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Best of LinkedIn: Digital Products & Services CW 08/ 09 · Best of LinkedIn: Digital Transformation & Tech

• 0:00
  Speaker 1: This episode is provided by Thomas Allgaier and Frennus, based on the most relevant LinkedIn posts about digital products in services.
• 0:07
  Speaker 1: In calendar weeks eight and nine, Frenness is a B to B market research company helping enterprises gain the market customer and competitive insights needed product development.
• 0:20
  Speaker 0: And welcome to the deep dive, everyone!
• 0:21
  Speaker 0: I'm really looking forward to getting into this.
• 0:23
  Speaker 1: Yeah today we are serving up a well basically a focused smart shortcut To exactly what's happening in the ICT and tech industry right now.
• 0:34
  Speaker 1: We've been scouring the top of digital products and services trends seen across The professional landscape over the past two weeks.
• 0:40
  Speaker 0: Right...and mission here is pretty simple We want to cut through the corporate fluff and deliver the actionable insights you actually need, To understand how product management is fundamentally shifting in twenty-twenty six.
• 0:51
  Speaker 1: Because it's shifting fast!
• 0:53
  Speaker 0: It's incredibly fast If your building digital products right now The ground under feet are actively shifting.
• 1:00
  Speaker 0: we're seeing a massive evolution of AI integrated into daily workflows A radical rethinking of what a product operating model actually means and entirely new survival skills required for products careers.
• 1:13
  Speaker 1: Yeah, so we are going to distill the most critical takeaways from.
• 1:20
  Speaker 1: Okay, let's unpack this with our first major theme because we have to talk about AI and product work.
• 1:25
  Speaker 1: Yeah And to be clear We are moving way beyond the hype cycle here.
• 1:29
  Speaker 0: Oh absolutely
• 1:30
  Speaker 1: like.
• 1:30
  Speaker 1: AI is no longer just a trend or A fun chat bot you play with on a second monitor.
• 1:35
  Speaker 1: It has been aggressively integrated into the core tool chain of how software is built
• 1:42
  Speaker 0: Staggering.
• 1:44
  Speaker 0: Powered her and actually shared a phenomenal insight recently regarding Anthropics' new tools, he highlighted this incredible statistic that Anthropic's plug-ins wiped two hundred eighty five billion dollars with the B from legacy software stocks in a single day.
• 1:58
  Speaker 1: Wait!
• 1:58
  Speaker 1: A quarter of a trillion dollars?
• 2:01
  Speaker 1: Just for plugins.
• 2:02
  Speaker 1: How does even happen?
• 2:03
  Speaker 0: Well because these new tool bypass traditional software ecosystems entirely.
• 2:08
  Speaker 0: they just sit right there on your sidebar doing their work natively.
• 2:11
  Speaker 0: Poway broke down the crucial difference in how these models operate now, and it's worth visualizing.
• 2:17
  Speaker 0: You have chat which is what most of us are used to.
• 2:20
  Speaker 0: you know conversations quick answers drafting an email.
• 2:23
  Speaker 0: but then you have co-work.
• 2:24
  Speaker 0: this is autonomous knowledge work.
• 2:26
  Speaker 0: a co-working agent can spawn parallel sub agents to tackle different parts of a project And they actually read and write real files In your environment and CLI
• 2:38
  Speaker 1: meaning command line interface, right?
• 2:40
  Speaker 1: So we aren't talking about a browser window anymore.
• 2:43
  Speaker 1: Precisely!
• 2:43
  Speaker 0: It has direct access to the computer's file system.
• 2:46
  Speaker 0: it can navigate directories execute scripts and change code autonomously.
• 2:50
  Speaker 1: That is a massive leap in capability I mean fundamentally changes the role of a product manager.
• 2:56
  Speaker 1: In fact Kosh Gupta argued recently that product managers shouldn't be relying on separate prototyping environments any more.
• 3:02
  Speaker 1: With tools like Claude Code, PMs should be building prototypes directly in the code base using actual production components.
• 3:10
  Speaker 0: Which used to be strictly engineering territory?
• 3:12
  Speaker 0: Exactly
• 3:13
  Speaker 1: but The barrier entry has plummeted and if you want the financial proof of the value teams are extracting from this Akash noted that Claude code went from zero To two point.
• 3:23
  Speaker 1: five billion dollars an annual recurring revenue In just nine months.
• 3:28
  Speaker 0: That adoption curve is almost vertical.
• 3:30
  Speaker 1: it really is.
• 3:31
  Speaker 1: There was also a fascinating case study shared by Peter Yang about a professional named Carl, who has basically built a custom brain to run his day.
• 3:39
  Speaker 1: Carl connects Cloud Code directly to Google Workspace to prep for his meetings hooks it into linear-to-automatically create development tickets and connects at the slack of status outdates.
• 3:49
  Speaker 1: He essentially uses it to create an incredibly powerful personal operating system.
• 3:53
  Speaker 0: But here is the function point with all this.
• 3:56
  Speaker 0: With this kind of immense power readily available The immediate reaction from executive leadership is almost always to shove AI into absolutely everything.
• 4:05
  Speaker 0: Every feature, every screen, every workflow...
• 4:08
  Speaker 1: Oh yeah the classic.
• 4:09
  Speaker 1: just add chat GPT and let's ship it mandate.
• 4:12
  Speaker 0: Yes!
• 4:13
  Speaker 0: And that is a recipe for disaster.
• 4:16
  Speaker 0: Shardul Nayak addressed this brilliantly with a concept he calls framework.
• 4:22
  Speaker 0: He points out that traditional prioritization completely breaks down when AI is involved.
• 4:27
  Speaker 1: because Traditional rice for anyone who hasn't used it recently, he's just scoring a potential feature based on its reach Its impact your confidence in building and the effort It takes.
• 4:35
  Speaker 1: so why does That fail?
• 4:36
  Speaker 1: When we talk about AI?
• 4:38
  Speaker 0: Because The Effort metric in traditional software usually Just means developer hours.
• 4:42
  Speaker 0: once the code Is written it's mostly free to run.
• 4:44
  Speaker 0: But AI models rely on LLM API's large language model interfaces, and those require massive compute power.
• 4:51
  Speaker 1: So every time a user interacts with that feature it costs you money in token usage?
• 4:55
  Speaker 0: Exactly the cost compound!
• 4:57
  Speaker 0: So Sherdouls Framework introduces three specific AI multipliers to the traditional model.
• 5:02
  Speaker 0: First is data quality or DQ because if your internal data is garbage, you're AI feature will be garbage.
• 5:09
  Speaker 0: Second is the AI cost factor AC which forces you to mathematically factor in those ongoing monthly running costs.
• 5:16
  Speaker 0: and third is AI maturity
• 5:19
  Speaker 1: AM.
• 5:19
  Speaker 1: I mentioned that.
• 5:20
  Speaker 1: last one is crucial right now given how fast things move.
• 5:22
  Speaker 0: it acts as a necessary guardrail.
• 5:25
  Speaker 0: It prevents you from building mission-critical features on bleeding edge, experimental tech that might be deprecated next month.
• 5:31
  Speaker 0: What's fascinating here is the real world result.
• 5:33
  Speaker 0: Shardul shared.
• 5:34
  Speaker 0: He used this exact framework with a team where CEO wanted AI everywhere resulting in an immediate backlog of thirty eight different AI features.
• 5:41
  Speaker 0: Wow Yeah, by applying these multipliers they cut that roadmap down from thirty eight to just seven viable features.
• 5:48
  Speaker 0: That ruthless prioritization alone saved the company forty thousand dollars a month in unnecessary API
• 5:53
  Speaker 0: costs.".
• 5:54
  Speaker 1: That is incredible!
• 5:55
  Speaker 1: It really highlights that implementing AI isn't just about the code.
• 5:59
  Speaker 1: it completely exposes the reality of how your company functions.
• 6:03
  Speaker 1: there was a fantastic quote from Jessica Hall at ProductCon London who perfectly captures this.
• 6:08
  Speaker 1: she said AI isn't a portrait mode filter for your business.
• 6:12
  Speaker 1: It's high-definition mirror.
• 6:13
  Speaker 0: That is brilliant way to phrase it.
• 6:15
  Speaker 0: Right!
• 6:16
  Speaker 1: If you have broken organizational structure, massive technical debt or siloed data that different departments won't share... ...AI does not fix those problems.
• 6:25
  Speaker 1: It just reflects them back at you in high definition.
• 6:28
  Speaker 1: You cannot layer AI native speed on top of decades old bureaucratic project governance and expect magical transformation.
• 6:36
  Speaker 0: And if we connect this to the broader market, that mirror extends all the way out how customers even discover your product in first place.
• 6:43
  Speaker 0: Pavel Fabrikontov introduced his concept of The Shadow PM.
• 6:46
  Speaker 0: He argues that AI models, chat GPT Gemini, Perplexity are now essentially acting as unauthorized product managers for you brand
• 6:55
  Speaker 1: Unauthorize PMs.
• 6:57
  Speaker 1: I like that.
• 6:57
  Speaker 0: You didn't hire them, you can't fire them but they are handling the entire pre-selection process for buyers before your marketing funnel even begins.
• 7:05
  Speaker 1: So what does this all mean for The Listener?
• 7:07
  Speaker 1: If you're leading a product team right now why should care about the Shadow PM?
• 7:11
  Speaker 0: You should care because these AI models are framing how differentiation is explained to market.
• 7:17
  Speaker 0: They are setting the buyer's expectations.
• 7:20
  Speaker 0: If the AI cannot effectively crawl your product documentation or understand value proposition, it simply can not recommend you.
• 7:28
  Speaker 0: if nobody on team actively owns that relationship optimizing how these LLMs perceive their products You're losing out a massive segment of market before they ever click.
• 7:37
  Speaker 0: link to website.
• 7:47
  Speaker 1: Like, are we set up to deliver continuous value or just churning out features?
• 7:52
  Speaker 1: Which ties perfectly into our second theme—the shift toward true product operating models.
• 7:57
  Speaker 0: The structure of the organization itself is heavily under the microscope.
• 8:00
  Speaker 0: right now We're seeing a stark divergence between companies that actually operate on a product model and those who use buzzwords.
• 8:08
  Speaker 0: Rachel DeBoer proposed an unforgiving thirty-second test to figure which one your company is.
• 8:14
  Speaker 0: She says you have to look at how teams were funded
• 8:17
  Speaker 1: Not the agile rituals, not the job titles but the actual money.
• 8:20
  Speaker 0: Just the money!
• 8:22
  Speaker 0: If your company funds work by project meaning leadership hands a team A fixed scope?
• 8:27
  Speaker 0: A fixed launch date and a fixed budget?
• 8:29
  Speaker 0: you have NOT adopted a product model period.
• 8:32
  Speaker 0: You simply industrialized project delivery And slapped new label on it.
• 8:37
  Speaker 1: That is such harsh truth for a lot of organizations Because if your funding dictates that success just means shipping code on a specific Tuesday, all of your product strategy goes out the window.
• 8:47
  Speaker 1: Rachel noted that within a modern scale-up you might have different types of teams that need completely different funding structures.
• 8:53
  Speaker 0: Exactly!
• 8:54
  Speaker 0: One size doesn't fit all
• 8:55
  Speaker 1: Right.
• 8:56
  Speaker 1: For example A platform team's whole goal is reducing cognitive load.
• 9:01
  Speaker 1: for the rest engineering organization An exploration team is dealing with high market uncertainty and needs to run rapid cheap experiments.
• 9:09
  Speaker 1: If you apply the exact same rigid project-based funding model to all of them, You are guaranteeing that at least one those teams will be managed.
• 9:17
  Speaker 1: completely wrong.
• 9:19
  Speaker 0: And this funding issue usually stems from a deeper confusion about what a company actually considers its product.
• 9:25
  Speaker 0: Freya H. Finnerty brought up a great point on this.
• 9:28
  Speaker 0: she frequently asks enterprise companies what their products are and they will list things like the iOS app, The Android App or the booking portal.
• 9:36
  Speaker 0: but as she rightly points out A mobile app isn't a product.
• 9:38
  Speaker 0: it's just to delivery channel .The actual product is the guest booking experience.
• 9:43
  Speaker 1: That distinction changes everything about how you build.
• 9:45
  Speaker 1: When you organize your teams around the delivery channels, like having an isolated iOS team and an isolated Android Team.
• 9:52
  Speaker 1: You inevitably end up with inconsistent user experiences and massively duplicated work.
• 9:58
  Speaker 0: precisely Matthew Skelton emphasizes this heavily when talking about organizational design.
• 10:04
  Speaker 0: He advocates for using the principles from Team Topologies, which is essentially a framework for designing team interactions and boundaries.
• 10:11
  Speaker 0: The goal is to create a shared language so that your internal team architecture actually matches the flow of value to the customer rather than matching your internal org chart.
• 10:21
  Speaker 1: Here's where it gets really interesting maps.
• 10:25
  Speaker 1: this entire flow out beautifully with what he calls the value exchange loop.
• 10:30
  Speaker 1: He defines it as a continuous cycle.
• 10:32
  Speaker 1: on one side, you are solving customer problems.
• 10:35
  Speaker 1: that is The Value Delivery.
• 10:37
  Speaker 1: in Exchange.
• 10:38
  Speaker 1: You earn money or engagement from the customer.
• 10:40
  Speaker 1: That Is The Value Capture.
• 10:41
  Speaker 1: Yep and the most critical word In That Entire Concept Is Continuous.
• 10:46
  Speaker 1: A true product operating model never reaches a fixed end date because there are always evolving customer problems to solve.
• 10:52
  Speaker 1: And
• 10:52
  Speaker 0: if you break that loop, If you only focus on delivery without measuring the capture You become a feature factory and Johnny Longden pointed out a hidden danger of The Feature Factory Model It completely destroys your organization's data quality
• 11:05
  Speaker 1: Because if the only metric Of success is shipping the next feature On time Nobody actually cares what happens after it goes live
• 11:11
  Speaker 0: Precisely.
• 11:12
  Speaker 0: Teams in a feature factory don't care about measuring impact.
• 11:15
  Speaker 0: They don' t care about optimizing the workflow, and they certainly do not care about setting up proper telemetry.
• 11:20
  Speaker 0: Data is lifeblood of validated learning but a future factory neglects it because data might tell them that the features just rushed out were useless.
• 11:28
  Speaker 1: Which nobody wants to hear?
• 11:29
  Speaker 0: Exactly!
• 11:31
  Speaker 0: Furthermore if you talk to product leaders right now multi-should observe their number one hidden pain point isn't lack of strategic vision.
• 11:39
  Speaker 0: The real nightmare that keeps them up at night is invisible dependencies across teams.
• 11:43
  Speaker 0: It's having twenty disconnected teams operating in silos with no shared view of what depends on What you only discover a critical blocker after three weeks of development.
• 11:52
  Speaker 0: time have already been wasted.
• 11:54
  Speaker 1: So we know We need to escape this feature factory trap and we know.
• 11:57
  Speaker 1: We have to manage these invisible dependencies.
• 12:00
  Speaker 1: But how do you actually prioritize?
• 12:03
  Speaker 1: What to build while maintaining your sanity.
• 12:06
  Speaker 1: That brings us to our third theme product strategy and healthy boundaries.
• 12:11
  Speaker 0: This is where strategy has to move from a theoretical slide deck, to rigorous daily discipline.
• 12:17
  Speaker 0: Igor Voth shared very strong warning about the danger of building for the loudest demands.
• 12:23
  Speaker 0: instead
• 12:32
  Speaker 1: We will lose this massive enterprise deal if we don't build this one highly specific custom widget.
• 12:38
  Speaker 0: It feels entirely reasonable in the moment, but Igor shared from his own experience that when growth stalls The panic response is often to just build feature after feature based on whoever's screaming the loudest.
• 12:48
  Speaker 0: But what happens?
• 12:50
  Speaker 0: You dilute the core product.
• 12:52
  Speaker 0: That dilution leads to empty directionless roadmaps down the line, mountains of technical debt and eventually a bloated piece of software that your own sales team can't even explain anymore.
• 13:02
  Speaker 1: True strategy requires making genuinely hard choices... ...and one of the hardest choices a team could make is pricing.
• 13:08
  Speaker 1: Arun Kumar Palasimhi pointed out that Pricing Strategy is heavily undervalued in product development phase.
• 13:14
  Speaker 1: He used the Apple Vision Pro as prime example.
• 13:18
  Speaker 1: Apple launched that headset at thirty-four hundred ninety nine dollars.
• 13:22
  Speaker 1: Arun argues, That if you are designing a product You have to design it around the price point before you write A single line of code!
• 13:30
  Speaker 1: That conversation needs To happen during The earliest stages Of customer discovery.
• 13:34
  Speaker 1: Because If that Price Point inherently alienates Your core audience Then the Product Design itself is Fundamentally flawed from day one.
• 13:42
  Speaker 0: To help conceptualize how all these massive strategic decisions fit together without creating chaos, Tim Herbig referenced a brilliant analogy from Roger Martin the Russian Matryoshka dolls.
• 13:54
  Speaker 0: He calls it The Strategy
• 13:55
  Speaker 1: Stack.
• 13:56
  Speaker 1: I love this visual.
• 13:56
  Speaker 0: It works perfectly.
• 13:57
  Speaker 0: the outer largest doll is The company strategy that sets the overarching context, the mission and the massive choices you open.
• 14:04
  Speaker 0: That up in the product strategy Is the next all inside.
• 14:07
  Speaker 0: it has to fit perfectly Inside the company strategy and reinforce it right?
• 14:10
  Speaker 0: You opened that one And the feature strategy is the smallest All-inside.
• 14:14
  Speaker 0: they all have To align seamlessly.
• 14:16
  Speaker 0: if your featured all as a completely different shape than Your product all the whole thing breaks.
• 14:22
  Speaker 0: Roman Pishler echoed this exact sentiment recently, warning that whenever you try to separate strategic thinking from daily execution You end up with suboptimal decisions at best and completely disastrous ones at worst.
• 14:35
  Speaker 1: And when strategy breaks down the human element of execution is what suffers the most.
• 14:40
  Speaker 1: We are talking about team dynamics in boundaries.
• 14:43
  Speaker 1: There was a fantastic podcast discussion between Teresa Torres and Petra Will on this exact topic.
• 14:48
  Speaker 1: They took direct aim at the age-old myth that The Product Manager is the CEO of the product,
• 14:53
  Speaker 0: A title that sounds glamorous but usually just means you are the default dumping ground for everyone else's problems.
• 14:59
  Speaker 1: It's exactly!
• 15:00
  Speaker 1: That CEO mindset leads to PMs taking on responsibilities they absolutely should not own like managing the minutiae bug tracking or untangling system architecture?
• 15:10
  Speaker 1: They made it crystal clear Product owns the, what are we building?
• 15:15
  Speaker 1: and why does it solve a customer problem?
• 15:17
  Speaker 1: Engineering owns.
• 15:18
  Speaker 1: how do we architect this securely and reliably.
• 15:20
  Speaker 0: When a product manager steps over that boundary and starts acting as a glorified middleman for bug status updates on JIRA It destroys their ability to think strategically.
• 15:29
  Speaker 0: Yeah And the downstream effect of that blurred boundary is severe industry-wide burnout.
• 15:34
  Speaker 0: Tom Scott made a sobering observation that product designers in particular are facing immense burnout right now.
• 15:40
  Speaker 0: Their expectations are sky high, their creative space is being decimated by relentless two-week iteration cycles and many are trapped in toxic dysfunctional team environments where the strategy isn't protecting them.
• 15:51
  Speaker 0: it as direct result of the relentless pressure to just ship code without clear protective Matryoshka doll strategy we talked about
• 15:58
  Speaker 1: When you have level strategic disconnect And teams are burning out from playing middleman on bug tickets.
• 16:05
  Speaker 1: It really forces a conversation about our fourth and final theme, product careers and skills in twenty-twenty six.
• 16:12
  Speaker 1: given the acceleration shift operating models this high risk of burnout what does it actually take to survive an advance as a professional today?
• 16:25
  Speaker 0: Ed Biden shared a real wake-up call about the transition from being a VP of product to becoming a chief Product Officer.
• 16:31
  Speaker 0: He outlined six major shifts, but the most jarring one is where your attention goes.
• 16:36
  Speaker 0: Okay As a VP you are mostly looking inward managing the product organization The processes the teams.
• 16:41
  Speaker 0: But the moment you become a CPO that flips Your focus becomes eighty percent external.
• 16:46
  Speaker 0: You are suddenly dealing with the board of directors exploring mergers and acquisitions And forging strategic partnerships.
• 16:52
  Speaker 1: You essentially had to stop doing the job that got you promoted in first place.
• 16:56
  Speaker 0: Exactly!
• 17:06
  Speaker 0: As a CPO, there is absolutely nowhere to hide on the P&L The Profit and Loss finance metrics.
• 17:12
  Speaker 0: You are making massive investments specifically to change the company's growth rate and profit margin And you're held entirely accountable by board for those financial outcomes.
• 17:20
  Speaker 1: It is completely different arena at that level.
• 17:23
  Speaker 1: But even if your aren't aiming for C-suite right now David Pereira had brilliant insight about career success.
• 17:30
  Speaker 1: He argues that your success is actually less about your raw talent and much more about intentionally choosing the right product game That matches your specific working style
• 17:39
  Speaker 0: if we connect this to the bigger picture.
• 17:41
  Speaker 0: This isn't crucial concept for anyone feeling stuck in their current role.
• 17:45
  Speaker 0: David outlined five distinct games you can play in the tech industry, first there is B to be corporate where building consensus and navigating internal politics as far more important than moving fast.
• 17:56
  Speaker 0: second is b to c fast-moving Where?
• 17:58
  Speaker 0: The goal Is To test everything instantly with thousands of users.
• 18:01
  Speaker 0: pure
• 18:01
  Speaker 1: speed
• 18:01
  Speaker 0: right.
• 18:02
  Speaker 0: third is the early stage startup which is pure chaotic survival mode.
• 18:07
  Speaker 0: Fourth is the scale-up where you have to build sustainable systems while desperately trying to maintain your startup speed.
• 18:13
  Speaker 0: And finally, established giants which are all about marginal optimization over disruptive innovation.
• 18:21
  Speaker 1: So if you're a PM who thrives on moving fast and breaking things but currently playing at an established giant when spending six months optimizing the color of check out button You will feel like complete failure.
• 18:34
  Speaker 1: Even if you were incredibly talented, You're just playing the wrong game.
• 18:37
  Speaker 0: Exactly!
• 18:37
  Speaker 0: You have to audit your own environment.
• 18:39
  Speaker 0: But regardless of which a game you choose there is hidden curriculum To product management that Daniel Thomason addresses in his newly launched book.
• 18:46
  Speaker 0: all over it He points out a glaring gap In how industry trains talent.
• 18:50
  Speaker 0: We train product managers meticulously on JIRA On road mapping software And how run an A-B test but we rarely Train them on politics required to actually succeed In complex organization.
• 19:01
  Speaker 1: The soft skills they get things shipped.
• 19:04
  Speaker 1: Carving out your territory, building a reputation that precedes you before even walking to a stakeholder meeting and knowing how to trade social capital.
• 19:12
  Speaker 1: get your features prioritized when engineering resources are tightly constrained.
• 19:16
  Speaker 0: It is the unavoidable reality of human organizations.
• 19:20
  Speaker 0: but what I find highly encouraging it's how professional community responding all these shifting realities.
• 19:26
  Speaker 0: people aren't just sitting back letting industry happen.
• 19:29
  Speaker 0: we're seeing massive collective drive up.
• 19:32
  Speaker 0: skill Leaders are actively seeking out structured learning to bridge the gap between traditional management and these new AI-native workflows.
• 19:41
  Speaker 1: Yeah, you see it everywhere!
• 19:42
  Speaker 0: You have experts like Malay Krishna & Siddharora offering incredibly focused AIPM courses And major industry events like Product on London and Product at Heart Are drawing huge crowds of professionals who were fiercely dedicated to mastering these new paradigms.
• 19:57
  Speaker 1: Absolutely.
• 19:58
  Speaker 1: The energy out there is incredible, the tools are changing and organizational models shifting but fundamental drive to build things that solve real human problems...is stronger than ever.
• 20:09
  Speaker 1: To wrap up today's deep dive I want leave you with a final provocative thought to mull over drawing on recent post by Bing Lu.
• 20:16
  Speaker 1: he was analyzing Anthropics new portable memory feature.
• 20:19
  Speaker 1: That feature
• 20:19
  Speaker 0: is wild!
• 20:21
  Speaker 1: It really is.
• 20:22
  Speaker 1: Think about it Right now.
• 20:24
  Speaker 1: A massive reason you stick with a specific AI tool or ecosystem is context debt.
• 20:29
  Speaker 1: Your current AI knows your coding style, it knows your brand voice...it remembers your project history!
• 20:35
  Speaker 1: But if your AI persona all that customized contexts can suddenly be unplugged and easily move to any other platform in an instant…your switching costs drop to absolute zero.
• 20:45
  Speaker 1: So here's the question for If AI standardizes memory across all platforms, will AI companies be forced to compete solely on raw reasoning capability?
• 20:55
  Speaker 1: And if they do how well?
• 20:57
  Speaker 1: that zero switching cost environment fundamentally changed the software you're designing right now.
• 21:02
  Speaker 1: That
• 21:02
  Speaker 0: is a fascinating question.
• 21:16
  Speaker 1: Sha, thank you so much for joining us and don't forget to hit that subscribe button.