🎫 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.

Mobile.de: THE BIG SECRET SUMMER COMMUNITY EVENT

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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!

🎫 Join our PMM Pub Special Edition on May 7th

We're getting together for a real, no-BS conversation about where PMMs actually fit into the messy world of B2B GTM, from the levers we truly own to the moments we're accidentally left out of the room. It’s a casual night to talk honestly about winning in a landscape where AI and "agentic buyers" are changing all the rules, without the dry slides or rigid frameworks. If you want to figure out how to stop just "contributing" and start actually leading the GTM motion, don't miss it!

PMM Pub Special Edition
with Vladimir Liashenko

🗓️ 7th of May
📍 Berlin

See You in Berlin

💎 Unlock Your Team’s Power: How to Audit Your Invisible Culture Signals

Every team has invisible rules — unspoken signals that shape what gets rewarded and what stays buried. In our next free webinar, Lucie McLean (Product Leader & Executive Coach at Google, ex-Zalando, ex-BBC) will walk you through a practical framework to audit your team's hidden culture signals before they quietly run the show. Join us live from anywhere on May 13 at 13:00 CET — 45 minutes, free to attend. Register here:

Join Webinar

📰 Product Leaders’ Wisdom

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

The PM role is evolving faster than most job descriptions can keep up with. These three pieces look at what's actually changing, and what it means for how you work, lead, and stay relevant.

• Amy Mitchell cuts through the noise with five sharp trends reshaping PM work in 2026. Her core argument: influence no longer comes from your title or org structure, it comes from how well you connect product decisions to business outcomes. She also raises something worth paying attention to: products are now being evaluated by AI systems before any human ever sees them. If the ground has been feeling shaky under your PM work lately, this piece puts words to exactly why.

• Based on a survey across the US, France, and Germany, Atlassian’s latest report paints an honest picture of where product teams stand today. Most PMs feel respected and say they have a real seat at the strategic table, but that visibility comes with serious pressure to prove business value. A great data-backed read if you want the full picture, not just the optimistic version.

• Skip the hot takes Ant Murphy went through actual industry reports to find out what’s really happening in product right now. The job market is recovering fast, companies have firmly shifted toward revenue and profitability as their north star, and strategy plus business acumen have become the skills that matter most. Data-grounded and written like a conversation, well worth 12 minutes.

💪 Open Roles

Brought to you weekly by Alessia Marchi​

1. Senior Product Manager – Risk Domain @ PPRO

2. Staff Product Manager - Fulfillment Domain @ Enpal

3. Director Product - Devices @ tonies

4. Head of Product @ 7Learnings

5. Product Marketing Manager - Investment @ Qonto

6. Product Lead - AI & Agentic Workflows @ getpress

7. Senior Product Manager - AI Analytics @ JetBrains

🎶 Song of the Newsletter

From our DJ Marco D’Avila

But the world has also changed. Our environments are noisier and our attention is more fragmented. Effective communication in today’s digital landscape may actually require many more - up to 27 times - to build brand trust and loyalty.

Exposure also matters when trying to grow our careers. We need to be visible to the right people, with the right message at the right time.

But if it takes (at least) seven touches for a consumer to remember a brand, why would it take any less for a busy SVP or board member to remember you and what makes you unique?

Subscribe now

So I want to share an experiment.

Imagine you’re the marketing director of your own executive exposure campaign.

The brand you’re building is you - who you are, what you do, what you stand for and what you’re capable of achieving in the future.

What do you need to do to ensure that your audience (the people key to your success) see and understand your brand often enough?

Use the steps below to see if there are opportunities to be more strategic in gaining executive exposure.

1. Defining the ‘audience’

First you need to define the ‘audience’ to reach:

• Who are the 3 to 5 people who hold the most influence over your current goals and aspirations?

• Who are the allies and sponsors you need to influence today to get the role you want tomorrow?

• Who is the one person in your organization who should know your value but doesn’t?

2. Mapping the ‘media placements’

Plot the places where executives ‘consume’ information:

• Which meetings and forums do they attend where you currently or could make a contribution?

• What kind of asynchronous communication do they read and engage with (ie, project reporting, launch emails, team slack channels)?

• Where are there opportunities for unscheduled, authentic, in-person interaction? This might include being present in the office, other offices or industry events.

3. Defining the problem to solve

The best advertising doesn’t interrupt; it answers. If you understand what problems your executives are seeking to solve then you can be part of the solution.

Review the following sources for clues. Even if you regularly read and observe them - revisit them with goal of seeking signals of where you can add additional value:

• company and departmental strategy documents and presentations

• the themes and stories execs talk about in all team meetings, newsletters and other regular updates

• media interviews and presentations given by executives

• investor calls (for public companies)

• asking your manager what strategic topics are coming up in discussions you’re not involved in

• asking your execs directly

4. Auditing your current exposure frequency

How often are you spending time with key executives at the moment and what kind of relationship do you have?

You can use the explosure ladder below to think about the volume and quality of your relationships. The numbers aren’t a hard rule - just a starting point for reflection.

👀 Interactions 1 to 3: First impressions 👀

At this stage, you are laying foundations. You are generating first impressions of who you are, and what you care about. It can be hard to get a big ‘win’ at this stage as ongoing trust and relationship haven’t been established yet.

The goal: Listen, learn the language of the room, and create a good first impression through a confident and engaged presence. Here are some questions to think about for this phase:

💡 How do I ensure I show up calm, confident and present?

Solutions might include:

• preparing for any questions you might be asked (perhaps with an AI sparring partner) so you have the answers - just in case

• ensuring you have a go-to way to say ‘I don’t know, I’ll follow up with the answer”

• taking a few minutes to reset your posture and breathing before you join the meeting

• minimizing physical and virtual distractions to help you stay present and catch the nuances of what’s being said (and what’s not)

👀 Interactions 3 to 6 : Building familiarity 👀

This is where the brand begins to form. Executives start to evaluate you more deeply against the strengths and behaviors they value. They also start connecting your name to specific ideas and themes.

The Goal: Consistency and credibility. You want them to think: “Every time I see [Name], they demonstrate x.” Some questions to optmise your approach here include:

💡 What leadership traits are valued and measured by your ‘audience’?

You can find signals of this in the following places:

• speaking to people who interact with these executives regularly

• looking for clues in communications which celebrate achievements, promotions and key milestones - who is rewarded and for what?

• reviewing your role expectations and any documented leadership/teamwork principles to understand what is the ‘official’ benchmark

💡 What do you want your ‘x’ to be and why?

• What do you want to be recognised for - based on what you do now?

• What additional skills and capabilities do you want others to see to help you attract new opportunities?

• How might you find ways to better demonstrate your potential?
  

👀 Interactions 7+ : Top-of-mind awareness 👀

This is where the magic happens. When an opportunity arises - a new territory, a promotion, a high-stakes task force - your name surfaces naturally.

The Goal: Trust and advocacy. You aren’t just remembered; you are assumed and your opinion matters. Other people are proactively advocating for you. Things to consider here:

💡 Where are you already engaging with your ‘audience’ on topics beyond your scope?

💡 How will they know what else you want to achieve?

💡 Who can advocate for you in the room when you’re not there?

5. Iterating your campaign impact

Of course, it’s also important to evaluate how successful your campaign is, and where you might need to adjust it:

• Track your exposure frequency - how are you tracking towards top of mind awareness?

• Look for qualitative shifts in interactions - what kinds of questions and discussions are you having with executives? What evidence is there that they see you and what you are capable of?

• Proof of advocacy - is your name coming up in discussions of best practice, achievement and upcoming opportunities?

Consistency is key

Not every interaction needs to be a grand slam. Exposure can be as simple as being present, visible, engaged, and present.

But if you aren’t showing up regularly, you may be starting from zero every time a big moment arrives.

So remember that this is a numbers game, be patient, consistent and authentic in your approach.


Feel free to share below how you’ve created quality, authentic interactions which help you grow your executive exposure. Sharing is caring!

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

The next circle starts in June. More information here.

Bonus .md Claude file to start Now!

What this does Turns Claude into an executive coach. 16 focused questions, one at a time, about your goal, the people who influence it, and where you’re visible (or not).

What to expect A 10–15 minute conversation. Claude listens, pushes back if answers are vague, and builds context as you go.

What you get at the end A written strategy: your audience mapped by relationship stage, your brand signal, specific touchpoints, and a 30/60/90 day action plan.

Get .MD

Last Wednesday, Berlin had one of those perfect spring days. The kind where you feel guilty being indoors. And we had 40+ people pack into Techspace for a conversation about user test validation and AI agents.

Ronja Quester took us behind the curtain of building a menopause app in the corporate world.

Bayer Canesmeno App Ai User Research Ronja Quester

2.82MB ∙ PDF file

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Her team used synthetic users in their research, and she was refreshingly candid about both sides of that:

✅ yes, they can reflect real audience needs almost immediately.

❗ But they can also miss the outliers. The edge cases. The experiences that are so specific and so human that no algorithm would think to surface them.

Then Csaba Tamas got up and said the quiet part loud: most AI projects just don’t deliver. We’re talking 5–15% success rates. And yet nearly half of enterprise AI users made at least one major business decision in 2024 based on information that turned out to be hallucinated. While trust in AI output still remains high.

Succeeding With Ai Agents Cssaba Tamas

2.39MB ∙ PDF file

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We’re at this weird inflection point where the technology moves faster than our ability to be appropriately skeptical of it.

That’s not a reason to stop. It’s a reason to get smarter about how we build and validate.

Big thanks to our sponsors UserTesting and Techspace for providing the food and space, and the whole Productlab team.

Grateful to everyone who showed up, asked hard questions, and kept the conversation real. That’s the only kind worth having.

See you at the next one. 🙌👇

PMM Pub Special Edition
with Vladimir Liashenko

🗓️ 7th of May
📍 Berlin

See You in Berlin

📰 Product Leaders’ Wisdom

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

The Art of Not Using AI (And Using It Better)!
We’ve moved past the initial AI hype. In 2026, the real “flex” isn’t just plugging in an LLM; it’s knowing exactly when to step back and rely on core product principles. These three articles have been on my mind because they challenge the “AI-first” status quo in all the right ways:

• Decision Surfaces: The Fine Line Between Helpful and Bossy

  Priyank Sharma hits on Mind The Product, on a feeling many of us have had: why do AI features often feel “off” even when they work? He argues that because LLMs always speak with unearned confidence (even when they’re hallucinating), we have to design “Decision Surfaces.” It’s about deciding where the system should be an authority (giving an answer) versus where it should be an assistant (just showing options).
  

• The Peril of Laziness Lost: Why “More Code” is a Trap

  Is shipping 37,000 lines of code in a day actually a win? Probably not. In this piece, Bryan Cantrill defend the “virtuous laziness”, the human instinct to find the simplest, cleanest solution to avoid future headaches. In an age where AI can churn out infinite, messy code for free, our job is to be the friction. We need to make sure we aren’t just building “layer cakes of garbage” just because the AI makes it easy to do so.
  

• The Build: Why Math Still Beats GPT-4 for Recommendations

  Jay Stansell shares on Product Coalition why he literally hit “delete” on a perfectly good GPT-4 prompt and went back to classic math for his product’s recommendation engine. Why? Because in a coaching product, users deserve a “why.” They need to know that a suggestion is based on their specific skill gaps, not a black-box “vibe.” It’s a great reminder that if a problem can be solved with a transparent algorithm, that’s usually the smarter bet.

💪 Open Roles

​​​​​Brought to you weekly by Alessia Marchi​

1. Principal Product Manager @ lemon.markets

2. Senior Product Manager - Matching Platform @ Aroundhome

3. Senior VP Product @ A11

4. VP Product Management @ HiveMQ

5. Head of Product @ Kleinanzeigen

6. (Senior) Product Director @ sennder

7. Senior Product Manager @ Cloover

🎶 Song of the Newsletter

From our DJ Marco D’Avila

Whether you work in health tech, want to find out how to prototype fast and validate even faster, or want to learn what it means to build infrastructure for teams at scale — this event is for you.

Thanks to Astrid for making this event possible, and thanks to our speakers for joining us! Ronja Quester (PM at Bayer) and Csaba Tamas (CTPO at Parloa)

Come for the insights, stay for the people.

🗓️ 22nd of April
📍 Berlin

See you in Berlin

🇮🇹 Milan event was a blast, here is why

I am an expat. Like many of you, product was my second life — a career I moved into, not grew up in.

That’s why I’ve always built Productlab as a crossroads. Think of a train station like the Hauptbahnhof: dozens of stories passing through, intersecting for a minute or an hour, each one shaping the others before moving on.

Milan at WeRoad was exactly that.

Three speakers. Three very different journeys:

Matteo Risso — the senior PM stepping into leadership, showing us how to prototype fast and validate even faster.

Show & Tell Weroad Defshare

2.94MB ∙ PDF file

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Giovanni Ravone — the expat who left the US and came back home to lead a payments company, now rebuilding his org around flat hierarchies and speed.

Luca Mastella — the founder disrupting his own learning platform, taking cues from companies like Intercom and Netflix to rethink how learning works at scale.

Luca Mastella

19.8MB ∙ PDF file

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We had the slides. But slides are never the point.

The point was the room. The Italian community showed up with warmth, energy, and curiosity that no deck can capture. And none of it would have been possible without the incredible support of Product Heroes, who hosted the event alongside us.

This is what the crossroads looks like. See you at the next one.

See you in a few months or so, Matteo Risso is joining the team to organize once a quarter in Milan <3

Organizational note! We implemented live Speaker’s feedback and is amazing how a room of PM’s are so active to share and support the hard work of the people on stage! Well done Ahmed!

📰 Product Leaders’ Wisdom

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

This week, we explored a set of new AI tools that are quietly changing how product teams actually work.

• Claude Code – Content audit as a real workflow
  Using Anthropic’s Claude Code, a full content audit (keywords, SEO gaps, rankings, new topics) can be done in minutes. The key insight: with the right context (files, APIs, structured inputs), AI moves beyond chat and becomes a true research operator that can analyze and recommend at depth.
  By Teresa Torres

• Gemini ; Turning ideas into visual models
  Google Gemini can now turn complex product concepts into interactive visualizations directly in chat. From pricing models and cohort retention to roadmap dependencies, you can simulate and iterate in real time. It shifts communication from explaining to showing, making it much easier to align stakeholders on complex ideas.

• Claude Code ; Simulating high-stakes meetings
  With Claude Code, you can simulate meetings before they happen. Define participants, agenda, and context, and run a realistic scenario. It helps surface objections, weak arguments, and blind spots, turning stakeholder management into something you can actually rehearse.
  By Rich Holmes

• Internal AI tools ; The new product advantage
  More teams are building their own AI tools instead of relying on SaaS. From memory systems to automation and internal “skills,” companies like Ramp are creating custom workflows tailored to how they operate. Internal tooling is no longer secondary, it’s becoming a real competitive advantage in the AI era.
  Read more on Department Of Product

💪 Open Roles

​​​​​Brought to you weekly by Alessia Marchi​

1. Director Product Management @ Contentful

2. VP Product - Capital Markets @ Keyrock

3. Senior Product Manager - Accounting Integrations @ Pliant

4. Group Product Manager @ mobile.de

5. Product Marketing Lead @ Maxon

6. Vice President Product @ Andercore

7. ERP Group Product Manager @ Emma – The Sleep Company

🎶 Song of the Newsletter

From our DJ Marco D’Avila

🎫 Join us on April 22nd, UserTesting: From Fast Validation to Autopilots

Save the date for our next meetup in Berlin. We’re bringing together the product community for an evening of cutting-edge insights and networking.

We are thrilled to host two incredible speakers:

• Ronja Quester (PM at Bayer) on AI-driven user insights.

• Csaba Tamas (CTPO at Parloa) on building scalable agents.

Come for the insights, stay for the networking with our resident DJ Marco d’Avila and amazing food by Crosta Berlin.

🗓️ 22nd of April
📍 Berlin

See you in Berlin

🎫 Don’t forget to join tomorrow’s online session with ​Iglika! We’re going beyond basic prototyping and learning how to use Lovable professionally: connecting to databases, integrating your own design system, structuring inputs, and building the right context for production-ready apps.

We’ll walk through advanced techniques for system integration and creating scalable prototypes that feel like real products.

Register Here

📰 Product Leaders’ Wisdom

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

• User Testing in the Wild! Sony is currently beta-testing a UI update for the PS5 to fix a long-standing navigation issue. It’s a perfect example of how continuous user testing helps even.
  

• Is User Feedback the New Code? According to a recent piece by Bits&Chips, GenAI is transforming user insights into something executable, versioned, and continuous, just like software code. By using Virtual Users to simulate real-world interactions, teams can now get feedback on every design iteration without waiting for weeks of manual testing.
  

• In the era of rapid iteration, Trenhunter introduces the Feedback Widget. This new breed of feedback widgets opens directly within the browser, capturing insights without forcing users to leave the page. By reducing navigation friction, products get higher response rates and contextual data, showing that the best feedback comes from where the user experience happens.
  

💪 Open Roles

​​​​​Brought to you weekly by Alessia Marchi​

1. Staff Product Manager @ Enpal

2. Principal Product Manager @ Parloa

3. Senior Product Manager - Acquisition & CRO @ Every.

4. Product Director - Conversational AI CS & Pharma Advisory @ Redcare Pharmacy

5. Senior Product Manager - Mobile @ Superhuman

6. Director of Product @ deskbird

7. Product Manager - Agentic AI for Corporate Communications @ movingimage

🎶 Song of the Newsletter

From our DJ Marco D’Avila

Next week we’re bringing Productlab to Milan for the very first time, in collaboration with Product Heroes. It’s been a long time coming and I can’t wait to finally meet the Italian product community in person.

If you want to double up: the day after, Matteo Risso (host at WeRoad) and I are organising a Lenny meetup at an amazing “Fischladen“ in the city. 25 spots only, and it’s going to be intimate and real.

🗓️ 15th of April
📍 Milan

Join Lenny Milan

🎫 UserTesting: From Fast Validation to Autopilots

We come back to Berlin stronger. We have a special evening sponsored by UserTesting and Techspace, and it wouldn’t have happened without Astrid Pocklington and Deniz Sebik making it possible. Genuinely grateful.

Two speakers worth clearing your calendar for: Ronja Quester (PM at Bayer) on AI-driven user insights, and Csaba Tamas (CTPO at Parloa) on building scalable agents. That's already a great night. But honestly, what makes these events is our planned networking around it.

Marco d’Avila, our resident DJ, will be there for the networking. We’re going full yummy with Crosta Berlin (their founder Luca Pignatelli was Senior PM at Delivery Hero, so yes, the food will be excellent and he knows exactly what we need). And Aleksandra Kononchenko will be capturing the moments on video.

🗓️ 22nd of April
📍 Berlin

See you in Berlin

👀 The PM role isn’t dying. It’s splitting.

We published something last week that hit a nerve: the product manager role isn’t disappearing, it’s diverging into three distinct profiles depending on how you’re actually using AI. The Operator, the Product Builder, the Specialist. The skills that got you promoted two years ago, writing detailed requirements, translating business to engineering, managing the backlog, are no longer what separates you. What does? Judgment. Domain depth. Commercial thinking. The ability to build and evaluate AI systems that work in production, not just in demos.

And speaking of the PM role changing...

We dropped the first names for our Conference on September 17th.
Julius Danek (Head of Product DACH at Stripe) on machine payments and the headless economy.
Jana Waldschmidt (Director of Product at GetYourGuide) on leading teams through AI transformation.
Malte Landwehr (CPO at Peec AI) on how LLMs are reshaping product discovery.
And Csaba Tamas (CTPO at Parloa) on building agentic products at production scale. More names coming.

Full Lineup

📰 Product Leaders’ Wisdom

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

From Empathy to AI: Mastering Product Sense this week

We often call it a ‘gut feeling,’ but Product Sense is actually a muscle built from deep empathy and strategic insight. In 2026, as AI automates routines, your ability to discern the ‘why’ behind user behavior is what distinguishes you from a machine. Without understanding what truly drives users, even the best Agile methodologies won’t save your product.

• Diana Stepner breaks down Product Sense as a learnable skill blending deep empathy with creative conviction. She argues that true “sense” comes from prioritizing user needs over rigid methodologies. To keep your Product Sense fresh, you must embrace “scrappy” prototyping and dare to pursue ideas that others might call “crazy.”
  

• In the age of LLMs, Product Sense must evolve. Lenny’s Newsletter reveals how modern PMs need “AI intuition“, understanding how probabilistic models think. By practicing “Vibe Coding“ and hands-on prototyping, PMs can transform unpredictable AI capabilities into deterministic, high-value user experiences that feel intuitive.
  

• Leah Tharin delivers a vital warning: AI cannot simulate human irrationality. While “Synthetic Personas” are tempting shortcuts, true Product Sense is forged through direct human observation. To build authentic trust, PMs must resist the urge to automate empathy and stay grounded in the messy, unpredictable reality of actual users.
  

💪 Open Roles

​​​​​Brought to you weekly by Alessia Marchi​

1. Product Marketing Manager - Payroll @ Personio

2. Senior Product Manager @ FORMEL SKIN

3. Senior Product Manager - User Activation & Growth @ Taxfix

4. Lead Product Manager @ Leapsome

5. Senior Product Manager - Analytics @ Aiven

6. Principal Product Manager - AI/LLM @ Neko Health

7. Staff Product Manager - Web Growth @ Intercom

🎶 Song of the Newsletter

From our DJ Marco D’Avila

I’ve been running Productlab for two years, talking to senior product people every week across Leaders Circles, the community, and the conference circuit. And something I keep seeing doesn’t have a clean name yet. The people in the room are all called product managers. But they’re not doing the same job anymore. They don’t want the same things from their career. They don’t need the same skills. And the gap between them is growing.

Let me try to put a frame on it.

How we got here

Two years ago, the dominant question was “what is AI and should I care.” That wave produced credentials, explainers, bootcamps. Most of it was behind where the actual work was already happening.

Last year the question changed. Teams started shipping real AI features and hit the same production walls across every industry. How do you evaluate a system whose outputs are never identical twice? How do you design an agent that isn’t just an expensive autocomplete? How do you build something users trust enough to act on? The teams that moved fastest weren’t the ones with the best tools. They were small, cross-functional, and led by people with specific domain knowledge that the model couldn’t replicate on its own.

Now we’re in a third shift, and it’s the hardest one. The question is no longer technical. It’s organizational. When everyone can build, what is actually yours? When building speed is no longer the differentiator, what is?

That question is reshaping what product management actually means. And it’s producing three distinct profiles.

The three product managers

The first is what I’d call the Operator. They use AI to do the existing PM job faster and better. PRDs in twenty minutes. Research synthesis in two hours instead of two days. Meeting prep automated. Customer interviews summarized before the call ends. This is genuinely valuable. The work is real and the efficiency gains are measurable. But the playbook is visible to everyone, and so is the tool being used to run it. The efficiency is not a moat.

The second is the Product Builder. This person has shipped something real with AI. They know what evaluation systems are because they’ve needed them, not because they read about them. They’ve hit the production wall where a feature that works perfectly in a demo produces garbage in the wild. They’ve had to redesign a workflow from scratch because the architecture they chose was impossible to debug when it failed. They think about prompt engineering at the production level, not the conversational level. They’re T-shaped: enough technical fluency to make real architectural decisions, enough product craft to stay focused on the user problem. This is the direction individual product contribution is heading. It’s smaller than it looks. A lot of people believe they’re here when they’re still in the first group.

The third is the Specialist. This person has gone narrow and deep, combining AI capability with domain expertise that’s genuinely hard to replicate. A former teacher who writes her own evaluation code specifically because she knows what good pedagogy looks like and a generic model doesn’t. A product leader who spent years working with local government who knows that “this is a really big problem” is positive sentiment in civic technology, not a complaint, and that no off-the-shelf model will catch that distinction. Their competitive advantage isn’t the tools they’re using. It’s what they already know that the tools can’t. This is the rarest profile, and the gap between them and everyone else is widening, not closing.

How skills are actually changing

The skills that are losing value are, uncomfortably, some of the skills that got people promoted in the last decade. Writing detailed requirements that get handed to an engineering team. Being the translator between business and technology. Managing a backlog as the central organizing activity of the job. These aren’t gone. But they’re no longer the differentiator.

What’s becoming more important, not less: taste and judgment, because when anyone can build anything quickly, the decision about what’s worth building becomes the job. Domain expertise, because AI amplifies what you already know and can’t substitute for it. Commercial thinking, because the best product people now think about positioning, pricing, and go-to-market as product decisions, not someone else’s problem. And communication, which sounds obvious until you realize that as AI handles more of the execution layer, the human ability to facilitate alignment, challenge assumptions in a room, and build trust under pressure becomes the actual leverage.

The genuinely new skills are real but learnable: designing AI systems that degrade gracefully rather than confidently wrong, building evaluation infrastructure that isn’t just a spreadsheet of thumbs-up ratings, understanding how context windows fill and degrade so you design workflows that account for it. The most honest thing I’ve read about this is that you can’t predict how long it will take to get to good. Getting to good takes a lot of iteration. The knowledge lives in the failures already made, not in the frameworks describing them.

Why we designed three days

The conference structure is a direct response to these three profiles and the organizational layer that sits above all of them.

Day one is for the leaders trying to navigate from the top. The question is: given that the rules are changing faster than any planning cycle can accommodate, how do I make directional decisions without waiting for clarity that won’t come? We called the best person we know to lead that conversation: Ravi Mehta, who has spent the last two years building the most widely used framework for executive AI strategy and building AI-first teams. Not a lecture. A working session with people who have the same problem.

Day two is a full operating system for the Builders and Specialists. Six workshops, maximum twenty people each, at The Social Hub. Not lectures, practice. The new execution layer: agentic system design, building a personal Product AI OS, discovery and validation at AI speed. The judgment layer that hasn’t changed: stakeholder communication, strategy-to-execution, go-to-market thinking.

The people running the rooms: Zsuzsanna Tamas (Amazon Music) on agentic AI architecture. Tamer El-Hawari (Productbench) on building your Product AI OS. Birte Loecked on discovery and validation under pressure. Rich Mironov on ROI and managing business demands. Tim Herbig on connecting strategy to measurable execution. Rory Woodbridge on product marketing and go-to-market. Six practitioners, six rooms, maximum twenty people in each. One day to upgrade both sides of the equation.

Day three is the room where all three profiles are in conversation. Morning: companies and practitioners showing what the new terrain actually looks like when you’re operating inside it. Afternoon: the practitioners who went first, with the real stories. What the AI-native playbook doesn’t tell you. What it takes to build 0-to-1 agentic products inside a large organization. What happens when complexity is your moat and your end user isn’t your buyer. Then we close with something that isn’t a talk at all, a live robotic music performance exploring what happens when human intent meets algorithmic agency and neither is fully in control. It’s the honest description of where we all are right now.

Not three days of content. Three days designed for the three conversations that actually move people.

Which profile are you building toward?

Check Lineup

With love from Berlin,
Daniele

Last week, we gathered at Beam Berlin, the venture builder for the BEUMER Group, to dive into the gritty reality of logistics innovation. As a hub that connects industrial giants with the startup world, Beam provided the perfect backdrop for a night focused on solving the hard logistics problems!

Our first speaker, ​Abhishekkumar Savita Rai (Founder & CTO of Aerolead.ai), who is currently building his platform with Beam’s support, shared how he managed to launch a complex aviation product in just nine months. His core message was a wake-up call for the AI era: the days of “feature-driven” products are over; the future belongs to “workflow-based” mindsets. Abhi demonstrated how deep domain expertise, not just AI itself, is the true differentiator. By moving from isolated features to connected workflows, his platform integrates everyone from airlines to ground handlers into a single intelligence layer. Using real-world examples like smart baggage tracking and fraud prevention, he showed how solving complex, “broken” industrial processes requires shipping fast, learning faster, and prioritizing end-to-end solutions over simple tools.

Next, Daniel Quiter (Founder of Kiezbote) took us on a very different journey, moving from 2.5 years of academic research to a functioning business. He was refreshingly honest about the “solo founder” struggle and the gap between theory and reality. Using the “Mayring Method” to decode customer needs, Daniel’s biggest lesson was that what people say they’ll pay in a survey is rarely what they actually pay. He shared how Kiezbot pivoted from B2C to a sustainable B2B model, carving out a niche with CO₂-neutral cargo bikes. By offering hyper-flexible delivery windows and last-minute address changes, Daniel proved that green logistics can actually be more customer-centric and is now on the verge of hitting profitability.

It was a night that reminded us all: whether you’re moving fast with AI or taking the long road through research, the goal is the same; stop building backlogs and start solving real-world friction.

Check all the Moments

💡🎫 Product Lab Online; Build & Ship with Lovable: Advanced Techniques.

Welcome to our new series bringing industry-relevant topics to PMs across the EU.

In our first workshop, we’re going beyond basic prototyping. Learn how to use Lovable professionally: connecting to databases, integrating your own design system, structuring inputs, and building the right context for production-ready apps. We’ll walk through advanced techniques for system integration and creating scalable prototypes that feel like real products.

Join us using the link below and keep an eye on Luma for the exact event date.

P.S. The workshop will be happen either on the April 2nd or the week after -> we’ll keep you posted!

Request to Join

📍 🎫 We’re heading to Milan!

In collaboration with WeRoad and Product Heroes, we’re hosting an exclusive session covering the essentials of scaling in the AI era, from rapid prototyping and building AI teams to the growth strategies behind Learnn. We’re booked, thank you for your trust!

🗓️ 14th of April
📍 Milan

See you in Milan!

📍 🎫 Next up: Berlin!

On April 22nd, we’re gathering at Techspace Eiswerk to explore the journey from “Fast Validation to Autopilots.” We’ll be joined by Ronja Quester (Bayer) to talk about AI-driven user insights and Csaba Tamas (Parloa) on building scalable agents. Registration opens April 13th, don’t miss out!

🗓️ 22th of April
📍 Berlin

See you in Berlin

📰 Product Leaders’ Wisdom

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

If you missed our deep dive into Logistics Innovation at Beam, or if you’re just looking to stay ahead of the curve, we’ve curated three essential reads for Product Managers navigating the future of supply chains and AI.

• How do you build a product where “safety“ isn’t just a requirement, but the core value proposition? Chinmay Jain (Director of PM at Waymo) shares on the LogRocket blog how they moved beyond “vanity metrics” to focus on human trust. For PMs in autonomous logistics, this is a masterclass in using massive simulations to solve edge cases and why the world’s safest driver isn’t human.

• Integrating Generative AI into logistics isn’t just about picking an LLM; it’s about navigating “hallucinations” in shipping IDs and protecting sensitive trade data. Cleveroad explores the high-stakes trade-offs PMs face when adopting GenAI. From automating customs documentation to intelligent customer support, learn where the tech provides real ROI and where the risks of data leakage are too high to ignore.
  

• The “Last Mile” accounts for a staggering 53% of total shipping costs. In this strategic deep-dive by DHL Discover, explore how data-driven innovations, like micro-fulfillment centers and crowd-sourced delivery, are reshaping urban logistics. This is a roadmap for optimizing unit economics through tech, proving that the future of delivery is as much about smart algorithms as it is about electric cargo bikes & drones.

💪 Open Roles

​​​​​Brought to you weekly by Alessia Marchi​

1. Staff Product Manager @ Databricks

2. Senior Product Manager - Growth and Customer Experience @ Andercore

3. Senior Technical Product Manager - Commercial Data @ SumUp

4. Product Group Owner - HR IT Solutions @ Schaeffler

5. Senior Product Manager - App @ Sportstech Brands Holding GmbH

6. Product Manager - Customer Hub @ 1KOMMA5°

7. Senior Product Marketing Manager @ Wire

🎶 Song of the Newsletter

From our DJ Marco D’Avila

We’re experimenting with visiting new tech hubs and getting to know other communities. For our conference, people joined from all around Europe, and we thought, why not meet them in person and see how conversations and challenges are evolving?

📍 Berlin, 🎫 We are coming back to Beam!

We’re bringing together around 40 people from the community for a focused evening on one of the hardest things in product: the 0 to 1 journey. If you’re a builder — someone working on early-stage ideas, running experiments, or trying to figure out what’s actually worth building — this one is for you. The goal isn’t to hear polished success stories. It’s to sit in a room with people who’ve been through it and get honest about what worked, what didn’t, and why. The reasoning behind the decisions matters just as much as the outcomes, and that’s exactly the kind of conversation we want to create space for.

🗓️ 26th of March
📍BEAM Berlin

Join Us

📍 BCN, Lenny Meetup

Our Founder Daniele will host with Marc Bisbal Arias a Lenny’s Meetup. Be ready to mingle about product, and tasty food!

🗓️ 26th of March
📍 Barcelona

Join Lenny Meetup

📍 🎫 Built in Milan

In collaboration with WeRoad & Product Heroes, we’re hosting a special event that spans topics from fast prototyping and scaling AI teams to AI-driven growth at Learnn.

Thanks to Simone Basso for hosting us, and to our speakers—Matteo Risso (sPm at WeRoad), Giovanni Ravone (CPO at Satispay), and Luca Mastella (Co-founder / Growth at Learnn).

🗓️ 14th of April
📍 Milan

See you in Milan!

📰 Product Leaders’ Wisdom

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

FinTech 2026: Prompt Optimization & the Death of Transaction Stress

In FinTech, minor AI hallucinations create major liabilities. This deep dive from Product Faculty explores how Prompt Optimization, shifting from vague instructions to strict “Output Contracts”, eliminated 100% of formatting drift. By treating prompts as cognitive architecture, teams can stabilize complex financial workflows, ensuring the deterministic accuracy required for modern FinTech systems.

Melissa Douros (CPO at Green Dot) argues FinTech must move beyond transactions to optimize for human emotion. In this standout episode of the Launchpod, she introduces the “Cortisol UI”, a framework for building FinTech experiences that actively fix empathy problems and reduce user anxiety before a transaction occurs.

In this edition of FinTech Pulse, Lina Lim explores how Pay-by-Bank and AI-driven checkout optimization are disrupting traditional card networks. As merchants seek to slash fees, the shift toward direct, intelligence-led account-to-account (A2A) payments is becoming the new gold standard for high-conversion FinTech platforms in 2026.

💪 Open Roles

​​​​​Brought to you weekly by Alessia Marchi​

1. Senior Product Manager - Partner Platform @ Aroundhome

2. Head of FinTech Products @ Freenow

3. Product Manager - Payments & Checkout @ HomeToGo

4. Product Group Owner - HR IT Solutions @ Schaeffler

5. Senior Technical Product Manager @ Libra

6. Head of Product @ 7Learnings GmbH

7. Senior Product Manager

8. Product Lead Connectivity @ gridX

9. Product Lead Flexibility @ gridX

🎶 Song of the Newsletter

From our DJ Marco D’Avila