AI chatbots are getting better at answering questions, summarizing documents, and solving math equations, but they still largely behave as helpful assistants for one user at a time. They’re not designed to handle the messier work of real collaboration: coordinating people with competing priorities, tracking long-term decisions, and keeping teams aligned over time.
Humans&, a new startup founded by alumni of Anthropic, Meta, OpenAI, xAI and Google DeepMind, believes that closing this gap is the next major frontier for fundamental models. The company this week raised a $480 million round to build a “central nervous system” for the human and artificial intelligence economy. The startup “AI to empower peopleThe framework has dominated early coverage, but the company’s real ambition is more innovative: to build a new core model architecture designed for social intelligence, not just information retrieval or code generation.
“It looks like we’re finishing the first scaling paradigm, where the question-answering models were trained to be very smart in certain verticals, and now we’re entering what we think is the second wave of adoption where the average consumer or user is trying to figure out what to do with all this stuff,” said Andi Peng, one of humans&’s, a former Anthropic employee.
Humans&’s pitch is focused on helping people usher in the new era of AI, moving beyond the narrative that AI will take their jobs. Whether it’s just marketing or not, timing is critical: Companies are moving from chat to agents. The models are capable, but the workflows are not, and the coordination challenge remains largely undefined. And through it all, humans feel threatened and overwhelmed by AI.
The three-month-old company, like several of its peers, managed to raise its amazing seed by rounding out that philosophy and the pedigree of its founding team. Humans& doesn’t yet have a product, nor has it made clear exactly what it might be, though the team has said it could replace multiplayer or multi-user environments such as communication platforms (think Slack) or collaboration platforms (think Google Docs and Notion). In terms of use cases and target audience, the team hints at both enterprise and consumer applications.
“We’re building a product and a model that’s focused on communication and collaboration,” Eric Zelikman, co-founder and CEO of humans& and a former xAI researcher, told TechCrunch, adding that the focus is on helping the product help people collaborate and communicate more effectively — both with each other and with AI tools.
“Like when you have to make a big group decision, it often comes down to getting everyone in a room, getting everyone to express their different camps, like what kind of logo they would like,” Zelikman continued, beaming with his team as they recall the time-consuming hassle of getting everyone to agree on a logo for the startup.
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Zelikman added that the new model will be trained to ask questions in a way that feels like it’s interacting with a friend or colleague, someone who’s trying to get to know you. Chatbots today are programmed to ask questions all the time, but they do so without understanding the value of the question. He says that’s because they’re optimized for two things: How much a user immediately likes an answer they’re given, and how likely the model is to correctly answer the question it’s given.
Part of the lack of clarity about what the product is may be because people don’t quite have an answer to it yet. Peng said that humans& designs the product in conjunction with the model.
“Part of what we’re doing here is also making sure that as the model improves, we’re able to co-evolve the interface and the behaviors that the model can do into a meaningful product,” he said.
What is clear, however, is that people are not trying to build a new model that can plug into existing applications and collaboration tools. The startup wants to own the collaboration level.
AI plus team collaboration and productivity tools is an increasingly hot field — for example, AI note-taking startup Granola raised a $43 million round at a $250 million valuation as it rolled out more collaborative features. Several high-profile voices are also explicitly framing the next phase of AI as one of coordination and collaboration, not just automation. LinkedIn founder Reid Hoffman argued today that companies are misapplying AI by treating it as individual pilots, and that the real leverage lies at the coordination level of work – that is, how teams share knowledge and conduct meetings.
“AI lives at the workflow level, and the people closest to the work know where the friction really is,” Hoffman said. he wrote on social media. “They are the ones who will discover what needs to be automated, compressed or completely redesigned.”
This is the space where people & want to live. The idea is that his model-product would act as the “connective tissue” in any organization – whether it’s a 10,000-person business or a family – that understands the skills, motivations and needs of each individual, and how they can all be balanced for the good of the whole.
Getting there requires rethinking how AI models are trained.
“We’re trying to train the model in a different way that involves more humans and AI interacting and working together,” Yuchen He, a human and co-founder and former researcher at OpenAI, told TechCrunch, adding that the startup’s model will also be trained using long-term and multi-agent reinforcement learning (RL).
Long-horizon RL is meant to train the model to plan, act, revise and monitor over time, rather than just generating a good one-time answer. It trains multi-agent RL for environments where there are multiple AIs and/or humans. Both of these concepts are gaining momentum recent academic work as researchers push LLMs beyond chatbot responses to systems that can coordinate actions and optimize outcomes across multiple steps.
“The model has to remember things about itself, about you, and the better its memory, the better the understanding of the user,” he said.
Despite the stellar crew running the show, there are many dangers ahead. People will need endlessly large amounts of cash to fund the expensive effort of training and scaling a new model. This means it will compete with major incumbents for resources, including access to computing.
The top danger, however, is that people are not just competing with the Concepts and Brooms of the world. It’s coming for the Top Dogs of AI. And these companies are actively working on better ways to enable human collaboration on their platforms, even as they vow that AGI will soon replace economically viable work. Through Claude Cowork, Anthropic aims to optimize work-style collaboration. Gemini is built into Workspace, so AI-enabled collaboration already happens inside the tools people already use. and OpenAI has recently introduced developers to orchestration and multi-agent workflows.
Crucially, none of the major players seem ready to rewrite a model based on social intelligence that either gives people a leg up or makes them a takeover target. And with companies like Meta, OpenAI, and DeepMind looking for top AI talent, M&A is definitely a risk.
Humans& told TechCrunch that it has already turned down interested parties and is not interested in being acquired.
“We think it’s going to be a generational company, and we think it has the potential to fundamentally change the future of how we interact with these models,” Zelikman said. We trust ourselves to do that and we have great faith in the team we have assembled here.”
This post was originally published on January 22, 2026.
