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The Convert Era (2016–2017)

In 2016, Amit Badlani came out of Stanford’s d.school and wrote about it like someone who’d found religion:

“The design thinking framework has helped me traverse the problem space and stay patient. Design thinking is all about iterating. It is not a magical process that guarantees solutions to the challenging problems. It will, however, lead you to the right answers eventually.”

“Lead you to the right answers eventually.” That’s pure faith. And I don’t mean that dismissively. If you’d gone through that program in 2016, you probably felt it too. The prototyping, the reframing, the permission to throw your first idea away. It felt new.

By 2017, demand had outrun supply. Yasith Abeynayaka built a self-study guide for people who couldn’t get to Palo Alto, calling design thinking “a mandatory skillset” for professionals. The d.school-to-IDEO-to-Google-Ventures pipeline was becoming the canonical path. If you cared about product, you were supposed to care about this.

The Bumper Sticker Problem (2019–2021)

Then the sloganization kicked in. Sefi Keller wrote a piece in 2019 that I keep coming back to:

“The problem is that as time goes by, many people find it hard to unpack the depth behind the idea’s ‘sticker version’ and might dismiss it altogether.”

She was talking specifically about empathy, and how it had been reduced to a step on a diagram. Her point was subtle and important: the people who created design thinking made it catchy on purpose, because leaders need bumper stickers to rally teams. But catchy eats nuance for breakfast.

Meanwhile, by 2021, Nathan Mckinley was writing five-stage explainers citing Apple, Disney, IBM, and Microsoft as proof that design thinking worked. Stanford teaches it. Harvard endorses it. This was DT at its most institutional, and maybe its most hollow.

“You Can Learn 90% of It in Five Minutes” (2023)

The backlash didn’t arrive as a single takedown. It crept in.

Lee Fischman wrote a piece in 2023 that basically said the quiet part out loud:

“The Design Thinking folks say ‘It’s method, not magic’ and they’re right, but I’d go one step further: it’s obvious and you already do it.”

His framing: before design thinking, design was a priesthood. After, it was democratized. Involve diverse people. Iterate. That’s it. The $3,000 MIT certificate was teaching you something you probably already knew.

Jackie Colburn published a workshop guide that same year acknowledging what everyone felt: people have been “burned in the past by inefficient, unproductive, and boring sessions that feel like a waste of time.” We’d turned design thinking into a calendar invite people dreaded. Post-Its were still there. The magic wasn’t.

The Quiet Dissolution (2024)

Here’s what surprised me. I pulled up Connor Joyce’s 2024 piece on building AI products, expecting at least a nod to design thinking. Nothing. The whole article is about LLM integration, deployment strategy, user outcomes. The closest you get is “just because it’s powerful doesn’t mean it’s the answer for everything,” which is basically empathy wearing different clothes.

Design thinking didn’t die dramatically. Nobody published a eulogy. It just… stopped being named. The principles got absorbed into how competent teams work. Table stakes now, not a framework.

What I’m Hearing on the Podcast

Rachel Wolan, CPO at Webflow, came on the show recently and put it well: “Human creativity remains vital in the design process, even with AI automation.” She never used the phrase ‘design thinking.’ She didn’t need to. The human-centered instinct is still there. It’s just no longer branded.

So What Actually Replaced It?

I’m not sure anything replaced it so much as the industry grew out of needing a name for it. The best PMs I talk to empathize with users, prototype quickly, iterate constantly. They just call it product management.

Maybe design thinking succeeded so completely it became invisible. Or maybe we just got tired of the Post-Its.

What’s your read? Did design thinking win by dissolving, or did we just collectively agree to stop talking about it? Reply and tell me. I genuinely don’t know the answer.

You’re reading the Product Coalition newsletter. Every week, I dig into the archive of 3,500+ articles and 100+ podcast episodes to trace how product thinking has evolved. If someone forwarded this to you, subscribe here so you don’t miss the next one.

Jay Stansell · Lisbon, Portugal · Product Coalition

Brought to you by ExecReps — AI-powered executive coaching for product leaders. Product Coalition members get extended access.

When ‘Ping Them Again’ Was the Plan (2019)

Before anyone was saying ‘product-led retention,’ the playbook was straightforward. A 2019 Product Coalition editorial on app retention laid out the accepted wisdom:

“A good onboarding experience can improve retention by up to 50%.”

The toolkit: onboarding flows, push notifications, personalization, re-engagement campaigns. Nudge the user. Remind them you exist. Hope they come back.

It wasn’t wrong. But it treated retention like a marketing problem. The question was always ‘how do we get them to open the app again?’ Nobody was asking ‘why did they close it?’

The Structural Turn (2018–2020)

The smarter thinking was already percolating. In 2018, Rob Finney wrote about network effects using the VHS vs Betamax story:

“What I had witnessed was a platform based network effect kicked off by a small advantage. The small advantage was then accentuated by a positive feedback loop.”

A system where more users equals more value equals less reason to leave. Retention was becoming structural, not tactical.

Then 2020 cracked things open. Carlos Gonzalez de Villaumbrosia named the shift to PLG: “It’s getting easier to build a business, but not easier to grow one.” When competitors replicate your features in six months, the product itself has to be the retention engine.

But my favorite retention concept in the entire archive came from Derek Skaletsky that same year. He’d built a search engine with genuinely excellent tech. Users kept churning after 90 days. His diagnosis was brutal: “Search is the most perishable activity on the web. You search for something, find your answer, and… close the tab.”

His conclusion? When users pour their data, workflows, and routines into your platform, switching feels like losing a part of yourself. He called this the ‘All My Shit’s In There’ factor. Still the most honest description of SaaS retention I’ve read.

The Number That Stops You Cold

That same year, Dennis Meisner pulled the Amazon Prime data:

“A stunning 93% of Amazon Prime members renew their subscription after the first year. After the second year, this number goes up to an incredible 98%!”

98%. By year two, Prime isn’t competing for your loyalty. It has become infrastructure. You don’t cancel your water bill. That’s the endgame of retention done right: you stop being a product and start being a utility.

From Tool to Infrastructure (2024–2025)

Lee Fischman wrote in 2024 about maintaining 90%+ B2B retention, and his framing was disarmingly simple: “The first reason our retention was so high was simply because customers needed our stuff. When they didn’t, they cancelled.”

No growth hacks. Just be so embedded in your customer’s context that removing you requires rewiring how they work.

Then Asher Atlas wrote in 2025 about a retention crisis when a music service lost its catalog overnight. His team’s reframe changed everything: “What if this isn’t a search problem? What if this is a discovery problem?” They turned a broken search into a trust-building experience. Retention, it turns out, lives in how you handle the moment when things go sideways.

What I’m Hearing on the Podcast

Nesrine Changuel (ex-Google, Spotify, Microsoft) came on the show and pushed this further. Her argument: “User loyalty is significantly enhanced by emotional connections.” The products people stay with longest are the ones they genuinely love, not just the ones they can’t figure out how to export their data from.

(Listen to EP82 with Nesrine Changuel)

So Where Does This Leave Us?

The arc is clear if you step back far enough. Retention went from ‘remind them you exist’ to ‘make leaving expensive’ to ‘make them not want to leave at all.’ I think most teams are still stuck in the ping-them-again era, measuring retention without asking what’s actually retaining people.

If your retention strategy starts with ‘how do we reduce churn,’ you might be asking the wrong question. The better one: why would someone choose to stay?

Reply and tell me where your team sits on this spectrum. I’m genuinely curious whether the AMSIT factor resonates, or if you’ve found something completely different keeping people around.

You’re reading the Product Coalition newsletter. Every week, I dig into the archive of 3,500+ articles and 100+ podcast episodes to trace how product thinking has evolved. If someone forwarded this to you, subscribe here so you don’t miss the next one.

Jay Stansell · Lisbon, Portugal · Product Coalition

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Just Ship Something, Please (2015–2019)

In December 2015, Fabrice Wegner wrote ‘The Vicious Circle of Preparation’ for Product Coalition, and reading it now feels like stepping into a time capsule. Fabrice was watching teams get stuck in endless preparation loops. Stakeholders would prioritize half-baked epics, product owners would scramble to validate them, engineers would wait around, and nobody shipped anything. His frustrated question cut through the noise:

“Is it wrong to want ship fast?”

The answer back then was a loud no. Speed was the gospel. Fabrice also dropped a line that I think most MVP evangelists never fully internalized: “Your customers won’t get happier or pay you a dollar if your team has learnt something. But the learning increment is the basis of a successful product.” Learning was supposed to justify shipping ugly. The trouble was, a lot of teams took that permission and ran with it.

Four years later, Vaibhav Gupta published ‘How to Define MVP’ on Product Coalition as part of a Product Management 101 series. His framing was textbook Lean Startup: “It is the smallest thing that you can build that would deliver some value to your customers and also help you gather validated learning about customers with least effort.” He walked through the Uber example (Travis Kalanick driving a car, a basic web app for hailing it), the skateboard-to-car analogy, the Build-Measure-Learn loop. All the hits.

This was still peak MVP optimism. The assumption was clear: build the smallest useful version and the path forward reveals itself. What nobody was really asking yet was whether the smallest useful version might also be the version users hate.

Ship Fast, But Please Make It Good (2020)

OK so here’s where it gets interesting. I pulled up two articles from 2020 and they basically argue with each other without meaning to.

In March of that year, Yellow Systems wrote ‘An MVP Can Save Your Product’s Life’ and was still firmly in the pro-MVP camp. Their argument: “launch delays have killed millions of startups and will probably kill millions more.” Fair enough. Ship now. Worry later. But then they snuck in a line that stopped me: a reduction in features is expected, they wrote, but “there should be no reduction in quality.”

Wait. Quality? In an MVP? I had to reread that. The whole MVP playbook, at least how most teams ran it, was basically trading quality for speed. Yellow was drawing a line nobody had drawn before. Strip the features, sure. But the stuff you keep? It better work. And it better look like someone cared.

Then Carlos Gonzalez de Villaumbrosia dropped ‘What Is a Minimum Lovable Product?’ that same summer and I remember reading his opening line twice. He basically said: meeting needs isn’t enough. Your users want to be delighted. They don’t want to tolerate your product. They want to love the thing.

I keep coming back to his next line: “being Viable just doesn’t cut it anymore. You need to be Lovable.” Carlos wasn’t really killing the MVP. He was renaming it, adding a higher bar. The MLP, he explained, is like an MVP “but with more thought and care taken in design and UI.”

And honestly? He was right about the timing. By 2020, users had lived with Slack and Notion and Figma. Their baseline for ‘acceptable first version’ was miles above where it sat in 2015. The floor had moved and a lot of teams hadn’t noticed.

RIP MVP? (2025)

This is where the backlash got loud. Garima Srivastava, one of our contributors, wrote a piece titled ‘Minimum Viable Product (MVP) is Dead’ earlier this year and she pulled zero punches. The MVP, she wrote, was supposed to get you early feedback. What it actually does? It produces “half-baked products that nobody loves.”

Garima’s analogy is the kind that stays with you. She compared most MVPs to someone serving you an uncooked pizza and telling you to imagine how great it’ll be once it’s done. Nobody wants that. Nobody shares that with friends. Her point: viability isn’t the bar anymore. Loveability is. People don’t recommend products they merely tolerate.

I’m not sure I fully agree. The original MVP concept, the one Eric Ries actually described, was never supposed to be a product you ship to the market and walk away from. It was a learning tool. But the PM community took ‘minimum viable’ and heard ‘minimum effort,’ and that misreading created a decade of products that launched to crickets.

The correction isn’t wrong. It’s just late. And honestly, I wonder if MLP will get misread the same way in another five years.

What I’m Hearing on the Podcast

Raksha Vashishta joined us on the podcast for an episode she called ‘The MVP of My Career.’ She talked about her journey as an immigrant woman in tech, applying MVP thinking not just to products but to her own career path. Start small. Validate. Pivot when the data says to. Her story of building from an accounts receivable internship to a product leadership role mirrors the MVP-to-MLP arc in a way I wasn’t expecting: the first version of your career doesn’t need to be polished. But at some point, you stop iterating on the minimum and start building something you’re genuinely proud of.

So What Does This Mean for You?

The MVP isn’t dead. But the era of shipping something ugly and calling it strategy? That part is over. What actually changed isn’t the framework itself. It’s the floor. User expectations in 2025 are so far above where they were in 2015 that the ‘minimum’ in ‘minimum viable’ now means something completely different.

When was the last time you shipped a true MVP, the ugliest working version you could get away with, and actually got useful feedback from it? Or has your team already moved past that into MLP territory without calling it that? Reply and tell me. I genuinely want to know if the skateboard still works.

You’re reading the Product Coalition newsletter. Every week, I dig into the archive of 3,500+ articles and 100+ podcast episodes to trace how product thinking has evolved. If someone forwarded this to you, subscribe here so you don’t miss the next one.

Jay Stansell · Lisbon, Portugal · Product Coalition

I’ve been pulling North Star Metric articles out of our archive all week, and honestly? The pattern surprised me. In 2019, our contributors were so sure. One metric. One number. That’s all you need. Three years later, some of those same people were writing about how that advice nearly wrecked their product teams. I don’t think most of us caught the shift as it happened.

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One Metric to Rule Them All (2019-2020)

If you want to feel the vibe of peak single-metric evangelism, go read Smit Shah’s ‘Tracking ‘One Metric That Matters’ (OMTM)‘ from September 2019. I pulled it up again this week. The certainty in it is wild:

“The concept of One Metric that Matters (OMTM) states that any organization should focus on optimizing only one metric that matters at that particular stage of the product’s lifecycle.”

Smit was channeling the spirit of the time. Pick one number. Align the team. Ship toward that number. He even acknowledged that the metric should shift as the product matures, but the core belief was unwavering: at any given moment, there is ONE number you should care about.

Six months later, Rashmi Shukla wrote ‘Product Metrics — How to Measure a Product‘ and slipped in the first crack. She argued for “chasing a north star metric accompanied by a few major metrics.” A few. Not one. Rashmi also dropped a warning that didn’t get enough attention at the time: focusing on MAU is “just another vanity metric” that hides the real picture of product stickiness.

I almost skipped that ‘a few’ caveat when I first read it. Seemed like a throwaway line. Turns out it was probably the most important sentence in the piece.

The Year the North Star Cracked (2021)

OK so here’s where it gets uncomfortable. Two pieces from 2021 basically describe the wreckage. People who followed the OMTM advice, did everything right by the book, and still ended up in trouble.

Tiziano Nessi wrote ‘How to Position Yourself as a Strong Product Manager From the Get-Go‘ and did something I don’t see often enough in our industry: he confessed to the exact mistake that the previous era’s advice had produced.

“I did the mistake to set the total number of users as an NSM. This led to a focus on the wrong value lever, and despite constant growth, the engaged users were decreasing...”

Read that again. Growth was going up. Engagement was going down. The North Star was shining and the product was quietly dying underneath it. That kind of failure mode doesn’t show up in a framework diagram.

Around the same time, Sebastian Straube published ‘North Star Metric — Measure the Right Thing‘ and reached back to 1956 for ammunition. He cited Ridgway’s classic critique:

“What gets measured gets managed — even when it’s pointless to measure and manage it, and even if it harms the purpose of the organisation to do so.”

Sebastian proposed a three-tier system: vanity metrics at the bottom, proxy metrics in the middle, business-aligned metrics at the top. The North Star should sit at Tier 1, sure, but only if it demonstrates “a clear and direct relationship between your product’s problem and the degree to which it is solving it.” Even that wasn’t enough on its own, because you still needed the lower tiers for context.

From Star to Constellation (2022-2023)

This is where the thinking got genuinely interesting.

I remember reading Elena Seregina’s May 2022 piece ‘Metrics Hierarchy and Metrics Pyramid‘ and thinking: finally, someone said it. She named the thing that had been bugging me for months:

“NSM is a product metric: most likely, it will measure customer behavior, not business goals.”

That distinction sounds small. It changes everything. Your North Star can be humming along perfectly while your business loses money. Elena proposed a layered pyramid with business goals at the top and product metrics below, each level checking the one above it. She also shared a story that stuck with me: “Our business metrics were rising. But as we were cracking a bottle to celebrate, the metrics suddenly dropped.”

By 2023, even the evangelists were hedging. Sriram Parthasarathy wrote ‘Decoding Business Growth: The Art and Science of Choosing the Right North Star Metric‘ and spent most of the piece making the case for NSMs. Then he landed here:

“While the North Star metric is a critical guide, it’s not the only measure of success. Companies should monitor other KPIs to ensure a balanced approach to growth.”

Sit with that for a second. Sriram just spent a whole article making the case for North Star Metrics. And his own conclusion is ‘not the only measure of success.’ That hedging at the end? That’s the sound of a correction happening in real time, right on the page.

What I’m Hearing on the Podcast

Bhav Patel came on the podcast to talk about fighting feature factories, and his rant connected directly to this whole metrics story. His argument: PMs became “feature managers” precisely because they lost the discipline of measurement. Not because they measured too little, but because they measured the wrong things and then stopped owning the numbers altogether.

“Product folks need to get their head out of their asses and start measuring what they do,” Bhav told us. His point isn’t that the North Star idea was wrong. It’s that most PMs never did the hard work of picking the right one, and when the single-metric approach failed them, they abandoned measurement entirely instead of fixing the metric.

So What Does This Mean for You?

The North Star didn’t die. It got demoted from solo act to lead instrument. The product community learned (sometimes painfully) that a single metric can focus a team, but it can also blind one. The fix isn’t to stop measuring what matters most. It’s to make sure ‘most’ isn’t doing all the work alone.

Here’s what I want to know: does your team still rally around one North Star, or have you moved to something more layered? Reply and tell me. I’m genuinely curious whether the correction has reached the teams doing the work, or if it’s still mostly happening in the articles.

You’re reading the Product Coalition newsletter. Every week, I dig into the archive of 3,500+ articles and 100+ podcast episodes to trace how product thinking has evolved. If someone forwarded this to you, subscribe here so you don’t miss the next one.

Jay Stansell · Lisbon, Portugal · Product Coalition

In 2016, the PM job felt clean. Three jobs, one framework, minimal existential dread. Ten years later, a PM writes about burnout so deep that “just take a break” feels like a joke. Somewhere between those two moments, an entire profession lost the plot on what it was supposed to be.

I spent the last week reading through a decade of Product Coalition articles about the PM role. What I found is less a career arc and more an identity crisis playing out in slow motion.

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“Three Jobs, Not Enough Time” (2016)

Christina Wodtke wrote The Three Jobs of Product Management back in 2016, and it still reads like the clearest thing anyone has said about the role. Business Owner. Vision Holder. Team Coordinator. That’s it.

But Christina also flagged something most people glossed over. “A Product Manager often has influence without authority,” she wrote. “She can’t fire anyone, or even get them off her team.” Think about that for a second. We spent years calling ourselves mini-CEOs when we couldn’t even choose who sat at our own table.

She also nailed something about the daily reality: “Product Managers, like all humans, tend to do the work that has the most screaming associated with it.” If you’ve ever abandoned your roadmap to fix a billing escalation, you know exactly what she meant.

“The Title I Prefer Is Servant Leader” (2022)

John McDonald didn’t tiptoe around it. His 2022 piece Why Acting Like the “CEO” of Your Product Might Be Doing More Harm Than Good went straight at the Horowitz memo that started it all. “Many a product managers use this line as a justification for their behavior,” he wrote. And honestly? I’ve seen it happen.

His replacement? “The title I prefer is ‘servant leader’. I get it, it’s not as sexy as ‘CEO’, but I think it’s a lot more evocative and representative of the role.”

Meanwhile, something awkward was happening. PM jobs had grown 230% between 2017 and 2022. But Kasey Fu confessed in The Hidden Value a PM Brings to the Product Team that engineers were still asking the uncomfortable question: “What value do you folks even bring?”

That line still makes me wince. Not because it’s unfair, but because most PMs, if they’re honest, have struggled to answer it clearly.

“Wait, Are We Even Needed?” (2023-2026)

Then AI walked into the room. Jing Hu put it bluntly in No Such Thing As An AI Product Manager: all product managers now have to swim in the AI pool. There’s no special “AI PM” title. There’s just PM, with a whole new set of capabilities to understand.

What fascinates me about Jing’s piece is the diagnosis underneath. PMs had become “button placers, conversion makers, document writers” for so long that bold technology actually felt unfamiliar. AI didn’t threaten the PM role. It exposed how small the role had become.

Then Dan Apps published the title that stopped the scroll. Product Management Is Broken: This Is Where It Ends. After 16 years in the field, Dan wrote that he’d been “quietly haunted by the same dysfunction” across every company. His verdict: “Product Managers need to stop internalising blame for a system that’s broken by design.”

And in early 2026, Irina Bulygina made it personal. I’m Burned Out and “Just Take a Break” Is Not Helping reads less like an article and more like a late-night conversation with a friend. “I sit on both sides of the barricades,” Irina wrote, “trying to understand everyone at the same time.”

This is the part that gets me. She’s not questioning the strategy frameworks or the org chart. She’s questioning whether the emotional cost of the job is sustainable. “Fear that AI is replacing us. Fear that the product manager role is becoming obsolete. Fear that we are watching the beginning of the end.”

What I’m Hearing on the Podcast

This tension showed up on the Product Coalition podcast too. In EP98, Margaret-Ann Seger argued that the best product ideas shouldn’t come from product managers at all. That’s the servant leader thesis taken to its logical conclusion: your job isn’t to have the ideas, it’s to create the conditions where good ideas surface from anywhere.

Brian Glassman explored the other side of the coin in EP81, making the case that generative AI can actually free PMs from the button-placing and document-writing that Jing described, letting them get back to the bold thinking the role was always meant for.

So What Does This Mean for You?

Here’s what I keep coming back to. The PM role has survived every identity crisis of the past decade. Mini-CEO, servant leader, empowered teams, AI disruption, burnout. It survives because the need for someone to hold the thread between business, technology, and users never goes away. The title changes. The job description changes. The core need stays.

So try this at your next dinner party. Someone asks what you do. You can’t say “product manager.” What comes out instead? I genuinely want to know. Hit reply and tell me.

You’re reading the Product Coalition newsletter. Every week, I dig into the archive of 3,500+ articles and 100+ podcast episodes to trace how product thinking has evolved. If someone forwarded this to you, subscribe here so you don’t miss the next one.

Jay Stansell · Lisbon, Portugal · Product Coalition

Brought to you by ExecReps, AI coaching that helps product leaders practice tough conversations before they satisfice easy ones

The Quiet Recommendation (2016)

Before OKRs became a mandate, they were a suggestion. Christina Wodtke, author of Radical Focus, mentioned them almost casually in her 2016 piece ‘The Three Jobs of Product Management.’ Her take:

“Vision holding is the most neglected job of a PM, yet it is the one that makes teams and product succeed. (OKRs can help!)”

That exclamation mark and parenthetical still make me smile. OKRs weren’t yet the thing every VP demanded in their quarterly planning session. Christina framed them as a useful tool alongside team norms and mission statements. A helper, not a religion.

“30 Days and You’ll Never Look Back” (2018)

Two years later, the tone changed completely. Brad Dunn’s ‘Moving to OKRs in 30 Days‘ captured peak enthusiasm perfectly. He opened with an admission that tells you everything about the era:

“I have been talking to a LOT of people over the last few months about OKRs, more than I thought I would actually. It is such a hot topic.”

Brad’s confidence was infectious. Follow his plan, and in 30 days you’d be transformed. But I love this moment of honesty buried deep in the optimism: “Trust us here. The first cycle you do will be a mess, just accept that and get the cadence and routines down.”

The seeds of disillusionment were planted right inside the hype. Most people skipped past that line. I bet they wished they hadn’t.

The Warning Shot (2019)

Then Itamar Gilad showed up. A former Google PM (the company most associated with OKR success), Itamar wrote ‘5 Ways Your Company May Be Misusing OKRs‘ and dropped what I consider the single most important sentence in a decade of OKR discourse:

“OKRs are just containers for goals. They serve bad goals just as well as they do good goals.”

That line changed my thinking about frameworks in general. Containers don’t care what you put inside them. Itamar went further: “Bad OKRs can amplify the issues the org is troubled with rather than fix them.” Coming from inside the Google house, this wasn’t a hot take. It was a warning from someone who had watched OKRs fail at scale.

Seeking Alternatives (2023)

By 2023, the community had started publishing “what to use instead of OKRs” articles, which is the clearest signal any framework has crested its hype curve. Lee Fischman’s ‘Goal-Question-Metrics: A Holistic Alternative to OKRs‘ proposed GQMs as a more rigorous approach. His critique was specific:

“Why is asking questions so worthwhile? Look at the examples above and notice how their Key Results are basically arbitrary.”

Arbitrary. That word landed hard with anyone who had sat through a quarterly planning session watching leadership pick Key Results out of thin air. Lee didn’t reject OKRs entirely, but he exposed a real weakness: the framework skips the “why are we measuring this?” step.

The Framework Survives (2024-2026)

This is the part that fascinates me most. Noa Ganot wrote about OKRs for Product Coalition twice, two years apart, and watching her thinking deepen is its own story.

In 2024, her piece ‘OKR Planning: Break the Chains‘ treated OKR problems as therapy problems: “OKRs are meant to bring your dreams into reality. If you don’t eliminate these limiting beliefs, you are left with a lot of reality that shapes and limits your dreams.”

By January 2026, her perspective in ‘When OKRs Don’t Work, the Problem Is Elsewhere‘ had sharpened into something more profound. OKRs fail because “they surface gaps teams have learned to live with: unclear priorities, postponed decisions, and ownership that isn’t as solid as it looks.”

And then the line that closes the loop on a decade of debate: “The framework forces the question, but it can’t force the answer.”

Noa didn’t flip-flop between those two articles. She deepened. That’s rarer than you’d think in product writing.

What I’m Hearing on the Podcast

Andrea Saez joined me recently to talk about product strategy alignment, and her thinking connects directly to the OKR misuse thread. She’s been vocal about the difference between vanity metrics and meaningful customer KPIs, which is exactly where most OKR implementations go sideways. Teams pick Key Results that look impressive in a slide deck rather than ones that reflect actual customer outcomes.

Alex Blinov made a related point about how the PM role is shifting from “mini CEO” to strategic architect. When your job definition changes, the goals you set and how you measure them have to change too. Most OKR frameworks haven’t caught up with that shift.

So What Does This Mean for You?

OKRs survived the hype cycle. Not because they’re perfect, but because the problem they force you to confront (do we actually know what we’re trying to achieve?) never goes away. The framework is just a mirror. If you don’t like what you see, the answer isn’t a better framework.

Are you still using OKRs? Have you modified them beyond recognition, or abandoned them entirely? I’d love to hear what actually works on your team. Hit reply and tell me.

You’re reading the Product Coalition newsletter. Every week, I dig into the archive of 3,500+ articles and 100+ podcast episodes to trace how product thinking has evolved. If someone forwarded this to you, subscribe here so you don’t miss the next one.

Jay Stansell · Lisbon, Portugal · Product Coalition

I’ve been reading through our archive of Product-Led Growth articles this week, and something funny kept happening. The earlier the piece, the more certain the author sounded. By 2023, everyone was hedging. That arc tells a story worth tracing.

Brought to you by ExecReps, AI coaching that helps product leaders practice tough conversations before they satisfice easy ones

When the Product Sold Itself (2021)

In 2021, Michelle Yick wrote a piece for us called ‘How to Spot a Product-Led Company‘ that captured the PLG dream perfectly:

“If sales, marketing, and customer support disappeared, the core product would still attract and retain users (albeit at a slower growth rate).”

Think about that claim for a second. If your entire go-to-market team vanished, you’d still grow. That was the promise. And for a handful of companies, it seemed true. Michelle pointed to Zoom as proof: “Remember when you tried Zoom and immediately told your friends, coworkers, and overseas relatives with terrible wifi to switch over?”

Around the same time, Sandhya Hegde published ‘The 3 Modes of Product-led Growth,’ tracing PLG’s roots back further than most people realize. She argued that “1983 was the true birth year of product-led growth,” pointing to AOL free trials and the GNU open-source movement. By 2006, companies like Box and Skype had the playbook: “giving away free plans and trials to entice their end users to adopt software that could grow virally within companies.”

Every startup wanted to be the next Slack. PLG wasn’t just a go-to-market strategy. It was an identity.

Everybody Tried to Be Slack (2022)

Surrbhi Soni’s ‘Slack: A Product Led Growth Strategy Case‘ reads like peak evangelism. Slack, Dropbox, and Zoom had “removed the myth that without product manuals, traditional lead generation, sales demos, and POC setup, a product cannot grow.”

But buried in the same article was a counterpoint nobody wanted to hear:

“Microsoft launched Team in 2016 and took over many customers of Slack, and currently has almost twice as many daily active users as Slack.”

Microsoft Teams didn’t win on product experience. It won by being free with Office 365. Enterprise CTOs picked the bundle, not the better tool. That should have been a warning sign for the whole PLG movement. But in 2022, the hype was still running hot.

Meanwhile, Noa Ganot was already seeing the backlash build. In ‘Three Wrong Reasons to Give Up on Product-led Growth,’ she pushed back against lazy dismissals. Her observation was sharp: “Product-led company and product-led growth are two different things. While you can’t do PLG without being a product-led company, the other way around is not necessarily true.”

That distinction matters more than most people realize. A lot of companies thought they were doing PLG when they were really just not hiring salespeople.

The Confession Booth (2023)

This is where it gets honest. Guy Barner, a founder who actually built a PLG company, wrote ‘To PLG, or not to PLG?‘ and dropped this line:

“Even though we went with PLG, I still don’t think it’s the best choice for most startups.”

That’s a PLG founder saying PLG probably isn’t for you. He went further: “Trust me, there are zero sales-led startups with good onboarding.” Sounds like a point for PLG until you read the rest. Guy explained that PLG requires you to nail everything at once: lead generation, website conversion, onboarding, product quality, and a freemium model that converts. With sales-led, you need a good product and good salespeople. That’s it.

Then Noa Ganot came back with ‘Product-Led Growth Is a Misleading Name‘ and shared a stat that stopped me cold:

“Research shows that up until $10M ARR, it’s much easier to succeed without PLG than with it. After $10M ARR the opposite is true, and PLG wins big time.”

So PLG works best for companies that already have serious traction. But most of the advice and tooling is aimed at early-stage startups. That gap explains a lot of the wreckage.

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The Hybrid Reality (2024)

By 2024, the conversation had matured. Mart Objartel wrote about the challenges of choosing between product-led and sales-led strategies in ‘Navigating Challenges in Product-Led vs. Sales-Led Strategies for B2B SaaS,’ and he dropped the either/or framing entirely. His warning was practical: companies shift between strategies all the time, “sometimes subtly, akin to the proverbial frog boiling.” The real danger isn’t picking wrong. It’s changing direction without telling your product team.

Mart also highlighted something that rarely gets discussed. In sales-driven organizations, “aspiring product managers often feel constrained in effectively managing their products.” The PLG dream wasn’t just about growth metrics. For a lot of PMs, it was about autonomy. That’s partly why the backlash stung.

What I’m Hearing on the Podcast

Dan Balcauski joined me on the podcast to talk about SaaS pricing and packaging, and his perspective connects to PLG’s blind spot. Freemium tiers, trial-to-paid conversion, the whole pricing ladder that PLG depends on: those are the execution details where most companies fall apart. Dan’s insight about understanding customer value through qualitative research (not just usage data) explains why so many self-serve funnels leak. The product might sell itself. But if your pricing doesn’t match how customers experience value, the self-serve model collapses anyway.

(Listen to EP83 with Dan Balcauski)

So What Does This Mean for You?

PLG isn’t dead. But ‘PLG alone’ was always a mirage. The companies that tried to be Slack learned that being Slack requires being Slack: massive network effects, a product category that spreads virally, and enough runway to survive years of free users before revenue catches up. Most products don’t have those conditions.

What actually works for most teams is a hybrid. A product good enough that users want to try it, paired with humans who help close the deal. Not glamorous. Very effective.

I’m curious: did your company try PLG and pivot away? Or are you still running a self-serve motion? Reply and tell me how it’s going. I genuinely want to know.

You’re reading the Product Coalition newsletter. Every week, I dig into the archive of 3,500+ articles and 100+ podcast episodes to trace how product thinking has evolved. If someone forwarded this to you, subscribe here so you don’t miss the next one.

Jay Stansell · Lisbon, Portugal · Product Coalition

Every couple of years, someone in our community writes a piece declaring the product roadmap dead. Then a few months later, someone else writes about how to build a better one. I've watched this cycle play out across 3,500+ articles over eleven years at Product Coalition, and I've started to think the roadmap isn't dying at all. It's molting.

Brought to you by ExecReps, AI coaching that helps product leaders practice the conversations that matter most

The Gantt Chart Graveyard (2016)

In December 2016, one of our contributors, Swapna M, wrote a piece called ‘Product roadmap 2017‘ that perfectly captured where most teams were at the time. She laid out a top-down framework: Vision to Key Objectives to KPIs to Milestones. Pretty standard stuff. But then she dropped this line:

“I refuse to recognize Gantt charts as feasible tools to roadmapping though!”

That exclamation mark still makes me smile. She was frustrated. A lot of PMs were.

The tools we inherited from project management felt wrong for product work, but nobody had a clean alternative yet. Her solution was Trello boards and a strict no-deadlines policy. She wrote that she ‘personally does not put concrete deadlines since new variables get introduced randomly everyday in a startup environment.’

Looking back, this was the era of rebelling against the format without questioning the content. We stopped using Gantt charts. We kept building feature lists. Just on prettier boards.

The Outcome Turn (2019)

By 2019, the conversation had shifted. Elena Sviridenko published ‘Outcome-driven product roadmap‘ on Product Coalition in March of that year, and you could feel the frustration had evolved into something more focused. She started with this observation:

“Many organizations struggle with roadmaps, finding them difficult to maintain and hardly ever coming true.”

That resonated with thousands of readers. But the real gut punch came later in the piece:

“Prioritizing without knowing the context of the problem and the desired outcome is like shooting in the dark.”

Elena introduced the Now/Next/Future framework to our audience. Not features slotted into quarters, but problems organized by urgency. It sounds obvious now. In 2019, it felt radical. I remember the comments section on that article being split between PMs who found it liberating and PMs whose stakeholders would never accept a roadmap without dates.

The outcome-driven movement gave PMs a vocabulary to push back. ‘We’re solving for this outcome’ is a different conversation than ‘we’re shipping this feature in Q3.’ Better conversation, honestly. But it also created a new problem: roadmaps that were so abstract they didn’t actually communicate anything to engineering teams or executives.

Principles Over Process (2023-2024)

This is the part that fascinates me. John Utz published two pieces with us. ‘What is a product roadmap?‘ in May 2023 and ‘Rethinking product roadmaps‘ in November 2024. I think they represent where roadmap thinking has landed. In the earlier piece, he tells a story about pitching features to a stakeholder who stopped him cold:

“You are just sharing features; that’s your release plan.”

Ouch. John went on to frame the roadmap as fundamentally a communication tool, citing Bruce McCarthy’s definition: “A product roadmap is a tool for communication and alignment. It tells the story of where you are, where you are going, and how you will get there. It is not a project plan or a commitment. It is a strategic document.”

Then in late 2024, John came back with a first-principles framework. Eight principles for building roadmaps, rooted in the Elon Musk approach of questioning every assumption. He wrote:

“It’s the difference between following a recipe and understanding the chemistry of cooking.”

I think this captures the maturation perfectly. In 2016, we were arguing about the tool (Gantt chart vs. Trello). In 2019, we were arguing about the content (features vs. outcomes). By 2024, we’re arguing about the thinking underneath. The recipe doesn’t matter if you understand what each ingredient does.

John also admitted something most roadmap evangelists won’t: “We were behind our competition, pumping out features with low value, slow to release, and pandering to our stakeholders, not our customers.” That kind of honesty only shows up when someone has been through the full cycle.

What I’m Hearing on the Podcast

On a recent episode of the Product Coalition podcast, Valentina Coin told me something that reframed how I think about all of this. We were talking about change management and she said: “You have a human being that is grieving the way things were, very comfortable, very familiar. Maybe they took a little bit longer to get done. Maybe it was a little bit inconvenient, but it was familiar.”

She was talking about digital transformation broadly. But I couldn’t stop applying it to roadmaps. Every time we reinvent the roadmap format, teams have to grieve the old one.

The PM who mastered the Gantt chart had to let it go. The PM who perfected the feature-based quarterly roadmap had to learn outcomes thinking. Now we’re asking people to operate on principles. That’s harder. And people resist harder things, at least at first.

(Listen to EP100 with Valentina Coin)

So What Does This Mean for You?

The roadmap didn’t die. It grew up. And here’s what I’d actually take away from watching a decade of this evolution: stop optimizing the artifact and start getting better at the conversation around it. Your roadmap format matters less than whether your team and stakeholders walk away from a roadmap review aligned on what matters and why.

I’d love to hear from you. What does your current roadmap actually look like? Reply to this email and tell me, genuinely curious whether you’re still in the outcome camp or if you’ve moved on to something else entirely.

You’re reading the Product Coalition newsletter. Every week, I dig into the archive of 3,500+ articles and 100+ podcast episodes to trace how product thinking has evolved. If someone forwarded this to you, subscribe here so you don’t miss the next one.

Jay Stansell · Lisbon, Portugal · Product Coalition

“Just put your crash helmet on, and get on with it.” - That’s been my philosophy since 2007 when I pivoted from design to product. Now, with AI reshaping everything, it’s time to put that helmet on again.

Jay here.

After interviewing dozens of product leaders on our podcast (17,000+ downloads and counting), reading insights from our 1M+ annual readers across 225 countries, and engaging with our 11,000+ Substack followers, one thing is crystal clear:

The AI skills gap is creating two classes of product managers: Those who’ll thrive in 2026, and those who’ll be left behind.

Why I Built This Tool (And Why You Need It)

Look, I’ve been through major tech transitions before. Web to mobile. Desktop to cloud. Waterfall to agile. Each time, the PMs who adapted early won.

This time is different. The speed is unprecedented.

The Reality Check:

• 98% of PMs use AI but only 39% have proper training [Business Wire, Nov 2024]

• 66% admit using shadow AI - unapproved tools that could breach compliance [Business Wire, Nov 2024]

• EU Digital Product Passport hits in 2026 - are you ready? [Salsify, 2025]

• 82% of organizations will use AI agents by 2026 [Analysts Corner, 2025]

When I founded Product Coalition in 2014, the mission was simple: Make mastery of product management globally accessible.

Today, that means helping you master AI before it masters you.

Introducing: The 2026 PM AI-Readiness Scorecard

We’ve taken everything we’ve learned from:

• 3,500+ articles published on Product Coalition

• Interviews with leaders like Tamar Yehoshua (ex-CPO Slack) and Rich Mironov

• Our recent podcast with Chris Butler from GitHub on AI in Product Ops

• Research from McKinsey, Gartner, and MIT

• Feedback from our global community spanning 225 countries

And distilled it into one comprehensive tool that gives you exactly what you need.

What Makes This Different

Most AI assessments are generic. Built by consultants who’ve never shipped a product.

This one’s different. It’s built by a PM (me), tested by PMs (our community), for PMs (you).

From my experience leading product teams across the world over 25 years, I know what actually matters:

• Actionable insights, not theory

• Role-specific guidance (B2B SaaS PM needs different skills than B2C PM)

• Visual dashboards (because we’re visual thinkers)

• Progress tracking (what gets measured gets done)

• Regulatory readiness (2026 compliance is non-negotiable)

🚀 The Game-Changing Dashboard (Why PMs Love This)

Remember when I taught Lean Product Management at General Assembly? First thing I’d say: “If you can’t see it at a glance, you can’t manage it.”

That’s why we built a dashboard that would make any data-loving PM smile:

📊 Executive Summary Section

What it shows: Your overall AI readiness score (huge, can’t miss it), readiness level (🚀 AI-Ready to ⚠️ Needs Attention), and personal profile.

Why it matters: One screenshot to share with your manager. Shows commitment to growth and current capability in seconds.

💯 Key Metrics Cards

What it shows: Four critical KPIs - Skills Gap Average, Target Achievement %, Critical Gaps Count, Industry Comparison (+/- score).

Why it matters: Instantly see where you stand. No digging through data. These are the numbers that determine your AI readiness and market value.

📈 Skills by Category Breakdown

What it shows: Performance across 5 categories (AI Fundamentals, Product Skills, Technical Skills, Data & Analytics, Governance) with status indicators.

Why it matters: Identifies exactly which areas need attention. Stop wasting time on strengths when gaps are killing your effectiveness.

💪 Strengths vs Improvement Areas

What it shows: Your top 3 strengths and top 3 gaps, side by side.

Why it matters: Balance is key. Leverage strengths while systematically addressing weaknesses. This view prevents blind spots.

📊 Category Comparison Chart

What it shows: Visual progress bars comparing You vs Target vs Industry for each category.

Why it matters: See gaps visually. The ■□ symbols show progress at a glance. Perfect for visual learners and progress tracking.

🎯 AI Journey Timeline

What it shows: 4 milestone levels with dates: Foundation (30 days) → Developing (60 days) → Advanced (90 days) → AI-Ready (120 days).

Why it matters: Transforms vague goals into concrete milestones. You know exactly what to achieve by when.

⚡ Quick Stats Panel

What it shows: Total skills assessed, skills at target, days to 2026 deadline (countdown!), recommended study hours/week.

Why it matters: Critical context at a glance. That deadline countdown? It’s a daily reminder that time’s running out.

🎯 AI Readiness Meter

What it shows: Visual meter using 🟢⚪ circles showing your % AI-ready.

Why it matters: Gamification works. This simple visual motivates daily improvement. Share it on LinkedIn to show progress.

🚀 Next 3 Actions (Red Alert Box)

What it shows: Three prioritized actions based on your assessment, including your biggest gap and DPP compliance status.

Why it matters: Eliminates analysis paralysis. You know exactly what to do next. No more wondering where to start.

📈 Progress Tracker

What it shows: Historical tracking of assessments with dates, scores, and notes.

Why it matters: Prove your growth. Document your journey. Show consistent improvement to stakeholders.

Plus Four More Power-Packed Tabs

🎯 AI Skills Assessment

20 competencies with role-specific targets, industry benchmarks, visual gap analysis, and automatic priority ranking.

🔍 Quick DPP Check

8-point compliance checker with Yes/No dropdowns, instant scoring, priority levels, and action recommendations.

🎓 Learning Path

90-day roadmap broken into monthly milestones, linked to your actual gaps, with progress checkboxes.

📘 Welcome Page

Professional cover with my background, Product Coalition’s story, and how to use the tool effectively.

The Interactive Elements That Make It Addictive

We’ve learned from our 20,000+ newsletter subscribers what keeps PMs engaged:

• Dropdown menus everywhere - No typing required

• Role selector - Choose your PM type, everything recalculates

• Conditional formatting - Colors change based on your scores

• Data bars - Visual progress in every score cell

• Auto-calculations - Everything updates in real-time

• Emojis throughout - Because spreadsheets don’t have to be boring

Here’s What Happens Next

You have two choices.

Option 1: Keep doing what you’re doing. Use ChatGPT casually. Hope for the best. Watch as AI-fluent PMs get the promotions, the raises, the opportunities.

Option 2: Take 20 minutes today. Complete the assessment. Get clarity on exactly where you stand and what to do about it.

From my experience transforming teams blobally, I can tell you: The ones who act early always win.

Why This Is Free (And Always Will Be)

Product Coalition has always been about community first. No ads. No sponsors. Just pure value.

This scorecard is my way of giving back to the community that’s given me so much. From the talented people who’ve become friends, to the insights you’ve shared on Medium, to the 1M+ readers who trust us monthly.

We succeed when you succeed. It’s that simple.

GRAB YOUR COPY BELOW

A Personal Note from Jay

I’ve been through enough transitions to know: The scariest moment is right before you start.

When I moved from Sydney to Lisbon, when I left corporate to start Product Coalition, when I shifted from design to product – each time, the hardest part was taking that first step.

This scorecard is your first step. It’s not about being perfect. It’s about knowing where you are so you can get where you’re going.

As I always say: “Just put your crash helmet on, and get on with it.”

Let’s get on with it together.

Cheers,
Jay Stansell
Founder, Product Coalition
Connect on LinkedIn | ProductCoalition.com

GRAB YOUR COPY BELOW

Get Your AI-Readiness Scorecard Now →

1

The professionals who win in this next era won’t just do great work — they’ll be known for it. - Jay Stansell

We are living through the fastest change to career dynamics in decades.

AI tools can automate tasks.

Job descriptions are being rewritten.

Recruiters are changing how they find talent.

Visibility is currency.

And while skills still matter — perception and profile are becoming equally important.

It’s Time to Reposition Yourself for This New Reality.

This is especially true if you work in:

• Product Management

• Engineering

• Data or Data Science

• UX or Design Leadership

• Executive, Strategy, or Operations

• Technology Leadership (CTO, CFO, CPO)

You might be brilliant — but if nobody can find that brilliance, it might as well not exist.

This is why Product Coalition created Promote Me — a membership for ambitious professionals who understand that their next role, next raise, or next opportunity will come because of their public profile — not in spite of it.

Subscribe now

Why Does a Podcast Matter Now?

Podcasts are the most underutilized career asset available today.

They are searchable, evergreen, and emotive.

A podcast episode about you:

• Captures your story and expertise in your voice.

• Positions you as a thought leader in your field.

• Lives forever online.

• Shows hiring managers, recruiters, and your network that you are an active, strategic professional.

And at Product Coalition, we don’t just record it — we amplify it.

We Promote You To:

• 10,000+ LinkedIn product followers

• 10,000+ Substack readers

• 20,000+ community subscribers across platforms

• Global search engines forever.

This is professional reputation-building at scale.

Why a Newsletter Too?

Because words travel further than resumes.

A well-written newsletter about your expertise:

• Positions you in your category.

• Connects your name to topics people are searching for.

• Acts as your professional calling card.

This isn’t optional anymore — it’s smart career insurance.

Subscribe now

What’s the Real ROI?

Having a podcast and newsletter about you is not just content.

It’s:

• Job security (internal leaders notice).

• Job mobility (external recruiters discover you).

• Future-proofing (AI won’t automate your story).

• Community building (your network grows with you).

Subscribe now

And Here’s the Best Part — It Lasts Forever.

Social posts disappear in 24 hours.

A podcast and newsletter distributed by Product Coalition are discoverable for life.

Google your name in 3 years — this content will still be working for you.

Ready to Future-Proof Your Career?

We only have limited spaces for Promote Me members this year.

If you’re serious about repositioning yourself for the next era of work — now is the moment to act.

Let’s make your next podcast, newsletter, and event all about what matters most — you.

Subscribe now

Here’s what I’m covering this week:

1. 🤔 EVENTS: Product Strategy; Leveraging My Disability

2. 📝 COMMUNITY ARTICLE: Software Engineers Are Not Fungible

3. 🗒️ KNOWLEDGE: Product Hiring with AI in 2025 (without HR)

4. 🎧 PODCAST: Breaking Blockchain Barriers

5. 👉 OPEN TO WORK

LIVE EVENTS

🤔 Want your own live event to elevate your professional profile to 15k LinkedIn followers? Subscribe as a Premium Member! More details here.

What Is Product Strategy Exactly? And Why It Matters

Leveraging My (Dis)ability

COMMUNITY ARTICLE

📝 Want to write for Product Coalition on Medium? Subscribe on Substack and receive the info!

Software Engineers Are Not Fungible

Different engineers. Different skills. Different value.

🗒️ KNOWLEDGE: Product Hiring with AI in 2025 (without HR)

Last week, while sorting through applications for our new senior product role, I remembered how we used to hire back in 2015. Mountains of CVs, gut feelings, and hoping for the best. Fast forward to today, and there I was, using AI to spot patterns I'd have missed entirely.

McKinsey's latest research backs up what I've been seeing: organizations using AI in talent management are 83% more likely to have made successful hires. But here's what caught my attention - it's not just about finding people anymore. It's about understanding them.

Let me share what I've learned about using AI in talent management, including some specific prompts that have changed how I approach hiring.

Oh, and I’ve written this approach for those without HR teams (or those that want to keep HR team usage to a minimum), mainly because for most of my career in startups this has been how I’ve discovered the top 1% of talent.

Creating Job Posts That Are Talent Magnets

First up, let's talk about writing job descriptions. Textio's analysis shows that AI-optimized job posts get 25% more qualified applicants. I've been experimenting with AI to create posts that don't just list requirements but tell a story about the role. My hack; put the 90-day onboarding plan in the advert - the top talent LOVES this! It shows planning, foresight, transparency and organisation.

Here's the prompt I use:

"Act as a hiring manager for a product-led organisation. Write a concise, engaging, and inclusive job description for a Senior Product Manager role focused on AI and data analytics. Ensure it highlights collaboration, growth opportunities, and company culture."

Smarter Resume Assessment

LinkedIn data shows that hiring managers spend an average of 7.4 seconds per resume. In a pile of 300 applications, that's a recipe for missing great talent. Here's how I use AI to dig deeper:

Refined ChatGPT Prompt:
"You are a recruitment assistant. Compare these resumes (provide/paste details) against the following criteria (list your needs). Create a ranking of the candidates with a summary of their strengths and weaknesses."

Mining Your Talent Database

Remember that great candidate from six months ago who wasn't quite right for that role? They might be perfect for your current opening. Gartner reports that companies with strong internal talent mobility retain employees for twice as long.

Here's my prompt for revisiting past applications:

"Act as a talent scout. Given this database of past applications (paste details), identify candidates who meet the following job criteria (list specific qualifications). Highlight relevant experience and provide recommendations."

Culture Fit: The Make or Break Factor

According to Deloitte's research, poor cultural fit can cost an organization between 50-60% of the person's annual salary. I've found AI particularly helpful in crafting questions that reveal cultural alignment:

"You are an HR expert. Create five interview questions designed to evaluate a candidate's cultural fit for a fast-paced, collaborative product management team. Focus on teamwork, adaptability, and long-term alignment."

Testing That Actually Tests

Gone are the days of generic coding tests. Harvard Business Review found that companies using AI-designed assessments see a 40% better prediction rate for job performance. Here's my go-to prompt:

"You are a product management trainer. Create a 30-minute case study task for a Product Manager candidate to solve. The task should test prioritisation, problem-solving, and communication skills. Provide clear instructions and evaluation criteria."

Getting Salary Right

Read more

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Here’s what I’m covering this week

1. 🤔 EVENT: A.I. LIVE EVENT DAY - 3 SPECIAL EVENTS FRIDAY

2. 🗒️ STUDY WITH JAY: Digital Twins

3. 🎧 PODCAST: EP67 Breaking Blockchain Barriers

4. 📝 COMMUNITY ARTICLE: The Puppet Master Without Strings: How I Learned to Influence

5. 👉 OPEN TO WORK

A.I. LIVE EVENT DAY - 3 SPECIAL EVENTS

🤔 Want your own live event to elevate your professional profile to 15k LinkedIn followers? Subscribe as a Premium Member! More details here.

STUDY WITH JAY: Product Shadow Powers

🗒️ Each week I share what I’m studying, with the world. This week I’m studying digital twins and the opportunity for SaaS.

Last month, I was having a virtual coffee with Sara, the CTO of a rapidly growing SaaS platform. "You know what saved us last month?" she asked, stirring her flat white. "Our digital twin spotted a potential system collapse before any alarms went off. Saved us from what would have been a nightmare."

Now, if you're thinking digital twins are just for factories and fancy manufacturing plants, you're in for a treat. The software world has taken this concept and turned it into something rather brilliant for SaaS platforms. Mind you, getting it right isn't exactly a walk in the park, but the payoff is worth every bit of effort.

Let me share what I've learned from chatting with some SaaS product people who have or are setting up digital twins, and why this matters more than ever for your business.

The Real Deal About SaaS Digital Twins

Think of a digital twin as your platform's stunt double. While your actual system handles the day-to-day operations, its twin runs scenarios, spots potential issues, and gives you insights you never knew you needed. Matterport's been doing incredible things with this technology, creating digital replicas that do more than just look pretty – they provide actionable insights that make proper business sense.

AWS IoT TwinMaker has made this technology more accessible than ever. One of my contacts, a logistics software provider, used it to model their entire distribution stack. Within three months, they'd found inefficiencies that were costing them thousands. Pretty clever stuff.

A Proper History Lesson (But the Interesting Kind)

Read more

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Here’s what I’m covering this week

1. 🗒️ STUDY WITH JAY: When Thoughts Become the New SaaS Market

2. 🎧 TWO PODCASTS: Services Management and 2025 Intro to Video

3. 🤔 EVENT: AI FRIDAY EVENTS DAY - 3 Dedicated AI+Product Sessions

STUDY WITH JAY: Who needs keyboards when you’ve got brainwaves?

🗒️ Each week I share what I’m studying, with the world. This week I’m studying The Brain Computer Interface Platform Revolution, and paid members can DM me to access my notebook here.

The BCI SaaS Gold Rush has begun

I’ll be honest, this has been one of the hardest newsletter topics to research and write. 

Bringing a product mindset to brain computer interfaces seemed like an exciting product opportunity landscape, but when you start pushing hard on finding verifiable sources, it becomes very challenging.

However, I hope you’ll enjoy the opportunities I’ve uncovered below, which in summary is best positioned as this… AI/ML and BCI will come together to give us revolutionary new ways to interact with our computers, and all of that opportunity begins now, in the software space.

Once we get healthy, approved and validated hardware, an entire new market of SaaS will open up.

BCI is Brain-Computing Interface - yep hooking your noggin up to a computer. While everyone's obsessed with the AI and BCI hardware race, I've spotted something very interesting in the software layer.

After spending three weeks deep in developer documentation and chatting with engineering teams, I've seen a pattern that most market watchers are missing. Sure, Grand View Research's latest market analysis gives us the big numbers - $1.9 billion market value, headed to $5.1 billion by 2030. But the real story lies in where this growth is coming from.

Also, Palantir possibly getting friendly with Blackrock Neurotech signals big tech's serious interest in BCI software platforms. Their focus on developing cloud infrastructure for neural data processing validates the growing SaaS opportunity.

But what could this mean? Well let me take you to 2035 and then let’s come back to the current state.

Emma in 2035

At 7:00 AM, Emma awakens as her smart home system gently adjusts the lighting and temperature, responding to her brain’s natural waking patterns detected by her non-invasive Brain-Computer Interface (BCI) headband. This device monitors her sleep cycles, ensuring she wakes at an optimal time, feeling refreshed.

During her commute, Emma reviews emails and schedules meetings using her BCI-enabled augmented reality glasses. By focusing on icons, she can compose messages and set appointments, streamlining her workflow without physical devices.

At the office, Emma collaborates with colleagues through a BCI-integrated platform that allows for seamless idea sharing and brainstorming. This technology enhances team productivity by enabling direct thought communication, reducing misunderstandings and increasing efficiency.

Midday, Emma’s BCI alerts her to elevated stress levels. She initiates a guided meditation session through her neural interface, which helps regulate her breathing and heart rate, promoting relaxation. This proactive approach to mental health is facilitated by continuous monitoring of neural signals.

In the evening, Emma engages in a virtual reality game controlled entirely by her thoughts. The immersive experience adapts in real-time to her emotional responses, providing a personalized entertainment experience that was unimaginable a decade earlier.

Before bed, Emma decides to learn a new language. Her BCI connects to an educational platform that stimulates specific brain regions associated with language acquisition, accelerating her learning process and making it more intuitive.

So, what’s making Emma’s day a possibility?

Read more

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Here’s what I’m covering this week

1. 🗒️ STUDY WITH JAY: Biomimicry in Design: Nature-Inspired Innovation

2. 🎧 AUDIO STUDY SUMMARY: 21 minutes

3. 🎧 PODCAST: EP64 The Psychology of Business Agility

4. 🤔 EVENT: 2 new live events this week

5. 📝 COMMUNITY ARTICLE: Stockholm Syndrome with Work: When Your Job Takes You Hostage

6. 👉 OPEN TO WORK

STUDY WITH JAY: Biomimicry in Design

What do Amazon, Netflix and squirrels have in common?

🗒️ Each week I share what I’m studying, with the world. This week I’m studying Biomimicry in Design, and paid members can request access to my notebook here.

"Mate, Your Product Strategy Might Need Some Gecko Feet"

Right then, there I was in my office last Tuesday, proper distracted by this cheeky gecko on my window. As you do. While we product folks were all wrapped up in our fancy methodologies and sprint planning, this little master of gravity got me thinking - nature's been running the world's most successful R&D lab, and here's the brilliant bit: she's happy to share her code base with us.

Crikey, talk about a humbling moment.

The Billion-Year Head Start

We product folks pride ourselves on our agile methodologies and innovative solutions. Yet here's something to consider with your morning coffee: nature's been perfecting these practices for 3.8 billion years. That's one impressive sprint backlog!

Take that gecko on my window. It uses millions of tiny hairs creating something called van der Waals forces - physics so elegant that scientists still marvel at its simplicity and effectiveness. [^1]

Mother Nature: The Ultimate Product Mentor

Let me share this week's discoveries, about resilient systems in nature. For any product leaders thinking "Jay's gone full David Attenborough," stick with me - this will transform how you think about product strategy.

The Fire-Tested Framework

Organisms thriving in fire-prone environments serve as brilliant strategists, employing three approaches that would make any product architect envious:

1. Full-spectrum security: They develop general resilience, creating robust architectures that handle both today's challenges and tomorrow's unknowns. Entropic Materials applies this principle in their self-degrading plastics, mimicking protective chaperone proteins. [^2]

2. Built-in redundancy: Nature champions multiple backup systems. Consider how plants develop complex root networks. When did you last review your system's redundancy plans?

3. Sacrificial systems: Think of it as strategic feature deprecation - letting go of one component to protect the core product's integrity.

Nature's Resource Management Masterclass

Right then, before we dive into more tech examples, let's talk about how nature handles its resources. And trust me, this is where it gets properly interesting.

The Squirrel Economy

Ever watched a squirrel during autumn? These little fellows make your typical ERP system look primitive. They'll gather thousands of nuts, distribute them across hundreds of locations, and somehow remember where about 90% of them are buried. It's like watching a master class in inventory management and distributed systems.

Here's what product leaders can pinch from our bushy-tailed mates:

1. Distributed Resource Management

   • Store resources close to where they'll be needed

   • Create multiple backup locations

   • Build in redundancy for critical resources
     Real-world example: Amazon's distribution center strategy mirrors this approach, placing inventory strategically near demand centers.

2. Seasonal Planning
   Just as squirrels know when to start gathering for winter, successful products anticipate and prepare for changing conditions. Take Netflix's content strategy - they're constantly gathering and distributing new content, adjusting their library based on predicted viewing patterns.

The Bamboo Bootstrap

Here's another brilliant bit of natural wisdom. Bamboo might look like it's growing slowly for ages, but it's actually building an extensive root system. Then - boom! It can grow up to 91cm in a single day (much like the last 25 story points on last day of the sprint?).

Sound familiar? It's the same pattern successful products use:

• Build robust infrastructure first

• Create strong foundations

• Scale rapidly when conditions are right

Nature's Just-in-Time Manufacturing

Consider how a spider builds its web:

• Uses exactly the right amount of silk

• Creates structures that are both strong and efficient

• Repairs and recycles materials constantly

This isn't just clever - it's genius level resource optimization.

The M4 Robot: Nature's Engineering Masterpiece

Let me introduce you to the M4 robot - or as the technical folks call it, the "multimodal mobility morphobot." (Good luck saying that three times fast!)

Nature's Swiss Army Knife

The M4 excels at flying, rolling, crawling, and tumbling - and that's just the beginning. Its real genius lies in how it chooses between these abilities.

Consider a sea lion: graceful swimmer in water, adaptable waddler on land. Or watch meerkats: swift runners on all fours one moment, alert sentinels standing tall the next.

The M4 embodies this adaptability. Each of its four limbs transforms for different situations:

• Wheels for efficient ground travel

• Legs for rough terrain navigation

• Thrusters for aerial maneuvers

Engineering Brilliance

The M4 replicates both animal forms and intelligence. Its sensors and onboard computers enable:

• Terrain analysis (like a mountain goat evaluating its next leap)

• Energy-efficient movement selection (matching animals' natural conservation instincts)

• Seamless mode transitions (as smooth as a bird switching from walking to flight)

Watch it in action: On flat ground, it rolls efficiently. Encountering an obstacle? It takes flight, then returns to rolling once clear. Facing a steep slope? It combines movement types for optimal performance.

Your Product Strategy Connection

Let's connect this to your product development:

1. Adaptive Design
   The M4's morphing abilities mirror how your products should adapt to user needs. Consider how your interfaces could flex for different contexts, or how your architecture might scale under varying demands.

2. Energy Efficiency
   The M4's movement optimization offers lessons in resource management. Time to audit your product's resource usage?

3. Intelligent Transitions
   Study the M4's seamless mode switching. How smooth are your product's state transitions and user journey handoffs?

Here's something to make you smile - and think. I've translated Mother Nature's human development project into proper product management speak. The results? Eye-opening...

MOTHER NATURE'S PRODUCT ROADMAP

Human Evolution Enhancement Project v2024

Status: Thriving (3.8 billion years of continuous deployment)

Product Owner: Mother Nature
Scrum Master: Natural Selection
Key Stakeholder: Humanity (actively participating)

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Here’s what I’m covering this week

1. 🗒️ STUDY WITH JAY: Product Management in the Quantum Age

2. 🎧 PODCAST: Challenging the Status Quo in CRO

3. 🤔 LIVE EVENTS NEXT WEEK

4. 📝 COMMUNITY ARTICLE: Have You Learned Nothing From Your Retros?

5. 👉 OPEN TO WORK

STUDY WITH JAY: Quantum Computing's PM Challenge

🗒️ Each week I share what I’m studying, with the world. This week I’m studying Quantum Computing, and paid subscribers can request access to my shared notebook here.

Here’s what I’m going to cover…

• The truth about quantum product development

• Why most product playbooks fail in quantum environments

• Real stories from PMs tackling quantum projects

• Plus a framework for managing quantum teams that actually works

The Morning My Product Brain Broke

5:43 AM. Saturday. I'm at home, scrolling through research papers because sleep is apparently optional. My awesome geisha coffee hasn't kicked in yet when I stumble across a quantum computing paper that makes me spill my geisha all over my laptop.

(At least it was a quantum spillage - the coffee existed in both a spilled and unspilled state until I observed it. Physics humor, anyone? No? Really? Moving on...)

The paper revealed something fascinating: companies are already shipping quantum products. 

• Not proof of concepts! 

• Not lab experiments! 

• Real, proper, revenue-generating quantum solutions!

It's All Gone a Bit Weird, Hasn't It?

Remember when quantum computing was just that thing physicists talked about at conferences? Recent research shows quantum technology has snuck out of the lab while we weren't looking (or too busy looking at AI).

Here's what's actually happening, whilst we’re all focusing on AI ethics…

In Financial Services

Picture this: A trading floor in Manhattan. Screens everywhere. Traders doing their trader things. But in the background, quantum algorithms crunch through portfolio optimizations that would make classical computers cry.

In Drug Discovery

Studies in molecular modeling show quantum computers simulating chemical reactions in hours that would take classical computers centuries. That new cancer drug? It might come from a quantum computer.

In Supply Chain

Remember that chip shortage that made it impossible to buy a PS5? New quantum optimization techniques could help prevent the next one.

The Product Manager's Quantum Crisis

Last week, my mate Sarah (a seasoned PM at a fintech) messaged me at midnight. "Jay," she said (the no “Hi” gave it away as a serious message), "my CEO just announced we're building a quantum division. I've got six months to deliver something. Help."

Blimey. Where do you even start?

Why Your PM Toolkit Just Exploded

According to groundbreaking research in quantum software development, traditional product management tools fall apart in quantum environments. Here's why:

1. The Observer Effect (No, Really)

In classical software, you can monitor your system without affecting it. But in quantum? Recent studies show that observing your quantum system literally changes its behavior.

Imagine trying to run A/B tests when the act of measuring your results affects the outcome. It's like Schrödinger's Product Analytics - your metrics exist in multiple states until you look at them.

You with me? No? I’m barely with me too, so, here’s another example…

Imagine you have a row of toy soldiers (these are ions in the experiment) lined up in a very chilly place (a cryogenic quantum register). Each soldier is supposed to follow only their own orders, but sometimes they hear the instructions meant for their neighbour and get confused (this is called crosstalk). This confusion isn’t helpful for the team, so scientists are trying to stop it.

To give each soldier their orders, scientists use tiny laser beams—like laser pointers focused precisely on each soldier. But sometimes, these lasers spread out a little and accidentally give neighbouring soldiers mixed signals. To fix this, the scientists came up with a clever trick: they shine an extra light beam at each soldier’s neighbour, which cancels out the confusing signals. It’s a bit like playing a sound that cancels out background noise, letting each soldier only hear the orders meant for them.

The scientists tested this by seeing how well each soldier could follow orders after using this trick. They found that with the right setup, they could almost completely get rid of the “mixed signal” problem, and each soldier behaved almost perfectly! This means the soldiers can now work together better, and the scientists are even trying other tricks to make sure their commands don’t get jumbled in the future.

2. The Two-World Problem

Here's something wild from IBM's quantum research team: every quantum product actually needs two parallel development tracks:

• The quantum implementation

• A classical simulation of the quantum implementation

It's like building a rocket while simultaneously maintaining a perfect video game version of that rocket. Both are essential. Both need different teams. Both need different tools.

3. Error Rates: Your New Best Friend

Remember how we obsess over five nines of reliability? New research shows quantum systems follow different rules entirely. Some quantum algorithms actually perform better with certain types of errors. Mad, right?

The Quantum PM's Survival Guide

After consoling Sarah, I've put together what I'm calling the Quantum PM's Survival Guide. Based on empirical studies and, frankly, a lot of trial and error:

1. Embrace the Hybrid Approach

Research published in Nature shows the most successful quantum products aren't pure quantum plays. They're hybrid solutions that cleverly combine classical and quantum approaches.

For example, when JP Morgan Chase's quantum team optimizes portfolios, they use:

• Classical computers for data preparation and constraint definition

• Quantum algorithms for exploring the massive space of possible portfolio combinations

• Classical systems again for finalizing and presenting results

Each mode for its proper purpose. No one teleports to their kitchen for a snack.

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Here’s what I’m covering this week

1. 🗒️ STUDY WITH JAY: Matter and IoT (and learnings for SaaS)

2. 🎧 PODCAST: Challenging the status quo in CRO

STUDY WITH JAY: Is Matter the Glue or the Mess of IoT?

“My window sensors still aren't on speaking terms!” - Me

🗒️ Each week I share what I’m studying, with the world. This week I’m studying Matter and IoT. Paid subscribers can DM me for access to my notebook here.

Hey there! 👋

I've been neck-deep in smart home devices lately, and let me tell you - it's both exciting and frustrating. Last week, I spent hours trying to get my smart lights to talk to my thermostat (spoiler: they still aren't on speaking terms). This got me thinking about the bigger picture of IoT and where we're headed.

So, this week’s newsletter is packed with information about the smart home and IoT landscapes which continue to expand making interoperable solutions becoming critical.

And I won’t lie, this took me down memory lane. You see back in 2015, I was contracting for Telstra (AT&T for Australia), and I was dedicated to their smart home product offering. It was the honeymoon period of IoT, and as a product manager with a software background, it exposed me to an incredible world of hardware, firmware and industrial design principles that have stuck with. 

One of my most memorable moments was, during a contextual inquiry, seeing how a household's tech decisions are made. The husband, who’d just spent $300 on a bookshelf based camera that he was so excited to unbox, was so excited. He unboxed like he’d birthed it. He placed it on the shelf like a proud father. Within 0.002 seconds of it landing and disturbing the dust, a massive “NOPE! NOT HAVING IT!” belted from across the room.

You see wifey had just spent $10k redecorating the lounge, and the industrial design of this futuristic curvy black plastic tech with it’s dangling black twisted plastic coated cord, just didn’t match the Hampton’s inspired decor. That day I was strongly reminded that industrial design research and testing needs to be with all the persona’s whose lives it will intrude!

Anyway, this week I’ll explore Matter—the emerging standard for device interoperability—and how smart product management can make or break your IoT strategy. 

I’ll also touch on:

• Security

• Intermittent device challenges

• Lessons for SaaS

• Unresolved issues that product leaders need to keep in mind

If you’re a CPO, CFO, or CTO, this could offer some valuable insights into where IoT is heading and how your teams can stay ahead of the curve. Even if you’re not in the IoT game, I’ll be connecting learning from IoT over to SaaS for you.

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Here’s what I’m covering this week

1. 🗒️ STUDY WITH JAY: AI Ethics

2. 🎧 PODCAST: EP62 Ancient wisdom for modern leadership

3. 🤔 EVENT: Breaking Blockchain Barriers: How Chain Abstraction is Shaping the Future of Web3

4. 🎓 MICRO-COURSE: Create Your Own Daily Industry News Podcast

5. 📝 COMMUNITY ARTICLE: Three Reasons to Insist on Outcome-Based Planning

6. 👉 OPEN TO WORK

STUDY WITH JAY: AI Ethics

“AI won’t take over the world, but it might just politely suggest you refinance your mortgage—whether you need to or not.” – Sir Algorithm IV, Duke of Data

🗒️ Each week I share what I’m studying, with the world. This week I’m studying AI Ethics, and you can find my notebook here (DM me for access requests).

Study Summary…

Level up your AI ETHICS knowledge in under 15minutes, with the audio summary below (courtesy of NotebookLM), or keep scrolling to read my thoughts, in depth:

Jay’s thoughts…

We’ve all seen the films where AI decides to take over the world, but let’s be honest—real AI’s more likely to give you a dodgy mortgage rate than a robot apocalypse. The reality of AI is a bit more sneaky and, frankly, a lot more important. AI’s now handling everything from your bank loans to diagnosing illnesses, so it’s high time we ask some big ethical questions. Like, how do we make sure AI isn’t a bit of a dick, reinforcing the bad habits of the past?

Grab a cuppa, and let’s wade through the moral swamp of AI ethics, shall we?

The Real Worry: It’s the Quiet Ones You’ve Got to Watch

Forget the terrifying robot revolutions—AI’s ethical nightmares come in the quiet, subtle forms of good ol’ inequality. Algorithms are perfectly capable of recreating society’s worst habits, especially when it comes to jobs, loans, or healthcare. Picture this: you get denied a loan not because you’re bad with money but because some algorithm’s decided you’re too similar to someone who is.

This is why we need frameworks like the White House’s AI Bill of Rights. No, it’s not a superhero movie, but it’s just as dramatic—ensuring AI gets tested like a new medicine before being released to the public. And, of course, there’s an ethical “kill switch” in case things go sideways, like in those robot uprising films… oh wait, that’s not what we’re worried about, right?

AI That’s Safe and Sound—In Theory

The White House reckons AI systems need to be safe and effective. Sounds simple enough, right? Except when it comes to AI, “safe” gets a bit murky. The goal here is to make sure AI is tested within an inch of its life before it’s let loose on the world. You wouldn’t want a healthcare algorithm making assumptions about you based on dodgy data, would you? That’s what happened when an AI system gave Black patients lower risk scores, resulting in sub-par treatment. Not cool.

But making sure AI plays nicely isn’t the only problem. The algorithmic discrimination protections are there to ensure AI isn’t just another tool for inequality. It’s about fairness for everyone, not just the tech crews who built it.

The Battle of the Biases: The Algorithm Strikes Back

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