Before we jump into this week’s insights, I want to give a proper shout-out to Purchasely, who’s sponsoring the Productlab Conference this year!

If you’ve been wrestling with in-app monetization, paywall experiments, or personalized user journeys—you know how much friction there is. Purchasely’s basically saying: “let AI handle the heavy lifting.” They’re giving you actual control over your in-app experience without needing to rebuild it every other sprint. No more “we need engineering for another A/B test” conversations.

Their sponsorship of Productlab.Conf (Sept 15–17 | Berlin & Online) is a strong vote of confidence in where our industry is heading. The conference lineup is stacked; Jeff Grang (CEO) is speaking on “The New Growth Loop: Install to Renewal,” and you’ve got operators from Stripe, n8n, Parloa, and GetYourGuide on stage.

If you’re shipping subscription stuff or experimenting with pricing, it’s worth checking out. Summer Birds early-bird pricing is €399.

Get Your Summer Bird Ticket Here

📰 Product Leaders’ Wisdom

​​​​​Brought to you weekly by Leila Montazeri

This week's career essentials: Why emergence beats planning, how to distinguish growth from misery, and why junior talent is disappearing.

• Molly Graham, former COO at Quip and host of TED's WorkLife Podcast, challenges conventional career wisdom. Instead of climbing predetermined stairs, embrace emergence; let your principles guide each next step, trust your energy, and watch opportunities reveal themselves. This isn't about lack of direction; it's about creating the conditions for magic to happen. Read on Lenny’s Newsletter how some of the world's most successful people built careers without knowing their destination.

• Feeling miserable at work? Before you quit, distinguish between two types of discomfort: stretch discomfort (internal growth) versus values discomfort (structural misfit). Diana Stepner reveals how to tell the difference and offers two critical questions to ask before walking away. Sometimes the grass is greener because you haven't watered your own garden yet.

• Remote positions now demand 25% more skills and experience than in-person roles, squeezing out early-career talent. The Harvard Business Review study analyzing 50 million European job postings shows that companies are hiring for experience rather than potential, largely because remote work gutted informal mentoring and on-the-job learning. The fix? Rebuild training infrastructure, formalize mentorship, and recalibrate hiring standards. Early talent isn't less valuable; organizations have simply stopped developing them.
  

💪 Open Roles

Brought to you weekly by Alessia Marchi​

1. Product Manager - Deep Learning for Media/Video @ brighter AI

2. Product Marketing Manager @ Legartis

3. Head of Product @ ablefy

4. Product Lead - Platform @ MYNE

5. Senior Product Manager - Data and API @ Climatiq

6. Head of Product - Platform Growth @ IMAGO

7. Senior/Staff Product Manager - Accounting & Ledge @ bunch

🎶 Song of the Newsletter

From our DJ Marco D’Avila

A Product Lab webinar hosted by Dodane do Backlogu Podcast with Ravi Mehta (ex-CPO Tinder, ex-Facebook/TripAdvisor, Reforge) and Michelle Parsons (ex-CPO Hinge, ex-Netflix/Spotify, now building Lora). Deliberate anti-format: no slides, no frameworks, no AI talk, just failures.

The stories

TripAdvisor’s big redesign (Ravi) — A company that ran ~1,000 experiments a year went heads-down for 9–12 months on a rebrand and launched it all at once, no A/B test. Revenue dipped. The culprit: they replaced the ugly-but-familiar filter sidebar with a beautiful “personalization bar.” Filtering dropped 20%, bookings dropped ~20% on that page, single-digit revenue hit company-wide. Millions lost. Lesson: separate form from function; Amazon is ugly and works.

“Just For You” (Ravi) — Same company. Silently swapping in a personalized hotel ranking: +10% revenue. Then they surfaced it, named it, made it the default — revenue fell. Users resented the app deciding for them and felt FOMO about hidden hotels. Identical algorithm, different UX, opposite result. His framing: control matters in proportion to stakes. Netflix can pick for you; a €3,000 holiday or a date cannot.

Netflix’s family profile (Michelle) — Disney+ was coming. The team skipped discovery and went straight to “we need a family profile,” complete with marketing plan and research trips to Asia and India. Families turned out to be far too heterogeneous for one profile with one content set. Months burned. The honest part: she knew, and kept going to placate marketing and content. Sunk cost plus not wanting to be wrong in front of a staffed working group.

Hinge Roses (Michelle) — Roses/Standouts borrowed super-like economics from Tinder and Bumble into an ecosystem built on a different principle. Users read it as “Hinge is paywalling the attractive people.” Then TikTok invented a folk theory that X-ing out your Standouts makes the app surface them — which fed the algorithm false negative signal and made everyone’s experience worse. Years of cleanup.

Marcin’s dating app (2018) — Gamification plus virtual currency. Revenue grew, but from a tiny cohort: proto-influencers farming attention and gifts, then ghosting to pull the audience over to Instagram. Users optimize for the incentive, not the design intent.

Kuba’s CRM — Nearly a year on an ML-driven sales-insights product to move upmarket. Someone finally asked in a room: how many customers do we even have who could buy this? Silence. Also: a viral loop that grew signups 300% while conversion tanked, because it imported the wrong ICP.

Audience — Ruslan: chased whales, lost SMB momentum. Simon (WeRoad): launched their own app, migrated the audience off Meetup, and changed the supply model, and did it in five countries simultaneously. Would now change one thing in one country.

Takeaways worth keeping

• Form vs. function is the cleanest heuristic in the whole hour. Redesign the aesthetics, don’t touch the mechanics users have learned.

• Same algorithm + different UX = different business result. Naming a feature changes how people judge it.

• Copying a competitor’s monetization mechanic into a different ecosystem imports their incentives, not their revenue.

• Change one variable at a time. Simon’s story is the textbook version.

• Michelle on leadership: at Hinge (80 → ~300 people in two years) she carried a private priority list. Her #20 was someone else’s #1, and nobody could see the ranking. Publish the order and the reasoning, not every detail.

• Ravi on meetings: exec and investor meetings are not where you discover the answer. Align beforehand, arrive with a recommendation, and state explicitly whether the meeting is to decide, explore, or inform. Also: learn how each leader consumes information — deck vs. memo, recommendation up front vs. at the end.

• Kuba’s addendum: pre-reads should be three bullets and the actual question, not a 13-page AI-generated dump.

Lightning round — “I will never again…”
Ravi: redesign without knowing the customer problem.
Michelle: say yes to everything; ship on a Friday.
Kuba: trust a surface-level signal.
Marcin: assume users want what I designed them to want.
Audience winner: assume the alignment meeting is where alignment happens.

🎡 Most fun

The webinar about failures failed live! ☄️YouTube stream died in the first three minutes, Michelle’s audio dropped twice, including on the final question about her own company. Daniele’s closing line was roughly “regarding fuck-ups, tonight couldn’t have been worse.”

Welcome to UserTesting!

Imagine you’ve just used AI to design, code, and deploy a brand-new feature in record time. It feels like a massive win. But here’s the million-dollar question: Are you running faster toward success, or just sprinting faster in the wrong direction?

With AI drastically lowering the cost of creation, speed is no longer our biggest blocker. The real challenge today is clarity—knowing exactly what is worth building before wasting valuable resources.

That is why we are incredibly excited to announce UserTesting as an Official Sponsor for Productlab.Conf this September 15–17 in Berlin and Online! They are the ultimate antidote to “building in the dark,” helping product teams ground their rapid execution in real, human insight.

👥 The Session You Can’t Miss

Speaking of validation, we have a brilliant roundtable lined up that tackles this exact dilemma head-on: Confidence Trap: When Leaders Know They’re Wrong

🗓️ 15-17th of September
📍 Berlin & Online

Get Your Summer Bird Ticket Here

Product Hiring Managers Meetup #3

As AI continues to reshape the tech landscape, the traditional Product Management career ladder is quietly transforming. Managing larger teams is no longer the sole benchmark for seniority; instead, hiring leaders are looking for something much more distinct.

To unpack what it actually takes to get hired or promoted in today’s market, our community partner Employed.world is hosting an exclusive meetup in Berlin. This is your chance to hear directly from the people making the hiring decisions.

🗓️ 3 August 2026, 18:00 - 21:30 CEST

📍 The Delta Campus, Neukölln, Berlin

🎟️ Free for those affected by layoffs (requires approval) / Flexible standard ticket options

Grab Your Ticket

📰 Product Leaders’ Wisdom

​​​​​Brought to you weekly by Leila Montazeri

AI Changed the Game. Your Strategy Should Too.

Artificial intelligence has transformed everything. But there’s a lesson most founders are missing: a good AI product isn’t enough. You need the right strategy.

Do you know which roles are disappearing? Which capabilities are being recombined? And how your growth equation is changing?

Three sharp thinkers answer these questions. Let’s learn from them.

• The Beautiful Mess reveals that roles are illusions. What’s real is that capabilities flow across your organization, sometimes concentrated, sometimes distributed, sometimes embedded in tools. AI accelerates these movements. Work doesn’t disappear. It transforms. The real question isn’t what AI does. It’s which judgment and context you’re losing. Because once expertise gets baked into a system, people stop developing it.

• A great product is only one of four things you need to reach $100 million. You also need Product-Channel Fit, Channel-Model Fit, and Model-Market Fit. AI breaks all of them. A product that worked yesterday might fail today. Brian Balfour gives you a framework for thinking through these shifts, and spotting when your growth machine is about to break.

• Thousands of new AI startups have launched. But 95% of them will never make enough money to survive. Why? Beliūnas is blunt: you need a moat, something competitors can’t copy. Without it, you’re just selling a cheaper commodity. Anyone can build the product now. Almost no one can build the company.

💪 Open Roles

Brought to you weekly by Alessia Marchi​

1. Product Manager - AI Platform @ Scalable Capital

2. Senior Product Marketing Manager - US @ voize

3. Principal Product Manager - Apps @ HomeToGo

4. Senior Product Manager @ Superhuman

5. Product Owner - Onsite Experience @ momox

6. Director of Product Management - Platform @ Taxfix

7. Lead Product Manager - SmartPOS @ Unzer

🎶 Song of the Newsletter

From our DJ Marco D’Avila

Meet Our Next Sponsor: Miro!

When it comes to bringing product teams together, mapping out complex roadmaps, and turning messy brainstorming sessions into structured plans, there is one tool we all rely on.

We are incredibly excited to welcome Miro as an official sponsor for the upcoming Productlab Conference! We are proud to partner with a platform that is central to the daily workflow of modern product creators.

To celebrate Miro joining us as an official sponsor for the upcoming Productlab Conf, we are launching an exclusive Leaders Bundle giveaway! 🚀

Want to attend the flagship conference in Berlin (or online) from September 15-17th and bring a colleague, co-founder, or product peer for free? Here is your chance to turn your single ticket into a 2-for-1 bundle.

Here is how to enter:

1. 🎟️ Buy your Ticket at the current rate via productlab.app.

2. ✍️ Write a post sharing why you want to join us at the conference this year.

3. 🏷️ Tag @Miro, @Productlab, and our incredible speaker @Ravi Mehta.

The author of the best, most creative post by August 15th will receive a free extra ticket to bring someone along with them! 🥳

Get Your Summer Bird Ticket Here

🌴☀️ Packing your bags? Don’t pack away this masterclass.

August is just around the corner, and we know most of you are either heading out for the summer or already in holiday mode.

Honestly, enjoy the break! But before you completely unplug, we have an online session with two of the sharpest product minds in the industry you absolutely shouldn’t miss: Ravi Mehta (Former CPO at Tinder) and Michelle Parsons (Former CPO at Hinge), teaming up with the Dodane do Backlogu team. If you want practical insights on surviving product failures and navigating the AI wave without the usual sales pitches, this conversation is for you.

🗓️ 29th of July, 18:00–19:30 CEST

Save your Spot for the Livestream

📰 Product Leaders’ Wisdom

​​​​​Brought to you weekly by Leila Montazeri

The AI Whiplash: Why Our Trusted Playbooks Are Breaking

• In his insightful piece, Florian Bonnet highlights why optimizing for velocity is meaningless if you’re running in the wrong direction. AI makes building features cheap, leading teams to chase shipping speed while burying themselves in complexity without driving revenue. We must rethink our product metrics.

• According to an interesting article on Product Management IRL, the instincts that make us a great PM, seeking stability and managing risk, will actually break our AI projects. Because AI is unpredictable, we must ditch the traditional playbook and switch to a transformation mindset focused on fast, micro-level learning.

• Over at Growth Unhinged, a new guide explains why tracking AI search success through referral clicks is completely wrong. Less than 1% of users click links inside AI answers. The piece offers a practical framework to stop chasing vanity traffic and start measuring your actual brand presence.

💪 Open Roles

Brought to you weekly by Alessia Marchi​

1. Senior Product Manager - Tech, Amazon Music AI and Personalization @ Amazon

2. Senior Product Manager - Consumer Mobile @ Gigs

3. Senior Product Manager – Connectivity @ GIATA

4. Lead Product Manager - Paid Search @ GetYourGuide

5. Senior Product Manager - House Owner & Service Request Acquisition @ Aroundhome

6. Senior Product Manager - Payment @ Agicap

7. Product Manager - Digital Health Studies @ Data4Life

🎶 Song of the Newsletter

From our DJ Marco D’Avila

If you’ve ever wondered how to turn user behavior into revenue actions, truly, Contentsquare has the answer. As a global leader in Digital Experience Analytics, Contentsquare empowers product teams, marketers, and businesses to look beyond traditional analytics. Their platform transforms billions of digital behaviors- every click, scroll, and hover—into actionable insights. With their intelligent data, you can build deeper customer empathy, prioritize the right product updates, and unlock unprecedented growth.

We are incredibly proud to partner with a team that is redefining how we understand user behavior and build better products.
Ready to level up your product game? Grab your ticket today and join us at the Productlab conference 2026! CODE: 10X10OFF to celebrate!

Get Your Summer Bird Ticket Here

☀️ Summer evenings in the city are meant for good company.

Next Friday, we’re converting that summer energy into great product conversations. We’re putting together a special end-of-month meetup for the Lenny’s Newsletter community, and you’re invited.

Think of it as a relaxed Friday happy hour, but with people who love talking about conversion rates, user behavior, and scaling products just as much as you do. Bring your ideas, your questions, and your friends.

Shoutout to Matic for sponsoring the drinks and keeping us refreshed all evening!

🗓️ 24th of July, 18:30–22:30 CEST

📍 The Castle Berlin Mitte, Berlin

RSVP Here

📉 The product masterclass nobody talks about: Failure

We learn the most not from the shiny roadmaps that went perfectly, but from the features that flopped and the strategies that crashed.

Next week, we are skipping the theoretical advice and diving straight into real-world product f*ck ups. Join us online for an unfiltered conversation with top-tier product leaders who are ready to pull back the curtain on their biggest career missteps.

Who you’ll hear from:

• Ravi Mehta (Former CPO at Tinder) and Michelle Parsons (Former CPO at Hinge), teaming up with the Dodane do Backlogu team.

What’s on the agenda:

• Real, unedited stories of product mistakes at scale.

• How to actually handle failures when they happen.

• A realistic look at the AI landscape (minus the sales pitches).

If you’re tired of the “perfect launch” narrative and want insights you can actually use, this one is for you.

🗓️ 29th of July, 18:00–19:30 CEST

Save your Spot for the Livestream

📰 Product Leaders’ Wisdom

​​​​​Brought to you weekly by Leila Montazeri

System Dynamics & Context Management for Scalable Growth

• Most founders view sports marketing as an expensive vanity project. But there is a smarter path: performance-driven partnerships. This playbook on Henry’s Best Hits breaks down how a tech startup evaluated 10+ leagues to secure a Tier 1 NASCAR deal on their own terms. By leveraging distribution instead of raw cash, they unlocked a masterclass in trust transfer and measurable ROI. Read this to learn how to turn a cold DM into a national brand moment.

• Is your AI failing to generate compounding returns? The problem isn't your prompting; it’s a missing context layer. This deep dive from Growth Unhinged explores how growth teams can stop brand drift by building a four-layer AI GTM system using Claude Code. Learn how to architect dedicated context folders that sync with Hubspot and Gong, so your autonomous agents never forget your true ICP and messaging.

• AI has supercharged prototyping and documentation, yet fast product initiatives still end up feeling fragmented. Why? Because AI accelerates local tasks but leaves invisible integration work orphaned. Amy Mitchell shares how Builder PMs can prevent end-stage surprises. Discover how to loop in systems thinkers early to manage hidden dependencies and turn fast features into cohesive product growth.

💪 Open Roles

Brought to you weekly by Alessia Marchi​

1. Head of Product - Clients @ Upvest

2. Principal Product Manager - Operations @ Rohlík Group

3. Head of Product @ tandem

4. Product Manager - App & Digital Experience @ Lovehoney Group

5. Product Manager - Consumer Platform @ AUTO1 Group

6. Senior Product Manager - General Contractors @ Cosuno

7. Lead Product Manager - Shipping @ eBay

🎶 Song of the Newsletter

From our DJ Marco D’Avila

The countdown to the ProductLab Conference 2026 has officially begun! From September 15th to 17th, we are bringing together the brightest minds in product management, both live in Berlin and online.

To celebrate the season, we’ve just launched our exclusive Summer Bird Tickets at just €349! This is your chance to grab full access to world-class keynotes, networking, and actionable insights at the best possible price.

Don’t wait until prices go up. Claim your spot today and get ready to elevate your product game this September.

Get Your Summer Bird Ticket Here

Bringing ProductLab Closer to You: Satellite Events Across Europe

Can’t make it all the way to Berlin in September? Don’t worry, we are bringing the ProductLab experience directly to your local community!

We are excited to host a series of Satellite Events across various European cities, including Amsterdam, Brussels, Vienna, Madrid, Barcelona, and Lisbon. To support local product communities, we are providing budget assistance and online tickets for local hackathons, workshops, and exclusive watch parties.

Stay tuned for more details on locations and schedules; we can’t wait to connect with you locally!

Wrap Up July with Our Exclusive EOM Events!

We have curated two fantastic events that we are hosting and organizing just for you. Whether you want to network in person or dive deep into honest product stories online, we've got you covered.

Here is what’s coming up in July:

🇩🇪 Lenny’s Newsletter Meetup in Berlin

Join the local Lenny’s Newsletter community for an energetic evening of conversations around product, growth, and everything in between. This informal meetup is a brilliant chance to meet fellow product people, exchange real-world ideas, and have deeper conversations with members of the European product community. Drinks are on us, courtesy of our friends at Matic!

🗓️ 24th of July, 18:30–22:30 CEST

📍 The Castle Berlin Mitte, Berlin

RSVP Here

📺 F*ck Ups in Product: Your Stories w/ Ravi Mehta & Michelle Parsons

What if we talked less about perfect, shiny launches and more about what actually goes wrong behind the scenes? Join this raw and honest online conversation with senior product leaders Ravi Mehta (ex-CPO at Tinder, founder of Outpace) and Michelle Parsons (ex-CPO at Hinge, founder of Lora), together with the Dodane do Backlogu podcast crew. Expect real stories, lessons learned, actual product mistakes, and reflections on navigating the AI wave without the usual marketing hype.

🗓️ 29th of July, 18:00–19:30 CEST

Save your Spot for the Livestream

📰 Product Leaders’ Wisdom

​​​​​Brought to you weekly by Leila Montazeri

Grand promises of absolute AI automation are everywhere. But on the ground, the reality is different. This week, we explore the unsexy foundations of the AI era: sound product strategy, normalised data infrastructure, and rigorous, human-led documentation.

• Ed Zitron tears into a recent report by the Bank for International Settlements (BIS), exposing how tech giants are bleeding cash on hardware for demand that is largely manufactured. It’s a sharp reminder that massive compute power means absolutely nothing without an actual, sustainable business model behind it.

• Andrei Rebrov (Co-CEO, Finsi) shatters the illusion that AI is a magic bullet for B2B SaaS. His takeaway? AI doesn’t fix a broken product hypothesis; it just burns cash and pushes you to the wrong destination faster. He digs into the messy reality of data normalization and why human empathy still can’t be coded.

• Fred Walton argues that without intentional human “Conversation Design” your AI agent will sound like every other boring, clinical LLM on the market. By treating tone, structure, and human-handoff logic as core product features, he shows how a simple change in humanized phrasing can immediately spike CSAT.

💪 Open Roles

Brought to you weekly by Alessia Marchi​

1. Product Lead @ marta

2. Senior Product Manager - Supply Incentives @ Bolt

3. Head of Product – Agentic Offerings @ commercetools

4. Principal Product Manager - Agentic AI Platform @ Flatiron

5. Product Marketer @ Clera

6. Senior Product Manager - AI-Native, Product & Product Ops @ Eye-Able

7. Lead Product Manager - Home Connectivity @ Deutsche Telekom AG

🎶 Song of the Newsletter

From our DJ Marco D’Avila

And here 🥁…..

Possibly one of the best recaps of the whole talk: what actually is the risk with AI today.

Huge thanks to Christian Idiodi and the whole team for the massive support and for sharing the content so openly. This is exactly the kind of depth we live for.

Below is the full community recap, including a peek at what went down at the Leaders lunch. The video recap and the slides are both in there. HAPPY READING 💚

And here the lunch recap on Founder-style leadership

Check all Moments

Get the Slides

🥇 Two ways into Berlin this September [extended]

Productlab Conference 2026 lands September 15-17 at CIC Berlin: three days with 350 of Europe’s senior product leaders. We just opened two ways in, depending on how you like to move.

Bring your team. Group pricing now starts at 3, and when you bring 4 the 5th is on us. Ten bundles only, summer-only. Built for teams who plan their learning together.

No L&D budget? Win your seat. Post on LinkedIn before July 26 tag @Productlab, add #ProductlabConf, and share one reason you’re coming.

One winner takes the full bundle free (AI-Craft Day + Conference Day).
Ten runners-up get €100 off. Winners announced July 27.

That’s the whole idea: those who can, bring their people. Those who’d rather spread the word, win their way in. Sharing is Caring. ❤️

Bring your team

🤝 Want to join the behind-the-scenes crew at ProductLab 2026?

Last month I joined Marcin Jedrzejczak (Principal PM @Celonis) and Tomasz Tomaszewski (Founder @Product Academy) on their podcast, Dodane do backlogu, to talk about what makes product communities actually work across Berlin, Poland, and Italy.

It turned into a conversation about the people who shape how we think: the mentors and friends who ask the harder question instead of handing you the easy answer. Honestly, most of what I know about building product I owe to people like that.

We also got into the myths of community building, how to make a conference connection that outlives the badge, and the slightly absurd “dating psychology” behind getting world-class speakers to say yes.

If you listen, there’s a gift waiting: comment on the post with one of the codes and grab €100 off, 20% off, or a free online conference ticket.

📰 Product Leaders’ Wisdom

​​​​​Brought to you weekly by Leila Montazeri

As AI accelerates product shipping speeds, teams face a new operational crisis: ensuring systems and knowledge bases can keep up. This week, we explore balancing fast execution with human emotional intelligence, strict engineering discipline, and bulletproof AI Agent readiness

• Data and AI mine customer insights, but Emotional Intelligence (EI) is the human superpower AI cannot replicate. Roman Pichler highlights Daniel Goleman’s framework (Self-Awareness, Empathy, Conflict Resolution), proving EI impacts product success more than mere IQ. For leaders, strong EI builds stakeholder trust and decodes deep user needs.

• AI enthusiasts chase speed; AI skeptics fight technical chaos. Charity Majors tackles this dangerous rift where fast vibe coding leaves invisible architectural ruins. The solution? Stop ideological debates and treat AI adoption as a rigorous engineering problem. By exposing downstream cleanup costs and enforcing observability and guardrails, leaders can harness rapid AI code generation without letting their core systems collapse into complete entropy.

• Shipping features fast means nothing if your AI support agent hallucinates or breaks customer trust post-launch. Intercom shares its battle-tested New Product Introduction (NPI) process, making agent training upstream in development. Learn how to craft clear, literal knowledge assets, review duplicate content, and run aggressive pre-launch FAQ testing.

💪 Open Roles

Brought to you weekly by Alessia Marchi​

1. Head of Product - Growth @ Doodle

2. VP of Product @ Clue

3. Senior Product Marketing Manager @ Shine

4. Senior Technical Product Manager @ Staffbase

5. AI Product Manager @ Cortea

6. Senior Product Manager Retention @ Every

7. Principal Product Manager - Rides Matching @ Bolt

🎶 Song of the Newsletter

From our DJ Marco D’Avila

1. Founder-style leadership is really just two things: product sense and coaching.

Not charisma, not “founder mode” as a personality. Product sense is the accumulated expertise of being close to customers, to the business, to the work for a long time. Coaching is your ability to pass it on. Everything else leaders argue about sits downstream of those two.

2. You can’t coach what you don’t have. And you can’t give what was never given to you.

This was the line that stuck. Most weak leadership isn’t bad intent, it’s leaders who simply never experienced good leadership themselves, so they have nothing to pass on except instructions. “Do it because I said so” is what’s left when there’s no product sense underneath. Which means before we hand anyone a leadership role, the real question is: have they done the work well enough to have something worth coaching?

3. The chef analogy is the clearest definition of product sense I’ve heard.

A great cook has two things. Sense: give her any dish she’s never made and it comes out right. Taste: she tastes yours and knows instantly it needs more salt. Nobody is born with either. She built it from years in the kitchen, tasting things that failed. Product sense and product taste work exactly the same way, and you develop them the same way: real customers, real data, real decisions, real failures. Not a book, not a training.

4. So coaching product sense looks like teaching someone to cook.

You don’t hand them a recipe. You create a safe kitchen, you cook together, you taste things that suck and try again. In our world that’s time with customers, time in the data, time with stakeholders. And the tell of a leader who actually has product sense: the questions they ask after a presentation. Not “great job,” but “how long did you cook the chicken.” Deep, specific questions, asked to sharpen your judgment, not to catch you out.

5. The photographer analogy is how I now think about AI.

AI is the iPhone. It lets everyone take a decent photo, and it lets everyone build a decent-looking product. But the iPhone never handed anyone picture sense. The photographer still wins, because the value was never the click, it was the discernment: the angle, and the selection afterwards. That “selection afterwards” is discovery. It’s the part that decides whether a product wins or just exists. AI makes the building cheap, which only raises the value of the taste deciding what’s worth building. The best people in that room cook first, then ask AI what they missed. They don’t ask AI to cook for them.

6. AI can be the coach when your manager isn’t one.

This is the part I keep thinking about for our community. Set up as a product coach, available 24/7 and psychologically safe, AI compresses what used to take three months of onboarding into about three weeks. It doesn’t replace a great manager, but it’s far better than a bad or absent one. The honest takeaway: weak product sense is no longer something you get to blame your manager for.

A few thanks to: Salvador Restelli and Christin Schink for opening the doors at mobile.de for a full day, and to Miro for supporting the community event. All the joiners on making in a such hot day. And to Christian Idiodi: the best storyteller I have ever met, humble and crystal clear, the way real leaders are. Thank you!

Subscribe now

Last week Christian Idiodi, Partner at Silicon Valley Product Group and co-author of Transformed*, came to Berlin for one of our most electric meetups yet: Product Management in the Generative AI Era. Sponsored by mobile.de and Miro. What follows is less a recap than a reflection, stitched together from what the room wrote down afterwards.*

“If we want things to stay as they are, things will have to change.”
Giuseppe Tomasi di Lampedusa, The Leopard

Lampedusa named the paradox of every technology revolution a century before generative AI. Everything must change so that everything can stay the same. The tools turn over completely, the workflows become unrecognizable, and yet the thing that actually matters underneath stays exactly where it was.

For product people, that thing has always been business outcomes. Not output. Not velocity. Not how many things we shipped. Value that customers will pay for, and viability for the business that serves them. This is Christian’s quiet argument: the AI era doesn’t rewrite the job. It raises the stakes on whether we remember what the job was.

The seduction of the builder economy

Here is what’s seductive. The builder economy tells us we can all build now. It’s easy. It’s fun. It makes us feel smart. Type a prompt, watch a prototype appear, ship something that would have taken a team a quarter.

But we’ve been here before. The internet was going to make everyone a publisher. The cloud was going to make everyone an architect. Mobile was going to put a software company in every pocket. Social media made us all photographers, each of us suddenly carrying a better camera than a 1990s professional.

And what happened? Instagram made us all photographers, but it didn’t create armies of new professionals. It created an influencer economy, new marketing channels, new ways to distribute attention. The democratization of the tool didn’t democratize the craft. It changed what the craft was worth and where the scarce skill moved to. The builder economy is the same story, one more time. Making building cheap doesn’t make good judgment cheap.

The aftermath: everyone looks smart, fast

This is the part that should make every product person uneasy. As Christian put it, and as Vladimir Liashenko wrote in the Productlab recap afterwards, AI gives you higher output, but it does not guarantee higher outcomes. That gap is on the product model to secure. If your model is broken, AI doesn’t fix it. It amplifies the dysfunction at speed.

So the aftermath is strange: everyone seems smart, everyone is moving fast, the prototypes are flowing ten and twenty and thirty in a week. The mechanical work got cheap, and we got a flood of look-alike products to prove it. But the thinking got more expensive, not less. And in the rush of output, the quiet danger is that we forget we were never supposed to be output people. We were supposed to be outcome people.

Miruna Popa caught the mood in one line Christian dropped: “We’re using AI to accelerate our misery.” The whole room laughed, because everyone felt it. Her reframe is the antidote: you don’t need to know which of your twenty ideas is best. You need to know which five are worst, and kill them. Ideas were never scarce. The discipline to experiment across them, and to stop when the data answers, is what’s scarce.

Change everything to keep the one thing

So how do you change everything in order to keep the one thing? The community’s notes converge on a surprisingly old answer.

Subir Paul reminded us that when Product Management was invented in 1931 by Neil McElroy, later P&G president and US Secretary of Defense, the role had four duties: Brand Advocate, Market Analyst, Sales Support Lead, Business Owner. Not one was a delivery task. Over the decades, as PMs got buried in sprint planning and backlog grooming, the strategic core got handed off to “the business.” Now AI is automating the admin, and the reckoning is simply this: we go back to what the job always was.

Christian’s framing for how gave the room two modes, the way Tural Nabizade captured it. First, build to learn: use AI to prototype heavily and cheaply, to test whether your solution actually solves the problem. Then, once you have clarity, build to earn: ship commercial-quality product as fast as the new tools allow. The mistake of the builder economy is to collapse the two, to do a great deal of fast building that earns nothing. And underneath both modes, the line PMs needed to hear most: value and viability are on us. Engineers and designers own usability and feasibility. No one else owns the risk of whether we picked the right problem.

Maybe that’s why so many said a version of the same thing afterwards. Alexander Tikhomirov put it best: Christian didn’t say a single thing they hadn’t heard before, and it still changed what they’d do that week. The SVPG principles are easy to nod at and hard to live by. What Christian does is drag the idealized picture back into the real world of deadlines and roadmaps, and show that behind every principle sit concrete, doable instructions. Deliver. Earn trust. Show by example that work can go differently. And always, always, think about the value people will actually pay for. Asked what he’d tell a founder with no money and a mountain of tasks, his answer was blunt: use every capability AI gives you to run as many experiments as you can, and find product-market fit as fast as possible.

The ride ahead

The builder economy isn’t the enemy. Cheap building is a gift, if you remember what it’s for. AI made the output trivial precisely so that the outcome could become, once again, the only thing that distinguishes us. Everything had to change for that one thing to stay the same.

That’s the conversation we’re carrying into the Productlab Conference this September. If half the talks are as good as this one, we’re in for a great ride. Huge thanks to Christian for extending his trip to be with us, to mobile.de and Miro for sponsoring, and to everyone who made the room what it was.

PS: We asked Christian the Slides, and we might get them in the upcoming weeks.

Check all Moments

🥇 Two ways into Berlin this September

Productlab Conference 2026 lands September 15-17 at CIC Berlin: three days with 350 of Europe’s senior product leaders. We just opened two ways in, depending on how you like to move.

Bring your team. Group pricing now starts at 3, and when you bring 4 the 5th is on us. Ten bundles only, summer-only. Built for teams who plan their learning together.

No L&D budget? Win your seat. Post on LinkedIn before July 5, tag @Productlab, add #ProductlabConf, and share one reason you’re coming.

One winner takes the full bundle free (AI-Craft Day + Conference Day).
Ten runners-up get €100 off. Winners announced July 6.

That’s the whole idea: those who can, bring their people. Those who’d rather spread the word, win their way in. Sharing is Caring. ❤️

Bring your team

🤝 Want to join the behind-the-scenes crew at ProductLab 2026?

We’re looking for 10 proactive volunteers to help us run our main conference days in Berlin this September 15–17. If you are reliable, sharp, and want to experience a world-class tech event from the inside, this is for you.

Why join the crew?

• Learn on the Job: Get full access to keynotes from global product and AI leaders whenever you aren’t on duty.

• Network with Pioneers: Work directly alongside the organizing team and rub shoulders with industry speakers.

What you’ll do: Help us handle registration, support the speaker stages, and keep the attendee experience flawless.

🚨 Deadline: We are closing applications as soon as we hit 10 rockstars, with a hard cutoff on June 30th. Apply now to secure your spot!

JOIN US!

📰 Product Leaders’ Wisdom

​​​​​Brought to you weekly by Leila Montazeri

The human element isn’t getting replaced by automation; it’s being forced to step up. This week’s reads dive into why outsourcing your coding, data tracking, and interviews to bots means your personal taste and real human judgment matter more than ever.

• Coinbase actually built a bot that takes a raw Figma design and turns it into working, live code without a developer needing to recreate it block by block. Department of Product reveals how they hooked large language models up to their existing design tokens to keep things consistent. If you are tired of losing small design details in the handoff from design to engineering, the step-by-step breakdown of their custom setup is a goldmine.
  

• Sahil Jain built an entire software platform with just a tiny skeleton crew, and his biggest takeaway is a bit upside down: engineering is no longer the bottleneck. Because bots can write the code instantly, the real struggle now is having the restraint to not build every random idea that pops into your head. It is a raw look at why human taste and saying “no” matter way more than actual technical execution right now. Louron Pratt gives us lessons about building during the AI Age.
  

• Product Coalition, shares a sharp, 60-year history lesson on how we stopped talking to actual people. It tracks the shift from old-school 1960s focus groups down to modern dashboards where users are just numbers on a screen. The author pulls no punches about the danger of using AI to run “synthetic” interviews, arguing that if you just stare at graphs and automated summaries, you completely miss the weird, irrational human quirks that make software successful.

💪 Open Roles

Brought to you weekly by Alessia Marchi​

1. Product Lead - AI-Powered Learning & CultureOS @ Sharpist

2. Senior Product Manager – AI @ smartclip

3. (Lead) Product Manager - Energy Utility Platform @ 1KOMMA5°

4. Senior Product Manager - Search @ mobile.de

5. Principal Product Manager @ Zalando

6. (Senior) Product Manager @ Customer Alliance

7. Product Director @ sennder

🎶 Song of the Newsletter

From our DJ Marco D’Avila

🎫 Next Up in Berlin: Christian Idiodi!

Together with mobile.de and Miro, we are bringing one of the industry’s most influential product leaders to Berlin: Christian Idiodi (Partner at SVPG & Co-author of Transformed). This is an exclusive, raw, and deep conversation limited to just 100 product professionals.

The Focus: Product Management in the Era of Generative AI, which is fundamentally redefining how we discover, validate, and launch products. If you think your role won’t change, Christian is here to challenge that assumption, and equip you with the toolkit to thrive in what’s coming next.

🗓️ 24th of June
📍 Berlin

Get your Ticket

Are you near Italy or looking for a reason to practice your Italian? We have an exciting local community event coming up in just a couple of weeks!

🇮🇹 Fireside with a CPO (Verona, Italy)

We’re hosting an open, filter-free fireside chat with Carlo Alberto Gaetaniello, the Chief Product Officer at Serenis. He’ll be diving into the real, unwritten realities of product management: how PM careers are evolving, how AI is changing team dynamics, and the unique challenges of scaling a high-trust digital health service. Come for the insights, stay for the networking dinner, and connect with the European product community. (Heads up: This event will be conducted entirely in Italian!)

🗓️ 1st of July
📍 Verona

See You in Verona

🤝 𝗧𝗵𝗲 𝗦𝗲𝗰𝗼𝗻𝗱 𝗔𝗰𝘁:𝗛𝗼𝘄 𝗚𝗿𝗲𝗮𝘁 𝗔𝗽𝗽𝘀 𝗘𝘅𝗽𝗮𝗻𝗱 𝗪𝗶𝘁𝗵𝗼𝘂𝘁 𝗕𝗿𝗲𝗮𝗸𝗶𝗻𝗴 𝗧𝗵𝗲𝗶𝗿 𝗥𝗲𝘁𝗲𝗻𝘁𝗶𝗼𝗻 𝗘𝗻𝗴𝗶𝗻𝗲

If you’re planning to be in Berlin next month, you’ll definitely want to catch this live panel at the App Growth Summit®. Daniele Ronca is teaming up with product and growth leaders from Gymondo, Acture, and N26 at The Spreespeicher. They’ll be breaking down the exact strategies top apps use to expand into new markets and business models without destroying the retention loops that made them successful in the first place. If you’re an app growth expert or product manager navigating the messy realities of scaling a product right now, secure your free invite and come join the conversation.

🗓️ 8-9th of July
📍 Berlin

Join AppGrowthSummit

🤝 Want to join the behind-the-scenes crew at ProductLab 2026?

We’re looking for 10 proactive volunteers to help us run our main conference days in Berlin this September 15–17. If you are reliable, sharp, and want to experience a world-class tech event from the inside, this is for you.

Why join the crew?

• Learn on the Job: Get full access to keynotes from global product and AI leaders whenever you aren’t on duty.

• Network with Pioneers: Work directly alongside the organizing team and rub shoulders with industry speakers.

What you’ll do: Help us handle registration, support the speaker stages, and keep the attendee experience flawless.

🚨 Deadline: We are closing applications as soon as we hit 10 rockstars, with a hard cutoff on June 30th. Apply now to secure your spot!

JOIN US!

📰 Product Leaders’ Wisdom

​​​​​Brought to you weekly by Leila Montazeri

This week, we’re diving deep into the messy reality of shipping AI agents and managing LLM costs without burning through our budgets. If you’re trying to move past the AI hype and figure out how to actually architect, prioritize, and scale these systems efficiently, these three pieces are essential.

How to Stop the Token Burn and Cut AI Spend

We’ve all heard the horror stories of companies blowing through their annual AI budgets in a matter of months. In his latest post on Ravi Mehta tackles the “tokenmaxxing” trend, our chaotic, undisciplined rush to burn tokens on the biggest models available. He shares three brilliant, counterintuitive architectural fixes to help teams stop over-engineering their prompts and cut their LLM costs by up to 10x without sacrificing quality.

A Product Manager’s Guide to Prioritizing AI Agents

Your backlog is probably stacked with half a dozen “agent” ideas, but trying to prioritize them using a standard impact-vs-effort matrix is a trap. Writing for Lenny’s Newsletter, drops a definitive framework that breaks agents into three distinct categories based on complexity and architecture. It’s a must-read if you want to stop comparing apples to jet engines and ship real ROI in weeks rather than months.

Managing AI Agents Like Human Freelancers

Why do most AI agents fail before the model even runs? In this incredibly insightful podcast episode, Julia Dalton (SVP of Product at Capacity) argues that coordinating thousands of AI agents is exactly like managing a massive network of human freelancers. Drawing from her background in crowdsourcing, she explains how to build robust validation loops, use recursive prompting, and set up triage systems that actually work in production.

💪 Open Roles

Brought to you weekly by Alessia Marchi​

1. VP Product @ KoRo

2. Senior Product Manager - Machine Learning @ voize

3. Head of Product – Agentic Offerings @ commercetools

4. Senior Product Manager @ Superhuman

5. Product Marketing Manager - Enterprise @ n8n

6. Senior Product Manager - Partner Platform @ Aroundhome

7. Group Product Manager - Dealer Inventory & Performance @ Attio

🎶 Song of the Newsletter

From our DJ Marco D’Avila

“What do I need to do to get promoted?”

If you’re managing people, this is likely a familiar question from your team members.

Your gut reaction might be to pull up the competency matrix, check their recent launch metrics, and start building a business case. After all, they’ve been consistently delivering, and have more responsibility than some PMs already at the next level.

But for you - the sponsor of a potential promotion - there are broader considerations too.

Every potential promotion case (whether it leads to a promotion or not) has a ripple effect through an organisation.

By understanding the ecosystem of a promotion, and being intentional about how you handle promotions within it, you’ll reduce the guesswork for both you and your team members.

The questions below are inspired by my 20 years in product management, chairing and participating in promotion reviews in four organisations and a 100% success rate of securing promotions and job family transfers for my team members.

1. How well do I understand the principles for promotion at my company?

Promotion processes are usually documented - but interpretation and execution of the process will vary. The better you understand the nuance, the higher chance you have of knowing when and how to successfully present a promotion case.

Things to consider include:

How much strong performance is ‘enough’ to get a promotion? Is sustained next level work for 12 months required or can a shorter period of exceptional impact also qualify?

How soon after a ‘no promotion’ decision can someone be re-presented?

What can cause an automatic ‘no promotion’ decision? Will someone who hasn’t demonstrated any community contribution or met their annual in-office days be automatically rejected?

💡 Actionable Ideas

Document the unwritten: Read everything you can find about the process and try to fill the gaps. Write down what you think is true, even if it is not explicitly written in the HR handbook.

Validate your assumptions: Talk to peers and leaders who have been in and chair promotion reviews to understand the reality better.

2. What does supporting this promotion communicate about my leadership judgment?

Promotion processes can be a fantastic opportunity for managers to demonstrate their leadership skills.

Bringing a promotion case is a visible indicator to your team, your peers, and your executives of how you perceive excellence.

Get it right, and you show that you hold an intentional and high performance bar, can clearly articulate the value your team is creating, whilst actively championing your people.

💡 Actionable Ideas:

Define next-level excellence: Develop a strong perspective on what next-level performance looks like and communicate it consistently and clearly to your team. You can do this through your comms around promotions which do happen (see question 4) and by drawing attention to work and impact which is ‘good for level’ in development discussions, team meetings etc.

Gather real-time evidence: Ensure your team members are consistently gathering evidence of their impact and collect feedback when the work happens and the observations are fresh - rather than waiting until ‘feedback season’. At the very worst, do it at the end of each quarter.

Leverage ‘ready soon’ forums and discussions: Some companies allow managers to present ‘ready soon’ cases at promotion reviews to get feedback on readiness. If yours doesn’t, then ensure you’re having routine conversations with your peers and executives about the skills and visibility of your team members. You might call a dedicated ‘team review’ calibration session or make conversations about your team members part of your regular chats with peers.

Embrace the friction: Get comfortable managing expectations and having the hard conversations early if someone clearly isn’t ready. Kim Scott’s Radical Candor blog and podcast offers great advice on how to have hard conversations including reseting team member expectations and how to avoid making empty promotion promises.

3. Have I validated their readiness with their cross-functional peers?

Whilst the promotion decision may be made by the product management job family, the cross-functional influence your PMs have is key to their success.

You can demonstrate your commitment to cross-functional partnerships too by making your cross functional partners part of the process.

This can also make it easier for you to share feedback about cross-functional team members in return.

💡 Actionable Ideas:

Map key relationships: Identify the critical cross-functional stakeholders (e.g., engineering, design, marketing, sales) for each candidate.

Articulate what good looks like: Share examples of good cross-functional relationships, forums, documentation etc.

Proactively gather qualitative input: Establish a regular cadence with cross-functional partners to review the candidate’s operational impact, collaborative health, and leadership presence before the formal cycle begins.

4. What signal will this promotion send to the rest of my team?

Every promotion sends a loud, public signal to three specific groups: those actively vying for advancement, those who aren’t quite there yet, and those already at the next level.

Consider what your promotions and rejected promotion bids send about skill, performance, impact and behavioural expectations.

💡 Actionable Ideas:

Model “good”: Use promotions to explicitly showcase to the wider team what excellent performance actually looks like. When a promotion happens, control the public announcement. Share openly, clearly, and objectively why they earned it.

Nurture the pipeline: Simultaneously, be generous with constructive feedback for the rest of your promotion-track cohort to foster healthy growth.

Consult the next tier: Include those already at the target level in your feedback-gathering rounds. This helps you understand current perceptions and evaluate what kind of peer dynamic the newly promoted person will be entering.

5. Have I built executive exposure for them with the next level up?

As part of the promotion consideration, existing senior leaders need to understand how this person will positively contribute to the organisation’s broader goals. The promotion review should never be the first place they learn about the candidate and their impact.

💡 Actionable Ideas:

Get them on radars early: Proactively create opportunities for your candidate to gain executive exposure, mentoring, and strategic positioning with leaders at the next level up.

Start with shadowing: If a candidate lacks confidence, start by having them watch and shadow executive sessions. This builds their familiarity with the culture, tone, and strategic dynamics expected at the senior level.

6. What are the headcount and financial constraints to consider?

Every promotion ultimately requires an available role at the next level and the budget to accommodate an increase in salary. It’s crucial that you understand this context.

Even when everything else in the case suggests the promotion should happen, macroeconomic and business constraints can still be the make-or-break factor.

Understanding these realities allows you to manage your team’s expectations realistically, preventing a high performer from feeling blindsided by factors entirely outside your control.

💡 Actionable Ideas:

Audit the budget early: Find out as much as you can about headcount allocations and financial parameters as early as possible. You can often find this out from speaking to your lead, HR and operational/finance colleagues typically involved in these processes.

Decouple growth from titles: Ensure your team knows you are invested in their skill development and scope expansion, even during quarters when corporate budgets put a temporary freeze on title changes. The better you understand what motivates your team members, the more successful you’ll be at ensuring they stay engaged and happy, regardless of promotion success.

Further reading & watching:
Promotion Schmomotion - Kim Scott, Radical Candor
12 tips for managers on how to approach promotions - Fast Company
The promotion mistakes that derail PM careers - The Skip

Lucie McLean is a product leader and executive coach based in Berlin. Lucie works with product leaders through 1:1 coaching and also leads the Productlab Leaders Circles - where curated groups of product leaders come together to support, inspire and energise each other to amplify their growth and impact.

To work with Lucie or other coaches with a product leadership background check our Program.

Learn More

🎫 Christian Idiodi is Coming to Berlin!

The wait is over. Following our unforgettable evening with Marty Cagan, we are thrilled to announce the next chapter. Productlab, alongside mobile.de and Miro, is bringing one of the world’s most respected product minds to Berlin: Christian Idiodi (Partner at SVPG & Co-author of Transformed).

No dry keynotes. No scripted panels. Just an honest, deep conversation in a room of 100 product professionals.

The Talk: Product Management in the Generative AI Era

Generative AI is shifting how we discover, test, and deliver products. If you think your role is immune, Christian is here to challenge that—and help you prepare for what’s coming.

🗓️ 24th of June
📍 Berlin

Get your Ticket

ProductLab Conference 2026: Agenda is Live + Exclusive 10% Discount!

We have some news regarding our upcoming ProductLab Conference on September 15–17! The agenda is now officially locked in and live on our website. Go check out the incredible lineup of sessions and speakers we have planned for you. Plus, even though our Early Bird tickets are sold out, we have a special treat for our newsletter community. Use the code “JUNE10” to get 10% off your ticket! It is limited to the next 10 people and expires at the end of June!

Explore the Agenda

🤝 Go Behind the Scenes: We’re Looking for 10 Volunteers!

For the Conference this September (15–17) in Berlin, and to keep everything running seamlessly, we need a crew of 10 proactive volunteers to join us on the ground. If you are reliable, energetic, and ready to dive in, whether you’re looking to break into product management or just love the energy of live tech events, we want you on our team.

As part of the crew and when you’re not helping with operations (like handling registration, supporting the stages, or guiding attendees), you’ll get full access to the keynotes to learn directly from top product and AI leaders. You’ll also work side-by-side with the organizing team, perfect for networking with industry pioneers, plus we’ll cover your food, drinks, exclusive crew gear, and after-party access.

We only have 10 spots available by June 30th and want to lock them in quickly.

Apply to Volunteer Here

📰 Product Leaders’ Wisdom

​​​​​Brought to you weekly by Leila Montazeri

This week, three sharp takes on the same uncomfortable truth: most teams are optimizing the wrong thing, building more, faster, instead of figuring out what’s actually worth building.

In ‘Why Prioritization Frameworks Are Killing Your Product’, Michael Goitein argues that frameworks like RICE or ICE often fail because they prioritize features instead of strategy. He contends that product teams should focus on solving the most important customer problems and aligning decisions with clear business goals rather than relying on scoring systems. Effective prioritization comes from strategic clarity and understanding user needs, not from mathematical formulas that can lead to feature bloat and misguided decisions.

The MVP is dead, and good riddance. Ravi Mehta makes the case that everything we inherited, specs, staged handoffs, minimum viable thinking, was designed to manage the cost of building the wrong thing, not to help us build the right one. Now that AI has collapsed the cost of software, the assembly line gives way to the jazz band. Prototyping is no longer a phase; it’s how the best teams think, decide, and validate every single day.

Not all building is the same, and confusing the two is quietly killing your product team. Marty Cagan (SVPG) draws a sharp line between building to learn (discovery) and building to earn (delivery), and argues that as shipping costs collapse, discovery is now where your competitive edge lives. If your PMs are still project-managing specs instead of prototyping solutions, this one will reframe what “doing the job” actually means in the AI era.

💪 Open Roles

Brought to you weekly by Alessia Marchi​

1. Product Lead @ Attio

2. Senior Product Marketing Manager @ Oviva

3. Director Product - Devices @ tonies

4. Principal Product Manager - Apps @ HomeToGo

5. Product Leader - Agent Platform @ JetBrains

6. Senior Product Manager - Conversational Banking @ N26

7. Product Manager @ PayPal

🎶 Song of the Newsletter

From our DJ Marco D’Avila

Product Meetup Milano: Lessons from the stage

Our Milan meetup was an absolute blast—packed and the conversations around AI were too good not to share. We had two sharp PMs break down how they’re moving past the AI hype and into actual, high-value workflows.
Alessandro Dadone (Lead PM at Qonto) gave us a candid look at the "temptations" of AI. He talked about how easy it is for PMs to fall into the trap of acting like "mini-engineers"—spending time writing scripts or prototypes that engineers then have to fix. His point was clear: AI shouldn’t turn you into a junior coder; it should help you be a better PM. At Qonto, they’ve moved from basic prompting to building "skills" directly into their workflow. Whether it’s using their internal tool, Minerva, to screen millions of customer data points in real-time or having AI agents challenge their product briefs, the goal is to kill the manual grunt work so the team can focus on solving real problems.

Next, Sebastiano Pighi (Senior PM at Sibill) shared how they validated whether AI was actually the right solution for their users. After building standard financial dashboards, they realized that while dashboards handle common issues, they struggle with specific, messy user questions. They ran a simple test to see if users would actually talk to an AI about their finances; 95% said yes. That led to Perla, their AI assistant that handles the heavy lifting, like analyzing price fluctuations or finding exactly where a business can save money. For Sebastiano, AI was the only way to solve those "one-off" complex problems that a static dashboard just can’t touch.

🎫 June is shaping up to be quite a month 🥁

We aren’t revealing the full plan just yet. For those who enjoy a bit of suspense and want to stay in the loop, this is your cue to save the date! 😉
We've partnered with mobile.de for a special Berlin event on June 24th, focused entirely on bringing together senior product minds. It’s an evening meant for high-level networking and fresh perspectives but with an unexpected twist.

Mobile.de: THE BIG SECRET SUMMER COMMUNITY EVENT

Register Here

📰 Product Leaders’ Wisdom

​​​​​Brought to you weekly by Leila Montazeri

AI matters: Stop defaulting to the obvious answer. Start with the actual problem.

The default response to a new situation is usually lazy, fear-driven, or disconnected from reality, and the people who win are the ones who slow down, ask a sharper question first, and calibrate their response to the actual constraint.

Dan Hock, in his article “How to Use AI Without Losing Your Mind,” argues that a lot of AI work is really just productivity theater: elaborate workflows built for problems that never needed solving in the first place. Instead of asking “How can I use AI here?”, he suggests starting with a more important question: Is this actually a meaningful problem, and does it require execution or exploration?

The Monday Cake, in “You’re Not Behind on AI,” takes aim at the constant pressure to keep up with every new AI development. The piece is a refreshing reminder that most of us don’t need to know everything. What matters is understanding the level of AI literacy that’s actually useful for our work right now, not chasing every headline or trend.

Pranav Pathak argues in “Most AI UX Is Lazy” that many teams start with the interface instead of the user problem. They ask how to add AI to a product rather than what new problem AI makes possible to solve. It’s a sharp critique of chatbot-first thinking and a useful reminder that good product design starts with user needs, not technology demos.

💪 Open Roles

Brought to you weekly by Alessia Marchi​

1. (Senior) Product Manager - Revenue Operations & Intelligence @ ablefy

2. Principal Product Manager - Fulfillment Planning @ Zalando

3. Senior Product Manager - Traffic/ Road alerts @ HERE

4. Head of Product @ 7Learnings

5. Product Marketing Manager @ UP42

6. Senior Product Manager - AI Pathology @ Aignostics

7. Sr Lead Product Manager - Compliance KYC @ PayPal

8. FROM OUR COMMUNITY:
   Technical Product Manager @ Tandem
   Head of Product @ Tandem

🎶 Song of the Newsletter

From our DJ Marco D’Avila

He called it a paradox. Economists now call it a law.

We are living through the same thing. The resource is not coal. It is attention. And AI is the new steam engine.

The promise was simple: AI handles the routine, you get the hours back. Satya said it. Sundar said it. Sam said it. Every SaaS dashboard with a sparkle icon in the corner said it. Save 5 hours a week. Reclaim your afternoons. Finally have time to think.

People in the highest AI-exposure jobs are working 3 hours and 15 minutes more per week than before.

UC Berkeley found that 67% of workers who adopted AI tools in 2025 reported working more hours by year-end, not fewer. Only 8% of the time AI saves is reinvested in activities that benefit the worker. The rest is absorbed by expanded output expectations, or consumed by the overhead of managing AI itself.

This was predictable. Jevons told us.

I sat with Alex Bleau, my cowriter on this piece, Senior Innovation Manager at E.ON and a Deep Dive host at the Productlab Conference this September. These are some reflections from that conversation.

Share Productlab Newsletter

If 77% of workers say AI increases their workload, where does that time appear in the hours-saved calculation?

The calculation has a structural problem. It counts the time saved generating the output. It does not count the time spent deciding whether to trust it.

77% of workers say AI tools increase their workload because of reviewing outputs, fixing mistakes, and juggling platforms. Only 17% of US adults say workplace AI is reliable without human oversight. One in three workers skips the review entirely, which does not solve the problem. It hides the cost until it surfaces as an error downstream.

There is also a baseline problem nobody names. The studies that claim time savings compare input hours to output volume. They do not compare outcomes.

“Are we comparing time saved against the same outcomes we were delivering, or just more output? It is one thing to generate more slide decks. It is another to say we delivered the same value in half the time.”

Alex gave me a small example that stayed with me. He spent three minutes asking an LLM to translate a single word into another language. A dedicated translation tool would have taken ten seconds. The instinct to reach for AI first is itself a new time cost, and nobody is counting it.

AI eliminated the cognitive break. When the 20-minute task takes 20 seconds, does the worker pause?

The 20-minute task used to have a second function nobody tracked. It was a break. Not rest exactly: you were working. But a lower-intensity moment that let the mind reset before the next hard problem.

AI compressed that task to 20 seconds. The worker does not pause. They move immediately to the next thing. And the next thing is also cognitively demanding.

This sits on top of a calendar that was already broken. Microsoft’s 2025 Work Trend Index found employees receive a ping every two minutes during core hours: 275 interruptions per day. It takes 23 minutes to regain deep focus after a single interruption. AI made it easy to run four or five prompts simultaneously, multiplying the threads to review.

“The switching cost was not removed. It was multiplied. You feel like you are doing more because the output pile is bigger. The cognitive fragmentation is worse.”

MIT Media Lab coined the term cognitive debt: participants who relied on LLMs showed the weakest neural connectivity, while those who worked from memory showed the strongest. Frontiers in Psychology traced the symptoms: long-term AI use is associated with mental exhaustion, attention strain, and reduced decision-making confidence.

What AI removed were the moments between tasks. Those moments were not wasted time. They were processing time.

If the people at Klarna freed by AI are now generating 3.6x the revenue per person, who actually got the time?

Klarna is the cleanest case study in the Jevons Paradox applied to a company. Between 2022 and 2025, headcount fell 49%: from 5,527 to 2,907. Revenue grew 108%. Revenue per employee went from roughly 340,000 to 1.24 million euros, 3.6 times the prior level.

The freed time did not go to the workers who survived. It became revenue.

Glassdoor ratings fell from 3.8 to 3.0 in the same period. That is the sound of the survivors.

When a company says AI freed up time, the question nobody asks in public is: freed up for whom?

Non-work AI adoption (50%) now exceeds work adoption (41%). Did the Jevons Paradox follow you home?

Federal Reserve data from April 2026 shows non-work AI use (50% of the population) growing faster than work use (41% of the workforce), up 26% year-over-year.

People are spending evenings building things with AI. Personal tools, side projects, apps they wanted to exist. This is genuinely exciting. It is also the Jevons Paradox running on personal time.

The promise is: build anything in an afternoon. The realistic timeline for a beginner project is 1-2 focused weeks. The AI made it possible. The AI did not make it fast.

There is a more specific version of this for product managers.

“When AI makes you a builder, it also makes you an experimenter. Experiments look like work. They feel like professional development. The risk: a portfolio of AI projects nobody asked for, solving problems that do not exist, while the real product bottlenecks bleed money.”

Efficiency expands what you attempt, not how much you rest.

If the FOMO is rational, is staying current with AI itself a form of overload?

The FOMO conversation usually goes one of two directions: psychological failing to be managed, or noise from the easily distracted. Neither framing takes the situation seriously.

A 2026 study in BMC Psychology identified FOMO, AI dependency, and anxiety as antecedents that all converge to increase cognitive load. ManpowerGroup’s 2026 Global Talent Barometer: AI use up 13% in 2025, confidence in its utility down 18%.

The most diligent people, the ones reading everything, trying every new tool, are accumulating the most cognitive debt. They are right that the floor is moving. But the act of staying current is itself exhausting, and that exhaustion compounds the problem it was supposed to solve.

There is a name forming for it: learning burnout. The specific exhaustion of trying to stay current with a field whose floor moves faster than you can absorb it. You are not tired of the work. You are tired of the homework that comes with it.

And this learning sits nowhere on the books. AI spending is projected to rise 44% in 2026. Training budgets grow 5%. Average employee learning time fell from 47 to 40 hours per year. Fewer than 20% of organizations track defined KPIs for their AI initiatives.

“Both the team and the company are paying for this learning right now with way more time and cost than we are getting out of it. And it is just accepted.”

Alex sharpened the edge. The investment framing is not wrong. Both sides are treating this as an investment. The problem is the invisibility. In every ROI conversation, in every productivity headline, these costs are real, they are paid, and they are almost never reported.

The FOMO is not irrational. The response to it is unsustainable.

Production went infinite. Time did not. Attention collapsed.

Time is the only fixed unit in this equation. Compute scales. Capital scales. Headcount scales. Production capacity is effectively unbounded. But the audience, the user, the colleague, still has the same 24 hours they had in 1865.

When publishing a blog post drops from a writer’s day to four minutes, companies do not publish four times more. They publish forty times more. The hours users are willing to spend evaluating, learning, and adopting did not expand to match. They contracted.

Emilia Korczynska, VP of Marketing at Userpilot, laid out the drop rates clearly. The numbers are uncomfortable:

• Average product adoption fell from 20% to 6% as shipping accelerated. Teams shipped more in the last 12 months than the previous three years combined, with core engagement metrics moving less than 2%.

• Cold outreach open rates are collapsing.

• Webinar attendance is down.

• Email engagement is down.

• Blog traffic is flat or declining, even at companies producing 5x more content. Users are routing around the content layer entirely and asking AI tools for instant answers.

Emilia named the mechanism. Vibe marketing is what happens when production cost goes to zero and discovery gets skipped. The same vibe coding pathology, one layer up. Nobody asked whether anyone wanted the ROI calculator. But it ranks for three long-tail keywords and ChatGPT might cite it, so ship it.

So what is actually working? The opposite of vibe marketing. The channels where authentic human signal cannot be faked:

• Founder-led content. Real humans saying real things from real experience.

• Founder sales. CEOs and VPs personally selling to prospects.

• Niche creators. Trusted precisely because they cannot be vibe-produced.

• Community. Slack groups, meetups, conferences. The places AI cannot follow you yet.

Scarcity 101. As the supply of automated content explodes, the value of authentic human signal climbs in lockstep.

The market is already voting with its calendar. Conferences are multiplying: invite-only summits, founder gatherings, regional product communities, peer dinners. The format that costs the most to produce and demands physical presence in a specific room on a specific day is the one the market is rewarding.

The leverage in 2026 is not producing more. It is showing up as a recognisable human, on the platforms where humans are getting rarer.

The contrarian take on AI code: it is a bifurcation, not a quality collapse

You already know the headline numbers. 48% of AI-generated code contains security vulnerabilities. Forrester projects 75% of tech decision-makers will face moderate-to-severe tech debt by 2026. Cleanup for the 8,000+ startups that built production apps with AI is estimated between 400 million and 4 billion dollars. 2025 was the year of speed. 2026 is the year of the bill.

The interesting part is not the bill. It is who is paying it.

Two patterns are emerging on the AI slope.

The accelerators. Senior engineers and designers who treat AI as a junior collaborator, not a shipper. They read every line. They refactor what does not fit. They use AI to expand the scope of what they take on, not to lower the bar of what they ship. Their craft is compounding. The gap between their output and the average is widening every quarter.

The accumulators. Mid-level builders who treat AI output as finished work. They ship faster than they understand. They lose the ability to debug what they did not write. Their first-year output looks impressive. Their second year is consumed by maintenance on systems they no longer understand. Stack Overflow developer sentiment is the early indicator: 70% positive in 2023, 60% in 2025, and the steepest drop sits with the cohort using AI most heavily.

The new role nobody put on a slide is already being hired for: the AI cleanup engineer. Salaries are above market. Someone has to read the code that was written without being read. That work is going to the people who refused to outsource their judgment.

The people who got better with AI are the people who stopped trusting it. The most diligent prompters are the most stuck.

That bifurcation is the actual story of 2026. The quality bill is the symptom. The widening gap is the diagnosis.

So is there a version of AI adoption that returns time?

The NBER surveyed nearly 6,000 executives in 2026. More than 80% reported no discernible impact from AI on either employment or productivity. Fortune called it the return of the Solow productivity paradox: computers everywhere, productivity nowhere.

If the law holds, the promise of more time was never a communication problem. It was a structural impossibility. Efficiency creates demand for more ambitious work, higher output expectations, new categories of maintenance, new categories of learning. Every time you close the gap, it reopens somewhere else.

The companies that might break the pattern would have to frame AI differently. Not more, but different. Not faster, but better. And they would have to subtract something from the roadmap every time AI adds capacity, which no roadmap I have seen is designed to do.

The promise of more time assumes that time is the constraint. The evidence suggests the constraint is something harder to name.

One practice to try this week

Alex and I landed on one thing both of us are trying. Name the subtraction.

Every time you adopt a new AI tool, write down what you are going to stop doing because of it. Not “save time.” A specific activity, a specific meeting, a specific deliverable that you are going to stop producing. If you cannot name the subtraction, you have not adopted a tool. You have added one.

It is small. It is also the only practice I have found that pushes against Jevons rather than accelerating it.

Why we write this newsletter

We run this newsletter to surface the leadership topics that are not getting talked about clearly enough, and to help product people move up the ladder.

That same mission is why, alongside the Productlab Conference, we are building Leaders Studio: 1:1 coaching, company group
coaching, and Leaders Circles. We work with product people across the full ladder, from first-time people managers stepping into leadership, up through Heads of Product, VPs, and CPOs.

In an AI world where everyone can produce more, what compounds is the opposite. The human work. Soft skills, judgment, presence, the ability to lead other humans through change. That is what we sharpen, because that is what the next decade of product leadership will actually reward.

It is also why we asked Alex to host a Deep Dive at the Productlab Conference in September. If you are wrestling with this in your org, that is where the conversation continues. September 15 to 17 in Berlin. Details at www.productlab.app.

With love from Berlin,
Daniele

Subscribe now

Sources

• The AI productivity paradox: More work, not less, Fortune (March 2026)

• AI Does Not Reduce Work, It Intensifies It, Harvard Business Review (February 2026)

• Thousands of CEOs admit AI had no impact on productivity, Fortune (February 2026)

• Klarna CEO says AI helped company shrink workforce by 40%, CNBC

• AI helps Klarna double revenues with half the staff, Computer Weekly

• One in Three Workers Skip Reviewing AI Output, Allwork.space (April 2026)

• AI output will increasingly require more oversight, HR Dive

• FOMO, AI dependency and cognitive load, BMC Psychology / Springer Nature (2026)

• Cognitive offloading or cognitive overload, Frontiers in Psychology

• Monitoring AI Adoption in the US Economy, Federal Reserve (April 2026)

• Your Brain on ChatGPT: Accumulation of Cognitive Debt, MIT Media Lab (2025)

• Vibe Coding and Technical Debt, Codepanion (2026)

• The Vibe Coding Crisis, Kyros (2026)

• Deep Work and Focus, Reclaim.ai

• Companies are pouring billions into AI and cutting training budgets, Fortune (March 2026)

• Photo by Morgan Housel on Unsplash

🎫 June is pretty Packed 🥁

A world-class speaker, an incredible venue, and an evening designed specifically for product leaders and senior PMs who want to connect with people who truly "get it." We are teaming up with mobile.de for an exclusive summer event in Berlin on June 24th. Here’s the catch: it’s a total mystery.
If you’re the type of person who loves being ahead of the curve, and doesn’t mind a bit of mystery, this is one to mark in your calendar.

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🎫 Level Up Your Fintech Game in Milan

Get ready for an unfiltered look at scaling fintech in Europe this June 4th in Milan. Join us for a deep dive with leaders, Sebastiano Pighi from Sibill and Alessandro Dadone from Qonto, followed by an evening of networking. Grab your ticket before they’re gone!

🗓️ 4th of June
🙌 Matteo Risso
📍 Milan

See You in Milan

📰 Product Leaders’ Wisdom

​​​​​Brought to you weekly by Leila Montazeri

How Agentic AI and Autonomous Workflows are Rewiring Fintech

• We’ve spent a decade building beautiful dashboards for users to manage complex tasks, but we’ve just been moving the work around, not eliminating it. This piece on Medium argues that the next wave of fintech isn't about better UI; it’s about autonomous agents that actually execute the work, shifting the model from "Software-as-a-Service" to "Work-as-a-Service." If you're still building "AI wrappers" that just summarize data, it's time to rethink your strategy. The future belongs to platforms that automate end-to-end workflows.

• Have you ever thought about how to price your product when the buyer is an AI agent, not a person? The Growth Unhinged has a sharp look at why traditional SaaS strategies, like "contact sales", are becoming obsolete and how you need to start rethinking your value proposition for the machines.

• Many companies are slapping AI features on top of their products, only to find they aren't delivering real value. This piece on Product Faculty’s AI Newsletter gets into the "craft" of building AI as a core system, helping you move past the hype to build something that actually sticks and creates a real defensive moat.

💪 Open Roles

Brought to you weekly by Alessia Marchi​

1. Lead System Product Manager @ Personio

2. Director - Product Marketing @ Semrush

3. Lead Product Manager @ NICE

4. Senior Product Manager - Streaming Platform @ Snowflake

5. Director - Product Marketing @ Pleo

6. Lead Product Manager @ PayPal

7. Senior Project Manager - Real-World Health Data Platforms @ Data4Life

🎶 Song of the Newsletter

From our DJ Marco D’Avila

If you’re based in Berlin, we’ve got a great reason to get you out of the house. Daniele is hosting the next Lenny’s Newsletter meetup on Friday, June 5th.

Even better? Our friends at Clerk are picking up the tab for drinks.

🗓️ 5th of June
📍 The Castle Berlin Mitte

Register Here

🎫 Join us in Milan on June 4th for an evening of real fintech product stories

Sebastiano Pighi from Sibill and Alessandro Dadone from Qonto will share firsthand insights on scaling fintech products, from treasury management to onboarding across eight European markets. Expect practical lessons, candid conversations, sharp Q&A, and aperitivo networking with fellow product professionals.

🗓️ 4th of June
🙌 Matteo Risso
📍 Milan

See You in Milan

📰 Product Leaders’ Wisdom

​​​​​Brought to you weekly by Leila Montazeri

• Building AI-Generated Opportunity Solution Trees? This is the rarest kind of PM writing: raw and honest about what it actually takes to ship AI in production. Teresa, a product manager and designer, not an engineer, just finished an all-out engineering sprint to build an AI-powered service that auto-generates Opportunity Solution Trees from customer interviews. Her key lesson published on Product Talk: it’s fairly easy to get to an impressive prototype with AI, but getting to a real production-quality product is a fundamentally different challenge.

• Growth Unhinged reveals how B2B pricing is shifting fast in 2026. Poyar’s survey of 230+ companies shows that three-quarters have changed their pricing recently, moving away from per-seat subscriptions toward usage- and outcome-based models. Even Salesforce and HubSpot are scrambling. Plus, there’s a big reality check on AI margins—they’re sitting around 50%, way below traditional SaaS numbers. Dig into this if you touch monetization.

• For IC product managers feeling busy but unproductive, this is a must-read on Product Management IRL. As AI accelerates development, traditional PM work, such as stakeholder alignment and managing delivery friction, is losing its value. The real leverage is now upstream: clearing ambiguity and nailing customer pain points early. Mitchell shares a solid operating model to help you make this shift.

💪 Open Roles

Brought to you weekly by Alessia Marchi​

1. Head of Product - Europe Fleet @ Corpay

2. Sr. Manager of Product - Search and Cache @ Tripstack

3. Product Manager - Conversational AI @ Riverty

4. Head of Product - HealthTech @ Famedly

5. Senior Product Manager - Matching Platform @ Aroundhome

6. Head of Product @ tandem

7. Senior Product Manager - Tech, Amazon Music AI and Personalization @ Amazon Music

🎶 Song of the Newsletter

From our DJ Marco D’Avila

What the event was

Eight speakers across one day. Eric Ries (Lean Startup, Incorruptible) opened. Then Jefferson Rabb (CPO, Business Insider), Carlos Gonzalez (founder, Product School), Penny Szeto (Head of GenAI, Amazon Games), Vinod Suresh (VP Product, GoDaddy), Mathias Davidsen (VP Prototyping, Miro), Meaghan Choi (Head of Design, Anthropic), and Fonda Jam (PM, Intuit).

The stated theme was AI in product. The actual theme, once you stepped back from individual talks, was more uncomfortable: what breaks in a product org when AI works.

Not if it works. When.

Where the market actually is

Vinod Suresh from GoDaddy said it plainly at the start of his talk:

“AI has definitely taken away a product manager’s favorite excuse: limited engineering bandwidth.”

He framed the structural shift this way: the whole product development lifecycle was built on one assumption, that engineering bandwidth is the most expensive and most limited resource in any company. Supply and demand governed the roadmap. That assumption is no longer true.

The data backs this up, but with an important asterisk. CircleCI’s 2026 State of Software Delivery tracked 28 million CI workflows. Overall activity is up 59% year-over-year. The top 5% of teams nearly doubled their throughput. But the median team improved by only 4%. And on the main branch, the code that actually reaches production, throughput fell by 7%. Main branch success rates are at 70.8%, the lowest in five years.

Fewer than 1 in 20 teams have figured out how to ship at AI speed.

The same gap shows up organizationally. An NBER study of 6,000 executives across the US, UK, Germany, and Australia found that 80% of firms report zero measurable productivity gains from AI. Goldman Sachs puts median productivity improvement in software development at 30%. The gap is not between AI and no-AI. It is between the 5% who restructured for it and the 95% who added tools to an org built for a different era.

Carlos Gonzalez from Product School named this the false summit. Individual productivity rises fast. Team and business outcomes stay flat. Most product orgs are stuck there right now.

Three things that stuck

1. AI is making individuals more confident and organizations less coherent at the same time.

Mathias Davidsen from Miro gave the sharpest diagnosis of the day:

“AI has massively raised the floor. One person and their agents has become the most powerful creative unit that has ever existed. But when we zoom out from the individual to the wide organization, we don’t really see the results follow. Company output hasn’t 10xed. Strategic clarity hasn’t 10xed.”

The mechanism: when someone is pointed in a slightly wrong direction, AI amplifies that by moving fast and constantly agreeing. His framing of the result:

“Six people, six AI co-pilots, six confident, polished, and completely divergent strategies.”

“We’re no longer potentially building one wrong thing slowly. We’re potentially building a hundred wrong things very quickly and we’re not even aware of it.”

“The bottleneck moved from ‘can we build it?’ to ‘are we choosing the right thing to build?’ And when you’re planning, your competitor is shipping.”

The old buffer was the planning cycle. The forced alignment moments. Those are gone. What replaces them is not a tool. It is a leadership function.

2. For customer-facing AI, the model is the least important decision you will make.

Penny Szeto from Amazon Games built a generative party game with Snoop Dogg as an AI celebrity judge. Entirely new court cases, live dialogue, new visuals every session in real time. In building it, she ran into something that should make every PM uncomfortable: reducing latency was hurting the experience. Snoop was responding so fast the jokes didn’t have time to land.

She referenced the Eliza Effect, a 1966 MIT chatbot that had no intelligence at all and yet people fell in love with it. Her point: the human instinct to anthropomorphize AI has gotten stronger with more capable models, not weaker. Your customers will form a relationship with your AI whether you design it intentionally or not.

Her framework for what actually determines customer AI experience, none of which is the model: Identity (who is your AI and what character does it have), Context (what does it know, what does it remember), Judgment (your guardrails, your values, your policy), and Interaction (pacing, tone, emotional calibration).

The model is table stakes. The product is everything built around it.

3. Only 16% of the world has actually used generative AI.

Fonda Jam from Intuit said something that cuts through the noise:

“As of late 2025, only about 16% of the world has used generative AI at all. One in six people out of six billion people who are online, fewer than 1.1 billion have tried it. You are at a ProductCon conference watching a recording about Claude Code. You are not behind. You are early.”

She also said the thing that gives the PM role its clearest new shape:

“For the first time in the history of software, the person with the product information can produce working artifacts without waiting on engineering bandwidth. The product manager who can build does not replace their triad. They make their whole triad faster.”

The one job AI will never take

Vinod Suresh from GoDaddy ended his talk with this:

“That is one job that AI can never take away from any of us: aligning finance, sales, marketing, tech, product, and go-to-market. Because those are people. To bring those people together still takes a human.”

Eric Ries opened the day with a connected thought, using the story of Sol Price who founded FedMart in the 1950s with a lawyer’s logic: the customer is the client, I have a fiduciary duty to the client. Price built a company that made shareholders rich for 20 years, then got fired by them. The company went bankrupt within seven years. Sol went upstairs, started Price Club, which eventually merged to become Costco.

Costco is a $400 billion public company that has kept its commitment to customers for 40 years. Ries’s argument: it survives because it has both the ethos and what he calls structural integrity, a governance architecture that resists the pressure to deviate from the mission.

“If you have a mission statement but not a mission, then you are lying to your customers.”

He mentioned he played a role in setting up Anthropic’s governance structure. The connection to every other talk on AI was not coincidental.

My takeaways

The constraint moved. It was engineering bandwidth. It is not anymore.

Ries’s word for what Costco built is worth sitting with. Not a mission statement. A governance fortress: a structure designed to hold its direction even when financial pressure, a bad quarter, or a fast-moving competitor creates urgency to ship the wrong thing faster. For product teams, that is not abstract. It means the decision-making layer is designed to resist drift, not just respond to it.

Davidsen called the planning cycle a buffer. It is gone. What needs to replace it is a clarity infrastructure, a shared source of truth that keeps six people with six AI tools pointed at the same thing. Not another tool. A practice. Explicit, repeated alignment on what is actually being built and why, before the agents run.

The 1 in 20 teams that figured out how to ship at AI speed built both things. The governance layer that holds direction under pressure. The alignment layer that keeps the whole org pointed at the same thing as execution accelerates. A product org that can make good decisions faster, not just execute faster.

What that looks like in practice in scaleups like yours, Zalando or N26, a Series B company, nobody said clearly. Not at ProductCon. Not in the research I read after.

It is the question we structured our own conference around.

Leaders Day on September 15 is curated by Ravi Mehta for Heads of Product and CPOs planning AI strategy and building AI-native teams.

Craft & AI Lab on September 16 is a full day on building AI products, getting faster with AI tools, and the judgment and strategy the tools will not give you.

Conference Day on September 17 runs three layers in parallel: a main stage with opening and closing keynotes reflecting on where we are and how this year is different, deep dives for 30 to 50 people going properly into the hard topics, and roundtables for 12 for the deeper, more personal conversation about your professional journey.

We curated this around the people actually moving in this direction.

Daniele Ronca is the founder of Productlab: Europe’s product leadership platform. Productlab runs the annual flagship conference in Berlin, the Leaders Studio coaching program, and a year-round community of 3,000+ senior product professionals. With love from Berlin.

The week Berlin stopped being “also ran” in AI

I was scrolling LinkedIn on Thursday when I noticed something. Two names kept appearing in my feed, n8n and Parloa. Both Berlin. Both in the same announcement. Both suddenly worth a lot more than they were on Monday.

SAP had just walked off the stage at Sapphire in Orlando and dropped something quietly significant for anyone building products in Germany: strategic investments in both companies, framing them as cornerstones of its vision for the “autonomous company”, a future where AI agents handle entire business processes, not just assist with individual tasks.

n8n… one of those tools you adopt quietly, almost apologetically, “it’s just for internal stuff.” This week, that tool became one of the most valuable AI startups in Germany. SAP’s investment pushed n8n’s valuation to $5.2 billion, more than doubling it in under a year, with 1.7 million monthly active builders and over 1,400 enterprise customers already depending on it. It was never just internal stuff.

Parloa’s story is just as sharp. Their AI agents for customer service across digital channels and call centers will now connect directly to business data and processes in the SAP Service Cloud. Clients include Allianz, Booking.com, and IKEA. Half a billion raised. HQ: a 20-minute walk from Alexanderplatz.

Here’s the thing that stayed with me. SAP serves 99 of the world’s 100 biggest companies. That’s the distribution network two Berlin product teams just plugged into overnight. Not by relocating to San Francisco. Not by pivoting to whatever was trending. By building things people actually use, and staying put.

The “autonomous company” is now the product brief landing on enterprise roadmaps across Germany. The wave is here. The question is whether you’re positioned to help your company navigate it, or to build the next thing that rides it.

The best news? The people building those tools are your neighbours!

🎫 Join us in Milan on June 4th
Scaling Fintech: Product stories from Sibill and Qonto

Two fintech PMs who have been in the trenches, Sebastiano Pighi scaling a treasury product at Sibill, Alessandro Dadone managing onboarding across eight European markets at Qonto, walk you through what product work really looks like when money is on the line. Expect honest stories, sharp Q&A, and proper aperitivo networking afterwards.

🗓️ 4th of June
📍 Milan

See You in Milan

📰 Product Leaders’ Wisdom

​​​​​Brought to you weekly by Leila Montazeri

Worth Reading This Week:

• The Product Context You Already Built Isn’t Driving Growth? Amy Mitchell on Product Management IRL argues that the bottleneck to growth often isn't missing features, it's that your context can't travel without you attached to it. Every answer gets rebuilt from scratch. You become the dependency.

• SaaS Mag points out that the companies pulling ahead are layering sales-assisted motions, AI-driven onboarding, and usage-based expansion on top of self-serve foundations, making Product-Led Growth less a tactic and more a full operating system for growth. Cursor's $2B ARR trajectory is the case study.

• Leah Tharin on ProducTea’s 2026 PM Career Guide - V1 argues that the PMs getting passed over right now aren't the ones who can't ship; they're the ones whose entire track record is shipping. The skill stack underneath that is exactly what AI commodified first. Sharp and uncomfortable.

💪 Open Roles

Brought to you weekly by Alessia Marchi​

1. Senior Product Manager - AI, Data and Analytics @ SAP

2. Director of Product Management - Data Streaming @ HiveMQ

3. Senior Product Manager - Connectivity @ GetYourGuide

4. Growth Product Manager @ keleya

5. Staff Product Manager @ Intercom

6. Senior Director Global Product @ Progyny Global

7. Senior Product Manager - Connect @ Qonto

🎶 Song of the Newsletter

From our DJ Marco D’Avila

This week’s issue is a bit different.

Building has never been faster. Shipping is almost frictionless now. But getting to people, actually reaching them and making something land, is getting harder every month. Everyone is building. Not everyone is being heard.

So we dedicated a meetup to that exact tension. PMMs, GTM leads, and operators, in a room together, not to sell solutions but to map the situation.

That’s what this issue is about.

Navigating GTM Ownership and AI-Driven Discovery

A huge thank you to those who joined our second “Product Marketing Management in Real Life” (PMM_IRL #2) meetup. While our first gathering laid the groundwork, this second iteration shifted toward a more tactical and organizational dialogue.

Here is a refined recap of the key themes and strategic insights from the session:

Real-World Case Studies

• Burnout Prevention & Workplace Wellness: We conducted a roundtable analysis of a startup navigating B2C, B2B, and B2B2C motions. The discussion highlighted that in crowded categories, trust-based distribution—such as insurance partnerships—and measurable ROI for employers often outweigh raw features. A key takeaway: ambassador programs and community-building can provide a more sustainable competitive moat than product functionality alone.

• Community-Led Growth: We explored how communities now serve as vital distribution channels and positioning laboratories. The core insight? The most impactful communities don’t just market a product; they actively co-author the product narrative, helping PMMs validate messaging and influence internal adoption through champion users.

The PMM Ownership Gap

A recurring theme was the inconsistency of the RASCI model for PMMs across organizations. Despite influencing foundational pillars like segmentation, GTM strategy, and category narratives, many PMMs lack direct ownership of revenue outcomes. This disconnect often forces PMMs to fight for a strategic seat at the “drawing board” rather than just being execution-focused. The consensus: securing the future of the role requires PMMs to move toward strategic influence and commercial accountability.

The Evolution of Product Discovery

Product discovery is moving beyond traditional SEO. With users increasingly discovering products through LLMs like ChatGPT and Claude, PMMs must now pivot toward AEO (Answer Engine Optimization) and GEO (Generative Engine Optimization). Tools like FindableApp were discussed as essential for managing how AI systems interpret, compare, and recommend products in conversational interfaces.

From Linear to Multi-Threaded GTM

The room agreed that the “silent build followed by a big bang launch” model is increasingly risky. Instead, a multi-threaded GTM approach—characterized by small, iterative launches and continuous feedback loops—is becoming the standard for resilience. The prevailing mindset: “Dream big, start small, scale fast, fail cheaply.”

Key “Hot Takes” from the Session:

• AI is shifting discovery from search-driven to conversation-driven.

• Community is becoming a more defensible moat than content.

• “AI-powered” has lost its value as a standalone positioning statement.

• PMMs must transition from messaging experts to commercial and operational influencers.

To thrive in today’s landscape, PMMs must become more cross-functional and commercially integrated. Success no longer belongs to the loudest launch, but to the organizations that build the tightest feedback loops between their product, community, and market understanding.

Looking forward to seeing you at the next one!

🛠️ Let’s Build Together: ProductLab Hackathon

We know you’re wired to solve problems, so we’ve decided to stop just writing about them and start solving them together. We are officially planning the first Hackathon, and in true product fashion, we want to co-create the roadmap with you.

📰 Product Leaders’ Wisdom

​​​​​Brought to you weekly by Leila Montazeri

• Growth Unhinged explores the GTM in 2026 shifts from manual “plays” to AI systems. Agents now use dynamic signals for closed-lost re-engagement, automate micro-campaigns based on real-time patterns, and map relationship graphs for warm intros, moving beyond “spray-and-pray” automation.

• Intercom has launched a first-of-its-kind outcome-based pricing for its AI agent, Fin for Sales. Shifting away from activity-based costs, customers now pay $10 per qualified lead, ensuring costs align directly with pipeline value rather than just chat volume.

• OpenAI projects an 80% drop in its $20/month ChatGPT Plus subscribers, from 44 million in 2025 to just 9 million in 2026. To recover, the company aims to grow its cheaper, ad-supported ChatGPT Go plan by 3,600%, targeting 112 million subscribers. Read More

💪 Open Roles

Brought to you weekly by Alessia Marchi​

1. Head of Product - Transport & Customs @ Zalando

2. Senior Product Manager - Flights @ Priceline

3. AI Product Manager @ Cortea

4. Lead Product Manager @ PayPal

5. Senior Product Marketing Manager @ voize

6. Senior Product Manager - AI Products @ Aignostics

7. Director - Product Marketing @ Pleo

🎶 Song of the Newsletter

From our DJ Marco D’Avila

I have been pulling this thread for a few weeks. I sat with Guannan Li, Director of Product Growth & Design at ablefy, who is actively hiring for this role and has screened more than 200 applications. These are some reflections from that conversation and from what the market is already showing.

What we already know

Ablefy has a live job posting for this role right now. Mid-to-senior design experience, strong product thinking, and enough technical reach to build product components in production. The expectation: 80% independent ownership, AI tools as the infrastructure that makes the breadth possible. That is not a whitepaper. That is a job posting with a salary attached.

Zoom out and the signal gets louder. LinkedIn had its decade-long APM program: the most copied entry path into product management in the industry. They scrapped it in December 2024. The replacement is an APB: Associate Product Builder. No resume accepted. Candidates submit a working product and a 60-second demo. LinkedIn stopped selecting for credentials and started selecting for the artifact.

Linear has been running a version of this for years without calling it anything. No product managers, one Head of Product, teams that assemble around a project and disperse when it is done. Typically one designer and two engineers. Profitable for two years. $35,000 spent on paid marketing in the entire history of the company. The model is not theoretical: it has a track record.

At the other end of the scale, Walmart filled all their agent builder roles internally. Every single one. Their CPO confirmed it publicly. And at Meta, PMs are already calling themselves AI builders without any title change. The title stayed the same. The output changed.

A few kilometres away, Nick Mulder at Hypofriend posted something even more direct. A team of fewer than 20 people, rebuilding a mortgage broker AI-native from scratch. The role: Junior AI Product Manager. His note: “The title doesn’t matter.” The application: build something with Claude and show us. Fresh out of university is fine.

This should not surprise anyone. The Product Manager role has had the same problem since the beginning. At some companies a PM writes code and sits in engineering sprints. At others they never open a Figma file. At others still they are project managers with a better title. The label has always landed differently depending on stage, size, and what the founder decided mattered. The Product Builder is inheriting that same ambiguity on day one. Hypofriend wants someone who can ship from zero. Ablefy wants a senior specialist who has been quietly crossing disciplines on their own time. Both call it the same thing. What sits underneath both definitions is the same question the PM role never fully answered: can you decide what to build, build it, and know if it worked?

What this means if you’re hiring

The ROI case for this role has two parts. The first is communication overhead: three people doing one job spend more time transferring context than most companies admit. Think about the simplest case: a customer reports a minor UX issue on mobile. As a PM, you validate it, write a ticket, brief the designer, wait for the solution, brief the engineer, wait for the build, then validate again with both. Five or six touches to fix one small thing. A Product Builder sees the issue and ships it. Two fewer people to bring into context. No back-and-forth on whether the brief was understood correctly.

The second part is accountability. The user does not experience your spec, your design, or your code. They experience the integrated thing. When three people own three separate pieces, accountability is distributed across the seams between them. When one person owns all three, there is a clear owner for what the customer actually encounters: the full experience, not a handoff.

And the expectation is not that this stays rare. The companies running this experiment are not building around one exceptional person:

“We do not expect this to go into one person as a hero. We actually expect the majority of people will become product builders” — including engineers who can own a problem end-to-end, from customer feedback to shipped fix.

The hiring approach that seems most honest right now is running two parallel bets: promote one person internally, hire one externally, and see which model works better. The internal bet is on expandability: someone who already knows the product, the users, and the context, and can grow their craft into adjacent disciplines. The external bet is on someone who has already crossed disciplines on their own time, through their own projects, out of their own curiosity. The real interview is not a whiteboard: it is a case study. Identify the problem, connect it to business metrics, audit the UX, improve the design on brand, ship something. Show the artifact, not the slide.

“You do not have to prove you can draw, or use Figma. But you need to prove that you can create a user-friendly product yourself.”

The portfolio is now non-negotiable — not just for designers, but for product managers and engineers applying for this role too. That is a structural shift in how candidates are evaluated.

But the harder implication is the one nobody writing about this role seems to surface. The first friction when moving someone into a Product Builder role is not capability. It is time. PM work is organised around availability: many meetings, constant stakeholder contact, scattered attention across many parallel conversations. Design and engineering require the opposite: deep focus, sustained craft time, the ability to hold a problem in your head for hours without interruption.

“Skill is not the only benchmark.”

Which means that before you hire or promote a Product Builder, you have to decide whether you are willing to restructure how that person’s time works. If you are not, you are giving someone a new title and the same impossible calendar. This is why Linear’s model works. The whole organisation is designed to protect focus time. The structure is what makes the role possible, not just the person in it.

One more risk worth naming: what breaks when the Product Builder is not exceptional? In a traditional triad, a weak PM gets caught by the designer or the engineer. In a team of one PB and two engineers, the gap has no one to catch it. The risk concentrates instead of distributing.

What six months of preparation actually looks like

At ablefy, one person has already been successfully transitioned into the role. It took six months. The story of how it went wrong before it went right is more useful than the outcome.

The first problem was not the person being transitioned. It was the engineers reviewing their work. When a designer starts submitting code, the PRs are rough. They do not follow internal engineering standards, naming conventions, or the review processes the rest of the team has spent years internalising. It was slow, it created friction, and some of that friction came from something more uncomfortable than code quality: engineers worried that the industry was changing in ways that were not good for them.

What helped was treating the transition as a two-sided problem. Engineering training for the product and design team: workshops, knowledge sharing, learning how to use AI to review your own code before submitting so you are not dumping half-baked PRs on engineers who feel like they are babysitting. And on the other side: volunteer engineers who stepped up to give educational feedback on early PRs rather than simply rejecting them. Both sides had to move.

There was also a technology factor: an Anthropic model release in late 2025 meaningfully improved the quality of AI-generated code, making it easier for non-engineers to produce work that engineers could actually review without wincing.

Six months in, it works. The resistance that felt structural turned out to be time-based. The team needed to see it working before they stopped pushing back.

What this means if you’re looking for a job

The question worth asking yourself: is your career built on coordination that is disappearing? A lot of senior PM careers were built on moving work through the system: aligning research, design, and engineering, managing the handoffs, holding the context across three separate calendars. That work is genuinely valuable when the roles are separate. When one person owns all three, the coordination layer compresses dramatically. What remains visible is the craft itself.

Roger Wong wrote something sharp about this. The senior people succeeding in Full Stack Builder roles at LinkedIn almost all spent years as a specialist first. They developed taste through depth in one discipline, then crossed into others sequentially. The profiles that stand out are the ones who are already senior in one domain and have spent the last six to twelve months expanding into adjacent skills on their own.

If you are trying to make this transition yourself, the threshold is not vibe coding. It is whether you have good taste: do you know what good UX looks like? Can you use a product and feel when something is off, before anyone tells you? That does not require a design background. It requires having built enough things, used enough products, and cared enough about the experience to develop an eye for what works. That gap does not close through a course. It closes through building things and being wrong enough times that you start to recognise the pattern before it happens.

On salary: the market has not caught up yet. Companies are not paying significantly more than senior PM. The harder question is seniority. If the role is genuinely new, how do you evaluate it? Do you need to be senior across all three disciplines to earn a senior title? If yes, almost nobody qualifies. Most companies are working around it by using the PB path as a promotion track for senior PMs who have hit the ceiling of their current band. The financial case is real: but it is a career structure argument, not a market premium.

Speed was never the problem

AI compresses the execution layer. That is visible now. What remains is judgment about what to build and why.

This is where the Product Builder framing gets partially wrong. The excitement is mostly about execution capability: one person can design, ship, and iterate without waiting on three separate calendars. That is real. But it says nothing about whether that person has the critical thinking to decide what is worth building in the first place.

Leah Tharin put it plainly recently: most teams now ship the wrong things, faster. AI did not solve the speed problem. It exposed the direction problem that was always there. The PM wrote a spec. The designer interpreted it. The engineer built something adjacent to both. Each translation lost a little fidelity. The Product Builder does not fix this by being faster. They fix it by being the only person in the room who has to live with all three decisions at once.

Speed without direction is just chaos with better tooling. [Epic sentence Leah!]

One view on where leadership lands: the role bifurcates into product strategists who focus on direction and product builders who own execution end-to-end with a small team. Fewer layers in between. It is a compelling hypothesis for now.

What is already visible is that more small teams running in parallel does not mean fewer meetings. The coordination problem moves but does not disappear. More teams means more alignment surface. AI has not helped with this part yet.

What I do not know yet

The Product Builder at its best is a return to an older shape of the role: one person who sees the problem, designs the solution, and builds it. Before companies got large enough to justify splitting those three into three headcount, that was just called building a product.

What I do not know is whether that role, inside a company that is not yours, can develop the same sharpness that founders develop. The founder’s critical thinking gets honed by something specific: the knowledge that if you build the wrong thing, it costs you everything. That is not a capability you develop from a job description, however well written. It comes from skin in the game.

There is a second thing founders have that the Product Builder inside a company does not: control over their own calendar. The focus that makes good craft possible is not a personality trait. It is a structural condition.

And there is a third thing worth sitting with. What happens to the people who are genuinely good at this and start to feel the pace as accumulation rather than progress? AI makes you produce more. But more for whom, and at what cost? The Product Builder model assumes that removing friction in the handoff is a clean win. I am not sure it accounts for what happens when there is no one else in the room to slow you down, and whether the time you used to spend in those handoffs was also, sometimes, the time where the thinking happened.

LinkedIn is running the experiment at scale. Berlin startups are running smaller ones. In a year or two, we will know more.

Sources

• Daniele Ronca — Founder, Productlab

• Guannan Li — Director of Product Growth & Design, ablefy

• Ablefy Product Builder job posting

• Why LinkedIn is replacing PMs — Lenny’s Newsletter

• How Linear builds product — Lenny’s Newsletter

• Who Teaches the Product Builder? — Roger Wong

• In AI land, everyone’s a builder now — SF Standard

• Direction Over Speed — Leah Tharin

• LinkedIn APB program — Sophia Sun

• Jr. AI Product Manager at Hypofriend — Nick Mulder

Product Builder: The New Market Reality in the Age of AI

Alongside everything we’re already juggling as product people, where our biggest headache is honestly just trying to keep up with AI and not get left behind, there’s this new role called the Product Builder starting to pop up... It’s basically the answer to that "how do I stay relevant" anxiety. Instead of just using AI to write an email or a doc, these folks are using it as their entire engine to do what used to take a whole team. They’re blurring the lines between strategy, design, and shipping code, turning the job from "managing the process" into "actually building the thing." Major players in Berlin and even LinkedIn and Linear are already shifting their focus toward these all-rounders who can show a finished product instead of just a fancy slide deck.

The full deep dive will be in next week’s newsletter. Stay tuned!

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