Author: a16z New Media Translation: Block unicorn
As investors, our responsibility is to gain a deep understanding of every corner of the technology industry to grasp future development trends. Therefore, every December, we invite investment teams to share what they believe is a major vision that technology companies will need to address in the coming year.
Today, we will share insights from the Infrastructure, Growth, Bio + Health, and Speedrun teams. Stay tuned for other teams' presentations tomorrow.
Infrastructure
Jennifer Li: How Startups Can Navigate the Chaos of Multimodal Data
Unstructured, multimodal data has always been the biggest bottleneck for enterprises, and also their greatest untapped treasure.
Bio + Health
Julie Yoo: Healthy Monthly Active Users (MAU)
By 2026, a new healthcare customer segment will become the focus: "Healthy Monthly Active Users."
Traditional healthcare systems primarily serve three user groups: (a) "Sick Monthly Active Users": those with fluctuating needs and high costs; (b) "Sick Daily Active Users*": such as patients requiring long-term intensive care; and (c) "Healthy Young Active Users*": relatively healthy individuals who rarely seek medical attention. Healthy young active users face the risk of transitioning into sick monthly/daily active users, and preventative care can mitigate this transition. However, our treatment-focused healthcare reimbursement system rewards treatment rather than prevention, thus proactive health checkups and monitoring services are not prioritized, and insurance rarely covers these services.
Now, a new demographic of healthy monthly active users has emerged: these are not ill, but want to regularly monitor and understand their health—and they are likely to be the largest segment of the consumer base. We anticipate a wave of companies—including AI-native startups and upgraded versions of existing businesses—will begin offering recurring services to serve this user group. With the potential of AI to reduce the cost of healthcare, the emergence of new health insurance products focused on prevention, and consumers increasingly willing to pay for subscription models out of pocket, "healthy monthly active users" represent the next highly promising customer segment in the healthcare technology space: they are engaged, data-driven, and prevention-focused. Speedrun (the name of an investment team within a16z)
Jon Lai: World Models Shine in Narrative
By 2026, AI-driven world models will revolutionize storytelling through interactive virtual worlds and the digital economy. Technologies such as Marble (World Labs) and Genie 3 (DeepMind) are already capable of generating complete 3D environments based on text prompts, allowing users to explore them as if in a game. As creators adopt these tools, entirely new forms of storytelling will emerge, potentially evolving into "generative Minecraft," where players can co-create vast and ever-evolving universes. These worlds can combine game mechanics with natural language programming; for example, a player could issue a command like, "Create a paintbrush that turns everything I touch pink."
... Such models will blur the lines between players and creators, making users co-creators of a dynamically shared reality. This evolution could give rise to interconnected generative multiverses, allowing different genres such as fantasy, horror, and adventure to coexist. In these virtual worlds, the digital economy will flourish, with creators earning income by building assets, mentoring newcomers, or developing new interactive tools. Beyond entertainment, these generative worlds will also become rich simulation environments for training AI agents, bots, and even artificial general intelligence (AGI). Therefore, the rise of world models not only marks the emergence of a new game genre but also heralds the arrival of a completely new creative medium and economic frontier. Josh Lu: "My Year Zero" 2026 will be "My Year Zero": by then, products will no longer be mass-produced but tailor-made for you. We are already seeing this trend everywhere. In education, startups like Alphaschool are building AI tutors that adapt to each student's learning pace and interests, ensuring every child receives an education tailored to their learning rhythm and preferences. This level of attention would be impossible without spending tens of thousands of dollars on tutoring for each student. In health, AI is designing daily supplement combinations, exercise plans, and dietary programs tailored to your individual physiological characteristics. No coach or lab is needed. Even in media, AI allows creators to repackage news, programming, and stories to create personalized feeds perfectly aligned with your interests and preferences. The greatest companies of the last century succeeded because they found the average consumer. The greatest companies of the next century will win by finding individuals among the average consumers. In 2026, the world will no longer be optimized for everyone, but for you. Emily Bennett: The First Native AI University I predict that in 2026 we will witness the birth of the first native AI university, an institution built from scratch around an AI system. For the past few years, universities have been experimenting with applying AI to grading, tutoring, and course scheduling. But what is emerging now is a deeper level of AI—an adaptive academic system capable of learning and self-optimizing in real time. Imagine an institution where courses, counseling, research collaborations, and even building operations are constantly adjusted based on data feedback. The timetable will self-optimize. Reading lists will be updated nightly and automatically rewritten as new research emerges. Learning paths will adjust in real time to suit each student's learning progress and individual circumstances. We've already seen some harbingers. Arizona State University's (ASU) university-wide collaboration with OpenAI has spawned hundreds of AI-driven projects across teaching and administration. The State University of New York (SUNY) has now incorporated AI literacy into its general education requirements. These are the foundations for deeper deployments. In AI-native universities, professors will become architects of learning, responsible for data management, model tuning, and guiding students on how to question machine reasoning. Assessment will also change. Detection tools and plagiarism bans will be replaced by AI-aware assessments, where students are graded not for whether they used AI, but for how they used it. Transparency and strategic use replace prohibitions. As industries scramble to recruit talent capable of designing, managing, and collaborating on AI systems, this new type of university will become a training ground, producing graduates adept at coordinating AI systems to support a rapidly changing labor market. This AI-native university will become a talent engine for the new economy. That's all for today. See you in the next part, stay tuned.