Big Ideas 2026: Part 1

The enterprise backend of today was built for a 1:1 ratio of human action-to-system response. It’s not architected for a single agentic “goal” to trigger a recursive fan-out of 5,000 sub-tasks, database queries, and internal API calls in under milliseconds. When an agent attempts to refactor a codebase or remediate a security log, it doesn’t look like a user. To a legacy database or rate-limiter, it looks like a DDoS attack.

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A few ideas we’re excited by:

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2026 unlocks multiplayer mode. Vertical software benefits from domain-specific interfaces, data, and integrations. But vertical work is inherently multi-party. If agents are going to represent labor, they need to collaborate. From buyers and sellers, to tenants, advisors and vendors, each party has distinct permissions, workflows and compliance requirements that only vertical software understands.

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For years, we’ve optimized for predictable human behavior: rank high on Google, appear among the first few items on Amazon, lead with a TL;DR. When I took a journalism class in high school, we were taught the 5Ws + H for news, and to start with a hook for features. Maybe a human would miss the deeply relevant, insightful statement buried on page five, but the agent won’t.

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We’re already seeing this in practice. When I run DeepResearch queries on ChatGPT, I capture an enormous amount of value despite almost no screen time. When Abridge magically captures the patient-provider conversation and automates downstream activities, the doctor barely looks at the screen. When Cursor develops entire applications end-to-end, the engineer is planning the next feature development cycle. And when Hebbia drafts a pitch deck from hundreds of public filings, the investment banker is getting well deserved sleep.

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The traditional healthcare system has primarily served three main user segments: (a) “sick MAUs”: people with spiky, high-cost needs; (b) “sick DAUs*”: like those in intensive, long-term care; and (c) “healthy YAUs*”: relatively healthy individuals who rarely see a doctor. Healthy YAUs are at risk of becoming Sick MAUs/DAUs, and preventive care could slow that shift. But our reaction-pilled healthcare reimbursement system rewards treatment over prevention, so access to proactive check-ins and monitoring services are not prioritized, and insurance rarely covers them anyway.

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The biggest companies of the last century won by finding *the average consumer.

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Picture an institution where courses, advising, research collaboration, and even building operations continuously adapt based on data feedback loops. Schedules optimize themselves. Reading lists evolve nightly and rewrite themselves as new research appears. Learning paths shift in real time to meet each student’s pace and context.

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In the AI-native university, professors become architects of learning, curating data, tuning models, and teaching students how to interrogate machine reasoning

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