Best of LinkedIn: Digital Products & Services CW 48/ 49

00:00:00: This episode is provided by Thomas Allgeier and Frennis, based on the most relevant LinkedIn posts about digital products and services in calendar weeks forty-eight and forty-nine.

00:00:10: Frennis is a B-to-B market research company helping enterprises gain the market, customer, and competitive insights needed to drive customer-centric and cost-efficient product development.

00:00:21: Welcome back to the Deep Dive.

00:00:24: Today we're distilling some really critical shifts we're seeing in the world of digital products and services.

00:00:29: I mean, looking at the industry conversation over the last couple of weeks, one thing is just crystal clear.

00:00:34: What's that?

00:00:35: The product discipline is, well, it's finally growing up.

00:00:38: It's moving past just shipping features for the sake of it.

00:00:41: It

00:00:41: really is.

00:00:42: That's the core finding, you know.

00:00:43: Leaders seem to be done with the vanity metrics, the output, the feature velocity.

00:00:48: The whole focus has pivoted and pretty intensely toward foundational strength.

00:00:53: Foundational strength.

00:00:54: What do you mean by that exactly?

00:00:55: I mean, defining and aligning the operating model.

00:00:58: for one and prioritizing rock solid customer evidence making sure the technical platform is actually ready to scale.

00:01:05: the market is demanding provable outcomes and well that's changing everything.

00:01:10: okay let's unpack that this whole mandate for outcomes.

00:01:13: we can start there with our first theme strategy roadmaps and this outcomes mandate.

00:01:18: we've all seen that classic flawed roadmap

00:01:21: right.

00:01:21: oh yeah The one that's just a list of features nobody really asked for, prioritized by politics.

00:01:26: Exactly.

00:01:27: And the chatter online confirms that this is a systemic problem.

00:01:30: It's a massive drag on success.

00:01:33: The real tension seems to be that most roadmaps are just designed to be reactive.

00:01:37: They

00:01:37: are.

00:01:38: They serve internal stakeholders instead of driving a strategic vision.

00:01:41: There was a great post from Jasmine grew a gray on this.

00:01:44: She observed that most roadmaps fail because they are reactive.

00:01:47: The focus shifts from the product's actual direction to, and this is her quote, who you're trying to please.

00:01:54: The system itself is often set up, maybe unintentionally, to pull PMs into that reactive whirlpool.

00:02:00: You know, urgent fixes, sales demands.

00:02:02: So you're just stuck in that mode.

00:02:04: You're never strategic.

00:02:05: Never.

00:02:06: The conclusion is you have to retire that kind of roadmap.

00:02:10: You have to set a clear North Star and then really concentrate your resources on outcome driven bets.

00:02:16: Things that will actually move the needle.

00:02:18: That

00:02:18: transition sounds great in theory, but it immediately brings up the question of ownership.

00:02:23: I mean, how are product leaders supposed to handle this new pressure to deliver huge business results?

00:02:29: Well, that's where the scope of product leadership is expanding.

00:02:32: And sometimes, frankly, unreasonably so.

00:02:36: Sean King highlighted this.

00:02:37: He's seeing product leadership roles that are asked to own these incredibly broad business outcomes.

00:02:43: Like what, for example?

00:02:44: Things like overall policyholder retention for an insurance company, or guest satisfaction across an entire hotel chain.

00:02:51: But the product team's actual responsibility only covers the digital front end.

00:02:56: So just the mobile app or the checkout flow?

00:02:58: Exactly.

00:02:59: So the PMs are being held responsible for, I don't know, operational gaps or bad sales training.

00:03:04: Things completely outside of their control.

00:03:06: Which is not going to work.

00:03:07: No.

00:03:08: He called it product management theater.

00:03:10: The PM is sort of performing the role of an outcome owner, but they don't have the real levers to pull across the business.

00:03:16: So the implication is that digital is just one piece of the puzzle.

00:03:20: product teams have to collaborate way more deeply with ops, sales, support, if they actually want to influence those big results.

00:03:27: Precisely.

00:03:28: Otherwise, the digital product just becomes the scapegoat when the service model itself is broken.

00:03:33: Okay, so that brings us back to strategic clarity.

00:03:36: If roadmaps are just feature lists and feature lists lead to this theater, we need a whole different system for making decisions.

00:03:43: We do.

00:03:44: Sarah Perkins had some really sharp advice on this.

00:03:46: She said, stop presenting roadmaps and start leading strategic dialogues.

00:03:51: I like that.

00:03:51: So it's not about showing a gaunt chart.

00:03:53: No, it's about forcing the hard uncomfortable questions.

00:03:57: The kind of questions that separate the companies that will last from the ones that, you know, won't.

00:04:02: She suggested this customer trust audit.

00:04:04: Right.

00:04:05: Asking what single product failure would destroy customer trust overnight?

00:04:10: A question like that just cuts through all the tactical noise.

00:04:13: Yeah.

00:04:13: It forces everyone to focus on fundamental value and risk.

00:04:17: And that focus is what leads to the organizational blueprint, right?

00:04:21: I saw Joachim Torres, a joker, he noted that when we talk about product culture and the product operating model, we're really talking about the same thing.

00:04:30: Yeah, essentially, it's the same critical transformation, the same mindset shift.

00:04:34: you need to get that strategic alignment.

00:04:36: It's a holistic view.

00:04:37: That makes a ton of sense.

00:04:39: The culture is the mindset and the product operating model, the POM, that's the structure that makes it real.

00:04:45: Which is a perfect transition to our second theme, product operating models.

00:04:49: The human and the technical challenge of making all this work.

00:04:52: So where do we start with the POM?

00:04:54: Well, if we zoom out, the POM is where the strategy hits the technical reality.

00:04:59: John Cutler might a point on this that I think is often overlooked.

00:05:01: He said at any real scale all this talk of POM transformation and empowerment is and I'm quoting hollow propaganda without a serious focus on two things.

00:05:10: Okay, what are they?

00:05:11: architecture and a platform strategy?

00:05:13: That's a strong statement.

00:05:15: Why is architecture so critical to the operating model?

00:05:18: Because the model demands speed and autonomy.

00:05:22: I mean, if every team trying to ship a feature gets stuck in dependency gridlock or tangle deployment pipelines or massive tech debt.

00:05:30: Then, empowerment is just a word on a slide.

00:05:32: It's

00:05:32: meaningless.

00:05:33: The architecture has to enable independent teams.

00:05:36: Otherwise, the POM is just a fancy deck.

00:05:39: That really clarifies what the organization is actually creating.

00:05:42: Luca Mahoney put it well.

00:05:43: He said the core work product isn't just a piece of software.

00:05:46: Right.

00:05:46: It's the orchestration of three things.

00:05:48: People.

00:05:50: Process.

00:05:51: and technology.

00:05:52: All of it designed for maximum system performance and you know the best customer experience.

00:05:57: The whole system is the product.

00:05:58: Okay so the system mechanics are important but the implementation that's all human isn't it?

00:06:03: A hundred percent.

00:06:04: Melissa Perry shared that POM implementations fail way less often because of bad frameworks and way more often because of poor change management.

00:06:11: So you can have the perfect diagram on the wall, but if you haven't won over the people who have to actually live with it.

00:06:17: It's

00:06:17: stalled out, exactly.

00:06:19: Transformation is a human process.

00:06:21: It takes influence, stakeholder management.

00:06:23: You have to navigate the politics.

00:06:25: I saw a post from Kasim Harani about that, the politics of it.

00:06:28: Yeah, he was very real about it.

00:06:29: He said real world product management is knowing when to apply the framework.

00:06:34: You know, when to say no, and when you just have to say yes to a high-ranking stakeholder, the hippo.

00:06:40: The highest-paid person's opinion.

00:06:43: Sometimes that yes is a necessary political move.

00:06:45: It buys you the capital for the long term.

00:06:48: It's a tricky balance that one strategic yes on a less-than-ideal request could buy you a dozen strategic no's down the line.

00:06:55: It's all about judgment.

00:06:57: It is.

00:06:58: And speaking of judgment, the POM has to be designed to handle different kinds of demand.

00:07:03: Shrathikalapu made a great point about needing two distinct intake pathways as you scale.

00:07:08: A dual intake model.

00:07:09: Tell me more about that.

00:07:10: Sounds like a practical way to balance everything.

00:07:12: Think

00:07:12: of it like a hospital.

00:07:13: You need your scheduled surgeries, but you also need a functioning ER.

00:07:17: Path one is the product engine.

00:07:19: It's systematic, evidence-led, driving the core roadmap.

00:07:22: And path two.

00:07:23: Path two is for strategic and urgent demand.

00:07:26: This handles the time sensitive, off the politically charged request from the CEO, or from sales, or finance.

00:07:32: And the trick isn't just having the two paths, but managing in the flow, I assume.

00:07:36: That's the key.

00:07:38: You have to process paths too quickly.

00:07:40: We're talking rapid assessment cycles, like two to five days, not two months.

00:07:44: And you offer smart options.

00:07:46: Like what?

00:07:46: Like we can't build that full feature right now, but we can run a pilot.

00:07:50: Or here's a third-party tool we can use as a shortcut.

00:07:53: It protects the main roadmap while still respecting that real urgency.

00:07:57: It requires PMs who are commercially fluent.

00:08:00: That ability to triage and find alternatives is a perfect bridge to our third theme.

00:08:05: Customer discovery, evidence, and just building the right thing.

00:08:09: Because no matter how great your POM is, if you're building the wrong product, the whole thing fails.

00:08:13: Yeah,

00:08:13: Peter Drucker's quote, which Kimmy O'Doreen shared again recently, it still holds up.

00:08:17: Solving the right customer problem is so much more important than building the product right.

00:08:21: It all comes down to speed to learn, iterating until your customers make it painfully obvious that you've finally nailed it.

00:08:29: But that speed is also a trap, right?

00:08:30: Especially now, with AI making everything faster.

00:08:34: Well, Anna Pintar put out a clear warning about this.

00:08:38: AI makes prototyping incredibly fast, but that velocity can be really deceptive.

00:08:43: A polished, validated prototype.

00:08:46: It's not proof of demand.

00:08:47: It just proves people liked what they saw.

00:08:49: Exactly.

00:08:50: It doesn't prove they'll change their behavior.

00:08:52: Or, more importantly, that they will pay for it.

00:08:56: Her example was so good.

00:08:57: The one about the product with four hundred registered users, but only fifteen who are actually paying.

00:09:02: That's the one.

00:09:03: That tells you there's a massive gap between interest and realized value.

00:09:07: And to close that gap, you have to do real detective work.

00:09:10: You can't just listen to the fifteen people who converted.

00:09:12: No.

00:09:13: You have to talk to both.

00:09:14: The converters and the non-converters.

00:09:16: That's how you isolate the pattern, figure out who the product is really for and what's stopping the other three hundred and eighty-five people.

00:09:23: That's modern product discovery.

00:09:24: So if discovery needs to be this continuous thing, how do the best companies actually institutionalize it?

00:09:31: How do you make it part of the daily rhythm?

00:09:34: Chantelbatana's analysis of whys was a great example.

00:09:37: They basically engineered a culture where empathy plus evidence isn't a poster.

00:09:42: It's infrastructure.

00:09:44: So discovery isn't just a phase at the beginning.

00:09:47: No, it runs in parallel with delivery from day one.

00:09:50: They do a couple of things to make that happen.

00:09:52: They embed design researchers to continuously test hypotheses.

00:09:57: And critically, they have product compliance partners co-designing from the start.

00:10:01: So you know if an idea is safe and shippable before it even gets to the engineering backlog.

00:10:06: Exactly.

00:10:06: It's continuous learning baked right into the pipeline.

00:10:09: That continuous evidence loop feels more important than ever.

00:10:11: as we get into our final theme.

00:10:13: AI's impact on design and the new PM skill set.

00:10:16: Because the speed AI brings is forcing a conversation about what quality even means anymore.

00:10:21: It is.

00:10:22: Richard F. voiced a concern that I think a lot of people are feeling.

00:10:24: This AI hype cycle is leading to a market just flow with half baked kind of boring rushed products.

00:10:31: They lack creativity.

00:10:32: And attention to detail.

00:10:34: That pursuit of speed is sacrificing originality.

00:10:38: My jesuit be actually called this UX convergent evolution.

00:10:41: I've seen that term.

00:10:42: It's where all the interfaces start looking the same because they're all optimizing for familiarity.

00:10:49: Which, ironically, makes them totally forgettable.

00:10:52: But the really radical future, which Myrick Neisenbaum envisioned, is something called generative product design.

00:10:59: Okay, what is that?

00:11:00: Imagine LLM that uses your brand's personality and your design system to create a hyper-personalized product view for each user.

00:11:08: Yeah.

00:11:08: Instantly.

00:11:09: Based on their specific context, their needs, their history, we'd move way beyond static interfaces.

00:11:14: Wow.

00:11:15: That is a massive shift.

00:11:16: But to get there, the PM's own foundation has to be rock solid.

00:11:20: Dr.

00:11:21: Else Vandenberg had a really powerful take on this.

00:11:23: Oh,

00:11:23: I saw that.

00:11:23: She said LMS are powerful amplifiers.

00:11:25: They just amplify whatever you feed them.

00:11:27: So if you feed them shallow thinking,

00:11:28: you get poor results just at a massive scale.

00:11:31: You absolutely cannot skip the foundation, knowing your audience, grounding the pain points.

00:11:36: Garbage in, garbage out just faster and bigger than ever.

00:11:39: Pretty

00:11:40: much.

00:11:40: Akash Gupta broke this down really well.

00:11:43: He argued that successful AI PMs need expertise on three different levels.

00:11:47: Which are?

00:11:48: First, the foundation so AI and ML concepts, prompt engineering.

00:11:51: Second is the PM value layer, things like evaluation, cost optimization, choice analysis.

00:11:57: And third is strategy.

00:11:58: That PM value layer seems like the real differentiator.

00:12:01: It is.

00:12:02: The scarcest skill in AI right now is PMs who actually understand evaluation, who know how to test, iterate and figure out if the model is truly providing customer value.

00:12:12: It's hard work.

00:12:12: Which brings us back to judgment.

00:12:14: If AI can do so much of the execution, what's left for the human PM?

00:12:18: Rochelle Valentino framed it perfectly.

00:12:20: The question isn't, will AI replace me?

00:12:22: It's, how do I partner with AI to make better product decisions?

00:12:26: The AI is the co-pilot.

00:12:27: But judgment is the driver.

00:12:29: AI can cluster feedback.

00:12:30: It can draft a spec outline.

00:12:32: But it can't prioritize conflicting stakeholder needs.

00:12:35: It can't read the nuance of human emotion or organizational politics.

00:12:39: So how do you operationalize that?

00:12:41: How do you pair human judgment with AI speed?

00:12:44: Harsha Sravatsa proposed a really fascinating idea, the LLM Council.

00:12:49: This is such a cool concept.

00:12:51: It's basically an AI board of advisors for your product.

00:12:54: You use different AI personas, maybe one inspired by Marty Kagan for strategy, another by Melissa Perry for discovery to review your PRD.

00:13:02: And the Council gives you feedback before you even start sprint planning.

00:13:05: Exactly.

00:13:06: It synthesizes feedback, flags critical gaps.

00:13:09: You're institutionalizing critical thinking, but using technology to do

00:13:13: it.

00:13:14: That is a perfect way to think about how product management has to evolve.

00:13:17: It's about using sophisticated tools to enhance our own strategy and judgment, not to replace it.

00:13:23: So let's try to summarize the big shifts from the last two weeks.

00:13:25: There's a clear mandate to pivot to outcome-based product operating models, but those have to be grounded in a robust architecture and smart intake pathways.

00:13:34: And we learned that deep behavioral customer evidence, not just fast prototypes, is the only real cure for that dangerous feature.

00:13:40: velocity.

00:13:41: And finally, AI integration.

00:13:44: It demands that we prioritize strategic judgment and evaluation skills over just, you know, technical shortcuts.

00:13:50: And if I can add one final thought, looking at the bigger picture.

00:13:54: The evolution of product operations is the next strategic engine here.

00:13:58: How so?

00:13:59: Well, both Graham Reed and Aidan Zipor pointed this out.

00:14:02: Product ops isn't just an admin afterthought anymore.

00:14:05: As AI speeds up engineering and design, the bottlenecks move.

00:14:09: They shift to organizational alignment, governance, process.

00:14:13: The exact problems ProductOps is designed to solve.

00:14:16: Exactly.

00:14:17: It's becoming the central nervous system for the modern product org.

00:14:20: It's solving the crucial problems that, before, nobody was really solving properly.

00:14:24: If you enjoyed this episode, new episodes drop every two weeks.

00:14:27: Also check out our other editions on ICT and tech, artificial intelligence, cloud, sustainability and green ICT, defense tech and health tech.

00:14:35: Thanks for diving deep with us.

00:14:36: We'll see you next time.