Big tech salaries are climbing into the millions. For startups, the gap has never looked wider. Yet founders at TechCrunch Disrupt 2025 say early stage companies can still attract world class talent by focusing on fairness, ownership, and purpose over paychecks.

Yin Wu, the founder and CEO of Pulley, said startups should stop trying to compete with big tech altogether. Instead, they should design compensation packages that make people feel like owners from day one.

“My strong opinion is that you should be more generous than you think you should be,” Wu said. “If the company becomes successful, you will never regret sharing that success with the people who helped you build it.”

Equity with purpose
Startups cannot match Meta or OpenAI in cash, but they can build value through equity. Randi Jakubowitz, head of talent at 645 Ventures, said every startup offer should connect performance with ownership.

That means setting clear goals, creating fair vesting schedules, and acting quickly when things do not work out. “If someone is underperforming and you wait too long, that is equity you will never get back,” she said. Accountability matters as much as generosity.

Build fairness early
Rebecca Lee Whiting, founder of Epigram Legal, said the best founders design compensation systems that are consistent from the start. They pay within set ranges for each role and document how equity is calculated. That transparency prevents bias, supports compliance, and protects the company as it scales.

Wu said Pulley follows a simple rule. Every role has a fixed pay band regardless of where someone lives, and all employees receive equity packages ranked in the ninetieth percentile. “It helps us grow without creating chaos. The structure stays fair even as the value changes,” she said.

Focus on intent, not perfection
Early stage founders often feel pressure to get everything right immediately. Whiting said the goal is to build with good intent, not flawless execution. “You will likely have to clean things up after your Series B, and that is okay,” she said.

Fairness, clarity, and flexibility are the real advantages startups have over massive companies. They can offer purpose and ownership in place of oversized paychecks.

The real takeaway
A strong startup compensation strategy is not about chasing numbers. It is about aligning people with a shared outcome. When done right, it builds loyalty, keeps teams focused, and gives founders the credibility to hire great people at any stage of growth.

When Manuele Aufiero was a child, his parents would take him hiking along a reservoir in northern Italy. It was not just a lake to him. It was alive. Pumps would lift water up when electricity was cheap and let it rush down to generate power when cities needed energy.

That simple idea of moving water uphill and downhill is the foundation of pumped storage hydropower, one of the oldest and most reliable ways to store electricity. Across the world, these reservoirs hold roughly 8,500 gigawatt hours of energy. They act like giant batteries, balancing the ups and downs of solar and wind.

But there is one big problem. Pumped hydro only works where the land allows it. You need mountains, valleys, and water. There are only so many places left to build one.

“I am in love with pumped hydro,” Aufiero told TechCrunch. “It’s just not enough to keep up with renewables.”

So he took the idea somewhere no one had gone before, under the sea.

Aufiero co-founded Sizable Energy, a startup that wants to move the concept offshore. Instead of carving dams into mountains, Sizable builds flexible reservoirs that float and sink in deep water. The company recently raised 8 million dollars in a round led by Playground Global, with backing from EDEN/IAG, Exa Ventures, Satgana, Unruly Capital, and Verve Ventures.

At first glance, Sizable’s design looks like an hourglass. One soft reservoir floats on the surface while another sits on the seabed. A tube connects them, along with a series of turbines. When electricity is cheap, those turbines pump salty water from the bottom up. When the grid needs power, the process reverses the dense brine falls back down, spinning the turbines and generating electricity.

From a physics standpoint, Aufiero says, it is like lifting a heavy block of salt. But instead of cranes and cables, Sizable dissolves the salt in water. The energy is stored as potential weight rather than chemistry, and that makes it scalable and reusable.

On land, each pumped hydro site must be custom-built for its location. Offshore, every Sizable system can be identical. That uniformity means mass production, faster installation, and lower costs.

Sizable has already tested small-scale models in wave tanks and off the coast of Reggio Calabria, Italy. The company plans to deploy a full demonstration unit by 2026 and several commercial sites soon after. Each turbine can generate up to seven megawatts, and deeper ocean sites can store far more energy.

The cost target is about twenty euros per kilowatt hour, roughly one tenth the price of large grid batteries today.

That price could make ocean-based storage a powerful partner for offshore wind projects, which already share transmission lines back to shore. But the same system could connect to any coastal grid as long as the water is deep enough, at least five hundred meters.

“We believe that long duration energy storage is required not only for renewable integration but also to make the grid resilient,” Aufiero said. “We need something new.”

If it works, Sizable Energy could open an entirely new category of energy infrastructure. The ocean is vast. Using it as a global storage network could stabilize renewables at scale, cut costs, and reduce the need for expensive lithium-based systems.

For now, the company is focused on proving it can operate safely and reliably in real ocean conditions. But if Sizable succeeds, it could redefine how the world thinks about storing power not just in batteries, but in water itself.

Read the original report by Tim De Chant at TechCrunch.

For more Laterstack startup insights, The Startup Teaching Machines How to Work Like Humans and Cluely AI cofounder says startups fail because engineers cannot make viral content.

In a small factory outside Shanghai, a new kind of worker is learning how to move. Its name is AgiBot, a humanoid robot that can be trained by people in real time to assemble electronics, test parts, and pass them down a production line.

AgiBot’s idea is simple but radical. Instead of teaching robots through endless simulation, the company pairs each machine with a human trainer who guides it through a task for about ten minutes. Then the robot learns to repeat it alone. This process, known as real-world reinforcement learning, blends human intuition with machine precision.

It is already being tested by Longcheer Technology, a major Chinese manufacturer that builds smartphones, VR headsets, and other electronics. The AgiBot system allows robots to take on repetitive but high-volume tasks, such as moving components from testing machines to assembly lines, while still adapting to shifting workflows.

Unlike traditional industrial robots that perform rigid motions, AgiBot’s machines learn through touch, vision, and trial. They are not coded to complete one routine forever. They evolve through repetition, much like human workers do.

Behind the system is Jianlan Luo, a UC Berkeley researcher turned entrepreneur. Luo helped pioneer human-in-the-loop robotics research in California before bringing the idea home to Shanghai. At AgiBot, his team of engineers and teleoperators trains robots for different factories across China, from electronics to consumer goods.

Training robots this way takes a surprising amount of human effort. In AgiBot’s training center, hundreds of operators guide robot arms through tasks, generating data that improves the company’s learning models. It is part of a growing trend in robotics where human labor fuels machine intelligence.

“Robots are not replacing workers,” said Yuheng Feng, an AgiBot representative. “They are learning from them.”

Each robot session creates more adaptable code, faster learning cycles, and smarter machines that can move to new production lines without weeks of reprogramming. For manufacturers, that flexibility is gold.

China’s government has made robotics a core focus in its latest five-year plan, alongside artificial intelligence and automation. The country already operates more industrial robots than the rest of the world combined, giving startups like AgiBot a vast playground for scaling quickly.

Experts say this fusion of human skill and robotic learning could define the next phase of manufacturing. “AgiBot is using some of the most advanced reinforcement learning seen outside a lab,” said Jeff Schneider, a Carnegie Mellon roboticist. “If it works as described, it could reshape how factories operate.”

Across the Pacific, startups in the United States are racing to catch up. Companies like Physical Intelligence and Skild are developing similar models that teach robots to adapt to new shapes, arms, and environments. But China’s scale and production speed may give AgiBot a lasting advantage.

AgiBot’s long-term goal is to create humanoid robots that can walk, handle tools, and work alongside people safely. For now, its focus remains clear: give robots a human touch and let them learn from the people who know the work best.

The quiet revolution is already underway, and it is not happening in a lab. It is happening on a factory floor where humans and machines are learning to build the future together.

Read the original coverage at WIRED.

Explore more Laterstack startup insights:

• Cluely AI cofounder says startups fail because engineers cannot make viral content

• Saquon Barkley joins Nvidia in $1.4 billion investment in data center startup Crusoe

[thb_gap height=”150″]

Born raises $15 million for a social approach to companionship tech.

In an era where chatbots promise intimacy but often deliver isolation, a Berlin startup wants to flip the script. Born, the company behind a breakout AI pet app called Pengu, has raised a $15 million Series A to build what it calls “social AI companions.” The goal is simple and ambitious: turn the loneliness epidemic into a shared digital experience.

Born’s flagship product lets users co parent a virtual penguin with a friend, partner, or sibling.

It is a Tamagotchi for the generative age, but one that requires another human to unlock its full potential. That social layer is what CEO Fabian Kamberi says separates Born from the rest of the AI companion market, which he describes as “exploitative and isolating.”

“Most companions today are built to trap you in one to one relationships with a bot,” Kamberi says. “We want to make AI fun, playful, and rooted in real connections.”

A Penguin with Network Effects

The numbers show early traction. Pengu has reached over 15 million users worldwide, though the company has not disclosed how many are paying subscribers. The business model relies on a freemium structure, with extra features locked behind a monthly “Pengu Pass.” That lack of transparency raises the familiar consumer startup question: can free scale be converted into real revenue. For now, investors appear confident. The round, led by Accel with participation from Tencent and Laton Ventures, brings Born’s total funding to $25 million.

“Pengu is proof that AI companions can be a social category, not just a chatbot,” says Luca Bocchio, a partner at Accel. “We see this as the beginning of a new consumer social platform.”

From Teen Compliments to Digital Friends

Born is not Kamberi’s first attempt to redesign online interaction. Under its former name, Slay, the startup ran a viral social app for teenagers where users exchanged compliments. The pivot to AI pets keeps the same ethos, technology as a bridge to healthier, more positive interactions. This fall, Born will expand its lineup of characters, adding a new “cute” companion designed to double as a learning coach. The company is also opening a New York office to support marketing and AI research. That research includes building a character engine that allows AI pets to form consistent personalities, remember past conversations, and evolve alongside their users.

The Next Phase: Cultural AI

Perhaps the boldest bet is still under wraps. Born is preparing to launch a second product aimed at users ages 16 to 21. While details remain scarce, Kamberi describes it as “culturally relevant companions” that behave more like real friends than scripted bots.

Instead of static chats, these companions might send TikTok clips, Instagram Reels, or memes tailored to the user’s taste. “We believe this product will have network effects as people share their AI friends across social platforms,” Kamberi says.

If Pengu was about co parenting, this next act is about co creating, making AI characters that feel woven into daily digital culture.

The Larger Question

For investors, the upside is enormous. Consumer social remains one of the few categories where a single breakout can generate hundreds of millions of users almost overnight. If Born succeeds, it could define a new form of social media built around emotional engagement rather than passive feeds.

But the stakes are also high. The loneliness epidemic is not a market trend to be casually gamified. Critics warn that AI companionship, even in social form, risks blurring the line between authentic bonds and algorithmic simulation.

Born is betting that the future of friendship is not replacing people with bots, but enhancing human connection through them. Whether Pengu and its successors can deliver on that vision will determine if this $15 million round is the seed of a new social category or just another fleeting experiment in the crowded consumer AI race.

Have a tip? Reach out at laterstack@proton.me