
Roundtable #7: Spotify, Adobe and Linkedin on How AI Changes The Future of Product & Design | E1097
Harry Stebbings (host), Scott Belsky (guest), Tomer Cohen (guest), Gustav Söderström (guest), Guest (brief laughter only) (guest)
In this episode of The Twenty Minute VC, featuring Harry Stebbings and Scott Belsky, Roundtable #7: Spotify, Adobe and Linkedin on How AI Changes The Future of Product & Design | E1097 explores spotify, Adobe, LinkedIn Reveal How AI Redefines Product, Design, Strategy Product leaders from Adobe, Spotify, and LinkedIn discuss how AI is shifting product development from UI-centric to AI-centric, where AI becomes the product and UI becomes the signal-capturing interface around it.
Spotify, Adobe, LinkedIn Reveal How AI Redefines Product, Design, Strategy
Product leaders from Adobe, Spotify, and LinkedIn discuss how AI is shifting product development from UI-centric to AI-centric, where AI becomes the product and UI becomes the signal-capturing interface around it.
They argue that AI-first strategy must come from the CEO down, forcing teams to accept probabilistic, non-deterministic experiences, rethink design, and deeply understand models and data rather than delegating AI to a specialist team.
The conversation explores multi-model architectures, routing and cost optimization, proprietary vs. foundation models, and why owning high-quality, proprietary user data is a durable advantage.
They also examine how AI will disrupt business models (e.g., seat-based SaaS and hourly billing), what skills designers and product managers must build, and why incumbents may be unusually well-positioned in this particular platform shift.
Key Takeaways
Treat AI as the core product, not a feature you delegate.
The leaders argue that AI strategy must be driven from the top and embedded in every product decision; product teams can’t outsource AI thinking to a separate “AI team” if they want to remain relevant.
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Designers and PMs must understand models as deeply as users.
Effective AI UX requires knowing capabilities, failure modes, and latency/cost tradeoffs of models (e. ...
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AI shifts experiences from deterministic to probabilistic, demanding new mindsets.
Product leaders must accept they no longer fully control outputs; they set objectives, constraints, and “knobs,” while models generate variable outcomes—sometimes “hallucination” is a feature (e. ...
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Multi-model architectures and routing will be a major innovation layer.
Instead of a few mega-models, they foresee many specialized models (some local, some open-source, some proprietary) orchestrated by dispatchers/routers that optimize for relevance and cost, abstracted away from most product teams.
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High-quality, proprietary user data and objectives design are critical advantages.
They stress that data is “oxygen” for AI: product leaders should own the definition of algorithm objectives and the design of data collection pipelines, rather than assuming data science will fix poor or missing signals later.
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Incumbents may benefit unusually in this platform shift if they move quickly.
Unlike cloud and mobile, AI can be embedded into existing products and channels (e. ...
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AI will force new business models beyond seats and hourly billing.
As AI boosts productivity and collapses functions, selling by seat or hour becomes misaligned; they anticipate a shift toward value- or outcome-based pricing and “selling the work, not the seats.”
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Notable Quotes
“AI is the product and the UI is there to help the AI.”
— Gustav Söderström (Spotify)
“When you're thinking in an AI-first principled kind of way, you're really unleashing the idea of control. What happens basically in AI is you don't control the experience anymore.”
— Tomer Cohen (LinkedIn)
“Designers and product people need to understand GPT-4 as well as they understand a user.”
— Gustav Söderström (Spotify)
“It's not the technology that makes us successful, it's the user's experience of the technology that makes us successful.”
— Scott Belsky (Adobe)
“Data is literally, according to me, your second most important job. The first is understanding the objective of the algorithm.”
— Tomer Cohen (LinkedIn)
Questions Answered in This Episode
How should a small or mid-sized product team practically reorganize to become truly AI-first without creating a separate, siloed “AI team”?
Product leaders from Adobe, Spotify, and LinkedIn discuss how AI is shifting product development from UI-centric to AI-centric, where AI becomes the product and UI becomes the signal-capturing interface around it.
Get the full analysis with uListen AI
What concrete steps can designers and PMs take in the next 90 days to deeply understand the models they’re using, beyond just writing better prompts?
They argue that AI-first strategy must come from the CEO down, forcing teams to accept probabilistic, non-deterministic experiences, rethink design, and deeply understand models and data rather than delegating AI to a specialist team.
Get the full analysis with uListen AI
How might SaaS pricing and procurement evolve when AI drastically reduces the number of human “seats” needed to produce the same or greater output?
The conversation explores multi-model architectures, routing and cost optimization, proprietary vs. ...
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In which domains is hallucination a useful creative feature versus an unacceptable risk, and how should product teams formally decide that boundary?
They also examine how AI will disrupt business models (e. ...
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For companies without massive proprietary datasets, what is the most realistic path to building defensible AI products in a world of increasingly powerful foundation models?
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Transcript Preview
What do the best product leaders think about AI? I talked with the heads of product from Adobe, LinkedIn, and Spotify. And we covered everything from LLM predictions in 2024 to how product teams should adopt AI.
I think it's actually common belief that there are gonna be a few mega models in the future that are gonna do everything for every company in the cloud. What we're saying is, actually, it will probably be the opposite.
When you're thinking in an AI first principle kind of way, you're really unleashing the idea of control. What happens basically in AI is you don't control the experience anymore.
Something that designers need to get good at in this world, they need to understand GPT-4 as well as they understand the user. So an example that I think is a good example is ...
Alrighty. I am so excited for this. I've wanted to do this one for a while. So we're gonna do a couple of intros first so everyone can get familiar with each other's voices. And so we're going to start with you, Scott, then Gustav, and then Tomer. Who are you and what are you most well known for?
I was the founder of a company called Behance back in the day, and, uh, we were acquired by Adobe. Um, for the last, uh, six years or so, I, I served as chief product officer for about five years overseeing the creative cloud business and then, um, and then have, uh, recently taken over strategy corporate development, uh, design and emerging products for the company in this kind of chief strategy emerging products officer type role, uh, over the last year.
(laughs) It's quite an all encompassing role. Um, Gustav, your turn.
So I'm Gustav Sederström and, uh, similar to Scott, I started and sold a few companies and then, um, I worked at Spotify for almost 15 years now as a CPO and then CTO and now recently as, uh, co-president together with, uh, Alex Nordstrom. So we run the company together.
Very exciting transition there. Tomer, your turn.
Hey, everyone. Uh, chief product officer for LinkedIn. Uh, responsible for basically what we build from the company's strategy to overseeing the teams building it. Been at LinkedIn for 12 years now. Joined, uh, right at the cuff of shifting from desktop to mobile as a company, so that was fun. I started my career as an engineer, so I was doing anything from semiconductors, chip on design algorithms, to embedded systems, all the way to the internet right now in AI.
Okay, so now everyone knows individual voices. We're actually also very lucky because there are three very distinct voices (laughs) . I didn't realize quite how, how apt the selection of this roundtable was in that perspective. I want to start with probably kind of the most broad but also kind of important, which is fundamentally we're all told that AI changes everything that we do. When we apply that to product, what do we think are the most significant ways that AI will change the product development process, specifically on the product development side? What will change specifically with AI? And I just want to throw that out there so anyone can jump on it.
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