Humans believe coordination is the next frontier for AI, and are building a model to prove it

AI chatbots are getting better at answering questions, summarizing documents, and solving mathematical equations, but they still largely act as helpful assistants for one user at a time. They’re not designed to manage the messier work of true collaboration: coordinating people with competing priorities, tracking long-term decisions, and keeping teams aligned over time.

Humans&, a new startup founded by Anthropic, Meta, OpenAI, xAI, and Google DeepMind alumni, believes bridging this gap is the next major frontier for foundational models. The company raised this week $480 million seed round To build a “central nervous system” for the human economy as well as artificial intelligence. the beginning “Artificial intelligence to empower humansFraming has dominated early coverage, but the company’s actual ambition is more recent: to build a new modular infrastructure designed for social intelligence, not just information retrieval or code generation.

“It feels like we’ve finished the first model of scaling, where question-answering models have been trained to be very intelligent 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 of this stuff,” Andy Peng, Human& co-founder and former Anthropic employee, told TechCrunch.

Humans& is focused on helping people usher in a new era of AI, moving beyond the narrative that AI will take their jobs. Whether it’s just marketing talk or not, timing is crucial: companies are moving from chat to agents. Models are efficient, but workflow is not, and the coordination challenge remains largely unaddressed. And through it all, people feel threatened and exhausted by AI.

The three-month-old company, like many of its peers, has managed to raise its impressive bottom line on the back of this philosophy and the pedigree of its founding team. Humans& still doesn’t have a product, and it wasn’t clear exactly what it might be, though the team said it could be an alternative for multiplayer or multi-user contexts like communications platforms (think… Recession) or collaboration platforms (think Google Docs and Notion). As for use cases and target audience, the team hinted at both enterprise and consumer applications.

“We’re building a product and model around communication and collaboration,” Eric Zelickman, co-founder and CEO of Human& and former XAI researcher, told TechCrunch, adding that the focus is on making the product help people work together and communicate more effectively — both with each other and with AI tools.

“Like when you have to make a big group decision, it often boils down to someone taking everyone into one room, and having everyone express their different camps on, say, what kind of logo they want,” Zelickman continued, laughing with his team as they recalled the time-consuming tedium of getting everyone to agree on a logo for the startup.

Zelickman added that the new model will be trained to ask questions in a way that resembles an interaction with a friend or colleague, or someone trying to get to know you. Today’s Chatbots are programmed to constantly ask questions, but they do so without understanding the value of the question. He says this is because they’re optimized for two things: how immediately the user likes the answer they’re given, and how likely the model is to answer the question they receive correctly.

Part of the lack of clarity about what the product is could be that humans don’t have a definitive answer for it yet. Humans design the product along with the model, Peng said.

“Part of what we’re doing here is also making sure that as the model improves, we’re able to evolve the interface and the behaviors that the model can do into a product that makes sense,” she said.

But what is clear is that humans are not trying to create a new model that can be plugged into existing applications and collaboration tools. The startup wants to own the collaboration layer.

AI as well as team collaboration and productivity tools is an increasingly hot field – for example, AI note-taking app Granola has sparked startup The round is $43 million With a valuation of $250 million as it launched more collaborative features. Many prominent voices are also working to clearly articulate the next phase of AI as one of coordination and collaboration, not just automation. Reed Hoffman, founder of LinkedIn, said today that companies are implementing AI the wrong way by treating it as silo pilots, and that the real impact is at the work orchestration layer — how teams share knowledge and manage meetings.

“AI lives at the workflow level, and the people closest to the business know where the actual friction is,” says Hoffman he wrote on social media. “They’re the ones who will figure out what should be automated, compact, or completely redesigned.”

This is the space in which humans want to live. The idea is that its modular product will act as a “connective tissue” across any organization – whether a 10,000-person company or a family – that understands the skills, motivations and needs of each person, as well as how to balance all of these skills for the benefit of all.

Achieving this requires rethinking how we train AI models.

“We are trying to train the model in a different way that will involve more humans and AI interacting and collaborating together,” Yuchen He, co-founder of Humans and former OpenAI researcher, told TechCrunch, adding that the startup’s model will also be trained using long-range, multi-agent reinforcement learning (RL).

Long-horizon RL aims to train the model to plan, act, review and follow up over time, rather than just creating a good answer once. Multi-agent RL trains for environments where there are multiple AIs and/or humans in the loop. Both of these concepts are gaining momentum Recent academic work Researchers are pushing MBA students beyond chatbot responses toward systems that can coordinate actions and improve outcomes across many steps.

“The model needs to remember things about itself, about you, and the better its memory, the better the user will understand it,” he said.

Despite the excellent crew running the show, there are plenty of dangers ahead. Humans would need untold large sums of cash to fund the expensive endeavor of training and scaling a new model. This means that they will compete with major players for resources, including access to computing.

But the greatest danger is that humans are not just competing with the world’s concepts and silences. It’s coming for Top Dogs of AI. These companies are actively working on finding better ways to enable human collaboration on their platforms, although they swear that artificial general intelligence will soon replace economically viable labor. Through Claude Cowork, Anthropic aims to improve collaboration in the way we work; Gemini is built into Workspace, so AI-powered collaboration is already happening inside the tools people are already using; OpenAI has recently been teasing developers about multi-agent orchestration and workflows.

More importantly, none of the major players seem willing to rewrite a model based on social intelligence, which either gives humans support or makes them targets for takeover. With companies like Meta, OpenAI, and DeepMind searching for top AI talent, mergers and acquisitions certainly pose a risk.

She told Humans & TechCrunch that it has already turned down interested parties and is not interested in being acquired.

“We think this is going to be a generational company, and we think this has the potential to fundamentally change the future of how we interact with these models,” Zelickman said. “We trust ourselves to do it, and we have great confidence in the team we have assembled here.”

This article was originally published on January 22, 2026.