The AI Podcast – Episode Summary

Episode Title: HumansAnd Raises $480M Seed Round to Build AI for Human Collaboration
Date: January 26, 2026
Host: Jaden Schaefer

Overview

This episode centers on the newly founded AI startup "HumansAnd," which has made headlines by raising an unprecedented $480 million seed round. The discussion explores HumansAnd's ambitious mission to create AI designed specifically for human collaboration, moving beyond single-user assistants to models capable of facilitating complex group dynamics and decision-making. Host Jaden Schaefer analyzes the company's vision, the challenges ahead, industry context, and whether their aims can shift the paradigm of AI from solitary automation to social intelligence.

Key Discussion Points & Insights

The Problem with Today's AI Chatbots

• Current Limitations: Existing chatbots excel at individual tasks (summarization, answering questions, solving equations), but struggle with messy, human-centric group collaboration.
• Lack of Social Intelligence: "Most of them still act like they're kind of this solo assistant ... they're doing one prompt at a time. What they're not doing and what they're not very good at is some of these really messy, more human kind of work of collaboration things that we do."
  — Jaden Schaefer, 02:10

HumansAnd’s Ambitious Approach

• Founding Team: Alumni from major AI labs including Anthropic, Meta, OpenAI, xAI, Google, and DeepMind.
• Vision: To build a "central nervous system for the human plus AI economy," focusing on social intelligence over simple information retrieval.
• Seed Round: Raised $480M pre-product, driven by the strength and pedigree of the team.

Beyond Efficiency: The Focus on Human Coordination

• Deeper Mission: Not just efficiency through AI, but reimagining how groups communicate, disagree, align, and make decisions over time.

• Target User Base: Both enterprises (teams) and consumer groups (families).

• Product Strategy: Vague on specifics, but hints at replacing/augmenting "multiplayer" collaboration environments (e.g., Slack, Notion, Google Docs).

  "They just raised $480 million in a seed round and they're trying to get ... a system designed around social intelligence rather than pure information retrieval."
  — Jaden Schaefer, 05:22

• No Product Yet: Deliberately secretive on the actual product, but positioning towards building a new AI foundation model for group interactions.

Redefining Chatbot Interactions

• The Next Paradigm: Annie Peng (co-founder, ex-Anthropic) suggests a shift from question-answering verticals to AI systems that help users figure out what to do with these tools.

• Moving to Agent-Based Systems: Cites industry trend toward more autonomous, multi-agent workflows.

  "It feels like we're ending the first paradigm of scaling where question answering models were trained to be very smart at particular verticals. We're now entering a second wave..."
  — Annie Peng, quoted by Jaden Schaefer, 10:28

Purposeful AI Questioning & Contextual Memory

• Eric Zeekerman (CEO, ex-xAI): Emphasizes that their model should ask questions "the same way maybe like your colleague would," with selectiveness, memory, and context drawn from prior interactions.

• Model Goals: Build trust, facilitate long-term value, and help with consensus, especially in scenarios with decision fatigue and unclear agreement.

  "We're building a product and a model that is centered on communication and collaboration. Our goal is to basically help people work together more efficiently, not with AI tools, but with one another."
  — Eric Zeekerman, summarized by Jaden Schaefer, 14:25

Industry Landscape & Competition

• Crowded Market: Many startups (e.g., Granola, Notion, Slack) compete in integrating AI into collaboration.

• Incumbent Giants: True rivalry with Anthropic (Claude Cowork), OpenAI (multi-agent orchestration), Google (embedded Gemini), and others—not just productivity apps.

  "I think the real competition is going to be coming from Anthropic and Google ... so their competition is against a bunch of really big players."
  — Jaden Schaefer, 26:58

• Unique Proposition: HumansAnd claim their focus on social intelligence as the model’s foundation differentiates them, potentially providing a "head start."

Technical Foundations & Research Directions

• Long-Horizon & Multi-Agent RL: Yu Chan (co-founder, ex-OpenAI) cites the use of advanced reinforcement learning techniques to give the model robust memory, planning, and coordination skills over time and across groups.

  "We're trying to train the model in a fundamentally different way ... planning to rely on long horizon reinforcement learning and multi-agent reinforcement learning."
  — Yu Chan as quoted by Jaden Schaefer, 21:45

• Memory & Self-Understanding: Model needs to retain knowledge about itself and users for effective relationship-building and context integration.

Risks, Skepticism, and Outlook

• High Stakes, High Cost: Training new models is expensive and compute-intensive; market dominated by tech giants.

• Unclear Product, Huge Funding: Raises eyebrows—can ambition alone justify investment? Schaefer is skeptical but hopeful.

  "I don't know if all of their problems are problems. I'm excited to see what they come up with ... they've raised, you know, half a billion dollars, I think they're going to be able to pull something off."
  — Jaden Schaefer, 17:38

• Commitment to Independence: The team is rejecting acquisition offers, aiming for a "generational company" and charting a unique path.

  "We believe this can be a generational company. We think it has the potential to fundamentally change how people interact with these models and we trust ourselves and the team we built to do that."
  — HumansAnd team statement, relayed by Jaden Schaefer, 30:10

• Future Watching: Ultimate success pivots on making "social intelligence" operational at scale and whether this approach provides more than just incremental gains over incumbent models.

Notable Quotes & Memorable Moments

• On Today’s Chatbots:
  "For all, you know, for, for how intelligent and how smart they are, most of them still act like they're kind of this solo assistant."
  — Jaden Schaefer, 02:12

• On HumansAnd's Philosophy:
  "They're trying to build a new foundation model, one that is architected specifically for understanding people in groups."
  — Jaden Schaefer, 08:44

• On AI Coordination vs. Automation:
  "Reid Hoffman has argued that companies are misusing AI by using it in isolated pilots rather than kind of getting it straight into how their teams are sharing knowledge and decision making."
  — Jaden Schaefer, 24:12

• On Long-Horizon Training:
  "Long horizon reinforcement learning... is focusing on outcomes over time rather than just like one off responses."
  — Jaden Schaefer, 23:05

Timestamps for Key Segments

• [01:00–05:21] – Introduction to HumansAnd & Problem Definition
• [05:22–10:27] – Founders, Funding, Vision, and "Social Intelligence"
• [10:28–14:24] – Paradigm Shift: Question-Answering to Group Coordination & Agency
• [14:25–18:13] – Product Philosophy, Decision-Making, Model Intentionality
• [21:45–24:11] – Long-Horizon & Multi-Agent RL, Academic Context
• [24:12–28:31] – Industry Competition & Market Positioning
• [28:32–30:10] – Risks, Skepticism, and Commitment to Independence
• [30:11–End] – Future Outlook & Closing Thoughts

Episode Takeaway

HumansAnd is betting that the next breakthrough in AI will not simply be smarter answers, but smarter collaboration—AI that understands how humans work together. With visionary founders, remarkable funding, and a focus on social intelligence, their challenge lies in delivering a tangible product that meets these lofty expectations in a fiercely competitive ecosystem.

For listeners and observers alike, HumansAnd’s evolution is set to be one of the most compelling stories in AI’s 2026 landscape.