We are soo back. Just two weeks in, our team is buzzing in the afterglow of one JPM Healthcare Conference, two Reach gatherings, and meeting many founders building solutions in health, work, and learning.

Last week, we co-hosted a breakfast with Inflect Health and Yosemite. In attendance: over 80 founders across robotics, women’s health, wearables, and AI-powered care, alongside practitioners from Stanford, Vituity, and California Health Care Foundation, and investors from Menlo Ventures, Opal Ventures, Bessemer, Ulu and beyond. Trends they’re excited about: Focused LLM and AI solutions that drive measurable ROI, AI models that simulate specific biological systems and processes, and longevity-focused electronic health records.

We followed that with an intimate dinner co-hosted with AIHF, gathering the brightest Stanford founders and researchers in healthcare and AI. We got a frontline seat into the diversity of solutions they’re building: Uber for dermatology, hormonal health wearables, diagnostics for measuring the health of your home, and Hims/Hers for peptides.

No technology is moving faster or unlocking more possibilities than AI. We’re seeing startups scale at unprecedented speed with smaller teams, overturning long-held assumptions about what it takes to build enduring companies.

Our excitement isn’t focused solely on productivity or efficiency. It’s rooted in the opportunity to materially improve how people learn, work, and care for one another. AI is expanding who technology can serve, opening doors to people, professions, and markets that have long been considered too small, too fragmented, or too “unscalable” to matter.

As we head into the new year, our investing team shares the breakthrough ideas that will define 2026.

Reach is excited to lead an $18M Series B in Manifold, joined by SilverArc Capital, Industry Ventures, TQ Ventures, and Calibrate Ventures. The company is tackling one of life science’s biggest bottlenecks: As health data volumes and modalities expand, drug discovery is getting slower and more expensive as researchers spend too much time wrangling data instead of testing ideas.

Manifold is building a vertical AI platform that brings together data, analytical tools, and organizational knowledge into one environment, enabling researchers to run complex analyses in minutes, not months. The team is already working with leaders like Champions Oncology, UCSF, Foundation Medicine, and the American Cancer Society to accelerate research discoveries. They are also partnering with AWS, Snowflake, Anthropic, and the Broad Institute to get this capability into the hands of many more scientists.

AI raises an old question with new teeth: Which jobs will disappear, and which ones will be invented?

One path to “AI‑proofing” your job is more obvious: learn to wield it. Prompt and “vibe” your ideas into software. Deploy agents to do your bidding, particularly the tedious stuff. Get more done with less.

Another path is less flashy, but more durable: becoming a better teammate, problem solver, communicator, creative thinker, and all the other human traits that we value as a social species.

As the Financial Times’ John Burn‑Murdoch notes, the biggest rewards don’t go to the pure quants, but to those who blend math with people skills like social perceptiveness, coordination, persuasion, negotiation. Building on Harvard economist David Deming’s earlier research, he shows how “soft” skills have outpaced raw maths in both employment and wages. 

Of course, choosing between high social skills and math abilities is a false dichotomy. Yet even if you only could pick one, those with high social skills and weaker maths reap greater returns than those vice versa.

For all the attention on AI, STEM, and each new technology du jour, the enduring advantage remains human judgment, empathy, collaboration, storytelling, and trust. These are the multipliers that make technical talent truly valuable.

Even as AI reshapes tools and tasks, the fundamentals of learning still matter just as much as ever. Longtime education writer Frederick Hess offers a contrarian take: AI “changes nothing about what students need to learn.” If anything, it raises the stakes on reading, reasoning, and knowledge rather than replacing them. While we’re busy building autonomous AI agents, we also need to be nurturing autonomous humans.

One of our most-used resources is back: the 2026 Reach Conference Calendar. It’s a cheatsheet to all the major industry events across learning, health, and work (filterable by sector, date, and location) so founders, operators, and partners can decide where their time and presence will matter most.

A few where you can find Reach in 2026:

Remote

Serving more than 325 school districts in 16 states, as the nation's largest provider of mental health services.

San Francisco, CA • In-person

Helping students and early talent access meaningful career opportunities.

Culver City, CA or Lehi, UT • In-person

Rebuilding higher education for the AI era — smarter, faster, more fun than lectures, and with less debt.

New York, NY • In-person

Building the AI-native operating system for schools, starting with the student information system.

New York, NY • Hybrid

Accelerating hiring and reducing mis-hires by automating phone screens with AI interviewers.