Reimagining Product Intelligence: Insights from the AI Platform Shift
The Difference Maker
We're living through one of those rare moments when technology fundamentally rewrites the rules of the game. Just like when smartphones made desktop websites feel clunky overnight, AI is making traditional product approaches feel surprisingly outdated.
The companies thriving in this shift aren't just slapping chatbots onto existing features. They're reimagining everything: how they understand their users, how they deliver value, and how they build trust in an increasingly intelligent world.
This is article #3 from a series of ‘horizons and edges’ that I call Lumépost—my digital campfire - the goal is to spark meaningful dialogue around emerging ideas in technology that are on the verge of or have the potential to be mainstream, and have readers connect the dots through disparate knowledge branches in the industry.
Go ahead, subscribe Lumépost (if you haven’t already)
Intelligence: Beyond Basic Behavioral Data
By 2025, collecting behavioral data has become table stakes. Spotify's skip pattern analysis and Netflix's viewing habits aren't revolutionary anymore, they're foundational expectations. The real transformation lies in the rise of contextual intelligence: systems that understand not just what you do, but the complex interplay of factors driving your decisions.
These systems synthesize behavioral signals, real-time context, multi-modal inputs, and trust networks to deliver genuinely predictive, adaptive experiences. Here are some examples at play
Notion AI doesn't just track what you write, it analyzes documentation patterns, meeting frequency, and project timelines to proactively suggest workflows tailored to your team's unique style.
Calendly has evolved beyond scheduling, understanding meeting context, participant dynamics, and optimal timing across your professional network.
Superhuman adapts its interface based on your current email load, urgency patterns, and time of day, surfacing different tools for high-volume sessions versus deep-work periods.
Otter.ai exemplifies this evolution, analyzing not just what you say in meetings, but your speaking patterns and engagement levels to generate contextually relevant follow-ups. This transcends transcription, it's understanding the nuanced dynamics of collaboration itself.
‘The cutting edge isn't just personalization, it's real-time behavioral adaptation. Today's breakthrough systems combine behavioral data with voice, visual, biometric, and social signals to model user intent and emotional state.’
Human-Centered Trust and Transparency
Perhaps most significantly, we're witnessing the emergence of systems that understand not just individual preferences, but how trust and influence flow through networks. LinkedIn's latest algorithms surface content based on whose opinions carry weight in your specific industry context, creating experiences that feel authentically human at digital scale.
The most successful contextual intelligence systems prioritize user empowerment over automation. Rather than making decisions for users, these systems surface insights that enhance human judgment. Notion AI helps you organize your thoughts; Superhuman streamlines your communication patterns. The systems that will thrive are those that make their reasoning transparent, give users control over their data, and create value through collaboration, not black-box automation.
As AI becomes more embedded in products, the winners will be those that seamlessly integrate technological capabilities with human creativity and strategic thinking, building trust and transparency into every interaction.
Beyond Screens: The Rise of Anticipatory Experiences
The most transformative products are breaking free from traditional interface limitations, proactively surfacing information and adapting to your needs in real time. Tesla revolutionized the driving experience, not just responding to driver’s inputs, but anticipating needs: preheating before the driver arrived, suggesting routes based on behavioral patterns, and adjusting settings for different drivers. This represents interface evolution in action.
Key Opportunities
Contextual Awareness- Understand not just what users do, but when, where, and why they act.
Multimodal Adaptation- Seamlessly adapt interfaces to user situations and preferences across touchpoints.
Proactive Value Delivery-Anticipate user needs, reducing cognitive load while increasing meaningful engagement.
The future belongs to organizations that view contextual intelligence not as a feature, but as a fundamental reimagining of how technology can amplify human potential.
The New Competitive Advantages
Traditional moats proprietary data, complex workflows, established user bases are being reshaped by AI's democratizing effect. The companies that will dominate the next decade are building entirely new forms of competitive advantage:
Behavioral Intelligence- Deep understanding of user motivations within specific contexts. It's not about having the most data, but having the most relevant insights about user behavior.
Adaptive Personalization- Systems that evolve with individual users over time, creating experiences that become more valuable the longer someone uses them.
Network Intelligence- Sophisticated understanding of how relationships, influence, and trust operate within your user community.
Contextual Prediction- The ability to anticipate needs based on environmental signals, behavioral patterns, and situational awareness.
In the image, contextual intelligence sits at the heart of today’s most advanced product strategies, driving new forms of adaptation, value, and human-machine partnership.
Roadmap
Phase 1: Behavioral Foundation- Starting by identifying the ambient signals that reveal user intent in your specific domain. What actions predict future needs? Which patterns indicate satisfaction or frustration?
Phase 2: Contextual Intelligence- Developing systems that understand not just what users do, but the context around their actions. Context transforms data from information into actionable insight.
Phase 3: Anticipatory Experiences- Creating interfaces that proactively surface value rather than waiting for explicit requests. The goal is making products feel intelligent and helpful, not pushy.
Phase 4: Trust Networks- Building sophisticated understanding of how trust and influence work within the user base. This becomes the foundation for more meaningful recommendations and social features.
Ideas for Embracing the Platform Shift
Navigating this transformation requires indoctrinating key insights that separate winning strategies from wishful thinking. Here ideas that should be valuable as we build through this platform shift:
The Stack Migration Imperative- If we are building foundational AI models, we must move up the stack fast. Models are becoming commoditized at unprecedented speed. The real value lies in application layers that deliver meaningful experiences to users.
The Data Capture Equation- Success demands capturing and leveraging first-party behavioral data to drive genuine personalization. This isn't just about knowing user preferences it's about understanding behavioral patterns that predict future needs.
The Connection Economy- We must build connectors to the broader ecosystem of apps the customers use. Third-party data integration enables deeper personalization. The companies winning today are those creating comprehensive data orchestration layers.
Social Graph Intelligence- Capturing social and professional relationship data transforms algorithms from generic to genuinely relevant. This isn't about social media integration, it's about understanding how trust and influence flow through the user network.
Beyond Prompts to Patterns- If system prompts are your competitive moat, you're building on sand. The real advantage lies in understanding behavioral patterns and contextual intelligence that can't be easily replicated through prompt engineering.
The Context Window Advantage- Your AI's memory and contextual understanding must be increasingly sophisticated. "Personalization effects" are becoming the new network effects—the longer someone uses your product, the more valuable it becomes to them personally.
Interface Layer Dominance- Markets will ultimately be won or lost at the interface layer, where the most seamless and intuitive experiences will capture user attention and loyalty. The companies that control these touchpoints will shape how users interact with the entire AI ecosystem.
The Emerging Imperative
We're not just witnessing technological advancement, we're seeing the emergence of truly intelligent systems that understand human behavior, context, and relationships. The companies that will thrive are those that recognize AI isn't just about automation—it's about creating more human-centered experiences through intelligent technology.
The future belongs to products that don't just respond to what users want, but anticipate what they need, understand why they need it, and deliver value in ways that feel natural and trustworthy.
The platform shift is here. The question isn't whether to embrace it, but how quickly you can reimagine your approach to building products that truly understand and serve human needs.
This article is from a series of ‘horizons and edges’ that I call Lumépost—my digital campfire for connecting fascinating dots between different worlds of tech, design, culture and business.
Let’s dive into the world of new technology, uncovering its potential applications, because novelty often paves the way for utility. Lean into what makes us human: our empathy, our unique tastes, our creativity, and our relentless drive to tackle old problems with bold, fresh approaches. Ride this exhilarating era of technological transformation exchanging thoughts into something meaningful.
Go ahead, subscribe Lumépost (if you haven’t already) for quality inferences & perspective into emerging technologies and experience innovation — unfold!
Note** - Some analysis in this article is inspired by and builds upon Scott Belsky's foundational work on AI platform shifts. My contribution focuses on extending these strategic insights into the specific realm of contextual intelligence, behavioral adaptation, and anticipatory user experiences. While Belsky provides the foundational platform shift framework, this piece explores how product teams can operationalize these concepts through sophisticated user understanding and predictive systems.
For Belsky's original insights on navigating platform shifts, see his work "The Data Wars & Reimagining Your Product During a Platform Shift”.