Proception, a robotics startup founded by former Tesla Optimus engineer Jay Li, has settled a year-long trade secret lawsuit with Tesla and raised an $11 million seed round led by First Round Capital to build dexterous robotic hands. The company told TechCrunch it is now shipping the first batch of its high-dexterity hand to researchers and robotics companies while opening to wider orders. Y Combinator and early-stage fund BoxGroup also participated in the round.

Tesla sued Li and Proception in federal court in Northern California in June 2025, accusing Li of downloading confidential files related to robotic hand actuation onto personal devices before resigning and founding the startup six days later. The lawsuit alleged that Proception’s hands bore “striking similarities” to Tesla’s internal designs. After months of legal proceedings, the two sides reached a settlement and Tesla dismissed the case earlier this month.

Li told TechCrunch he views the experience as “a resilience test, or pressure test” and believes the company emerged stronger for having survived it. He also said he would not be surprised if Tesla eventually comes to Proception for help with its own hand problem. Tesla did not respond to a request for comment.

Dexterous manipulation, the ability to grasp, rotate, and manipulate objects with human-like precision, remains one of the most stubborn unsolved problems in robotics. Even Elon Musk has called robot hands one of the biggest engineering challenges yet to be solved. Kevin Lynch, the director of Northwestern University’s Center for Robotics and Biosystems, told the Wall Street Journal last year that his team believes it will be a decade before robot hands become functional and useful enough to do what humans do.

Li thinks Proception can move faster, largely because of how it collects training data. Most companies training humanoid robots use teleoperators, where a human wearing a virtual reality headset controls a robot remotely and the system learns from the commands. A key drawback, according to Li, is that the operator receives no tactile feedback from the objects the robot touches, and the approach is limited to however many robots a company has available.

Proception’s alternative is a sensor-laden glove that captures human hand interaction data without requiring a robot in the loop. The same glove also serves as the sensor-packed “skin” on the robotic hand Proception is developing, which has 22 degrees of freedom and multiple joints per finger. Li argues this combination of scalable data collection and high-dexterity hardware is what the market is missing.

The dexterous hand market has attracted significant capital this year. China’s Linkerbot, which holds 80 percent of the global market in high-degree-of-freedom hands, is targeting a six billion dollar valuation after shipping more than 1,000 units a month. Genesis AI, a European startup, raised $105 million for a wheeled robot with dexterous hands, and Chinese competitors like Xynova have raised nearly one billion yuan.

Proception is betting that most humanoid robot companies will buy hands rather than build them in-house, mirroring how the automotive industry treats specialised components. First Round partner Bill Trenchard, who led the investment, told TechCrunch that dexterous manipulation is “the last mile of getting these robots to be truly performant.” He also praised Li’s leadership under the pressure of the Tesla lawsuit.

Tesla has discussed producing Optimus at its Shanghai Gigafactory and has deployed more than 1,000 Gen 3 units across its own facilities, but the robot’s hands remain its weakest link. Musk has set a target price of $20,000 to $30,000 per unit and projected production scaling to tens of thousands by 2028. Whether Tesla builds its hands internally or eventually sources them from companies like Proception is one of the open questions in the humanoid robot supply chain.

More than 150 companies are now chasing the humanoid robot market, with billion-dollar valuations common and only 23 percent of enterprise buyers satisfied with the products available. In that environment, a startup selling the component everyone agrees is the hardest to get right has a clear pitch, even at the seed stage. Whether Proception can scale from its first batch of shipments to a position where it shapes how an entire category of machines uses its hands is the bet First Round Capital just made.

• Grand Theft Auto 6 is selling eight times faster on PS5 than Xbox says IGN
• Xbox disputes this, however, in a statement to Windows Central
• This potential bad news comes just as Xbox announced console price hikes

IGN has reported that, based on its internal affiliate data, Grand Theft Auto 6 preorders on PS5 are surging ahead of Xbox preorders of the game at a rate of eight to one — Xbox is now saying this is far from the full picture. Though, I have a hard time believing Xbox is doing a heck of a lot better than this data suggests.

In a statement to Windows Central, an Xbox spokesperson explained that “This doesn’t represent pre-order data. We’ve had record orders. People should wait for real data and not clicks on affiliate links.”

I’ve spent years watching gaming phones make the same promise and stutter at expected chores. Needless to say, I’ve learned to brace for the caveat every single time. The chip is fast, the display refreshes at a number that sounds impressive, and then, twenty minutes into a ranked match, the experience starts to crumble, heat builds up, and the frame output quietly falls off a cliff. Throttling is an almost inescapable reality of mobile gaming.

So when Infinix offered me a sit-down with the product manager behind the latest and greatest in its GT Series, I went in with the one big conundrum that I actually cared about. Has a brand finally built a phone around the heat problem instead of skirting around it? The answer, it turns out, is the entire pitch of the GT 50 Pro. And to the team’s credit, they didn’t miss.

Starting Hot

The biggest draw of the Infinix GT 50 Pro is the HydroFlow Liquid Cooling system. It’s the headline achievement, and the team is proud of engineering what it claims to be the industry-first 100% coverage of the core heat sources. Most phones cool a region and hope the rest sorts itself out. Infinix’s approach is active circulation, and when I asked about the engineering challenges of cramming that system into a slim chassis, the manager framed it as the most ambitious thing the series has done:

“The integration of the HydroFlow Liquid Cooling system represents our most ambitious engineering achievement in the Infinix GT Series to date,” Infinix GT Series Product Manager told me. What struck me was that they treated it as a design constraint rather than a marketing afterthought. The biggest concern, they explained, was that even a powerful chipset throttles  after fifteen or twenty minutes of heavy play, leaving you to pick between graphics quality and stable frames.

Nobody wants to make that choice mid-match. I don’t want to live with that constraint either, but on mainstream phones, it’s inevitable. What I think is the standout aspect of this phone is how   Infinix took the idea of building around cooling. Rather than treating the thermal system as a supporting feature bolted on at the end, the team designed the chassis to accommodate it first. It’s a bold claim, and when I pushed on whether the engineering actually backed it up, I saw it   working in more ways than one.

HydroFlow Liquid Cooling Architecture is the bold secret

Now, HydroFlow might sound like a fancy name, but it’s actually what the tech is all about. It’s   essentially a liquid that carries heat and keeps the phone running cool. The conversation got technical at this point, but I appreciated it because I wanted to get an inside look at the thermal engineering. Most phones cool a region and hope the rest sorts itself out. Infinix’s approach is active circulation.

“The liquid cooling system precisely targets and suppresses thermal stress right at the source.”

At the heart of the whole system is a piezoelectric-driven ceramic micro-pump moving specially formulated coolant at 6.5ml per minute across a 6,437mm² diaphragm, which they say is the largest in the industry. The channels carrying the coolant liquid are laser-etched at micron-level precision so that heat gets pulled directly off the components that generate it.

Over the years, I’ve heard a lot of cooling claims from different brands, but what made this one land was the durability data. Infinix told me that they ran over 720 hours of accelerated aging    tests, including punishing sessions at 75°C ambient temperature and 85% humidity. When subjected to those conditions, the ceramic pump can manage hours of continuous operation with minimal degradation. The real-world example they gave was the one that mattered the  most, and this is something that mobile gaming enthusiasts ultimately want to hear.

“During intense team fights when gaming, a sudden performance surge can spike total  power consumption to a 9W peak. Without efficient thermal management, instant SoC overheating will immediately trigger frame rate drops and severe stuttering,” the Infinix executive tells me. “The liquid cooling system precisely targets and suppresses thermal stress right at the source.” Simply put, that’s the difference between bold claims and material engineering you can actually feel making a discernible difference in your hands.

There’s a showy element, too, and I’ll admit I’m a fan. Instead of hiding all this liquid cooling wizardry, the Infinix GT 50 Pro puts a transparent Pipeline Window on the back so that you can watch the coolant liquid’s flow in real time. The design language leans into hypercar aesthetics. You get Kevlar and carbon-fiber-inspired textures, and aerodynamic  contours that the team says were inspired by hypercar wind tunnel testing to improve grip during long gaming sessions. When I expressed that the design was bold and that I quite  liked it, Infinix pointed out that the design maturity over the GT 10 Pro was deliberate. It leans less into the overt “gamer” class and edges closer to a refined performance machine.

The inside look

It goes without saying that cooling is the foundation for any performance-centric phone, and the Infinix GT 50 Pro embodies that label. A phone, however, still needs the right silicon to justify the hype. The latest from Infinix comes armed with the MediaTek Dimensity 8400 Ultimate silicon built atop the 4nm process. It’s a fairly powerful chip, but the team, in particular, focused on a few key perks. We are the first to feature MediaTek D8400 frame rate converter ( MFRC) , delivering GPU motion estimation and motion compensation technology, both of which combine to push the native 144FPS output while reducing the graphics engine load. The core logic behind the whole exercise is fairly obvious — deliver segment-leading frame rates with a cooling system that can actually sustain it for long gaming sessions.

Mobile gaming, however, is not all about the raw firepower. Internet speeds play a crucial role, too, especially if you’re engaged in fast-paced multiplayer games. Thankfully, Infinix paid attention to this aspect, as well. On the Infinix GT 50 Pro, Connectivity gets the same in-house treatment courtesy of the self-developed N1 network chip, which the team linked to with a 360-degree layout of twelve antennas. Lab tests tout a roughly 60% improvement in weak-signal environments, like elevators and underground garages. For online play, fewer signal drops matter as much as frames, so I’m glad that a robust on-device network infrastructure wasn’t an afterthought.
 
Then there is the Pressure-Sense GT Trigger, and as someone who has tested physical and capacitive shoulder  buttons on smartphones for years, this is where I get picky. The Open-Cut Pressure-Sense GT Trigger on the Infinix GT 50 Pro is special for multiple reasons. It delivers sub-20ms latency, offers ten levels of adjustable sensitivity, and lets you play with up to eight mapping points. These are fairly resilient, too, thanks to a claimed lifespan rated at over three million presses. I asked Infinix what tangible edge these triggers bring to the table for a serious player over capacitive systems, which I’ve always found a little vague under the finger.
 
“This physical tactile feedback allows pro-level esports players to feel exactly how much pressure they are applying, enabling much finer control than capacitive systems, which  often feel imprecise,” the Infinix executive tells me. The manager’s advice for anyone learning, including my own tech-obsessed siblings, was refreshingly practical. The best  way is to start with the built-in trigger tutorial in XArena, begin at medium sensitivity, and expect noticeable gains within a week or two.
 

AI done meaningfully

 
I’m usually skeptical when a gaming phone claims “AI optimization.” Gaming enthusiasts aren’t  fans of AI seeping into the world of gaming, either. Refreshingly, the GT Gaming Co-Lab pitch,   which is Infinix’s engineering partnership with game publishers, came with specifics I could dug  into. The team described three engines working together during a 144FPS session in titles such as Call of Duty: Mobile.
 
“Most gaming devices in the industry operate on a reactive model, they only try to suppress the heat after the phone has already overheated. The Infinix GT Gaming Co-Lab changes this paradigm.”
 
Simply put, the intelligent power allocation system dials back the CPU and GPU during low-intensity moments like early-game looting, so the device runs cooler before the fight even starts. The AI Frame Rescue Engine touts predictive foresight, as it anticipates a processing deficit a few frames before a heavy scene hits. When needed, it delivers a frequency boost to    rescue the frame before players can experience a frame drop. And as the thermals approach     their limit, the Game Thermal Control Engine jumps into action and dials down the frame output in progressive gradients instead of the big 144-to-60 FPS drop I’ve seen on a majority of smartphones.
 
“While other devices wait until they are boiling hot to start cooling down, the Infinix GT 50 Pro uses AI to prevent heat before it builds, rescue frames before they drop, and gently smooth    performance when thermal limits are pushed,” Infinix tells me. Whether it holds up under my   own testing is another article, but as a design philosophy, it all makes sense.
 
The GT Magcharge Cooler 2.0 further extends that thinking with industry-first wireless bypass charging, routing up to 15W juice directly to the motherboard so the battery is largely skipped  during the top-up session. The team tells me that they measured a 4°C drop in peak temperatures when compared to charging through the battery. On the topic of battery health, I asked why they capped wired charging at 45W while rivals chase bigger numbers. The decision was strategic, I was told.
 
“We refused to sacrifice long-term battery health and premium design for marketing gimmicks, delivering a phone that stays slim, light, and reliable for years,” says the Infinix executive I interviewed. The team zeroed in on 45W wired and 30W wireless output with a bypass charging facility. Furthermore, the AI battery self-healing tech helps the battery unit reach 1,600 charge cycles. I respect this approach, because it avoids marketing hype at the peril of real-world in-hand experience.
 

The ecosystem and the long game

My conversation with Infinix branched off toward the end, as interviews tend to do. Notably, the Infinix GT 50 Pro anchors what the company refers to as the New GT Ecosystem, an “esports  sanctuary” built alongside the GTWATCH 5 Pro and GTBUDS 5. The smartwatch acts as a tactical second screen, pushing notifications to your wrist so that the phone stays distraction-free, while also monitoring your heart rate. The buds lean on Bluetooth 6.0 and LE Audio standards to deliver an impressive 44ms latency, while Dolby spatial tuning delivers an immersive listening experience with sharp sonic details.
 
For an average value-conscious buyer eyeing a switch from a major brand, Infinix’s pitch is that you’re investing in a platform that keeps evolving through the Co-Lab’s software work rather than a phone that peaks on day one. And now that Infinix has progressed to the fifth iteration of the GT Series, they are reaching for a new standard. What’s changed is the levels of sophistication and a holistic approach.
 

 
“ In the long term, this ecosystem represents a much smarter investment. While many flagship phones deliver strong one-time performance that may degrade over time, the New GT Ecosystem is designed as a continuously evolving platform. Infinix has a clear 3–5 year roadmap that includes new additions like the upcoming GT Game Controller, which will deliver enhanced ergonomics and powerful haptic feedback synced with the phone’s vibration motor,” Infinix tells me.
 
“This results in faster reaction times, smoother execution of advanced maneuvers, and reduced finger fatigue during long sessions.”
 
I’ll reserve my final verdict for a full hands-on, because claims are claims until the phone is in my hands, sweating through a few intense online battles. But what makes the Infinix GT 50 Pro interesting isn’t any single number. On the contrary, Infinix made cooling the organizing principle and then built everything else, which includes the triggers, a proactive AI engine, the clever bypass charging tech, and a whole ecosystem. If you’re a hardcore mobile gamer who keeps running into the throttling curse, or chasing top-tier endurance without elite sticker shock, this is  a phone worth experiencing in person. On paper, at least, it’s the rare gaming phone that seems to understand its own asterisk and set out to delete it handsomely.

The 23-year-old founder of Emagen AI argues the entire agent industry is optimizing the wrong unit. His answer is an operating system where AI drives the work and calls on humans, not the other way around.

Every week, another AI agent startup launches. They write code, draft emails, generate slides, analyze data. Each one promises to make you more productive. Yimao Zhou thinks they’re all solving the wrong problem.

Zhou is the founder and CEO of Emagen AI, the company behind Cagen, what he calls an “OS Level Agent,” an organizational operating system powered by AI. Backed by MiraclePlus (formerly YC China) and its legendary founder Qi Lu, Zhou is betting that the future of AI isn’t about making individuals faster. It’s about making teams fundamentally different.

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We sat down with Zhou to understand what that means, and why he thinks 90% of today’s AI agent companies won’t exist in three years.

You’ve said that AI is actually making teams worse. That’s a pretty contrarian take given that every AI company is promising productivity gains. What do you mean?

Think about what happens when you give every person on a five-person team their own AI assistant. Each person produces more, faster. The product manager generates specs faster. The engineer writes code faster. The designer iterates faster. Sounds great, right?

But here’s what actually happens: the output diverges. Everyone’s moving faster in slightly different directions, and nobody notices until it’s too late. The bottleneck in a team was never “one person works too slowly.” It was always “are these five people building the same thing?” AI tools accelerate the parts that weren’t bottlenecks and make the real constraint, coordination, worse.

60% of knowledge workers’ time goes to what I call coordination costs, syncing progress, writing status updates, relaying information between people, waiting for approvals. And these costs don’t just exist between humans. In the AI era, they multiply: human-to-agent coordination, agent-to-agent coordination, the overhead of keeping everyone and everything on the same page. AI is optimizing the other 40%, the actual doing, and completely ignoring the 60%. That’s not just a missed opportunity. It’s a directional error.

So what should the industry be building instead?

Every major computing shift follows the same path: tools come first, then platforms, then an operating system emerges. PCs had standalone software before Windows. Mobile had individual apps before iOS and Android unified the experience. Cloud had scattered services before AWS became the infrastructure layer.

AI is on the same curve. Right now we’re in the “standalone tools” phase. Hundreds of agents, each doing one thing well, none of them talking to each other. The platform phase is just starting. The OS phase hasn’t happened yet.

That’s what Cagen is. Not another AI tool. The operating system layer for how organizations work with AI.

“OS Level Agent” is a big claim. In concrete terms, what does that actually look like?

Here’s a structural problem nobody’s addressing. Notion built Notion AI. GitHub built Copilot. Salesforce built Einstein. Every SaaS company is embedding AI, but their incentive is to make their own product stickier, not to connect you across tools. Notion AI makes Notion more valuable. It has zero incentive to help you bridge Notion to GitHub to Linear to Slack.

That means cross-tool intelligence is structurally impossible for any incumbent to build. It can only come from an independent layer.

Now, some people will say: “What about MCP? Anthropic’s Model Context Protocol already connects AI agents to multiple tools.” True, and MCP is great. But MCP is a connector protocol. It’s USB, not an operating system. It lets one person’s agent plug into that person’s tools. There’s still no shared organizational context, no persistent team memory, no cross-role orchestration. MCP actually benefits us. The more standardized the plumbing gets, the easier it is to build an OS on top.

Cagen is that OS. But here’s what really separates it from everything else, and this is the part most people miss. Every AI product today, including the ones that call themselves “team AI,” works the same way: capture information, organize it, and wait for a human to query it. The human is still the driver. The AI is a librarian.

Cagen inverts that. Our agents have goals and context. They continuously reason about what needs to happen next based on the team’s objectives, the project state, and organizational context. When they need human judgment, a decision, an approval, creative input, they call on the human. The human is a resource in the system, not the operator of the system.

That’s what makes it OS-level. An operating system doesn’t wait for you to manually manage every process. It runs, it schedules, it handles events. It calls on you when it needs you. That’s how Cagen works for teams, teams of humans and AI agents working together.

The AI market is brutally competitive. Investors will ask: what’s your moat?

After six months of using Cagen, what makes it irreplaceable isn’t any feature we built. It’s what your team built on top of it: decision patterns, communication habits, quality standards, workflow knowledge. All of that is deeply coupled to your specific organization. A competitor can clone every feature of Cagen. They cannot clone six months of your team’s accumulated intelligence.

This is the same reason Salesforce has industry-leading retention. It’s not because the CRM is irreplaceable. It’s because the data, processes, and automations running on it are irreplaceable. The product becomes an organizational asset, not a software subscription.

But here’s the important distinction: that stickiness comes from accumulated value, not artificial lock-in. We’re not trapping anyone. Teams stay because they don’t want to lose what they’ve built.

Individual AI memory is well understood. How is organizational memory different?

Fundamentally different. Individual AI memory scales linearly. I learn something, I benefit. Organizational AI memory has network effects. One person’s learning benefits everyone on the team, and every agent on the team. The compounding rate is n-squared, not n.

That’s why a “Team Agent” isn’t just a multiplayer version of a personal agent. It’s a completely different species. When one team member refines how competitive analysis gets done, that knowledge immediately elevates everyone else’s output, and every agent’s output. When the system learns how your organization defines “good,” what quality looks like, what tone you use, how you structure decisions, it raises the floor for every piece of work across the company, whether it’s done by a human or an agent.

Personal AI makes one person better. An OS Level Agent makes the organization smarter as a unit.

You keep saying “team.” But the trend right now is the opposite: more solo founders, more one-person companies. If teams are shrinking, who needs a team OS?

That’s exactly the right question, and the answer actually makes our case stronger.

There are actually two trends happening simultaneously, and they’re squeezing from both sides.

On one end, organizations are getting larger and more complex. Global teams, cross-timezone coordination, regulatory overhead, multi-vendor supply chains. The coordination burden inside large organizations keeps growing.

On the other end, individuals are getting smaller and more independent. Layoffs are accelerating. The freelancer economy, digital nomads, solo founders, one-person companies, they’re all exploding. But here’s what people miss: a solo founder doesn’t work alone. They hire a freelance designer on Fiverr, a contract developer on Upwork, a fractional CFO, a marketing consultant. The “team” still exists. It’s just not a fixed org chart anymore. It’s fluid, temporary, project-based. And increasingly, it includes AI agents as full team members.

Both ends need the same thing: an orchestration layer. And that need is going to intensify. Work is atomizing. You’ll see more and more granular needs matched with more and more specialized providers, on-demand, globally, in real time. The old model was: hire five full-time employees, put them in an office, manage them. The new model is closer to Uber for work. Assemble the right people and agents for the right task, execute, disband.

But here’s the problem with that model: coordination costs explode. When your “team” is a rotating cast of freelancers, contractors, and AI agents who don’t share context, don’t know each other’s working style, and don’t have shared history, the coordination problem we talked about earlier gets ten times worse.

That’s where Cagen becomes essential. It’s the orchestration layer. It holds the organizational context, the project history, the quality standards, and it dispatches work to the right people and agents at the right time. The solo founder doesn’t need to manage anyone. Cagen manages the constellation.

So “team” doesn’t mean five people in a Slack channel. It means any group of humans and AI agents collaborating toward a goal. The more fluid and atomized work becomes, the more you need an OS to hold it all together.

Who are your first customers? I’d assume tech startups.

Actually, no, and this is counterintuitive. Tech companies already have deeply entrenched toolchains. Slack, Notion, Linear, GitHub. They’re locked in, and the switching cost of adding an OS layer is highest for teams that have already optimized their existing stack.

Our best early customers are organizations with high operational complexity but without deep commitment to any specific tool ecosystem. We’re currently deployed with a boutique hotel in Pittsburgh, for example. A hotel operations team juggles guest communication, maintenance coordination, shift scheduling, vendor management: dozens of handoffs per day across multiple roles. The coordination costs are extreme, but they haven’t built their workflows around a rigid SaaS stack.

That’s the sweet spot: complex enough to need an OS, flexible enough to adopt one. And if it works in hospitality, one of the most operationally dense environments for small teams, it works anywhere.

But hospitality, CPG, logistics: these are all very different industries. How do you scale across all of them without becoming a custom consulting shop?

This is the question everyone asks, and it’s the right one. The traditional answer is: you hire industry experts, do bespoke integrations, and it doesn’t scale. That’s the consulting trap.

Our answer is different. Think about the pipeline from customer acquisition to deployment: understanding a client’s operations, identifying where AI fits, building the right workflows. There’s no inherent reason that entire process has to rely on humans.

The bottleneck today is a mismatch. Non-technical users don’t understand what AI can and can’t do. At the same time, they struggle to articulate their own needs clearly. That’s why every AI integration today requires someone who has both domain expertise and AI expertise, and that combination is extremely rare and expensive.

Cagen’s roadmap is to fuse those two together inside the product. Ideally, a user just describes what their team does day to day, along with their company’s goals. The system then automatically understands, decomposes, and constructs the right workflows. It’s an automated consulting and execution layer. The AI doesn’t just run your workflows; it figures out what your workflows should be.

We’re not there yet. Nobody is. But even at the current stage, the approach gives us a structural advantage. And where full automation isn’t possible today, we can route specific needs into a marketplace: humans acting as builders, similar to Upwork or Fiverr, but orchestrated by the system. That turns bespoke integration from a consulting problem into a platform problem. And platform problems scale.

You were backed by Qi Lu, who decided to invest ten minutes into a thirty-minute pitch. That story’s been told before. What does it actually mean to you now, looking back?

What it means is that he wasn’t investing in a product. He was investing in a judgment.

Qi Lu spent his career at the OS layer: Executive VP at Microsoft, President and COO at Baidu. When he heard me describe the AI agent landscape as “everyone building apps, nobody building the operating system,” he didn’t need a demo. He’d lived through that exact pattern before. He knew what happens when someone identifies the right abstraction layer early.

Most AI pitches are “we do X better than Y.” My pitch was “the entire industry is building at the wrong layer.” He recognized the difference immediately. That’s what the ten minutes were about.

Claude Code surpassed $2.5 billion in annualized revenue by early 2026, contributing to Anthropic’s $44 billion total run rate by mid-year. OpenAI Codex has 5 million weekly users. OpenClaw has over 370,000 GitHub stars, more than the Linux kernel. Whether backed by the most powerful AI labs or the open-source community, the momentum behind AI agents is massive. How do you compete with that?

I don’t. Because we’re not playing the same game.

Look at what those products actually are. Claude Code is a terminal agent that helps one developer mass-produce code. Codex is the same thing inside ChatGPT. OpenClaw is an open-source personal assistant that runs on your laptop. They’re all extraordinary at what they do, and what they do is make one person more productive.

Claude Code even has something called “Agent Teams.” Sounds like team collaboration, right? It’s not. It’s one person orchestrating multiple AI instances. There’s no shared context between team members. No organizational memory. No cross-role coordination. Codex’s “Business plan” is seat management and billing. It doesn’t change how the product works at a team level.

This is exactly my point. The best-funded, most talented AI labs in the world are all converging on the same thing: supercharging individuals. They’re building the most powerful apps the world has ever seen. But nobody is building the OS.

There’s a way to think about this that I find clarifying. The infrastructure for AI-assisted coding, what some people call the “coding harness“, is essentially a solved problem. It’s a continent. Claude Code, Copilot, Cursor, Codex: the land has been claimed. But the infrastructure for AI-assisted working, coordinating teams, managing goals, orchestrating humans and agents together, is still a vast blue ocean. There are a few small islands, but no continent. That’s where we’re building.

When your engineer uses Claude Code and your product manager uses OpenClaw, each person gets faster. But the coordination between them, the context, the decisions, the handoffs, still travels through Slack messages and status meetings and Google Docs that nobody reads. The coordination costs are completely untouched.

That’s the gap. It’s not a feature gap. It’s a layer gap. And it’s not going to be filled by Anthropic or OpenAI, because their business model is selling seats to individuals. An OS for organizations is a fundamentally different product with a fundamentally different architecture.

Last question. Three years from now, what does the AI agent industry look like?

Most of today’s AI agent startups will be dead. Not because they’re bad, but because they’re building at a layer that’s about to get commoditized. When you’re essentially wrapping a prompt around a foundation model and optimizing for one vertical, your moat is prompt engineering. That’s not a moat. That’s a sand castle.

The survivors will be companies that built at a layer the foundation models can’t easily absorb. For vertical agents, that means deep domain-specific data flywheels. For us, it means the OS layer: the orchestration and organizational intelligence that sits above any single model.

But the real disruption isn’t about which companies survive. It’s about what becomes possible. The minimum viable team size for a serious business is about to collapse. Things that required 50 people will require 5 people plus an AI operating system. That doesn’t just change how companies work. It changes which companies can exist. A massive number of business ideas that didn’t pencil out under the old model suddenly become viable.

Three years from now, people won’t ask “what AI tool do you use.” They’ll ask “what OS is your team running on.”

Yimao Zhou is the founder and CEO of Emagen AI, the company behind Cagen. He previously studied medicine at Shanghai Jiao Tong University and cognitive philosophy and philosophy of science. He was the youngest founder in MiraclePlus’s F24 cohort. Learn more at cagen.ai.

China’s Guizhou province has once again made a name for itself by going overboard with extreme infrastructure; the Huajiang Grand Canyon Bridge is a new addition to the list as the world’s highest bridge, with its roadway dangling 625 meters over the Bei Pan River. Drivers may pass by in about a minute flat, which represents a big improvement over historic mountain roads and ferry crossings that used to take more than an hour if they were fortunate.

The Liuzhi-Anlong Expressway is a beast, winding its way through a stunning karst landscape of towering limestone cliffs and deep valleys, spanning a 2890-meter-long bridge from one side of the abyss to the other. The longest part is 1420 meters and is situated between two towers that stand 262 meters tall. With the alpine scenery in the background, it’s a genuinely stunning effort. The bridge is remarkable on its own, but what was added during construction elevates it to new heights.

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When one of the engineers boring a tunnel on one side of the bridge came across a massive underground water flow in the porous karst rock, they could have simply drained it all, but they chose to collect it in a reservoir and pump it back up to the bridge deck. According to Chinese government media, it was spread in the center of the main span to create this gigantic, misty waterfall that is approximately 300 meters wide and has a 600-meter cascade, making it the world’s largest artificial waterfall. With a simple adjustment of the pressure, you can change the height as well as volume of the spray, and when the sun sets, laser lights illuminate it, making the entire thing shimmer. Bonus points: the water is utilized to irrigate the fields next door, it serves as a comfortable rest stop for passing truckers, and it keeps the toilets operating.

People who have crossed the bridge, on the other hand, describe it as terrifying from above. The vehicles on the deck resemble small matchboxes, and several passengers have reported feeling as if they are nearly touching the clouds with their fingertips. The construction team, who spent months creating the thing, gushed about the breathtaking vistas and how many first-timers enjoy standing on the edge.

People now flock to the bridge for more than just the views, since there is now a glass walkway beneath the deck that provides an unobstructed view straight down into the valley, as well as a bright new glass elevator that transports visitors to a cafe high above the bridge, ideal for a coffee with a view. The bridge even provides some death-defying activities, such as bungee jumping and paragliding, with intentions to organize base jumping events soon.
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Ninja makes some of the most useful kitchen gadgets on the market, and the Crispi is up there with our favourites.

The Ninja CRISPi Glass Air Fryer is down to £119.99 from £149 right now, and that £29 saving is worth acting on before the price creeps back.