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100 AI Leaders Explain How to Build AI That Will Win in 2026 — WHAT BUILDERS SHOULD DO NOW

100 AI leaders across product, engineering, research, and design gathered at StratMinds’ Swell Summit to answer one question: What will actually win in the next era of AI products? From new interaction models to experience-first design, this reveals what thoughtful builders are paying attention to and what many teams are still missing. There's one particular idea they kept returning to throughout the summit, a critical insight that most of us rarely pause to consider deeply. Watch to discover what it is. Key Takeaways: 📌 We need to go beyond basic chat and embrace new interaction primitives like semantic resizing, remixing, and format translation that redefine how people engage with AI. 📌 Products that feel alive, emotional, and responsive create deeper user connection. 📌 As models become commodities, intuitive AI ergonomics becomes the true differentiator. 📌 Start with what the model can uniquely do to uncover solutions users haven’t imagined. 📌 Real progress comes from solving the right problems, not just shipping fast. 00:00 Intro 02:00 The New Building Blocks: Chat is not enough 03:26 The New Interaction Primitives of Gen AI - Jess Holbrook, Head of UX Research @Microsoft AI 05:46 Make AI Alive: Craft a Magical Experience 06:45 Spark, The First Non-Human Resident at the Hacker House - Pasquale D'Silva *Chief Creative Officer(correcting the CEO caption) @Illusion of Life 09:16 Don't Chase Users, Build on What the Model Can Do - Andy Szybalski @Cove, ex-Uber, Google 13:01 How to Design AI the Right Way - Jenny Lo @Global AI Platform, Ex-Grammarly, Uber 15:09 Don't Build Confusing Gadget - Ayça Cakmakli @Google 17:01 The Real Moat for Next-Gen AI Products Learn more about the Swell Summit 👉 https://stratminds.vc/swell EO stands for Entrepreneur& Opportunities. As we're looking to feature more inspiring stories of entrepreneurs all over the world, don't hesitate to contact us at partner@eoeoeo.net LinkedIn | @EO STUDIO X | @eostudi0

Jess HolbrookcameoAyça CakmaklicameoPasquale D'SilvacameoAndy SzybalskicameoJenny Locameo
Nov 29, 202521mWatch on YouTube ↗

At a glance

WHAT IT’S REALLY ABOUT

AI product winners in 2026 will be defined by UX

  1. The panel argues that “chat-only” interfaces are a UX dead end and that winning AI products will adopt new interaction primitives like structure, semantic resizing, remix, format translation, and better agent monitoring.
  2. As AI models become commodity infrastructure, competitive advantage shifts to ergonomics-like UX: clarity, safety, trust, and experiences that solve real problems rather than flashy gadgets.
  3. Builders should treat each LLM as a distinct “material,” starting from what the technology can uniquely do now while iterating back and forth with genuine user needs.
  4. Case examples (e.g., Grammarly’s evolution from correction to composition, and the Spark character demo) illustrate that emotional resonance, care, and “feeling seen” can drive adoption more than raw capability.
  5. User research must adapt to AI interfaces by studying prompts and conversations, measuring satisfaction, and designing systems that proactively surface help before users know what to ask.

IDEAS WORTH REMEMBERING

5 ideas

Stop treating chat as the default end-state UI.

Chat is universal but often linear and limiting; leaders highlight structured experiences (e.g., research reports with sources) and purpose-built interfaces as the next step in AI product design.

Design around emerging primitives: resize, remix, translate formats.

Future products will let users adapt content to context (semantic resize), freely recombine styles and ideas (remix), and move between media (format translation) with minimal fidelity loss.

Agents need “lobbies,” not just background automation.

If AI is running tasks across timescales, users need clear ways to start, monitor, and re-engage—otherwise downtime and ambiguity become the enemy of good work.

Treat each model like a different material with constraints.

Teams should “play with” models to learn strengths/weaknesses and identify the “why now” capability that makes a product newly possible, then iterate with user needs.

Earn the right to go beyond the user’s initial question.

Users ask for the tip of the iceberg; great AI first nails the explicit request, then helps uncover the underlying goal (e.g., venue → full birthday planning) and explores branches like a real thought partner.

WORDS WORTH SAVING

5 quotes

Chat is both universal and kind of a dead end for user experiences.

— Jess Holbrook

Agents, agents, agents, agents, agents is, is all the stuff right now. It's like all these things existing at wildly different timescales and just multitasking forever at ever-expanding scales.

— Jess Holbrook

A powerful AI model with poor UX is kind of like a heavy duty power drill with a terrible handle.

— Ayça Cakmakli

Anything that violates that, we do not do, and anything that supports that, we say yes to.

— Andy Szybalski

We say ship to learn, right? Uh, but shipping speed may not equal learning speed.

— Jenny Lo

Beyond-chat AI UX patternsNew gen-AI interaction primitivesSemantic resize, remix, and format translationAgent “lobbies” and attention managementLLMs as a new design materialProblem identification vs “add AI” mentalityTrust, magic, and AI experiences for kids/next generation

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