I started my product career at Swedbank as a business analyst in a team working with a few popular internet banking products across the Baltics. I was motivated - in the way only someone early in their career can be -convinced I was about to build things that would genuinely matter to people.

The excitement dissolves fast. In regulated business you’ll surely find yourself juggling among a range of wild requirements: starting from impossible deadlines from regulatory authorities, to some top-down decisions - which engineering teams do not quite buy in.

You are a smashing success if you manage to scope down the massive deliverables to reasonable requirements, and manage the skyhigh expectations of stakeholders across multiple business domains and layers of hierarchy. But, then!

You’ll most likely be hit with a few waves of framework updates (think of one battle after another), followed by consequential small reorg which brings some degree of disruption, resistance and anxiety within the teams. When it comes to people - a cultural change - you’ll obviously have an expensive consultant brought in to implement something complex that's supposed to magically fix everything. Disruption, resistance, anxiety. Repeat.

None of this is unique to Swedbank. It's simply what large organisations do.

I gained valuable experience as a Product Owner there. It's a fail-safe environment to start a product career - structured, guided, and low-risk by design. Extensive processes absorb mistakes before they happen. Maintaining a beloved brand for millions naturally makes the status quo the priority.

The cost of safety

Stability comes with a price. Risk appetite is low, and changes pass through layer after layer of approvals before they ever land with the product owner and engineers — who are handed only the execution. Discovery, the problem space, real customer insight — none of it exists in that setup. Decision-makers can become surprisingly disconnected from what’s actually happening on the ground.

At some point, I’d read enough Marty Cagan to know: sooner or later, I’d move somewhere the work I cared about was actually possible.

The other side

Looking back, having worked as a Product Manager at a fintech company for almost 2 years, it amazes me that I learned so much more about the real world!

Now I don’t have a polished framework or a process workflow that makes decisions for me, but I do have to make bets under uncertainty. I have the privilege of talking to customers about their problems, watching them be remarkably polite and friendly even while describing how much they struggled with a feature we haven't gotten around to fixing yet. Uncomfortable - but deeply insightful.

Product discovery and navigating the problem/opportunity space is the most valuable thing a PM can do. If we know what the biggest problems are, we already have half the solution. We can cut through the noisy backlog and identify the 20% of ideas that actually move the needle. That's the mission.

Product teams, together with customer support, are best positioned to understand customer problems in the most nuanced and intimate way. Customer interviews build real context. We have a good understanding where the customers struggle most, what moves the needle for many customers and therefore for our business. Knowing problems takes you to experimentation. We might know what the problems are, We won't build anything until we've validated the problem and experimented on possible solutions.

Why fintechs win

Most of what I've described is simply unthinkable at a traditional bank. Decisions about what to build or fix rarely sit with the people closest to the product. Empowered teams, experimentation, real discovery work - these are hard to achieve inside structures designed to protect stability above all else.

That's why fintechs and neobanks will continue to disrupt traditional banking - and with AI-assisted development accelerating the pace of shipping, that gap will only widen. But the disruption won't come from technology alone. It'll come from organizational philosophy. The engine of that disruption is empowered teams - people with real ownership, real responsibility, and genuine closeness to the customer. Not process-driven feature factories.

The verdict

Here's what that looks like in practice. A product engineer noticed something that wasn't right for customers. They raised it at the team's retrospective. The team made a decision the same day. By the next afternoon, the fix was live. Zero approvals.

In a bank, the risk of moving that fast feels enormous. In an empowered team of domain experts, the upside is bigger.

Fair warning - I leaned into the drama deliberately. I want my writing to entertain as much as it informs, and I hope you had as much fun reading this as I had writing it.

So, for anyone who’s comparing the two - both are valuable stages of a product journey. A Product Owner role is a solid starting point - but it's a ceiling for anyone ready to do real product work and get close to actual customer problems. For that, you need a seat at the table where the real decisions happen.

I started in 2022 with a focused task: launching a payment method MVP in two Nordic markets—Norway and Sweden—serving about 1,000 users per month across two clients.

As I gained experience, I took on broader scope. In 2023, I moved into a new product area and took responsibility for a product used in 9 markets across the Nordics, BENELUX, and DACH, supporting around 6 million customers and 11 million invoices per year. Later that year, my team merged with another, adding five people and extending my responsibilities to include customer communication topics.

In 2024, I transitioned to a growing product that was live with only a few clients but already served 2.6 million customers per year, with the goal of preparing it for expansion into new markets. In summer 2025, alongside my PM work, I took on the Interim Product Lead role for a team of five product managers during a parental leave. Most recently, I also assumed ownership of a major product serving 6.42 million customers annually for a single client.

What started in the Nordics soon expanded into markets with completely different expectations, regulatory landscapes, customer behaviour patterns, and revenue dynamics. These transitions pushed me to find a consistent way to learn fast and navigate new domains effectively. Over time, this evolved into a practical framework that helps me onboard unfamiliar topics, understand the new environment.

Below, I’ll outline the techniques that shape this approach

1. Start With the Business Goals

Every product exists to generate value, and understanding what “value” means in this new context becomes my starting point. Hence, the first step is always to ground myself in the business goals. I begin by identifying the core KPIs that define success in my role and exploring how the product contributes to the wider company strategy. At the same time, I look at the existing backlog to see whether there are initiatives prepared by others that I can pick up quickly. These early insights guide my decisions long before I make any changes or propose new ideas.

Example:

When I took over a new product, it became clear that efficiency metrics were the strongest drivers of value. The product had been on the market for years, so the biggest gains lay in optimisation rather than new features. Understanding this early helped me focus on improving performance and reducing operational costs instead of chasing unnecessary innovation.

2. Understand Your Manager

Your relationship with your manager plays a huge role in your success—not only in what you deliver, but in how effectively you can navigate the organization. Each manager has their own priorities, pressures, and expectations, and I was hired—or moved—into the role—to help achieve them.

I take time early on to understand what success looks like from their perspective: their goals for the product, their expectations for my first months, and how they envision the team evolving. But beyond goals, it’s also important to understand how they work. I observe their communication style, clarify how they prefer to receive updates, and discuss how we make decisions together. Important here is also to be very clear on what I need as a professional to succeed on this journey. Do not be shy! Success of your onboarding depends on a million factors but also your approach.

Building this relationship on trust, empathy, and clarity not only aligns our objectives but makes collaboration smoother. This alignment reduces friction, increases transparency, and accelerates the moment when both of us can operate at full speed.

Example 1:

As someone who thrives in chaos—juggling several projects at once and keeping everything aligned—I rely heavily on understanding context, background, and detailed nuances. The fastest way for me to ramp up is essentially a “brain transfer” from someone who has lived the problem space longer. In my case, my manager is exactly that person. For him, what matters most is that the needle moves quickly. To support both our styles, we set up a weekly deep-dive session where I can ask all my “million questions,” clarify assumptions, and connect dots. On top of that, he makes it clear that I can reach out anytime during the week, which creates an open channel that accelerates learning and builds trust.

However, I’ve also been in setups where a manager simply didn’t have the time to invest in regular knowledge transfer. In those cases, the approach from section 3 becomes essential: finding additional sources of information, tapping into experienced colleagues, and mapping stakeholders to uncover the context you can’t get directly from your manager.

Example 2:

I know that for my manager it’s important to hear about incidents or major issues directly and to stay closely informed. Because of that, I make a conscious effort to update him proactively whenever something critical happens. And yes, sometimes the instinct is to wait until the problem is fully resolved before sharing anything but keeping him in the loop early builds trust.

3. Know Your Customers

It’s widely accepted that you can’t build products people value without understanding the people who use them. In every product area I entered, I made it a priority to learn who my customers are and what they need. I looked at the most common customer support questions to identify recurring pain points and patterns, which helped me map the problem space more clearly.

Whenever language allowed, I spoke directly with customers through interviews. When it didn’t, I coordinated interviews through colleagues or external support—an experience that motivated me to start learning German so I can eventually speak with customers firsthand.

Understanding customers isn’t a one-time activity; it’s the foundation for informed decisions, especially when stepping into a new market or product domain.

4. Map Your Stakeholders

Although I shifted roles and scopes several times within the same company, my stakeholder map was never the same twice. Each product, each team, and each initiative introduced a completely new constellation of people, dynamics, and decision-making patterns. That’s why I always start by building a stakeholder map in Miro as a mind map—capturing not only names and titles but also the real dynamics: who actually makes decisions, who influences them, and who shapes conversations behind the scenes.

I followed the same approach even during my four months as an interim Product Lead. The role was temporary, but the need to understand the ecosystem quickly was just as important. To do this well, I always rely on someone who has been in the organization longer. They can explain the unwritten rules—the relationships, alliances, and power structures that never appear on an org chart. Often, this person naturally becomes a mentor, helping me navigate nuances and avoid common pitfalls.

While mapping stakeholders, I also make a point to ask about past projects, especially the ones that struggled or didn’t go as expected. These stories reveal a lot: where collaboration broke down, who needed more support, and which relationships require extra care. This context helps me understand whom I need to “give more love” to and who might become a strong partner moving forward.

Example:

During one of my role shifts, I learned that the Key Account Management team had a long list of frustrations about the product—missing documentation, unclear processes, and a general feeling of being left out of important updates. Hearing this early in my onboarding helped me understand not only their pain points but also the historical context behind the tension. It immediately showed me where to invest time, rebuild trust, and strengthen collaboration. This insight only surfaced because I proactively asked about past challenges while mapping my stakeholders.

5. Build the Relationships That Matter

With this context in place, I invest deliberately in building the relationships that matter. Collaboration is essential, especially when you’re new, and strong relationships multiply your effectiveness long before you make your first major product move. I focus on establishing genuine, trust-based connections with colleagues—not just understanding their roles, but also what motivates them and how we can support each other.

As a next step, I schedule individual calls with key stakeholders to get to know them personally and understand their perspective on the product and our collaboration. I usually ask three core questions:

1. What are your expectations from a Product Manager in this scope?

2. What is not working as expected or currently holding you back?

3. What should I be aware of—past challenges, ongoing concerns, or dependencies—that can help us work better together?

And whenever I’m in the office, I take the chance to deepen these relationships even further. I schedule lunches, grab a coffee, or organize a casual after-work drink. These informal moments often reveal more than formal meetings: they help build trust, uncover context, and create the kind of rapport that makes collaboration smoother and more effective.

Example:
I also learned early on that the QA team was an extremely scarce resource and often became a bottleneck. To avoid adding pressure and to secure the support I needed, I scheduled a get-to-know call with the QA lead. That conversation helped us establish clear routines and agreements on how to plan testing needs in advance. As a result, I could access QA support when required, while the team remained protected from last-minute stress and overload.

6. Execution in parallel with high standards

Once these foundations are in progress, the shift from onboarding to doing becomes much smoother. With clarity on the goals, the people, and the organizational landscape, I can prioritize effectively and deliver early wins that build credibility. At the same time, I keep learning loops actively observing, asking, challenging, and refining. Mastering a new product or domain is never a one-time effort; it’s a continuous cycle of understanding and adjusting.

From the 4 points above, I already have a huge backlog of items to prioritise from, I pick the ones that contribute to the main KPIs the most and do not have the longest time to market.

And here is something I believe strongly: first impressions matter. A product manager’s early reputation is shaped by how they manage their “brand” inside the organization, how visible their work is, how clearly they communicate, and how reliably they follow through.

I’ve seen many early-career PMs dive deep into execution, successfully launch something, and then unintentionally undermine their impact by neglecting communication. If no one knows what you’re doing or why it matters, it’s much harder to build influence and trust.

Example:

One of the very first things I did in a new PM role was launching an A/B test. And as we all know, A/B tests take time: you set them up, wait for results, and only then make a decision. To avoid leaving stakeholders in the dark, I proactively shared the plan, the timeline, and the key milestones with a broad stakeholder group. Throughout the process, I kept them informed about the progress and interim findings. It took only a few minutes each time, but it made a big difference. The feedback I received later—even during promotion discussions—highlighted that people felt informed, confident, and included. Those “small” communication habits ended up contributing significantly to my growth.

7. Well-Being: Navigating the Emotional Side of Change

When I was starting my career—and honestly, up until about two years ago—these constant changes and shifts made me incredibly stressed. Each new product, each new team, and each unfamiliar domain triggered the same pressure: I need to prove myself again. That feeling can be overwhelming, especially when you’re driven and ambitious.

And who am I kidding? It still happens sometimes. The difference now is that I’ve become more mature in how I handle stress.

A big shift for me came from feedback my manager once shared:
“Please watch out for yourself in terms of sleep and health. Don’t let your high ambitions become the blocker to achieving them.”

It struck me because it was true, I was pushing myself so hard to succeed that I was undermining my own performance. That feedback became a reminder that resilience and well-being are not “nice to have”; they are fundamental to sustaining impact.

Today, I try to build routines and boundaries that support me rather than drain me. I do not skip meals, I do things that I am excited about after work, like organizing community events, writing an article like this, mentoring a couple of amenities, doing regular sports and unwind with friends. I stay aware of my energy levels, make space for recovery, and accept that onboarding into something new is demanding—not because I am unprepared, but because growth always feels like stretching.

Looking back, what once felt overwhelming now feels energizing. Each transition that initially brought uncertainty eventually became a source of confidence. Every new market, every new team, every new responsibility stretched me—and then strengthened me.

To sum it up, below is a framework for stepping into new product domains, moving from understanding business goals and leadership expectations to customers, stakeholders, relationships, and execution. At its core, continuous learning and well-being create a sustainable cycle that turns uncertainty into confident impact.

There’s something deeply rewarding about stepping into the unknown and slowly turning confusion into clarity. About walking into conversations where everything feels complex and, a few months later, being the person who brings structure and direction. That transformation never gets old.

Today, instead of fearing the next shift, I’m curious about it. I know there will be moments of doubt. I know there will be steep learning curves. But I also know that I have a way to navigate them.

If you’re about to step into a new product, a new team, or a bigger scope, I wish you courage. Good luck! You’re more ready than you think.

🎁 We’ve got an early gift for you: fresh salary data from 79 product professionals across Estonia. Curious how you compare to the market?

In November 2025, our third annual salary survey reached product people through the Tallinn Product People WhatsApp group, TPG newsletter, and LinkedIn. We asked about salary and compensation, company context (size, industry, maturity, working arrangement), role and experience level, notable career events from the year, and more. Here’s what we found:

Open Product Salaries Full Report

TL;DR: Average salaries (gross / month)

• Product owner - 4300€

• Product manager (individual contributor) - 4400€

• Senior product manager (individual contributor) - 5600€

• Senior product manager (people lead) - 5900€

Want a detailed breakdown of salaries by experience, gender, company context and more?

Open Product Salaries Full Report

A word of caution

Titles in product are notoriously inconsistent. You might be hired as a product manager, do the work of a product owner, and get called a project manager all in the same week. While we, product people, care deeply about our titles, the rest of the organization often doesn’t distinguish between them. This ambiguity contributes to the wide salary ranges you’ll see in the data.

The same applies to seniority levels, which vary dramatically by company size. Moving from a startup to an enterprise company might mean losing your ‘senior’ title, or vice versa. These numbers tell a story, but it’s more complex than any spreadsheet can capture.

Who knows, maybe we’ll add questions about impact and scope next year to dig deeper into what these titles really mean.

Until then, enjoy exploring the data and happy holidays! 🎄

PS. If you found this useful, forward it to a fellow product person who might benefit from the salary benchmark.

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Still brutal. Still competitive. Still a place where “mid-level PM seeking relocation” might as well be your Tinder hell because everyone is swiping left. (That’s how I imagine CV check)

If you’re mid-PM and searching for your next role, settle in. Here are 3 stories — two perspectives, and tons of insights - 2 from job seekers, and 1 from recruiters. All for you, my fellow PM warriors wandering the job market desert.

Story 1: From Tallinn to Berlin—My 6-Month Emotional Endurance Test

Iurii Teslia - Product Manager with a strong Engineering background

The Background

After 8 years as an SDET, I made the career change to Product Manager within my company in Tallinn. Having built my own products on the side gave me practical experience that would prove invaluable. When I decided to relocate, I set my sights on Central European tech hubs: Krakow, Warsaw, and Prague.

Beautiful cities. Great tech scenes. Cheap beer. What could go wrong?

Ah, yes. Everything.

The Reality Check

Six months. 130+ applications → 4 interviews processes → Zero relocation offers.

The most common response?

“We’re only hiring candidates already based in this location.”

Companies (at least in these locations) no longer needed to offer relocation packages—they had plenty of local talent to choose from. Yet, I have a couple of interviews and even 1 on the final stage. But yet, in the end a local candidate has been chosen.

Side Note - I need to be honest: I was also going through some changes in my personal life during this period. My focus wasn’t entirely on the job search, which likely affected my results. But the market conditions were undeniably difficult.

The Breakthrough

After months of rejection, I pivoted my strategy. I applied to a couple of positions in Berlin—a city I hadn’t initially considered. Another opportunity came from a friend who referred me to their company for a fully remote role with potential relocation (though not to my preferred countries).

What happened next surprised me: within two weeks, I had interview processes running simultaneously at both companies.

• Company A (Remote): Just 2 interview rounds, followed by a pre-offer

• Company B (Berlin): 7 interview rounds, but remarkably, all compressed into 1.5 weeks once they learned I had another offer on the table

Both companies extended offers. I chose the Berlin position as a Technical Product Manager, finally achieving my relocation goal—just not to the city I originally planned.

Key Takeaways from My Experience

• Leverage referrals: Your chances of getting noticed for initial interviews increase dramatically with an internal referral

• Build your own products: Side projects strengthen your resume and give you hands-on experience to discuss in interviews

• Practice interviewing: Apply to companies you’re less interested in or schedule mock interviews to develop your interview skills

• Be flexible with location: Sometimes the right opportunity is in a city you hadn’t considered

• Having competing offers accelerates processes: Once I had a pre-offer, the other company moved remarkably fast

• Build your network in target locations: Referrals help you get noticed, but personal connections matter even more. Join local communities, speak at conferences, or connect with people at your target companies—it’s absolutely worth the time and effort. (Some of interviews I got though my personal contacts with people in local communities)

Story 2: “The Bathrobe, The Spreadsheet, and The European Job Hunt” — A PM’s Tale

Natalia Tykhonravova - Product Manager, Casino domain

The Funniest Interview & The Red Flags

I still haven’t had a properly funny PM interview — no one has asked me to design a toaster for astronauts yet — but I did once interview a senior developer who joined the call wearing what I thought was a very fuzzy sweater.

Spoiler: it was a bathrobe. A deeply confident bathrobe.

As for red flags, the classics never disappoint:

• “Here we love intensity!” → Translation: We burn out together like family.

• ‘Overtime is normal here.” → Translation: You’ll live here.

• Unprepared interviewers reading questions like they found them on ChatGPT five minutes ago.

My Job Search Strategy (a.k.a. My 7-Year Tracking Spreadsheet)

My strategy started with a Google Doc back in 2018. You know how some people track workouts or spending? I track recruiters.

Every company, feedback, stage, salary expectation — documented like I’m preparing for a court case.

Usually, it takes me 2–3 months to land a role, so the spreadsheet keeps me sane.

Over time, I added a portfolio — real projects, with real metrics, so I could say things like:

“Here’s something I didn’t just talk about, I actually did.”

Switching industries? That’s trickier. The portfolio must be adjusted to what the new industry values. For example, for Fintech, it’s more challenging because all my showcased projects are from the iGaming industry.

What Actually Helped Me Get Offers

My winning combo this year was:

• A real portfolio (what, why, how, metrics, the whole PM circus)

• Stalking interviewers on LinkedIn (professionally!)

• Real prep — reading company news, checking their socials, googling things like “What does this company actually do?”

This last time that I was searching for a job, my tactics and approaches included adding a portfolio with projects I’ve done to showcase my expertise based on real data and real use cases. For example, in my portfolio, I tried to answer a few key questions: what was done, why it was needed, what my role was, and what the outcomes were based on success metrics.

Also, one of the tactics is thorough preparation for the interview. It might sound very obvious, but people often don’t google that much about the company or the interviewers. I try to read news about the company, check their social media, and if I have the interviewers’ names, I look them up on LinkedIn to see if we have anything in common or to understand their background. It’s usually very interesting.

“It is crucial to check and understand the product as well. Once CEO asked me do I know their products or not.”

Another tactic is to be as genuine as possible so that the people who are going to hire me can see straight away who they’re dealing with. That way, it’s not a surprise later if I have a weird sense of humor or if I’m very straightforward. It takes a bit of bravery to honestly share past challenges and how I dealt with them, but in the long run, it pays off.

My Advice for Mid-Level PMs Interview Prep

• Think long-term, not just “I need a job next month.”

• Build your personal brand, share achievements, post certificates, show that you’re alive and learning.

• Network even when you don’t need anything. Your future self will thank you.

• And please — get curious about different cultures. European teams can include 10 nationalities in one Zoom call. Understanding how people think and work is half of the job.

This time, I prepared for interviews using ChatGPT. I also had a very helpful catch-up with a friend who had started interviewing a couple of months before me, and he gave me great hints about what interviewers might ask and how to prepare.

The only challenge was remembering every detail about each company so I wouldn’t accidentally mention something from one interview in another :)

As for questions that caught me off-guard, one memorable example was when HR asked: “What kind of people are the most challenging for you to work with?” I had to think about it, but I had a good example. I mentioned a conflict that happened a couple of years ago when I was working as a QA Team Lead. I was very honest and explained that at the time I didn’t handle the conflict properly, but I learned a lot from it. I also said that if the same situation happened now, I would approach it differently.

Even if you get a question that surprises you, answering honestly is the best strategy. As long as you show that you can learn from difficult situations and improve over time, it’s totally fine. Making mistakes is okay — not growing from them is the actual problem.

Story 3: “Rickrolls, PM Titles, and Visa Gods” — A Recruiter’s View of Hiring Product Managers

Joanna Dobosz - Senior Recruiter @ Bolt

Funniest Resume & The Simplest Red Flag

Let me start with the highlight of my career so far: the funniest resume I’ve ever seen.

One candidate sent their application with a “cover letter” containing exactly one line - a legendary lyric from an iconic 80s hit:

“Never gonna give you up, never gonna let you down.”

No explanation. No context. Just a full Rickroll in the middle of my workday. Honestly, 10/10 for confidence.

Red flag? When I finish the interview and say: “Any questions for me?”

And they smile and say:

NO

“No questions = no curiosity = big red flag for PMs.”

What are the biggest changes you’ve seen in the PM hiring market in 2024-2025?

If someone ever writes a documentary about Product Manager hiring in 2025, I hope they film it as a comedy. Because honestly, being a Technical Recruiter in this market feels like living inside a sitcom where every episode starts with:

“So… what exactly is a PM this time?”

In one company, a PM is basically a Principal Strategy Wizard with ten years of experience, a degree in rocket science, and a talent for mind-reading. In the next company, “PM” actually means “Please Manage This Spreadsheet.” And every time I join a new company or speak with a new hiring manager, I have to reset my full understanding again. It’s like starting a new level in a game I thought I already finished.

Does anyone pay attention to Cover Letter?

Do people read cover letters?

Short answer - no.

Long answer - still no, but with more feelings.

The job market is brutal. Nobody stays in one place for 30 years like our parents did. Now, if someone stays 3–5 years, we call them a “dinosaur” with respect. With layoffs, AI, nomad life, new tech stacks, and constant changes, people switch jobs often.

Recruiters are drowning in double and triple digit of applications for every new role.

The interview is where the real selling happens.

So cover letters? They’re… gently disappearing.

How important are referrals in your screening process compared to cold applications?

“ Referrals are very important! “

Word of mouth has huge value, and I love it when colleagues recommend people they actually know. Bonus points when they follow the “referral script” and tell me why this person is amazing, instead of just saying: “We once had coffee, they seem nice.”

Referrals help employer branding, too - if I love my company, of course, I want my best friend to join. Then my best friend tells someone from their community, and boom, suddenly half the town knows how cool our workplace is.

What are the most common mistakes you see PM candidates make?

The most common mistake? Candidates are holding too tightly to their title.

Every company defines PM differently.

Sometimes candidates apply before checking what our product even is, and later realize their experience doesn’t match.

Sometimes a Senior PM applies, but after the interviews, the Hiring Manager says, “You’re actually a Product Manager” or “Associate PM” and gives clear reasons. Some people get offended.

I get it - nobody likes to feel “more junior” than they thought.

But PM is one of the most fluid titles ever. It just works like that.

I also see a lot of people who are actually project managers, marketing managers, or product owners applying for product manager jobs thinking… well… potato-potato.

How do you evaluate candidates who are seeking relocation versus local candidates?

In a perfect world, there would be no difference.

But reality depends heavily on country’s rules.

Some places, like Australia, require us to prove there is absolutely no local talent before hiring someone from abroad. It becomes a long process of paperwork, emails, and praying to the visa gods.

In Europe, some candidates are simply harder to relocate due to conflict zones, lack of embassies, long visa timelines, and other lovely complications.

So when I see two good CVs - one local, one requiring relocation - the decision isn’t just “who is better.” It’s also “will the government let this person work here sometime before 2035?”

What advice would you give to PMs who have been searching for 3+ months without success?

If you’ve been searching for months, please don’t give up.

Learn new things constantly - tech changes so fast that curiosity is your best weapon.

Engage with the PM community, follow people who inspire you, build your personal brand (LinkedIn, portfolio). Make yourself visible to recruiters who are hunting talent every day.

Explore different PM styles: technical, less technical, Scrum-heavy, no Scrum at all, etc.

I work with PMs who are total powerhouses. Their secret is that they never lose the hunger to learn.

I’ve been on both sides: a recruiter and an employee, laid off and searching. The market is wild, trends shift, and sometimes you just need to adjust your strategy a bit.

Good luck - you’ve got this!

If someone asked me to summarize the PM market in Autumn 2025, I’d simply say:

It’s confusing, chaotic, competitive, but also full of brilliant humans trying their best.

And sometimes, one of them will Rickroll you in a cover letter.

Which honestly makes my day.

Time to spill the tea on what we’re all actually making! ☕ 
Our annual Product Salaries in Estonia survey is back for round three.

Take the Survey

Each year we get a sharper picture—more data, better trends, and finally some answers on whether salaries are keeping up with the cost of… well, everything. Take a look at last year’s numbers here.

Here’s what we need from you today:

• ⁠15 questions (mostly multiple choice)

• ⁠Takes about 3 minutes

• 100% anonymous

• Open until December 1st

Take the Survey

Your 3 minutes today = better salary benchmarks for tomorrow. Whether you’re gearing up for a raise conversation or just curious where you stand, this data hits different when we all chip in.

Know someone in product working in Estonia? Share the survey with them! The more responses we get, the more useful the results will be for everyone.

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Thanks for helping make our product community more transparent and informed.

Expect some spicy numbers in your Christmas stockings! 🎄

Seems like we hit a bingo in this one😄

In this episode, we spoke with Vitalik Kotik, co-founder & CEO of SuperApp, a startup building the iOS-native full-stack AI engineer - a tool that designs and builds apps in Swift without a human developer or designer.

Before founding SuperApp, Vitalik spent three years as a product designer at Bolt.

🎁 SuperApp Free Credits for TPG Readers

The SuperApp team is giving Tallinn Product Group readers exclusive free credits to test the app and build your first iOS app with AI.

Active period: 12–24 November 2025
Eligibility: Available only to TPG.ee newsletter subscribers

How to claim free credits

1. Visit superappp.com

2. Click “Get Free Credits”

3. Sign in and enter the promo code:

TALLINPRODUCTGROUP

Make sure to test it out and give your feedback to Vitalik Kotik

What we discussed:

• The designer-founder advantage — Why YC was looking for design founders. And what advantage they have over others.

• Unit economics and AI — We talked about language learning apps, and How to estimate unit economics of AI startup. and how they can be around 40–70% profit margins

• The engineering behind AI tools — multi-agent orchestration, context management, and efficiency, which models to pick, development tooling, etc. Would love to hear more on this topic.

• Freemium of tools like Lovable — How VC-funded players subsidize 90% of users while bootstrapped startups must break even fast.

• SuperApp’s growth plan — Reaching 10,000 users through hands-on workshops, product-led growth, do things that don’t scale, agencies, etc.

Episode timestamps:

00:00 – Intro: Building the AI iOS Engineer
02:10 – Do Vibe Coding Tools Make Money?
07:30 – How AI Tools Stay Profitable
09:50 – Multi-Agent Systems Explained
12:50 – Claude vs GPT for Developers
16:50 – Are AI Coding Startups Sustainable?
18:10 – Why Designers Should Be Founders
22:50 – From Product Designer to CTO
25:00 – Should You Learn Design or Engineering?
26:40 – The Italian Padel App Example
27:30 – Hitting the Limit of Vibe Coding
30:20 – Lessons in Unit Economics
34:10 – Bootstrapping SuperApp
36:50 – AI Margins vs Restaurants
37:20 – Growth Strategy for SuperApp
39:10 – B2B or B2C? Market Approach
40:35 – First Build TikTok, Then Product
42:20 – Bootstrap or Raise VC?
43:30 – Live Demo: Building an App
45:40 – The Pain of Xcode
47:10 – Final Thoughts & Free Credits

Connect with:

Vitalik Kotik (SuperApp)
LinkedIn – sharing updates on AI + iOS building

Nikolay Roll (Tallinn Product Group)
LinkedIn – sharing thoughts on everything Product related + Vibe coding as a hobby

Mentioned in the episode:

• Corporate Waters – https://corporatewaters.substack.com/p/how-cursor-windsurf-and-lovable-grow
  (Article by Mikhail Shcheglov about AI coding tools’ profit margins)

• Y Combinator: “Why Everyone Should Care About Design” – https://www.ycombinator.com/library

• Product Hunt – https://www.producthunt.com/products/superapp?launch=superapp (PH launch of SuperApp)

• Vibe Code Atelier (Tallinn) – https://allevents.in/tallinn/vibe-code-atelier-tallinn-meetup-for-builders-1/200028724137330
  (Community meetup in Tallinn)

• Cursor Meetups (Tallinn) – https://luma.com/cursorcommunity?k=c (Community meetup in Tallinn)

• Expo (React Native) – https://expo.dev (tech stack Superapp uses)

• SwiftUI (Apple) – https://developer.apple.com/programs/ (Preferred tech stack in Superapp)

🎧 Enjoyed this episode?
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Why grow on X?

Most people want to grow a personal brand, but let’s be honest, nobody’s got time for that. After binge-reading Nikita Bier’s Twitter, I decided to give it a shot and quickly realized: you can automate this thing.

My name is Gosha, and I’m a digital designer. And the goal is simple: promote myself on Twitter. And adjust ROI: minimize the “I” and make “R” as predictable as possible. In other words, to build an automated leadgen and a cumulative source of social proof of my mastery.

Result: after 2 months, I have: 450 followers (currently +-10 new subs per day), daily posts and comments, 1 booked consultation, and a couple of nuclear fans.

Bonus: Professional positioning and growing social proof of my professionalism (whatever it means).

Budget: +-$100 for infra. +-$300 of my (and not only) time.

The Playbook. How to grow on X?

So, let’s begin with the basics. After chatting with a few marketers, it turned out Twitter growth is just a system:

• Comment a lot.

• Follow people.

• Post viral stuff.

• Post smart stuff.

• Shitpost.

Growth formula:

A) First 2K followers → mass follow + heavy commenting.

B) 2-20K → viral posts (ask follow+comment for freebies, reviews, automations, “top lists”) + partnerships with other influencers (now you are, lol)

C) 20K+ → shitposting and audience migration, I guess.

I’m at stage A, so I’ll write about it. Here’s what actually works. You are welcome to steal it.

1. Nail your niche

Twitter isn’t about size. It’s about finding your weird, specific bubble.

Mine: product, marketing, and design people interested in behavioural design and interface nudges.

2. Adjust your profile

• Bio: clear hook, some numbers, a touch of humanity.

• Avatar: your face. No AI art.

• Banner: visual extension of your bio.

• Follow ratio: don’t look like a bot.

• name: easy to transcribe

3. Find ~100 influencers your people follow.

We’ll dance around them. They have what you don’t. Its visibility among your target audience and that’s something to take advantage of.

• If a company has a good Twitter (like Figma’s), that works too.

• Avoid people posting about politics (for example, I personally don’t comment on Paul Graham)

• I’m also not sure engaging with huge commentators is a good idea.

4. Comment like your life depends on it

30+ a day. It’s half your growth engine.

• Use TweetHunter or analogs for creating specific feeds.

• Comment within 2 hours after publication.

• Medium length = credibility.

• Buy the blue check. It boosts you to the top.

5. Mass following

The other half.

• Scrape followers of your influencers.

• Filter bots and randoms with automation.

• Follow 40–50/day, slowly ramp up until 100.

• Unfollow non-followers after 3–4 days.

• Auto-DM new followers with a chill welcome message.

6. Content

Post daily. Show expertise, not noise.

7. Sourcing

Steal smart. Use your old work, niche articles, and weird foreign blogs. Rewriting deepens your own thinking. Escape the sources that are close to your audience.

8. Welcome DM

It’s your first impression. That’s how I sold my first consult. (When we moved to WhatsApp from Twitter, I had a feeling of Tinder-like success)

Bonus points

Tool stack (~110 €/month)

• PhantomBuster — followers scraping, welcome DM, follow/unfollow automation

• self-hosted n8n — filtering for massfollow

• TweetHunter or Hypefurry — content

• Checkmark — cheap visibility

Extras:

• Freelance commenter

Avoid:

• Follow-for-follow

• Buying accounts

• Comment rings

• Threads before 2K

• AI stamps in your content

• 1:1 content сopy of Twitter and Linkedin

My go-to:

• Form a small “growth pact” with friends. Comment on each other, but keep it classy.

• Also, top lists perform insanely well. They get bookmarked like crazy.

And now stats

Most viewed piece of content: https://x.com/withgosha/status/1975622406288105974

New follows:

Last 2 months Overall:

Honesty Section

Maybe it’s not the best way to spend money, but I treat it as a pet project.

I deleted Twitter from my phone. Everything runs on autopilot: mass following, welcome DMs, and a freelance commenter. My only job is to spend an hour a week moderating automations and the freelancer’s work. Once a month, I write 30 posts, which takes about three hours.

The result is visible and cumulative. It’s my persistence in the professional community, my expertise, my social trust, my social capital. It’s nice that I can now share my Twitter alongside my portfolio site.

To get more out of it, I plan to adapt this flow for LinkedIn. I also generate a lot of content, so I think about adjusting my website for GEO/SEO.

If you want to talk about Twitter, ask for automation tips, or discuss my recent experiments. find me here: gosha.ee or x.com/withgosha

P.S. Now I trust the Dead Internet theory much more.

If you’re curious why to do it, read on.

I decided to repeat the survey this year to see what trends are emerging in the world of product management and how things have changed over the past year. To ensure comparability of the responses, most of the questions remain exactly the same.

I’ve added a few new questions about the use of AI and its impact on companies.

I heard about an Estonian startup where half the product and engineering team was let go, and the goal is to maintain the same productivity with half the team.
Very ambitious.
Or maybe not, considering the solo-founder of Base44 managed to build a product with AI about 6 months and sold it for 80 million.

I’m trying to get a sense of what’s happening in this space at other local companies and whether the rapid development of LLMs benefits smaller or larger companies more.

I know that several product managers have discovered vibecoding, and also user interviews are now being conducted using LLM models. I’m very interested in understanding the impact this has on strategic product management and on working with the real users.

With the TPG podcast episodes and articles, we’ve shared qualitative insights, but with this survey, I want to add a quantitative perspective.
As we product managers know, both are necessary to get the full picture.

I have no business interest in conducting this survey. I believe that the results of this survey will be of broader interest to product people and company leaders in general.
I want to make a small contribution to the field of product management in Estonia.

The survey results will be available at the end of November in Tallinn Product Group Substack channel.

Please take 10 minutes to complete the survey.
If you feel that you might be sharing information about your organization that you shouldn’t, don’t worry, the survey is anonymous.

Many thanks in advance!
Urmo

🎙️ Guest: Vladimir Ivanov – Co-founder & CTO at Supplied (ex-Bolt)

From rolling out a pre-seed through EWOR (Europe’s Y Combinator) to closing deals in one of the toughest funding climates, we talk about what it really takes to start a company in 2025 - without hype, without virality, and without 30 engineers.

Key takeaways

• Fundraising in 2025 is slower and leaner. Investors expect traction, not slides.

• “Too early” is not a no. It means: show customers and traction, then raising will be easier.

• AI replaces headcount, not execution. You can build a working product solo - if you understand what to build. However, you need capital to accelerate growth.

• Boring markets win. Compliance and tax automation might not go viral, but they pay the bills.

• EWOR experience. How to join, pitch, and stand out among the 0.1% accepted.

• The 30% rule. Never let one client define your business.

• Bootstrapping vs VC. When to take money and when to stay lean.

Chapters

00:00 From Bolt to Startup: The Journey Begins
04:16 Identifying Market Opportunities: The Birth of an Idea
09:17 First idea was a fail
14:47 First Sales
16:45 Leveraging Networking for Growth
18:43 Raising first money (EWOR)
22:55 Raising pre-seed
28:34 Should you apply to Accelerator/Incubator
29:57 How to be successful like Y Combinator ;)
32:01 The Role of AI in Startups
32:01 Raising Now vs Before
34:12 Do investors expect AI?
35:53 Hiring People or AI?
40:49 Why even raise if there is AI?
41:54 Plans after pre-seed raise
44:07 Why start a startup in 2025?
47:25 How to split responsibility between you and co-founder?
48:42 Good and Bad of building a startups?
51:36 Personal motivation
55:18 Maybe work for someone and build a side-project?
57:17 Great opportunity: go build something
59:05 Thoughts about product vision

Connect

Vladimir Ivanov — LinkedIn
Nikolay Roll — LinkedIn

Referenced

• Supplied - startup of Vladimir

• EWOR Accelerator – “The Y Combinator of Europe”

• Bolt – Where the founding team met

• DAC7 Regulation Overview – EU marketplace tax reporting

• [TPG Article] “Why your company isn’t ready for AI yet”

Scope:

• Role level: mid-senior

• Company stage: scale-ups -> mature

• Type: tech / product companies

I break this process down into several steps (and chapters):

• Market context

• Step 1 - Where do you want to get?

• Step 2 - Become discoverable

• Step 3 - Apply strategically

• Bonus advice! - oooh, you can’t even imagine what it is :)

And you 🫶 dear reader 🫶 have a chance to roast each step in the comments below or on my LinkedIn.

Market Context

This chapter is mostly my opinion and how I see the current market.
If you’re here just for the practical guide - feel free to skip to the next chapter.

If you like some data - while prepping this article, I read a report with lots of interesting stats for Q2 2025. Check it out if you’re into that kind of thing.

Now, my take: companies don’t want to hire. They have to.
And if they had the chance not to, they’d probably take it.

In early 2025, many companies started saying: “First, try automating it with AI before hiring someone.”
Honestly, that’s exactly what I would (and want to) do myself.

I treat my current position as: “It’s kind of sad that this role even exists. I want to automate it and fire myself.” As you can tell, I work in product operations.

And that’s not exactly a great foundation for an easy job search to begin with.

Generally, I do not see the market as favorable for applicants (let’s call it an employer market). There are many reasons for that: companies are not willing to hire, there’s over-employment, and too many candidates are applying for each position.

Companies might say, “We’re actually actively hiring.”
But in reality, many are mostly hiring senior positions. Which is fine for the scope of this article.

However, the problem is perfectly captured by a short dialogue I had with my friend while job hunting:

me: “Yo, every company is looking for a Senior… but I’m just a middle.”
friend: “Well, if they need a Senior and not a middle, then congrats - you’re now a Senior!”

Many juniors apply for middle positions, middles apply for senior ones, and seniors either don’t want to move or move too much.

It creates a lot of noise, making it very difficult to process applications — on top of the already low motivation to spend budget on hiring.

In my opinion, this means the following:

• You need to be clear about where you want to go (company, position, domain, etc.)

• You need to be discoverable when your skills or knowledge are needed

• You need to have a strategy

Step 1 - Where do you want to get?

Before applying, it’s worth deciding what you’re actually targeting.

Scope it using a few dials:

• Stage: early / scale-up / enterprise

• Size: headcount, markets, ARR

• Domain: fintech, e-commerce, hardware, AI, etc.

• Operating type: classic business, banking, tech, ops-heavy

• Function: analyst, ops, eng, product/project/program

• Level: mid / senior

• More to your taste

You don’t need laser focus, but you should define a few non-negotiables.
For example: “Fast-growing AI scale-up, product team.”

That might mean relocating, working remotely, or relaxing one of your criteria (maybe not AI, maybe not hyper-growth).

Doing this gives you a realistic shortlist and helps you coordinate your next steps.

Action items:

1. Define your key criteria. Example: “Fast-growing ride-hailing company located in the Baltics.”

2. Make a list of the top companies you actually want to apply to.
   For me, those were: Bolt, Wise, Lightyear, Twilio, Microsoft (and a few more).

🔥 Hot take 🔥

The classic “Why do you want to join this product/team?” question is pretty useless for junior, mid, and even for seniors.

Let’s be honest:
”In the end of the day, most of us want
a) a place to do meaningful work and
b) a good compensation.

Ideally, I’d be some CEO in some OpenAI/Google/[insert cool company here], “making the world a better place”, but I’m not there yet. So here you are, looking at my CV”😄

Truth is, I don’t have a 5-year plan where I want to be. So, I fail this recruiter’s question.

Therefore I started to approach it from a perspective of what I enjoy doing or maybe even good at: automating things, building systems, generating ideas, and generally working on stuff that excites me.
That’s how I would approach any new job search - and hope it would answer recruiter’s question 🤞

Step 2 - Become discoverable

Now that you know where you want to be - you need to become discoverable for people from there.

My definition of discoverable:

2 key aspects:

1. People search for something and they can find you

2. People need something and they remember you

Let’s cover each one

How to find you?

Linkedin search, website, being active in communities, public speaking, word of mouth (smth else what I do not know of)

The answer is above☝️ But if you want more here is a breakdown.

People, in our case recruiters, use the following tool → Linkedin (there are more tools, but let’s focus on this one).

There is a thing called “Boolean search”.

TL;DR recruiters have a set of criteria: “PM, >5 years, Java, Fintech” (Java?). They use it in search of Linkedin and get people out.

Say, you want to rank for PM in fintech in Payments - add something about Adyen, PSP, Orchestration, routing, etc. (dear Payments PMs don’t shame me, I needed an example).

If you want a guide on “how to fill out your linkedin” → let us know in comments and it could be our next post 😉

Action items:

• You are a recruiter of your dream job - come up with keywords that you would be using to find an Ideal Candidate. (if you can’t come up with keywords - find existing jobs and get keywords from there)

• Insert the correct words into your profile (“About”, “Job Description”), so that your name would definitely come up

• Optional. If you have a chance - search for these keywords, and iterate until you find yourself

• Bonus tip! Find a friend who knows how SEO works and ask them how to improve the results

Linkedin is the main playing field nowadays in recruiting (at least when it comes to Estonia). But Linkedin can be limited. Not everyone fills out their profile as well as you and I just did… So recruiters search in other ways.

Here are some ideas where else to be discovered by recruiters:

• Recruiters scrape Reddit/Facebook/Whatsapp groups of Product/Engineer/etc. You have a high concentration of specialists in one group - so recruiters do not need to hunt them 1by1. Great! Go join one and be part of next scraped list. (For example, join “Tallinn Product People” in whatsapp, IYKYK, ask around your product friends)

• Recruiting teams organize events/open doors so people would come and check out the company - visit those, maybe you get to know someone interesting.

• Other events. Say, ProductTank, Cursor Community, Lift99, PyData, etc. Go there as visitor, or as a speaker.

• More? (list your idea in the comments😉)

🔥Hot take:🔥

It is fine to add #OpenToWork badge. Why?

1. It shows recruiter that you actually open to job and their time won’t be wasted on ghausting candidates.

2. And not all recruiters use paid LinkedIn accounts, so not all recruiters can see your “Open for Jobs” setting

Side note:

I won’t be talking about how to optimize your CV or Linkedin in this article, but if you need help with it - let us know in the comments and we can figure something out 😉

Network your way to referrals

I believe that this aspect is the most important one, so bear with me.

💬Quote time💬

I believe that one strong reason why I got hired -

if you get referred - maybe good chance that recruiter won’t grill you as much?

Step 3 - Apply strategically

So now recruiters will start noticing you, your network’s active, and opportunities start coming your way.
Should you apply to everything right now?
Not really.

There are 2 problems:

1. Interviews are tests, like IELTS or SAT. They’re not real reflections of your skills; you can (and should) prepare for them.

2. Rejection cooldowns, many companies auto-reject candidates who’ve been turned down in the last few months. Say, if you aim to find a job in 3 months - getting early rejection from say Google means you won’t get to interview in the company for the next 2 months. So effectively you need to find a job 1 month. (not likely)

Action items:

• Start with companies you’re not dying to work for. Find similar roles — maybe a different domain, smaller scale, or just less exciting brands.

• Apply, interview, do home tasks, take culture-fit tests — treat these as your training ground.

• Refine your CV, pitch, and LinkedIn after every round.

Once you’ve done a few interviews and passed some, bueno! Now go for the real ones.

That’s where your results from Action items from Step 1 comes into play. You should have a list of companies where you actually want to get to. So you better prepare your best for them.

Again for me such were: Bolt, Wise, Lightyear, Twilio, Microsoft, and more.

Those were the ones I prepared referrals for, reached out to people, and didn’t waste early shots on.
Meanwhile, I practiced on others. I even had three interviews at the same company for three different roles. It was a total chaos, not a hiring process, but a great warm-up after all. 🤷

Bonus tip!

I think that finding a job is numbers game.
As many things - you need to apply many times to finally get what you want.

💬 Quote time 💬

For example, I applied ~12 to Bolt before I finally joine.
Before that a while ago I applied about 14 times before I got to Boku. (yes, I have a thing for “Bo..” companies)

In the end of the day it is not (only) about having the best strategy - it is about consistency. Keep applying - this is about 60-80% of success (I have no idea of actual %, take this number or leave it).

So the key is to be consistent + having a good strategy (+good if you are a good fit for the position).

It does not mean that you need to spam. Actually here it says that if you tailor your CV for the job description → you get a higher chance.

But definitely do not give up and keep applying to get what you want.

Summary

The job market in 2025 isn’t friendly - it’s an employer market.
Companies hire only when they must, and mostly for senior roles. That’s the reality.

So instead of fighting it head-on, play it strategically:

• Know exactly where you want to go.

• Make yourself easy to find.

• Build a network that works for you.

• Apply smartly, not desperately.

At the end of the day, finding a job is still a numbers game - but you can improve your odds by being visible, consistent, and intentional.

Keep your network warm, your LinkedIn sharp, and your energy steady.
Because when the right opportunity shows up - you’ll already be discoverable.

I’ve been building Phishbite with my co-founders Henrik and Mikk for two years. Along the way, I’ve faced the same trap most product leaders and founders know too well: the feature factory mindset.

I’ve spent hours with Henrik debating how we should measure success, not by how many features we release, but by the problems we solve and the value we create.

This mindset didn’t come naturally. It was shaped by my earlier experience at Touchpoint, where I learned the hard way what happens when you chase features instead of value.

Why features feel so seductive

On the surface, features look like progress.

• Executives like them because they’re easy to communicate: “Look how much we shipped.”

• Sales loves them because they fill competitor comparison charts.

• Founders fall for them because the next feature always feels like the one that unlocks growth.

But here’s the truth: features are not value.

A feature is just a capability.

Value is when a customer’s pain actually goes away.

Fail to make that distinction, and you end up in the feature factory: shipping output but not outcomes.

The hard lesson at Touchpoint

At Touchpoint, our strategy was simple: copy most of the features from the market leaders. Combine the best ideas from direct and indirect competitors.

It sounded like a path to success.

We built bells and whistles because that’s what competitors had.

But we never launched.

Why? Leadership looked at what we had and decided: “This isn’t enough compared to competitors.” So we kept adding more. More polish. More “missing features.” More scope.

The irony: in chasing completeness, we ended up with nothing. The product died under the weight of its own ambition.

That failure burned a lesson into me:

Copying features is not strategy. It’s insecurity disguised as progress.

Phishbite: starting with a clear metric

Phishbite’s mission is to reduce cybersecurity risk by reshaping user behavior.

We asked ourselves: how do we measure whether we’re delivering real value?

The answer was clear: reduction in click-through rates on simulated phishing emails.

This time, we focused our MVP on solving that core problem first.

It worked. Many companies showed steady drops in phishing click rates. But not all. Some users didn’t improve. Some companies didn’t see the effect we expected.

Now the question was harder: should we keep pushing on the same metric, or move on?

We decided to move on, partly because we were close to the bar we had set, and partly because prospects told us they wanted more general cyber hygiene training in addition to phishing simulations.

A second MVP and a mistake

We launched a micro-trainings module as a second MVP.

But this time we made a mistake: we didn’t define success metrics upfront. We assumed our competitive edge was practical content and interactivity. We got positive feedback, which felt encouraging.

But we didn’t define success criteria. Initially this wasn’t a problem. We launched an MVP for micro-trainings and got good feedback from some of our initial users and prospects.

Well done! Should we move on? We believed so.

There were a lot of things potential customers were asking for, either because competitors had them or because they believed those features would help them.

Now it became even more complicated. We had two MVPs launched. For both areas, we had feature requests as well as our own ideas for improvements.

We were dealing with these items, trying to understand the problems behind the requests and to prioritize our activities between keeping existing customers happy and acquiring new ones.

But then we started getting signals from some customers that completion rates for the micro-trainings module were quite low.

For some customers it was excellent, but not for all.

That’s when I realized it was a mistake not to have key metrics in place for the general cyber hygiene training.

Ideally, I would like to measure the real impact of these trainings, for example, whether users are now using stronger unique passwords or enabling 2FA, but that’s not easy to track.

So we decided to take a smaller step and define our initial KPI for the cyber hygiene training module: completion rate.

If users don’t complete the training, there’s no way we can expect their behavior to change.

The value of our product is not “sending phishing simulations” or “providing training modules.”

The value is changing behavior.

And solving that means doubling down on the core problem, not rushing to the next shiny feature.

The blend: qual and quant

Year one at Phishbite: qualitative insight dominated. Every customer voice felt critical.

Now, with thousands of users, quantitative data guides us more. But numbers alone don’t explain why things happen.

The real power is in combining both:

• Quant shows the pattern.

• Qual explains the reason.

Without both, you either drown in noise or miss the nuance.

When is it time to move on?

One of the hardest product questions is this:

When is it time to stop improving the same solution and move on to the next problem?

You can always polish. There’s no natural end.

My rule of thumb:

• Set an expected bar for your core metric.

• Compare to competitors when you can.

• Use customer feedback in the context of value, not features.

But I don’t pretend to have the final answer. Sometimes 80% is enough. Sometimes, for your core value, you need to push to 95%.

I’d love to hear how others decide: when is “good enough” really enough?

What if I’m wrong? The Featurebase counterpoint

Sometimes I ask myself: what if I’m wrong about all of this?

There’s an Estonian startup called Featurebase that’s doing incredibly well. They built a platform where companies collect feedback on feature ideas, prioritize based on that feedback, and ship what customers ask for.

It works. They have traction. They even use their own platform to build their product.

In some sense, they’re doing exactly what I warn against: building what customers request. And yet, it justifies itself.

The way I see it, Featurebase isn’t a feature factory enabler. It’s a feedback and communication tool. It helps companies listen, close the loop, and make customers feel heard.

So maybe the deeper lesson is not “never build what customers ask for.”

It’s: don’t confuse requests with value.

Feedback is signal. But solving the problem behind the request is what creates outcomes.

Final thought

If you are a product leader or founder, remember:

Features are tools. Value is the outcome.

Your job is not to build the most features.

Your job is to solve the most meaningful problems.

Metrics will give you signals.

But the deepest insights still come from talking to customers.

Product management is much about holding the widest context & distilling it into something tangible. Making hard things simple - that’s hard. But here I am, trying to do exactly that with the concept of product management.

What exactly is a "product"?

A product is a vehicle for value.

It doesn’t have to be pretty, new, or even software. It can be a clunky spreadsheet, a hacked-together script, or a polished app. If it helps someone get better, it’s a product.

Why do we need product management at all?

Because products can’t manage themselves.

Anarchy sounds romantic until you’ve lived through it. Left alone, every stakeholder will pull in their own direction: sales for revenue, engineering for reliability, marketing for attention. It’s chaos disguised as progress with no value to be seen.

What fundamental problem does product management solve?

Noise.

Every organization is full of competing opinions, demands, and distractions. Product management filters all that into clarity: here are the problems that matter and why, here’s what we’ll do about them, and here’s what we won’t.

Who is a product manager? (role definition in simplest terms)

A product manager is the compass.

Doesn’t row the boat or decide where to land, but points the direction and finds the best way to the destination. Over and over again, no matter how big the waves get.

What is the core essence of product management work?

Finding balance.

PMs translate customer problems into what the business needs to prioritize and business goals into what the team actually builds. They hold the widest context in the room, so everyone else can focus on execution without drifting off course.

How does a product manager create value?

By driving outcomes.

Features are trivial until they make a change. Shipping more is easy. Shipping what matters is the hard part, and that’s where the value lies.

What makes product management different from other business functions?

Breadth.

Every other function can afford to stay in its lane. Product can’t.

Product has to always hold the full picture and keep it in sync. Some days that means being the glue. Some days it’s duct tape. Some days it’s a hammer.

Why can't organisations succeed without product management?

It doesn’t scale.

You can ship without managing the product. You can expand the customer base without it. And you can even sell without product management.

But you can’t sustain it. Without product management, direction comes from luck or the loudest voice in the room. Both eventually run out.

What does success look like in product management?

Having clarity.

The team knows what they’re building and why it matters.
Customers’ problems are actually solved, the ones that matter.
The business sees meaningful progress, not just with OKRs.
Everyone can focus on what they do best, without debating priorities, questioning decisions, or drifting off course.

Final thoughts

This article is part of a series started by Toomas Koost & followed by Anna-Liisa Reinson, where all Tallinn Product Group members answer the same set of questions.

Why? Because we’ve come to realise that product management is different for all of us - and different from organisation to organisation. While we share many of the same values, it’s the tiny parts we see differently - that’s where the magic happens.

They begin with the lively debate between Marty Cagan and John Cutler, two voices with very different audiences and truths about product management. From there, the discussion flows into early-stage chaos and innovation, when (and if) to introduce processes, why founders struggle to hand off their “baby,” and the tricky timing of bringing in a product manager.

The episode also touches on sales as an essential part of product work, bootstrapping versus VC funding, and whether venture studios could be a smarter way to get products off the ground. The common thread: product is rarely black and white - it’s about context, trust, and finding the best possible way forward.

So join us in today’s talk—and let us know what you think.

AI generated summary:
Podcast Summary: The Realities of Product Work - A New Conversational Format

Episode Overview

Toomas and Anna-Liisa launched a new podcast format focusing on unscripted, real-time conversations about product management realities and current industry debates. Moving away from polished frameworks, they dive into what's actually happening in teams, companies, and the broader market.

Key Discussion Points

The Cagan vs. Cutler Debate

The episode opens with the ongoing tension between Marty Cagan and John Cutler's approaches to product management:

• Marty Cagan's perspective: Works primarily with senior management, sees many companies as "feature factories" due to reluctant product organizations. Advocates for a clear, black-and-white definition of proper product management.

• John Cutler's viewpoint: Champions the nuanced reality that different contexts require different approaches. Not everything needs to fit the "inspired" framework - sometimes hybrid approaches work better.

The hosts conclude these perspectives serve different audiences and both are necessary - Cagan for executive buy-in, Cutler for teams implementing the work.

Early-Stage Product Chaos vs. Process

A significant portion discusses when processes help versus hinder innovation:

• Process as innovation killer: In early stages (4-person teams), introducing frameworks can create unnecessary overhead

• Chaos enables innovation: Early-stage chaos is where breakthrough solutions emerge

• Context-dependent frameworks: Combining elements from multiple methodologies often works better than rigid adherence to one

The Founder's Dilemma

The conversation explores the challenge of transitioning from founder-led product decisions to professional product management:

• Trust dynamics: How do founders maintain trust while introducing new processes and frameworks?

• The "baby handoff" problem: Founders often struggle to truly delegate product decisions, turning product managers into "fancy secretaries"

• Timing challenges: When to hire a product manager and how to ensure they're empowered, not just operational

Modern Market Realities

The discussion touches on how product discovery has evolved:

• Pattern recognition over market creation: Focus on finding existing behavioral patterns to disrupt rather than creating entirely new markets

• Sales-integrated discovery: In B2B, customer interviews often work best when combined with sales processes

• Subject matter expertise: Founder-market fit becoming increasingly crucial for funding success

Alternative Business Models

The episode explores venture studios as a middle ground between bootstrapping and VC funding:

• Venture studio model: Full-stack teams providing temporary expertise across legal, marketing, engineering, product, and design

• Equity for expertise: Taking 5-20% equity in exchange for getting companies to profitability

• Market gap: Addressing the 97% of startups that don't make it to Series A but could succeed as profitable, smaller-scale businesses

The Sales-Product Connection

A key insight emerges about product managers needing sales experience:

• Essential B2B skill: Every B2B product manager should do sales for 3-6 months to understand overselling dynamics and customer conversations

• Buyer vs. user personas: Understanding the difference between who pays and who uses the product

• Distribution reality check: Great products still need great marketing and sales - neither alone is sufficient

Key Takeaways

1. Context over frameworks: There's no universal "right" way to do product management - success depends on matching approach to situation

2. Trust and timing matter: Introducing processes requires careful timing and strong trust relationships

3. Sales as product skill: Modern product managers, especially in B2B, must understand sales dynamics

4. Alternative paths needed: The industry needs more options between VC funding and pure bootstrapping

5. Pattern recognition: Focus on disrupting existing behaviors rather than creating entirely new markets

The episode successfully demonstrates their new format's value - providing practical insights from practitioners dealing with real challenges rather than theoretical frameworks.

Welcome back to Product Rants, where Anna-Liisa and Maria, two product people, grab their coffee cups and vent about the chaos, contradictions, and curveballs of product management.

In this fifth episode of Product Rants we explore the multifaceted journey of becoming a people leader, particularly within the realm of product management. We discuss the importance of communication, empathy, and self-discovery in leadership roles, as well as the challenges faced by middle managers.

The conversation takes us to dig into the need for curiosity, understanding one's strengths and weaknesses, and the importance of creating growth opportunities within organizations. Ultimately, we advocate for a more supportive environment for aspiring leaders, encouraging individuals to reflect on their motivations and the true nature of leadership.

We hope we enjoy this new episode of our rants!

Chapters

00:00 Introduction to People Leadership

05:17 The Role of Communication in Product Management

11:22 The Balance Between People and Business

17:11 Challenges Faced as a New People Manager

23:00 Navigating the Complexities of Team Dynamics

28:56 The Loneliness of Leadership

38:22 Understanding Managerial Responsibilities

44:43 The Importance of Open Communication

54:06 Redefining Growth Paths in Management

Host: Urmo Keskel, co-founder of Phishbite

Reelika’s background is not the usual one for a product leader. She has worked in HR in many different roles before stepping into product. At first glance this looks like a big leap. But as Reelika explains, the move was built on years of learning, curiosity, and persistence. She read books, took courses, and slowly built the skills needed to become a CPO.

She talks about how her main driver has always been the wish to understand what it really takes to innovate. This curiosity gave her the courage to cross from HR into product. It also shaped her leadership style, where she combines structure with creativity and keeps teams focused on customer needs.

We also discuss how AI is already shaping product management. From speeding up research to changing how teams make decisions, AI is creating new opportunities but also challenges for product leaders.

For people thinking about a career in product management, Reelika shares very concrete advice. She points out what to study, what to practice, and how to stay resilient when things don’t go as planned. She also highlights resources that helped her own journey.

The talk with Urmo moves between personal stories, lessons from Eesti Loto, and bigger questions about Estonia’s digital ecosystem. It’s an open and practical conversation for anyone interested in product, leadership, and innovation.

Books mentioned

• Anyone Can Design

• Build: An Unorthodox Guide to Making Things Worth Making

Course mentioned

• Stanford: Leading Innovation

As product organizations grow and mature, new roles emerge to fill the gaps between strategy and execution. One such role that's been appearing more frequently in the Estonian tech scene is the "Product Specialist", but what does it actually mean?

To better understand this emerging position, I recently shared a questionnaire within the local product community, asking those who have held Product Specialist roles to describe their responsibilities, challenges, and day-to-day work. While I received only two responses from fintech companies, two additional data points emerged: a current job posting from an AI-powered platform seeking a Product Specialist, and insights from a Product Operations Specialist at a major Estonian mobility company.

These four perspectives (three from practitioners and one from a hiring organization) provide surprisingly revealing insights about both the potential and the pitfalls of how organizations are structuring these roles. Rather than waiting for a larger sample size, I believe these early signals can help product leaders avoid digging themselves into deeper organizational holes when creating specialist positions.

The Role's Core Identity

The existing practitioners struggle with role definition, but their contexts vary significantly. The first, a Screening Product Specialist at a 5,000-person fintech, describes their work as making "delays on payments as seamless as possible" within regulatory requirements. When asked about success metrics, they admit:

At least on my team, this was a bit of a blur. We didn't have KPIs as we were working on fixing regulatory gaps... Once the regulatory gaps were done, there was no clear guidance on what was expected from us as Product Specialists.

The second respondent, a Junior Product Specialist at a 400+ employee banking company, offers perhaps the most telling description:

The funniest and easiest way I like to describe my role sometimes is 'santa's (my PM's) little helper' as I aim to decrease the burden of my manager with nitty-gritty, more hands-on and specialized tasks.

A fourth perspective comes from a Product Operations Specialist at a major mobility company, who reveals a different dynamic entirely. Rather than ambiguity, they describe frustration with artificial constraints:

I see exactly the problem, I know what would be the solution, I have contacts across [the company] to deliver the solution. But I am blocked by PMs like 'nana, wait for big boys to do their job.'

They note:

Your PMs come to us for consultation, not we to them...

Meanwhile, the AI company's job posting presents yet another vision. Their Product Specialist will "drive the adoption of new platform features, enhance operational workflows, and promote alignment toward shared goals." Rather than being a helper or being blocked, this posting positions the role as "critical" with ownership of "shaping how internal adoption happens at scale."

The contrast reveals four distinct models:

• Regulatory compliance executor - handling payments and regulatory gaps

• PM helper - supporting managers with specialized tasks

• Constrained problem-solver - seeing solutions but blocked from executing

• Empowered adoption driver - owning platform feature adoption at scale

This suggests either an evolution in how organizations think about the role, or a fundamental disconnect between job posting aspirations and workplace reality.

The Skills Paradox

The alignment between what practitioners have developed and what employers seek is noticeable. Both fintech specialists possess technical competencies—Jira, data analysis tools (Looker, Google Analytics), cross-functional communication, and framework knowledge (Agile, Scrum). The Junior Product Specialist specifically highlights "web design and design thinking" and "basic understanding of coding" as valuable skills.

The AI company's requirements mirror this almost perfectly: "basic scripting, coding, or AI-assisted coding tools," "excellent analytical and problem-solving abilities," and "strong cross-functional collaboration skills with the ability to explain technical concepts to non-technical stakeholders."

The mobility company specialist adds another dimension: deep operational knowledge and cross-company networks. They describe having "contacts across [the company] to deliver the solution" and serving as consultants to PMs rather than vice versa.

The measurement challenge persists across all contexts:

• Neither fintech organization has figured out how to systematically measure specialist impact

• The Screening Product Specialist worked for over a year without clear KPIs

• The Junior Product Specialist admits there's "no real metric" being tracked

• The AI company's posting focuses on activities rather than measurable outcomes

The Expertise-Authority Gap

Both respondents demonstrate deep operational knowledge—understanding regulatory requirements, architecting solutions, facilitating cross-team alignment—but report directly to Product Managers rather than having decision-making authority. This creates an interesting dynamic: they're positioned as subject matter experts but function as execution arms.

The Screening Product Specialist explains:

On a daily basis I don't think there was any difference [from Product Management]. We both would work on the discovery phase, and how to solve the specific problem. In my understanding... the Product Manager would be the one gathering the information to present to higher ups, board members, or regulatory bodies, while as a Product Specialist, I wouldn't do it.

They're heavily involved in analysis and problem-solving but rarely get to make the final call on solutions they've helped design.

What the Responses Don't Tell Us

The questionnaire responses reveal notable blind spots:

• No discussion of business strategy connection - how their work relates to broader company goals

• Missing customer outcome focus - no mention of end-user impact or satisfaction

• Unclear revenue impact - absence of financial or business metric discussions

• Limited roadmap influence - no indication of how they shape product direction

• Vague career progression - both struggle to articulate advancement paths

Most tellingly, both struggle to articulate career progression. The Screening Product Specialist notes:

From one level above (Associate Product Manager), there is a very nice career path and what is expected from it

implying their current level lacks such clarity.

The Biggest Challenges

When asked about their primary challenges, both responses point to organizational gaps rather than technical or market difficulties.

The Screening Product Specialist cites:

• Lack of guidance

• Lack of clear feedback from leadership team

• Unclear processes

The Junior Product Specialist identifies a growth paradox:

I think the more you grow in your role, the less time you have to 'build' something yourself or be more 'hands-on' because you have to spend more time managing and communicating with different people.

These aren't problems with the individuals. They're symptoms of organizations creating roles without thinking through their purpose, growth trajectory, or integration with existing structures.

The Industry Evolution

The initial fintech pattern suggested Product Specialists emerge primarily in highly regulated industries, dealing with compliance requirements and regulatory constraints. But the additional perspectives reveal a broader pattern.

Different contexts, similar needs:

• AI company - focuses on platform feature adoption and translation process optimization

• Mobility company - handles operational gaps and unfinished product workflows

• Fintech - manages regulatory requirements and payment processing complexities

This is the most illuminating perspective on why these roles really emerge:

Product Ops Specialists exist because there are many cracks or unfinished products/processes/workflows, which is why they require a person who would coordinate improvements to these unfinished products and manually resolve issues which emerge from these cracks.

This suggests Product Specialists aren't just responding to regulatory complexity or technological sophistication. They're emerging to handle the operational reality of incomplete product development. The common thread isn't the industry, it's the gap between what gets shipped and what actually works. Perhaps a problem of heavily operational industries?

Implications for Product Organizations

So, rather than Product Specialists emerging where product management is too broad, might they be emerging where product execution is systematically incomplete? Are they decomposing PM responsibilities or are they filling gaps that shouldn't exist in the first place?

Key advice from practitioners:

Screening Product Specialist emphasizes:

Focus on how to communicate with people and translate the conversation... it's our job to make sure this bridge is built and make things move forward.

Junior Product Specialist suggests:

If you have natural curiosity for the world in general... strong problem-solving and entrepreneurial mindset, and perhaps something that makes you stand out or special... you should be good to go.

These roles require people who can see problems clearly and have the network to solve them, but who may be artificially constrained from doing so.

All practitioners focus on individual adaptability and resilience rather than organizational support, suggesting even well-intentioned companies may be creating roles that require exceptional people to succeed despite structural limitations.

Conclusion

Four data points reveal both concerning patterns and uncomfortable truths about how product organizations are structuring specialist roles. The practitioners demonstrate competence and fill genuine organizational needs, yet three of the four describe systemic constraints: unclear purpose, lack of measurement, or artificial barriers to execution.

For product leaders, this represents both an opportunity and a warning:

The opportunity: Recognizing that if you need Product Specialists to handle operational gaps, you might have deeper product development process issues to address.

The threat: Creating these roles without fixing underlying execution problems creates technical debt at the organizational level.

Before creating your next Product Specialist role, ask yourself:

• What specific execution gap are you filling that wouldn't exist with better product development discipline?

• Are you hiring someone to coordinate fixes for incomplete work, or to genuinely extend capabilities?

• How will you measure success beyond "handling the things that break"?

When your specialists can see solutions but can't execute them, you've created a role designed for organizational friction.

The AI company's job posting suggests some organizations are learning to position these roles with genuine ownership and impact. Whether that translates to workplace reality remains to be seen, but it represents a more thoughtful approach than reactive gap-filling.

As one respondent beautifully summarized:

Product is a whole new world inside a company. It is at the same time very challenging, rewarding, and frustrating. It's up to us to focus on what brings us joy.

The question is: Are we creating Product Specialist roles that enable that joy by genuinely extending capabilities, or are we systematically preventing it by normalizing the cleanup of incomplete work? The early signals suggest the answer depends entirely on whether we're solving for better execution or just managing the consequences of poor execution, and that makes all the difference.

🎙️ Guest: Liisi German – Group Product Manager at Bolt (ex-Veriff)

From self-driving cars and document scanners to chatbots that hallucinate refunds, we talk about when AI is the right tool, and when a simple if-else statement might do the job better.

Key takeaways:

• AI product management is about designing around uncertainty and mistakes (in some context known as hallucinations)

• Don’t build AI unless you have to. Seriously. Start with manual hacks. Fake it, Buy it, then Build it.

• Companies do 2 types of AI. Real AI product features and systems. And the second is automation. Most “AI” today is just automation. And that’s okay.

• We go through examples of Bolt and Veriff, how to evaluate edge cases, label training data and more.

Framework: 5 Jobs of an AI PM

1. Design around machine failure and edge cases

2. Decide when to buy vs. build

3. Define “right vs. wrong” model behavior

4. Source, label, and manage training data

5. Manage legal concerns

Timecodes:

0:00 Introduction

1:25 AI Product Management Overview

2:10 What is AI product?

6:13 What is difference between: AI PM and Software PM?

13:18 How to work with uncertainty in AI Teams?

24:13 How to design around AI mistakes?

28:41 Understanding Data and Training

39:30 Should you Buy or Build your AI?

56:34 What are skills of AI PMs?

1:01:11 Liisi's University course

1:05:11 Future of AI in Product Management

1:06:01 Final Thoughts and Advice

Connect:

• Liisi German: https://www.linkedin.com/in/liisigerman/

• Nikolay Roll: https://www.linkedin.com/in/nikolay-roll/

Referenced:

• Alfred - name of AI chatbot of Bolt - https://bolt.eu/en-ee/

• Veriff - https://www.veriff.com

• OpenAI CPO on writing evals - youtube link

• Amazon walk in store - https://www.businessinsider.com/amazons-just-walk-out-actually-1-000-people-in-india-2024-4

• TPG article - Why your company is not ready for AI yet - https://www.tpg.ee/p/why-your-company-isnt-ready-for-ai

Specifically, we explore what makes some product and sales teams' relationship work as a partnership and why others are doomed, no matter how hard we try. We also touch on what the fudge is all that product-led vs sales-led talk about?

When the relationship doesn’t work, we ask ourselves why that may be, and which causes are rooted in the higher levels of the organization versus causes stemming in how the daily jobs are performed.

For the first time, we also invite you to comment on your experience, if you fancy that. However you wish to engage, make sure you brew yourself a good cup of coffee and join us as we explore what makes product and sales teams work or fail.

To solve this, Modash doubled down on SEO and built a content-driven engine that scaled them from €1M to €6M+ ARR with zero outbound sales.

In this episode, we spoke with Ryan Prior, Head of Marketing at Modash, to discuss:

• How Modash grew with 100% inbound sales from SEO and free tools

• Why mini-tools like a fake follower checker drove 250k+ visits/month

• The “95–5 rule” and why most of your market isn’t ready to buy—yet

• What it takes to build a brand that wins before the search even begins

• SEO vs. brand marketing: which gets you to €100M ARR?

• How Modash measures ROI when traditional attribution fails

Episode timestamps:

00:00 – SEO for customer acquisition

02:57 – How Modash built its early marketing

05:50 – Challenges and opportunities with SEO

08:48 – Mini tools to drive traffic

12:07 – Why Modash shifted focus to brand marketing

14:56 – 95/5 Rule

18:00 – Why video marketing is the next big bet for Modash

20:52 – How to build mental availability for your brand

29:58 – Choosing the right problem to own

30:41 – First principles of brand building

33:21 – Does design matter?

35:31 – Growing a brand through LinkedIn

40:54 – Making sense of LinkedIn ads for B2B SaaS

42:50 – Short vs Long term marketing

44:50 – How Modash measures go-to-market

48:19 – Why attribution in brand marketing is broken

51:49 – How to communicate marketing results to leadership

Some takeaways:

• SEO can be fast—if your market is already searching.
  Modash focused on high-intent keywords like influencer search tools, driving a 20%+ trial conversion rate. This worked because the target customers were already in-market and had clear pain points.

• Mini-tools scale traffic.
  Modash built lightweight tools like a fake follower checker and engagement rate calculator to satisfy long-tail queries. These tools bring 250k+ monthly visitors and feed into product trials.

• 95/5 rule, Long term vs Short
  The Modash is now shifting focus toward brand marketing, based on the 95-5 rule: only 5% of your market is ready to buy at any given time. The rest? They’ll choose from brands they already know.

• Brand marketing is “brain SEO.”
  If people search their brain before Google, your job is to make sure Modash is already there. That means building mental associations like “the only platform with enough influencer data” or “the one where filters don’t break the search.”

• What actually works? Ask your customers.
  Sales calls, branded search growth, contributor-led blog content, and even TikToks about “how many fake followers Ronaldo has” became indicators that their marketing is working—even when ROI can’t be tracked precisely.

Referenced

• Ahrefs / SEMrush – SEO tools used to identify keyword opportunities and validate search volume.

• Modash Fake follower checker – https://www.modash.io/fake-follower-check

• Modash Engagement Rate Calculator – https://www.modash.io/engagement-rate-calculator?influencer=%40therock

• Modash Blog – https://www.modash.io/blog

• Modash PSEO pages (e.g., “Influencers in France”) – https://www.modash.io/find-influencers/france

• TPG article on Copilot2Trip’s marketing tactics – https://www.tpg.ee/p/how-to-launch-0-to-1

Books & Marketing Theories

1. “The Long and the Short of It” by Binet & Field
   • Discussed in detail when explaining the balance between long-term brand marketing and short-term performance marketing.
   • Suggests a 60/40 split between long-term brand-building and short-term activation.

2. The “95–5 Rule”
   • A widely referenced B2B marketing principle: only 5% of your market is actively buying at any given moment; the other 95% need brand familiarity when they eventually come into market.

3. “Share of Search” Concept
   • Referenced as a proxy for market share in branding. Used by Modash to measure brand awareness vs. competitors based on branded keyword trends.

Connect with:

• Ryan Prior LinkedIn – https://www.linkedin.com/in/ryanprior1/

• Nikolay Roll LinkedIn – https://www.linkedin.com/in/nikolay-roll/

Enjoyed this episode?
Subscribe to the TPG Podcast for more insider insights from product-led operators in Europe and beyond. 🎧

In this article, we talk about using AI to automate your operations and grow your margins from 10% to 30% (not everyone will get there…), and what it takes.

📖 Word count: ~1700

✨AI Word count: ~35

⌛ Time to read: ~7 min

“Before asking for more Headcount and resources, teams must demonstrate why they cannot get what they want done using AI.”

- Tobi Lutke, Shopify CEO, on X

If that’s the case, then teams at Shopify just got a way to request any headcount or resources they need. 👍

Many CEOs, C-level managers, mid-managers, etc. talk tirelessly how AI will change our lives. Everyone says something along the lines: “AI will change everything”. No one knows what to do with AI exactly, but everyone wants to do it really bad.

Why does everyone want AI?

It’s a way to compete. Launch a cool AI feature, and you get the first-mover advantage: “We do what incumbents do—just better, and with ✨AI✨.”

But the more interesting angle, in my opinion, is “productivity” from AI.

AI can now take on tasks that were mostly handled by people, like understanding messy input (think lawyers parsing laws), interpreting intent (think customer service chat), and even basic reasoning (think accountants analyzing reports).

Now, you can do what people do, but faster, cheaper, and sometimes even better(?).

This isn’t just about faster spreadsheets—it’s about real operational leverage.

Tech-Enabled Roll-Ups: AI to Scale

That’s exactly the premise behind tech-enabled vertical roll-ups.
You acquire operationally heavy service businesses—think hotels, accounting, parking - and apply software and AI to streamline workflows, boost margins, and scale faster than traditional operators.

Take Metropolis (raised $1.9B) which bought legacy parking operators like Premier Parking and SP Plus. They automated license plate recognition and payments, cut operating costs, removed gate hardware, and improved throughput.

Why it matters: in a low-margin industry (~10–20% EBITDA), a 10–15% uplift per location compounds fast.
If you boost margins to 30%:

• Your cash flow triples

• Your valuation jumps (2x becomes 5x)

• You can take on more debt to fund even more growth

  

In the ZIRP era, the game was: spend all your revenue, lose money, and raise more.
(OGs remember Silicon Valley: “We’re pre-revenue—like Amazon!”) But now the new name of the game is “make profit”. Can you sustain operations even if you can’t raise a huge round?

That’s where AI and automation fit the moment perfectly.

But still “Why Your Company Isn’t Ready for AI (Yet)”

Let’s be honest for second. Most of what we call “AI transformation” today is just automation with a cooler interface. And companies have struggled with automation for decades.

Why are there still so many inefficient, manual processes?

There are three main reasons:

1. System fragmentation

Your tools don’t talk to each other.
One lives in an internal admin with customer PII, another in Salesforce, and a third is an Excel sheet that gets emailed around every Tuesday.

APIs are missing, security says “no,” and integrations break every other week.

Some processes can’t be automated simply because Jira can’t talk to internal tools, because security.

You want to automate something in Salesforce? It depends on:
a) the Salesforce team’s roadmap, and
b) whether your subscription tier even allows it.

If you do not have integrations between your tools and there is no free flow of data between them - it is difficult to automate things.

Maybe you go rogue: CSV exports, a Chrome plugin, and Python scripts.
Not great, but kind of works… Until the security team steps in faster than your script runs once.
Now you’re stuck proving your hack is safe, even before anyone agrees it was useful.

2. Engineering resources

To build solid automations to solve system fragmentation you need:
a) developer resource and
b) budget for better Salesforce subscription and on-prem.

You think, “Let’s do it right—on-prem, secure APIs, clean data layers.” Sounds great... right?

But engineers are already fully booked shipping “solid features,” fixing bugs, and cleaning up tech debt from 2019. No one’s going to write a bulk download endpoint for accounting, unless accounting somehow becomes a “strategic initiative”.

Automation sounds like a smart investment - until you realize it’s competing for the same roadmap space with other new features which have impact in $millions against your “saving couple of clicks every hour”.

3. Process ambiguity

But honestly, the biggest problem is probably process management—or rather, the total lack of it.

If a process isn’t clearly defined, you can’t automate it. Period.

You get the usual signs:

• “Our knowledge base is Slack.”

• “Code is the best documentation.”

• “Ask Martin.”

All of these are just polite ways of saying: we actually don’t know how our processes work.

Many internal processes aren’t really “designed” at all, they’re “improvised” through chaos, handovers, and legacy decisions no one remembers. Different teams follow different rules, often without realizing it.

Take something as basic as refunds. If the process isn’t documented, your agents are thinking every time:

• “It’s been 5 days since the order—do we refund or not?”

• “What’s our refund policy again?”

• “Wait, do we even do refunds on Fridays?”

You can’t automate tribal knowledge.

Automation needs a clear, rule-based process. In code, that usually means writing a lot of “if/else” statements.

If you can’t figure out your “ifs”, “elses”, and “thens”, no automation will work.

But AI can solve it, right?

All the same problems still apply. But now we’ve added a new layer of complexity:

• Where does the model run? (Cloud or on-prem?)

• What data can it access, Jira tickets, Zendesk tickets, DB, PII? (And what shouldn't it?)

• What happens when a prompt update accidentally refunds €10,000 to the wrong customer?

• Oh—and who’s responsible when it goes wrong?

AI doesn’t magically solve process ambiguity or system fragmentation.
It just guesses better than your average rule-based bot—until it doesn’t.
And when it fails, it fails confidently.

AI is powerful when it comes to converting unstructured data into structured, understanding intent, reasoning, and more. That’s why CS use case is so compelling. But it’s not plug-and-play.

It still needs clean processes, solid data flows, and real operational thinking.
The only difference is that now, if you get it right, the leverage is 10x.
But if you get it wrong? You just built the world’s most expensive random number generator…

So, “Why Your Company Isn’t Ready for AI? (Yet)”

Before you implement AI, ask yourself: What problem are you actually trying to solve? (very PM vibe)

Start by identifying the processes you want to improve.
This means mapping how things work today, estimating the potential impact of change, and figuring out the cost and complexity of making it happen.

Once you have clarity on the process and the numbers to back it up, you’re ready for the next step: getting buy-in.
That means selling your idea to PMs, EMs, your M, other teams’ Ms, and whoever else controls budget and engineering resources. You need allies before you ask for action.

Then? Don’t start with AI.
Start with something simple and rule-based.
Most workflows can be improved with basic automation - no LLMs required.
Think of customer support: long before AI chatbots, just showing the FAQ in the chat window solved most issues.

Once that works, and you’ve proven the value, then it makes sense to explore how AI might take it further.

It’s like learning to walk before you run.

Or better yet - as Maksim Butsenko shared in our episode on Bolt’s ML journey.
Start with a rule-based system. Once that’s working, then level up to machine learning. Then, maybe, go to LLMs.

If your company is already at the stage where every process is automated with AI, then congrats!
Make sure to share your story with us at tpg.ee, or drop it in the Tallinn Product WhatsApp group (if you know, you know). 🙂

Thanks for reading—and subscribe for weekly Product Content!

Subscribe now

As an extra note. In general, I’m genuinely happy to see more C-levels, managers, etc. starting to care about automation and improving general health of their business. My only concern is that all these words need to turn into real action - and in the right direction.