Good Growth Team, Great Growth Team

12 mistakes your growth pod will make, and how to fix them

Thank you Shreyas Doshi, Hiten Shah, Kate Syuma, Lilli Kulak for input.

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At peak, growth is your company’s greatest team.

Growth gets it done.

Other teams polish PRDs; growth ships. Core might launch 1-2x a month, growth launches 3-5x a week.

In doing so, growth delivers what every employee, investor, and even customer wants — growth.

Yet, many growth teams never reach legendary status. Leaders later lament, “Our growth efforts failed”.

Why?

Most growth teams play it too safe:

• They chase incremental wins, prioritizing certainty over impact.

• They play internal politics, paralyzed by dependencies.

• They focus on narrow metrics, ignoring the bigger picture.

Urgency and Impunity

Breaking this takes work.

Great growth teams don't operate within their roles. They break boundaries.

They step out of their comfort zones, and disrupt the comfort zones of others.

If every individual moves with urgency and impunity, the team outperforms.

Why does this matter? Quoting Matt Lerner in First Round Review:

Every great startup made wrong turns before unlocking hockey-stick growth.

How many wrong turns will your startup need?

As a thought experiment, let's imagine we know for certain that you need to make precisely 1,000 wrong moves, and, after 1,000 failed experiments, attempt 1,001 would be the one that catapults you to decacorn status.

If you knew that from Day 0, how would you run your business differently?

You would experiment like crazy. Every team. Ten tests per week — per employee.

Why not do that as fast as humanly possible?

In this essay, I break down the do's and don'ts for each member of the growth pod.

The mistakes are quintessentially human. Deep, emotional instinct around conflict, risk, and loss aversion, plus unchecked corporate rot, can decimate a growth pod’s impact.

We’ll first explore the do’s and don’ts, role by role, then unpack fundamental drivers.

Read this if you’re a founder, product leader, growth leader, or on a growth product team.

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Growth Pod Blueprint

I’ll focus on a growth pod’s four core roles:

• Product Manager

• Designer

• Engineering Manager/Tech Lead

• Data Scientist

Growth pods extend beyond these roles — into QA, marketing, support, and more. See Elena's write-up for more. But this is the core.

The pod is responsible for driving results. In small companies it’s "grow revenue". In larger companies, growth pods specialize: one owns acquisition, another activation, another monetization, etc.

The mistakes and fixes apply at every scale.

Do’s and Don’ts

Growth Product Manager

The Growth PM is the pod quarterback, holding strategic context and driving progress.

They frequently come from adjacent roles. Some were core PMs, while others were in service-oriented roles like data science or go-to-market.

1. Being too nice → Make bold swings
   PMs often default to cordiality — with leadership and with peers. This is most common in first-time Growth PMs who fear fumbling the bag. But so sayeth the proverb, “You can't make an omelette without breaking a few eggs.”
   
   Being too nice results in avoiding big swings. Great Growth PMs know nothing is off limits; everything is on the table. They should try anything that might drive results. This means challenging assumptions — including if the goal is even correct.
   
   Yes, it may be terrifying to tell the CEO you think you should focus on virality instead of activation. Or that core product needs an overhaul to unlock growth. But if you have conviction, it’s probably what the company needs. Great Growth PMs relentlessly make bold swings.
   

2. Trying to do it all → Push your peers
   Growth PMs often have a T-shaped skillset. As a result they end up ricocheting from minuscule task to task. A little design here, some analysis there, sprinkle in some code review. A customer call. Unblock on Slack. Prep the weekly update.
   
   Wait, where did the day go?
   
   Just because a Growth PM can do these tasks doesn’t mean they should.
   
   Great Growth PMs are expert at pushing their peers. They inspire others to tackle more, increase velocity, and improve quality.
   
   They push design to own solutions. They push engineering to own timelines. They push data science to own insights. Great growth PMs distribute workload, and create space for high-impact strategic thinking.
   

3. Analysis paralysis → Get out of the building
   It’s common for Growth PMs to think they can analyze their way to victory. Many are analytical and are comfortable crunching numbers.
   
   Yes, data is critically important. But it’s equally important to get out of the building and talk to customers. In an ideal world, every part of the growth pod talks to customers. But most growth pods are far from ideal, and the PM must be first to model this behavior.
   
   Great Growth PMs speak to 3+ new customers every week. The best move is putting discovery on autopilot, to never think about scheduling again.
   

Growth Designer

The designer brings ideas to life. They articulate a product you can touch and feel. Growth Design is a growing specialty; most designers working on growth will previously have been core product or brand designers.

1. Create polished UI → Rapidly explore UX
   Product design usually favors this workflow: deeply understand user problem → explore solutions. The designer goes deep.
   
   The failure mode is not stepping back and examining user flow. In growth, how it looks, sadly, rarely matters. Users care more about what they can do. Can they pay with Apple? Can they auth with Google? Was it easy to refer?
   
   Great Growth Designers spend minimal time on high-fidelity UI, and maximum time on low-fidelity UX. Instead of zooming in on pixels, they zoom out to the system. They think about multi-step journeys, flows, and loops. They polish only after validating impact.
   

2. Specialize in product → Own brand and product
   Many designers end up specializing — either in product areas, or disciplines of design. It’s common for an app designer to never touch the website, for example.
   
   This specialization is anathema to growth. Growth Designers must rapidly traverse surface areas in and out of the product. It’s critical to create engaging loops, regardless of where they are.
   
   Great Growth Designers tackle brand, marketing, and product. Great design teams enable this with clear brand guidelines, design systems, and a roster of contractors.
   

3. Design full solutions → Unblock engineering
   Last, designers may assume they’re responsible for delivering complete designs. This is common in core product where you usually do want to fully explore the feature before building.
   
   In growth, however, it’s critical to minimize time-to-experiment, to minimize time-to-learning. It’s most important to unblock engineering to start work. Kate Syuma: “In my team at Miro, we defined a principle: Think big, start small, iterate smart".
   
   When engineering begins, there are inevitably questions. Great Growth Designers work directly with engineers to unblock getting experiments live.
   

Growth Engineering Manager

Though pods obviously have many engineers, we focus on the lead. Growth Engineering is still maturing, and for now, most growth EMs came from core product teams.

1. Meet timelines → Beat timelines
   Most EMs earn the role from a track record of delivering scope, on time. This works in core product, where you need to deliver working features within a clear timeline.
   
   However, in growth, it’s critical to not just meet timelines, but to beat them. Growth is about rapid learning. An idea might be months of work — so it’s critical to figure out how to exert the smallest amount of effort possible to test if it’s worthwhile.
   
   Great Growth EMs internalize hypotheses, and are crucial in figuring out the smallest code change to test them. They then set and uphold aggressive timelines. The PM can relax, confident that the EM is paring back scope and accelerating work.
   

2. Operate the machine → Build a faster machine
   It’s common for EMs to see their role as running a prebuilt machine. Like other EMs in the company, they break down tasks, manage backlogs, provide updates. They attend daily standup, weekly planning, and many, many 1-1s. They sure as hell don’t ship on Fridays!
   
   Great Growth EMs don’t just operate the machine. They are constantly dissatisfied with it — so they build a better one. They question every step, every ritual, and every rule.
   
   They might accelerate task breakdown with AI, kill daily standup, and reduce 1-1s, all to boost velocity. They delegate, but judiciously — knowing it’s better to delete or automate. And yes, they ship on Fridays — to gain 20% more shipping time and 42% more experiment time.
   

3. Manage careers → Reward outcomes
   Finally, EMs commonly over-rotate on managing engineer careers. Especially as teams grow, EMs face increased upwards pressure to offer challenging work for career development.
   
   Great Growth EMs prioritize outcomes above everything else. They measure everything — from inputs like “time to first PR review” and “PR throughput”, to the output of business impact.
   
   Did an engineer review PRs within minutes? Did they ship twice the experiments as their peer? These efforts drive impact, so great Growth EMs reward these outcomes. And their engineers are delighted to deliver.
   

Growth Data Scientist

The Data Scientist (DSci) completes the growth pod quartet. Many DScis pivot to growth from product, marketing, or finance analytics.

Alarmingly, many companies overlook data science in their product teams. As a pithy example, many still label R&D teams “EPD” — engineering, product, design — excluding data science. But data science is non-negotiable for growth.

1. Service oriented → Strategic driver

   The first pitfall is when DScis are overly service oriented. Yes, they do serve insights. But this approach can lead to being omitted from critical conversations. Maybe they’re not in the “pod leadership” Slack channel. Maybe they’re only asked to analyze experiments once live.
   
   Great Growth DScis insist on a seat at the table. They’re part of key conversations. They input as much as their product, design, and engineering counterparts.
   
   They are expert at driving strategy and contributing ideas. They use data to argue against wasteful experiments, and advocate for those which seem more impactful. When an experiment wraps, they don’t just report results like a weather update. They drive momentum by identifying what we learned, and the next hypotheses to try.
   

2. Heads-down execution → Rigorous team execution
   A second pitfall is being overly heads-down. DScis are expert at extracting insight from messy data. So they might waste time analyzing an experiment that would never reach statsig. Or spend days teasing insight from botched telemetry.
   
   Great Growth DScis push the other way: upholding rigorous execution across the team.
   
   They challenge their counterparts. They insist on clear hypotheses, precise segments, meticulous telemetry. They venture into experiment docs, Figma mockups, and code review — improving rigor wherever they look. In turn, everyone benefits.
   

3. Gate-keeping insights → Widely shared insights
   Last, DScis may unintentionally gate-keep insights. Especially when they are afraid of declaring conclusions that might stir emotions in the org¹.
   
   In this failure mode, other teammates don’t know how things are going until they show up to the weekly meeting.
   
   This leads to a slow and stodgy culture. Teammates cannot contribute because they’re not in the feedback loop of “change → learn → decide”.
   
   Great Growth DScis spread knowledge relentlessly. They aggressively automate — for example, making A/B tests quick to launch, or creating automated Slack pulses. This frees up brain space to consider and conclude a “so what” for every analysis being run. Great Growth DScis ensure the pod and company learn at top speed.
   

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Fundamental themes

Of course, no one sets out to make mistakes.

So why do they happen in the first place?

1. Growth requires failure

Growth experiments have a naturally high failure rate. Companies commonly see 90% of their growth from 10% of their efforts.

As a result, solution quality matters much less than just getting to a solution. Because you don’t know, a priori, whether an effort will be part of that magical 10%.

This means every team member must change how they operate — strongly prioritizing rapid swings. This is diametrically opposed to core product, where careful execution to deliver quality features often wins.

2. Certainty stifles innovation

Humans are terrible at handling probability, especially in businesses. Leaders and Finance exert pressure on their teams to create certainty in their plans. Risk is unwelcome in the FP&A forecast.

This unwittingly stifles growth pod innovation and risk taking. If stakeholders expect certainty, will the growth pod bet on an idea that has a 10% chance at a 10x outcome? How about a 1% chance at a 100x outcome?

Leaders and Finance must fully internalize that they cannot expect initiative-by-initiative certainty from growth pods. They must instead ask how fast the team is moving, what we have learned, and how numbers are building over time.

3. Companies breed complacency

Companies reward harmony. They promote smooth operators. Dissent is discouraged, especially at scale.

This is self-fulfilling: larger teams obviously value attributes like teamwork and likability more than smaller teams.

But growth requires challenge. It’s part of the job to call into question assumptions, data, timelines, and more.

Productive tension is well understood in business. But growth thrives under heightened productive tension.

4. Career ladder blinders

Career ladders reward ICs who deepen their craft. Individuals are incentivized to get better at their thing. But a fundamental requirement of productive tension is having an opinion on what others are doing.

How cross-discipline are your players?

It’s normal for the PM to do “a little bit of everything”. So, does the designer read code? Does the engineer analyze data? Does the data scientist review mockups?

Growth teams flourish when each member casts aside their blinders, and dabbles in each discipline.

So what?

Founders, growth, and product leaders should pay special attention. You control the systems behind these fundamental themes, which in turn, result in growth team mistakes.

Fixing this requires changing the incentives you create.

Meanwhile, individuals on growth pods, ask yourself: do you resonate with these ideas? Do you naturally fight these themes? If so, you likely have Growth DNA: lean into it.

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Share this with your growth pod, and watch them find your million dollar opportunities.

1. The taxonomy of uncomfortable emotions a data scientist can unintentionally stir up probably merits its own write-up, but some select examples:

• Experiment everyone had high hopes for was negligible → disappointment

• Experiment a leader lobbied against was impactful → embarrassment

• Experiment shows another team is wasting their time → discomfort