Science Fiction Prototypes, Pent up Data, & Product Leader Expectations

This edition explores consumer breakthroughs, science fiction as a prototype, a set of expectations for product leaders, and more.

Edition #22 of Implications.

• We’ve got a new and more efficient format. This edition also debuts a series of product leadership insights.

• If you’re new, here’s the rundown on what to expect. This ~monthly analysis is written for founders + investors I work with, colleagues, and a select group of subscribers. We aim for quality and provocation over frequency and trendiness. We don’t cover news; we explore the implications of what’s happening.

• If you’ve missed recent editions of Implications, here are some highlights that got the most engagement from others:

  • The Era of Scaling Without Growing: Small teams, big businesses.

  • The AI threat we should be talking about: Scaled socialization as a service.

  • The Law of Displacement Speed: Comparing the current AI frenzy to previous platform shifts and their aftermaths

  • Disruptive Interfaces in the Age of AI & Modern First-Mile Experiences: The digital world is like a global game of “slap a hand” where a hand over a hand over a hand happens (in the form of interfaces) in rapid succession until the hand on top wins, only to be beaten by the new hand slapped upon it.

  • Brandertainment: Brands will create more mainstream media in direct competition with studios.

Assertions & Implications

Lets jump into five assertions with implications worth noting — all around the theme of consumer AI and the elusive goal of positively transforming everyday lives:

• All of our pent up supply of personalized data and analytics from our personal health wearables will enable breakthroughs in research and personal healthcare. Should you start collecting now?

• Proprietary data is the next great moat of consumer AI.

• How much will we trust the conclusions of AI? Consumers will require a compass.

• Science fiction is now a prototype for the near future.

All of our pent-up supply of personalized data and analytics from our personal health wearables will enable breakthroughs in research and personal healthcare. Should you start collecting now?

Today, our Whoop bands, Oura rings, and Apple watches offer a handful of health metrics and features that appeal to health obsessives and data nerds (like me), but the usefulness of daily engagement around the health-related metrics from these devices is still rather limited.

However, in the coming years as AI enables you to mix and analyze mass amounts of personal data at scale, the data we collect daily on these wearable devices will become a treasure trove of insights into ourselves. I anticipate a new era of applications that simply mount this data and leverage advance AI to let us — and our doctors — get alerts of insights based on correlations so nuanced that only AI could detect them. We will be able to have conversations with this data, much like Whoop has debuted with their “Coach” feature, leveraging advanced consumer healthcare models that connect the dots of our health in previously unimaginable ways, unlocking diagnosis before noticeable symptoms, suggesting personalized drug regiments, and more.

I am most excited about the prospect of network effects from anonymized data of large swaths of society that opt into these tools. Today’s clinical studies have enormous margins of error since infrequent office visits for blood pressure or testing - and even variables like the doctor’s mood - impact data collection. That ultimately yields too much variability and inaccuracy with results. But when participants in research are being monitored 24/7, and the data is far more complete, including all of the long-tail nuances that impact us, the health breakthroughs could be staggering.

So, if you’re not in data collection mode, what are you waiting for? Perhaps the greatest benefit of these devices we wear is not the fun physical competitions with friends and daily measurement of sleep and activity, but rather the option to leverage future healthcare models that will transform our lives.

Proprietary data is the next great moat of consumer AI.

If you’ve been paying attention, the emerging search disrupter Perplexity has been making deals to source data that enriches their results and further differentiates their offering from Google. For example, Perplexity features rich graphs and data driven results for certain queries through a relationship with Tako, which creates visual explanations on the fly, and Perplexity recently announced a partnership with Polymarket to surface real-time results on topics ranging from politics to weather to sports from their incredible betting market. I admire the playbook Perplexity is using to gradually differentiate their search results with modern, dynamic, and proprietary data. But search engines aside, I also think a lot about what new and creative ways of sourcing proprietary data will be used by new consumer apps to infiltrate the operating systems, devices, and software that is so embedded in our everyday lives? For example, when you look at the closed nature of the iPhone, will either wifi networks or bluetooth become paths for the next generation of AI first apps to break through the OS and app membranes to get at the actual data?

How much will we trust the conclusions of “expert” AI? Consumers will require a compass.

When a smart expert with far more experience and knowledge than you makes a declaration, it tends to carry weight. As we approach the moment of Artificial General Intelligence (AGI) (which will have a very long final mile, but will start soon), I often wonder how much default trust we will put in what we are told by this vaulted sentient being? If AGI makes a statement about a person or business, do we take it with a great amount of credence or not? Will we start to trust what we hear even if we don’t understand the underpinnings and proof points - much like we would trust a top tier physicist who can’t fully explain why something is true? This is one of my open questions and concerns about the role of advanced AI in society, and why I anticipate the need for consumer “explainability” products that are just as powerful but serve a different purpose: to coach us on what we can trust, what questions and doubts we should have, and help us develop the reasoning to keep up with the sources of AI we look up to. As AI gets more powerful, our default CANNOT become trusting whatever we are told. We must continue to ask why and how, and a new suite of features — or products — will be required to help us navigate this new world. One startup exploring this space is Consensus, which leverages AI and validated scientific research to create a more reliable source for answers — a bifurcated search product with explainability — related to health. I suspect we’ll see more shifts in this space.

Science fiction is now a prototype for the near future

I once attended Jeff Bezos’ MARS conference in Santa Barbara, which brings together about 150 or so leaders and thinkers in tech. I left with take-aways, but I was most struck by his inclusion of a dozen or so science fiction writers, all of whom presented concepts they were working on and ideas for what might materialize in the future — whether it be in space, in manufacturing, in medicine, in entertainment, or beyond. Science fiction has long served as a form of “prototyping” for the future, but it usually takes multiple decades for us to realize such breakthroughs as mobile telephony, driverless cars, virtual reality, or unmistakable AI personalities. But the gap between science fiction and realization seems to be shrinking. The forces at play here are AI-driven simulations, self-replication, open source technology, and the viral spread and adoption of enhancements thanks to social media. Today, crazy ideas can be vetted quickly by the masses. Open source technology improves on itself exponentially with adoption. Medical breakthroughs can be discovered through very advanced simulations. And new AI agents will not only do work but will also create AI agents to do work, thus unleashing a form of “self-replication” that speeds up cycles of discovery. Humans are best at coming up with ideas, especially the non-obvious breakthroughs that start as curiosities that machines would never have nor obsess over. Perhaps, over time, more of our human minds will be devoted to dreaming up the future — and imagining what can go right and wrong — rather than doing the work?

Insights from The Modern Product Leader Playbook, Part 1

Here’s a new section for Implications that includes insights I share with or learn from modern product leaders I admire.

• Don't call meetings to quell your anxiety, call meetings to get solutions and alignment. I see too many meetings called for the purpose of calming the mind of an overwhelmed executive who doesn’t trust their team or hasn’t done their homework (including reading their email). No doubt, meetings stall teams. They break regular cadences of work and they inhibit what I call “natural selection work,” the stuff that everyone does — and knows intuitively matters most — when empowered to use their time as they see fit. We all need to catch ourselves when we’re tempted to call a meeting and make everyone labor through our own process to understand something. Call meetings to get alignment or review progress, with specificity. If you are called into a “quell anxiety” meeting, what should you do? Start with the simple question: “What questions do you want answered in this meeting?” Often, this is far more effective than a long update and review.

• Resourcefulness > Resources: Resiliency and resourcefulness make up for many other things (experience, capital, etc) that you may lack in the uphill battle of building something new. If there’s anything we learned from exiting a boom cycle and returning to one of constraint and innovation, it is that too much funding and too easy funding delays meritocracy amongst products and is a distraction from building sustainable businesses. I like to say, if resources are carbs that you can throw at your problems, resourcefulness is muscle that has far longer lasting power and is worth building (despite the pain of doing so).

• Expectations of Product Leaders: While every leader must develop their own approach, it’s helpful to see how fellow product leaders articulate expectations for their team. I’ve been asked several times over the years for suggestions on how to develop product leaders. Below is an example I developed during a very particular set of challenges over the course of my first five years as chief product officer, when we were building an entirely new set of cloud capabilities with a new platform, and a new breed of applications covering new mediums with collaborative features. While no self-respecting product leader is ever fully satisfied with their products or pace — and I certainly had many lessons learned the hard way building in a big company — our team managed to ship new cloud and web capabilities, new products, and new plumbing for the future of cloud services and AI. My product leadership team stomached a volatile period of people and organizational change, frustrating dependencies and fits and starts, and the challenges of alignment and prioritization in a big company. Of course, these principles were also influenced by many other founders I work with as an investor or advisor. They’ve become very important in how I now manage and evaluate product leaders, and I’m happy to share them for your consideration:

  • Product Vision

    • Clarity In Product Strategy: Does every product have a flag planted and a roadmap for how to get there? We should always have a 3-year vision coupled with an annual plan, and your teams should be aligned around what this is throughout your organizations.

    • Steward The Narrative for Your Segment or Function: The narrative of why your work matters and how your strategy impacts customers is yours to write, share, and iterate.

    • Optimistic About Future, Pessimistic About Present: Do you lead with a balance of excitement and vision for the future of a segment/function — and willingness to take big bets — coupled with a pragmatic focus on obstacles and tasks to be done? Are you direct with what is going right and what is going wrong?

  • Product Execution

    • Customer Experience Centricity: Do you push your teams to show, not tell (“a prototype is worth a hundred meetings”), and anchor your review of products with empathy for the customer’s experience (what is onboarding/first mile, does this solve the key struggle, does this take into account a brand-new customer and an existing customer’s workflow?) Do you measure the success of a product around customer experience (active use, measures of delight (CSAT, NPS), etc.)?

    • Build For Ourselves or a Customer Zero: Who do you work with, for every product, that will hold us accountable and force empathy and stark reality? Are you the customer? If not, which customer are you obsessively close with?

    • Strive for Interdependency: Are you building services & components that can be leveraged by others? Are you building our products leveraging centralized services and components? (Platform & systems mindset)

    • Drives Initiatives to Raise The Bar: Are you moving us towards a culture of shipping when ready vs cutting corners and shipping on dates? Are you advocating and embracing modern practices that reduce risk and improve quality and customer success? Are you making tradeoffs to boost quality and bring surprise and delight into the product?

    • No Elephants in the Room: Are you speaking up and out about what you don’t believe, what you doubt will work or be executed well and on time, and what you think is better?

  • Product Leadership Behaviors

    • Credibility: Can we all trust that every update or assertion is backed by data, and that the right questions have been asked? I don’t want to feel like a game of messenger is being played and that I am trying to get to the bottom of something through someone in the middle. Strong signal:noise ratio. Consistent accountability on decisions and what comes out of meetings.

    • Embraces Debate & Change, Embraces Decisions When Made: We’re not here to just sustain, we are here to grow and reimagine. Each leader needs to engage and switch up their teams to make this so. We also must shed light on elephants and encourage speaking up when misalignments persist. Once you commit, we need 100% of your sponsorship and commitment as you lead your teams, especially behind closed doors.

    • Promotes & Empowers Those You Want to Give More Influence To: Let’s not be driven by tenure, or by those who spend the most energy on their career advocacy. Instead, let’s ask the questions: Is this leader driving change, showing results, pushing for clarity, and serving as the example of what we want this org to look like?

    • Manages a Team and Picks 2-3 Focus Areas To Drive: In addition to our day-to-day leadership and management responsibilities, we should all have our hands on a couple levers that we are uniquely qualified to pull or change. What are yours?

Ideas, Missives & Mentions

**Finally, here’s a set of ideas and worthwhile mentions (and stuff I want to keep out of web-scraper reach) intended for those I work with (free for founders in my portfolio, Adobe folks…ping me!) and a smaller group of subscribers. We’ll cover a few things that caught my eye and have stayed on my mind (including the rise of hardware startups, commentating as a form of entertainment, breakthrough technology for parents, AI-powered product placement, some data that makes the case for further AI growth and investment…), as well as my latest areas of interest as an angel investor. Subscriptions go toward organizations I support including the Museum of Modern Art. Thanks again for following along, and to those who have reached out with ideas and feedback.