a helpful reminder for me that distribution and execution are as decisive as the product idea itself. When building for net‑new‑customers, I re‑focus the questions on buyer change, activation friction, and early‑life cycle signals.
User feedback is the lifeblood of 0‑1. I collect inputs across interviews, product analytics, and support tickets, but I interpret them through the lens of the problem statement rather than raw feature requests. Product development must start with problem validation; otherwise, speed becomes a liability and discovery masquerades as delivery.
I also learn from builders who think in systems and act with urgency. Jack Dorsey: https://twitter.com/jack. Patrick Collison: https://twitter.com/patrickc. Shreyas Doshi: https://twitter.com/shreyas. Their public writing on product strategy, execution, and outcomes vs output informs how I evaluate talent, decide what not to build, and keep teams aligned as we scale beyond one product.
