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“I help organize FYSK, and even I don’t know what’s going to happen at the show.”

— David King, *emcee extraordinaire*

On November 18, we’re back at OpenAI in San Francisco with ten founders whose perfectly reasonable plans include:

🌊 Developing autonomous, ocean-roaming data centers powered by the sea.
🏢 Buying billion-dollar businesses and reinventing them with AI.
🛰️ Building the communications backbone for the space economy.

And that’s just the planned part of the evening..

Come meet the founders and see what happens. You might get a few exclusive founder updates. You might meet hear an ewi being played. You might end up dancing on a table. You might even leave with a new job.

Which, beneath all the novelty eyewear, is the point.

Our last showcase of the year. APPLY TO ATTEND!

We’re already near capacity so APPLY NOW to meet the founders in person! Give yourself the one thing nobody else can get you for the holidays: a new job you’re excited about.

This lineup spans ocean-powered compute, robot training, satellite communications, circuit-board manufacturing, molecular discovery, and the software and infrastructure putting AI to work.

On November 18th, the following 10 founders will take the FYSK stage:

• Garth Sheldon-Coulson, founder of Panthalassa

• Davide Asnaghi, founder of Diode Computers

• Varun Shenoy, founder of Long Lake

• Moritz Stephan, founder of Hone

• Vasek Mlejnsky, founder of E2B

• Ronak Malde, founder of Trajectory

• Philipp Wu, founder of XDOF

• Peter Voell, founder of Mount Thor

• Bridgit Mendler, founder of Northwood Space

• Navvye Anand, founder of Bindwell

A huge thank you to the community members who nominated these founders and made the introductions. Many of the top companies we feature start with someone in the FYSK orbit saying, “You should meet this founder.” Major thanks to Scott Nolan, Walden Yan, Jared Rosner, Mike Liu, Zabie Elmgren, Juan Lozano, Ravi Rahman, Tiger Sun, Eryk Dobrushkin, Max Mailman, Reggie Williams, Andrew Palacci, Amit Narang, Clara Shen, Justin Leong, Larry Erwin, Brittany Walker, Devin Gupta, Elena Deslongchamps, and Mike Annunziata.

And a sincere thank you to Larry Erwin and the team at OpenAI for hosting us again!

Want to meet these founders? Apply to the November 18th showcase. If you’re new to FYSK, apply to join the community too.

For an engineer choosing what to work on next, “hard problem” isn’t enough. A more useful question is what becomes possible if you solve one: pesticides protecting crops while sparing pollinators, robots learning to cook dinner, AI agents working through the night, or larger satellite fleets staying connected to Earth. The four founders below are building toward those possibilities.

Philipp Wu, Co-Founder of XDOF

Try explaining how to tie a shoelace without using your hands. At some point, it’s easier to say, “Here, let me show you.” AI labs such as Google DeepMind are now adapting their models to control robots that can tackle many different tasks. But the language and images that helped those models understand the world don’t tell them everything about acting in it. They also need experience of movements and their consequences.

At Berkeley, Philipp helped create GELLO, a small, 3D-printed arm that lets a person guide a larger robot through a task. XDOF now supplies robotics teams with physical demonstrations and tests their models on real machines. With research collaborators, it has released more than 130,000 demonstrations across nearly 200 tasks. That shared foundation could let more teams try new approaches to robot intelligence without first building an operation to collect experience and test what their robots learned.

Peter Voell, Founder of Mount Thor

Stealthy!

Bridgit Mendler, Co-Founder of Northwood Space

During the pandemic, Bridgit Mendler and her husband, Griffin Cleverly, built antennas from Home Depot supplies at a New Hampshire lake house to receive weather-satellite data. Today, their company Northwood is building the network that lets satellite operators make those connections reliably, at a much larger scale.

Commercial satellite fleets are growing, but the ground infrastructure they rely on has been slow to manufacture and deploy. SpaceX is focused on the sky, not the ground. More satellites can mean more frequent images of a changing planet.. provided operators can get the data back to Earth.

Northwood builds antennas, deploys sites and runs them as a shared network. Its Portal system can communicate with multiple satellites simultaneously, and a new Torrance factory is designed to produce hundreds of antennas a year. Bridgit’s goal is for a space company to add a mission without waiting for its ground connections to catch up.

Navvye Anand, Co-Founder of Bindwell

An AI system that learns from physical experiments could change how we discover medicines, protect crops and make useful materials. That’s the promise of bringing AI into the wet lab: each experiment can test a proposed molecule and help train a model to find better ones. Navvye Anand and Tyler Rose are building Bindwell around that possibility.

They’re starting with pesticides. Global agricultural production was worth $5.2 trillion in 2024; even small improvements in protecting harvests could mean more food from the land we already farm. Bindwell’s first target is fall armyworm, a caterpillar that can devastate maize harvests. The goal is to stop the pest while minimizing harm to people, pollinators and other beneficial species.

The founders built their own lab to test candidate pesticides on insects and use the results to improve their AI. Bindwell says it can now measure the early success rate of a model’s proposed compounds in these lab tests in about 72 hours. The ambition is for what it learns about one molecule or organism to help it tackle the next—a system that becomes more capable of discovery as it experiments.

Come meet Philipp, Peter, Bridgit, and Navvye—and the rest of the lineup. Apply to attend the November 18 showcase.

Hone, E2B, and Trajectory are working on different parts of the answer. Hone is building AI teammates that can take responsibility for work. E2B gives agents isolated cloud computers to run code and use tools. Trajectory is building a way for the models behind AI products to learn from real-world usage.

Join us November 18 at OpenAI in San Francisco for our final Startup Showcase of the year. Apply to attend.

Played last week’s lineup guessing game? The answers and our LEGO raffle winner are below!

Moritz Stephan, Co-Founder of Hone

At Cognition, colleagues used to say they needed ‘five more Moritzes’ according to Index Ventures. Moritz Stephan helped build the system that lets Devin plan and carry out coding tasks, then became chief of staff, taking on work across strategy, hiring, and product. The appeal of a colleague like that is easy to understand: you can hand them a difficult problem and trust them to figure out what needs to happen next.

Hone is building AI teammates designed to earn that kind of responsibility. You set a goal and boundaries, and the system learns the company’s processes and the people it needs to work with. For a customer rollout, that could mean tracking down missing information, coordinating handoffs, and following up before the whole thing stalls.

Giving an AI that much responsibility raises an obvious question: how do you know it’s ready? Hone lets teams test its AI teammates, called Engines, against work their company has already done. They can review how an Engine handles past tickets, deals, and decisions, give feedback, and judge whether it’s ready for live work. That puts a substantial engineering problem behind a familiar human expectation: a new colleague should learn how things work and become someone you can increasingly rely on.

Vasek Mlejnsky, Co-Founder of E2B

Vasek Mlejnsky and Tomas Valenta were supposed to be taking a break. In 2023, burned out from their developer-tools startup, they gave themselves two weeks to experiment with GPT-3.5. They built an agent that could run code in their existing sandbox, and the demo took off.

The cloud was built for humans, not agents. While a human chooses and configures the software they want to run, an agent can be writing new code, trying tools, and changing its approach while the job is already underway. You want your agent to have room to experiment. You don’t want it experimenting on the server your customers are using. E2B gives agents their own isolated cloud computers, where they can run applications, work with files, and test what they’ve built.

E2B says 94 of the Fortune 100 have signed up, and more than 100,000 teams are on the platform. That’s a substantial audience for a company whose broader ambition is still taking shape: Vasek envisions a cloud where agents can assemble the tools and computing resources they need as a job unfolds. For engineers joining now, there’s a working platform to build on and a fundamental design question still open: what should the cloud look like when software is doing both the work and the asking?

Ronak Malde, Co-Founder of Trajectory

Every time you fix an AI’s answer, you’re showing it what better work looks like. Whether the underlying model learns anything from that correction is a separate question.

Trajectory is building around that gap. Its approach uses signals such as edits and retries to train the models behind an AI product, with updates evaluated and approved before reaching production. Ronak helped train Windsurf’s SWE-1 coding model before working at Google DeepMind. Now he wants to put model training within reach of product builders. He doesn’t think you should have to assemble an ML team to improve the model behind your product.

The bigger vision is continual learning across the model, its prompts, and the software directing an agent’s work. A product team could use what it learns from its customers to improve the AI itself, without waiting for the next big model release.

Last week’s puzzles, solved 🧩

Thanks to everyone who took a guess at our November lineup! Here’s what each picture was pointing to:

1. Hone — “Phone” minus the P leaves Hone.

2. Long Lake — Exactly what it looks like: a very long lake.

3. Diode Computers — “Die” minus the E, plus an ode and two computers.

4. Panthalassa — A panther and a lasso: say them together for the sound-alike clue.

And congratulations to Richard Chao, our LEGO raffle winner! Your mini LEGO set will be waiting for you at the November 18 showcase.

Apply to the November 18 showcase to meet these founders in person.

You can meet the founders behind all of them at our next showcase. Panthalassa is using ocean waves to power offshore AI compute. Diode designs and manufactures circuit boards in its own factory. Long Lake buys established businesses and puts engineers inside them to rebuild how they operate.

Join us November 18 at OpenAI for our final Startup Showcase of the year. Apply to attend.

Garth Sheldon-Coulson, Founder of Panthalassa

Finding somewhere to build a data center is getting complicated. There’s the grid connection, the land, the cooling water, and the neighbors. Panthalassa is betting on a location with a different set of challenges: the open ocean.

Panthalassa is building autonomous ocean nodes that generate electricity from waves and use that power on-site to run AI inference. Instead of transmitting electricity back to land, the company puts the compute next to the energy, cools it with seawater, and sends the resulting data back over satellite. Garth and the team have been working on the same basic idea for a decade, and Panthalassa patented wave-powered computing grids back in 2018, years before data-center power shortages became a mainstream concern in AI.

This year, the company raised a $140M Series B led by Peter Thiel to finish its Oregon manufacturing facility and deploy its first Ocean-3 nodes.

If you’re wondering how you keep an AI data center running in the middle of the Pacific, come meet Garth at the showcase.

Davide Asnaghi, Founder of Diode Computers

Software engineers can change their code and test it in minutes. Hardware engineers often have to send a design to a factory and wait for a finished board before discovering what needs to change. Diode is working to shorten that loop. Customers bring requirements or an existing board, and the company handles design, fabrication, and assembly.

Davide told us that some of the most important work happens in the details of manufacturing. Diode’s models account for things like production yield and drill-bit failure rates. The team has also reverse-engineered manufacturing equipment and written its own software to make production faster and more reliable.

When we spoke, Diode had already shipped more than 400 unique board designs this year. The company raised an $11.4M Series A led by a16z and its customers include Physical Intelligence and Saronic.

If you want to help build hardware that feels more like shipping software, come meet Davide at the showcase.

Varun Shenoy, Founder of Long Lake

Most AI companies build software and then try to convince an old-school business to adopt it. Long Lake skips that step and buys the business.

Long Lake acquires what the team calls “sleepy American industries” and embeds its own engineers directly inside them. That gives Long Lake the workflows, historical data, employees, and customers needed to actually redesign how the business operates with AI. Its engineering team spans a shared platform called Nexus, vertical-specific AI systems, and forward-deployed engineers who sit with users and bring bottlenecks back to the product team.

In September, Long Lake completed its $6.3B acquisition of American Express Global Business Travel, taking the company private and bringing Long Lake’s AI engineering team into one of the world’s largest corporate-travel businesses.

If you want to be at the forefront of deploying AI into the real economy, come meet Varun at the showcase.

Apply to the November 18 showcase to meet these founders in person.

Come join us on November 18 at OpenAI, for your last chance to find a new role before the holiday hiring slow-down. If you’re hoping to start 2027 in a new role, now’s the time to get those conversations going.

The full lineup is coming soon. In the meantime, we’ve hidden four of the company names in a series of picture puzzles. Decode each one and submit your guesses. They start easy and get trickier as you go 👀

Think you can crack the lineup? Play here →

And because you apparently need more things to build, there’s a mini LEGO set up for grabs. Play and submit your entry by next Friday the 23rd at noon PT, and make sure you’ve applied to the November 18 showcase to be entered into the raffle. We’ll have the winner’s prize waiting at the show.

If a new role is on your mind for 2027, this is a good time to start the conversation. Apply Now!

Four rounds. Three startup pitches each. Two are real companies we’ve featured at FYSK. One we made up. Each round gets harder, though spending too much time at founder dinners or FYSK showcases may give you an unfair advantage..

Take the quiz: Spot the fake startup

As you play, ask yourself which one you’d actually want to work on. You might discover a company you’d never thought to look for. The reveals link to the real companies’ career pages, so you can explore their open roles.

If your favorite is fake, we’ve included a starting point for building it yourself 👀.

Find a company or role you’re excited about? Email me a short blurb about yourself and why you’re interested, and I’ll forward it to the founder!

If you’re wondering where talent, capital, and technical ambition are converging right now, our last Founders You Should Know showcase offered a pretty good snapshot.

Last Wednesday, 300+ people packed into OpenAI to meet 10 founders building across robotics, AI research, critical infrastructure, mining, human simulation—and even data transfer through space. These are companies hitting real inflection points, tackling hard technical problems, and attracting growing attention from both engineers and investors.

“Hearing from the founders in real life and having the chance to chat with them is the most effective way to find out whether there’s a fit.” - FYSK engineer, Sept. showcase attendee

And if you were in the room, you got more than the usual pitch: founders shared the stories behind the companies, the problems they’re obsessed with solving, and a few things that aren’t public yet. Sorry, we still can’t tell you. It’s a secret. 🤭

We heard about robots that can learn to operate in the physical world, models that keep learning after they leave the lab, simulations of human behavior, software rebuilding mining and construction, robots assembling AI infrastructure, and satellites designed to move the internet through space.

There was also a Woody intermission. Like Whitman, we contain multitudes.

If you missed the show, you can learn more about the companies below:

Mariana Minerals

Mariana Minerals is rebuilding mining and refining as a software-first industry, using AI, world models, and reinforcement learning to design and operate mines and processing facilities.

Founder: Juan Lozano

Open Roles: MLE/SWE with autonomy experience, Generalist MLE, Controls Engineer, Product Manager, and other roles

Core Automation

Core Automation is developing AI systems that can continue learning after deployment and using agents to automate the process of AI research itself.

Founder: Jerry Tworek

Open Roles: Software Engineers, Research Engineers, AI Researchers

Ploy

Ploy builds AI agents that continuously analyze and improve a company’s growth engine, from websites and content to experiments and campaigns.

Founder: Bryant Chou

Open Roles: Data Engineers, Product Engineers, GTM Engineers

Generalist

Generalist is building general intelligence for the physical world, developing models that allow robots to learn new skills and operate in unfamiliar environments.

Founder: Pete Florence

Open Roles: Research Assistants, Research Scientists (Pre-Training, Post-Training), Infra, ML Infra, ML Optimization, ML Robotics Systems, Product, Robotics Controls, Electrical Engineers, Mechanical Engineers, Engineering Technicians

EON

EON is building a space-based alternative to subsea fiber, using optical ground stations and satellites to move enormous amounts of data with infrared lasers.

Founder: Charlie Horowitz

Open Roles: FPGA Engineer, GNC Engineer, Embedded Software Engineer, Opto-Mechanical Engineer, Electrical Engineer, Thermal Engineer

Intelligence (Design Arena)

Design Arena is an eval platform for subjective AI tasks, using human preference to determine which model outputs are actually better.

Founder: Grace Li

Open Roles: Founder’s Associate, Product Engineering, ML Engineer, Post-Training Research, Data Science

Gradient Robotics

Gradient Robotics builds robots to manufacture and maintain the physical infrastructure behind AI.

Founder: JX Mo

Open Roles: Mechanical Design Engineer, Electrical Engineer, Robotics Software Engineer, Integration Engineer, Hardware Technician, Business Operations Lead

Simile

Simile builds models of human behavior that let companies simulate how different populations will respond to products, pricing, messaging, and other decisions.

Founder: Joon Sung Park

Open Roles: Hiring across Research, Engineering, Product, Deployed Engineering, Operations, and GTM

Unlimited Industries

Unlimited Industries is an AI-native engineering and construction company building factories, data centers, energy infrastructure, and other critical projects.

Founder: Alex Modon

Open Roles: Multidisciplinary Builders (Electrical, Mechanical, Aerospace, Robotics, Motorsports, Dynamic Systems), Team Builders, Business Development

Thank you again to OpenAI for hosting us, DigitalOcean for their continued support, and to all of the founders, volunteers, referrers, and 300+ members of the FYSK community who made the room so special.

Couldn’t make this one? Our next showcase is coming up on November 18. Apply to the FYSK community to get invited to future showcases, founder dinners, and other events.

We’re still 2 weeks out but almost at capacity so APPLY NOW!! You don’t have to be job hunting to do a little career window-shopping.

This lineup spans everything from data center robots and space lasers to human simulations, critical minerals, cyber operations, and models that keep learning after deployment.

On September 16th, the following 10 founders will take the FYSK stage:

• Pete Florence, founder of Generalist

• Bryant Chou, founder of Ploy

• Grace Li, founder of Design Arena

• Joon Sung Park, founder of Simile

• Charlie Horowitz, founder of EON

• Juan Lozano, Founder & CTO of Mariana Minerals

• Alex Modon, founder of Unlimited Industries

• Jerry Tworek, founder of Core Automation

• JX Mo, founder of Gradient Robotics

• Marko Elez, founder of Cathedral

And a huge thank you to our community members who nominated these founders. Some of the best companies we feature come from people in the FYSK orbit pointing us toward founders they think engineers should know. Major thanks to Rob Toews, Todd Jackson, Eryk Dobrushkin, Patrick Backhouse, Zabie Elmgren, Avery Lamp, Chris Owusu, Mike Liu, and Eric Joe

A sincere thank you as well to Larry Erwin and the team at OpenAI for hosting us at their beautiful new office!

Want to meet these founders? We’re close to capacity so APPLY NOW to our showcase and to join our FYSK community.

AI is getting better at doing the actual work rather than just telling us how. Ploy is building agents that can operate a company’s growth engine, while Gradient Robotics is taking that same shift into the physical world with robots built to manufacture and maintain AI infrastructure. One works through browsers and software, the other with servers—both are betting that the next generation of automation will be measured by what actually gets done.

Bryant Chou, Founder of Ploy

Most companies launch a website and then let it sit. Meanwhile, their growth teams bounce between analytics dashboards, SEO tools, ad platforms, CRMs, designers, and engineers just to figure out what’s working and make a change. Ploy makes the website to do that work itself.

Bryant Chou knows the problem well. He co-founded Webflow, architected the platform that now powers more than 1% of the active web, and along the way built and led its growth, marketing, sales, and data teams as Webflow scaled from $1M to $100M in revenue. After 12 years there, he came away frustrated that growth teams were spending more time measuring than doing — what he jokes has become “measureship.” Ploy is, fittingly, his ploy to automate away the operational work that got in the way.

Ploy’s agents continuously monitor a company’s website, traffic, and competitors and then act on what they find: writing content, building landing pages, running campaigns, identifying visitors, and feeding information back into the CRM. Teams like Hex and Clay are already using Ploy to automatically generate personalized enterprise landing pages and turn internal data into hundreds of programmatic SEO pages. The company launched publicly in June with a $27M seed from First Round Capital and Y Combinator.

If you want to build agents that turn insight into action, come meet Bryant at the showcase.

JX Mo, Founder of Gradient Robotics

Stealthy!

Apply to attend our next SF Startup Showcase and meet these founders in person.

These three companies are tackling a slightly different version of the same question: how do we make AI systems better at learning from the world around them? Core Automation is working on models that can keep learning after deployment, Design Arena uses human taste as an eval layer for subjective AI outputs, and Simile is modeling human behavior itself. The common thread is a move away from static models toward systems that learn, adapt, and respond to real people.

Jerry Tworek, Founder of Core Automation

Today’s frontier models are limited in design: once they leave the lab, they stop learning. They’re trained on enormous datasets, deployed in the real world, and then remain static until they’re trained again. Jerry Tworek believes the next major leap in AI will come from models that can continue learning through interactions with users and the problems they encounter.

Jerry came to that conviction after leading reasoning and reinforcement learning work at OpenAI. At Core Automation, the team is doing more than just optimizing the current process for better performance. They’re researching new learning algorithms that could move beyond large-scale pretraining and reinforcement learning, alongside architectures that scale better than transformers. Core is building what it calls “the world’s most automated AI lab,” using agents to automate its own experiments, systems work, and research so their small team can attempt problems that would traditionally require a much larger organization.

And that small team is stacked — including Avery Lamp, longtime engineer and LP at FYSK. When we spoke with Jerry, Core had grown to 20-something people drawn largely from OpenAI and Google DeepMind, along with researchers from Anthropic, Meta, xAI, and Amazon’s AGI lab. They plan to reach roughly 40 people by year-end and are hiring researchers across inference systems, synthetic data, large-scale reinforcement learning, neural network architectures, and agentic systems. Core had already raised $100M at a $1B valuation from investors including Nvidia, Accel, and Spark Capital.

If you want to help figure out what comes after today’s static models, come meet Jerry at the showcase.

Grace Li, Founder of Design Arena

AI models are now great at generating websites, images, videos, and slides. The newest problem is deciding which models have the best outputs for a certain task. It’s one thing to benchmark whether a coding model got the right answer. It is much harder to rank an output when human taste is involved – how do you concretely decide which generated image is most fun or which design is more aesthetic?

Grace Li found this problem shortly before graduating from Harvard. She and a group of friends were building an AI game engine. The models could generate games that worked but weren’t actually fun. There was no automated benchmark that could explain why. They realized that for subjective domains like design, the missing ingredient wasn’t another AI judge. It was human taste at scale. Users ask multiple frontier models to create the same thing and choose which result they prefer. Those comparisons rank the models while generating valuable evaluation data in domains where there often isn’t one objectively “correct” answer.

The company’s growth so far is ridiculous for its size. On August 3, Tech Crunch reported that Design Arena had reached 5.3M users, roughly $60M in ARR, and raised a $7.9M seed round led by Index Ventures. Speaking with Grace two weeks later, she told us they had already reached 5.8M users across 192 countries. The company is still only 10 people but is looking to scale dramatically over the next two months.

If you’re interested in figuring out how we measure what “better” means as AI becomes capable of creating almost anything, come meet Grace at the showcase.

Joon Sung Park, Founder of Simile

Companies spend enormous amounts of time and money trying to answer questions that ultimately boil down to the same thing: what are people going to do? Will customers buy a new product? Which advertisement will resonate? Today, answering those questions means surveys, months of research, and the time-honored tradition of paying consultants seven figures for predictions. Joon Sung Park thinks many of those decisions can be simulated.

Simile grew directly out of Joon’s Stanford research on generative agents and human behavior. Companies can tell Simile which population they want to understand and ask its simulated people questions about products, pricing, purchasing behavior, and more. They aren’t generic LLM personas: Simile trains and validates its models against real human data. The company works with ~40 data and panel partners, including Gallup, giving it access to tens of millions of real people for data collection and validation.

The company has scaled just as quickly financially. Revenue grew 5x in the five months following launch. Index Ventures led a $100M Series A in February, and five months later Simile announced a $200M Series B at a $2B valuation. The team is now around 60 people and Joon expects they could grow to 100–120 by year-end.

If building the models that could eventually simulate human behavior at planetary scale sounds interesting, come meet Joon at the showcase.

Apply to attend our next SF Startup Showcase and meet these founders in person.

This group of founders is building for a world where software moves beyond the screen. Mariana is rebuilding mining and refining around software, EON is moving data transfer infrastructure to space, Generalist is building intelligence for robots, and Unlimited is rethinking how we design and construct the infrastructure itself. Its a theme we’ve seen before; some of the biggest opportunities in technology now come from applying the speed, iteration, and intelligence of software to the physical world.

Charlie Horowitz, Founder of EON

Roughly 95% of the world’s intercontinental data still travels through long fiber-optic cables on the ocean floor. These cables take years to deploy, cost hundreds of millions of dollars, and can be damaged by ship anchors, natural disasters, and deliberate sabotage. EON is building an alternative: skip the ocean and move the data through space.

Charlie came to the problem after starting his career at Palantir and later joining satellite manufacturer Apex as its tenth employee. At Apex, he kept hearing the same request from potential customers: they needed enormous amounts of data capacity without being completely dependent on subsea fiber. The concern was primarily geopolitical; in places like Taiwan, contingency planning assumes subsea cables would be the first infrastructure targeted in a conflict. After connecting with a major cloud infrastructure company over pricing on existing routes, Charlie realized they could solve for more than just redundancy. They could also move data dramatically cheaper.

The technology is, in Charlie’s most simplistic description, “space lasers.” EON uses telescope-like optical ground stations to beam data to satellites with infrared light and back down again, targeting 2.4 terabits per second per link. The company just raised a $10.75M seed led by General Catalyst and a16z. When we spoke with Charlie, EON was just three months into operating formally, had seven employees, and is preparing to open roughly 15 roles across mechanical, electrical, embedded, controls, optics, and other disciplines.

If you dreamed of building “space lasers” as a kid, here’s your chance. Come meet Charlie at the showcase.

Pete Florence, Founder of Generalist

Robots are remarkably good at doing the exact thing they were designed and programmed to do, but they’re terrible at encountering a new object, environment, or task and figuring out what to do next. LLMs made the leap from narrow systems to general-purpose intelligence by scaling models, compute, and enormous datasets. Generalist is betting that the same transition is finally possible for robots.

Pete describes solving intelligence in the physical world as the “ultimate act of engineering.” In Pete’s words, everything they’re doing is ‘strictly harder than making language models.’ The challenges span across model training, data infrastructure, firmware, controls, mechanical engineering, and robotics simultaneously.

Generalist’s latest model, GEN-1, is trained largely from scratch using more than half a million hours of physical-interaction data. The team behind it has worked across OpenAI, Google DeepMind, and Boston Dynamics, and the company recently announced $400M in funding from Radical Ventures, 8VC, and USV among others. But one of Pete’s favorite company metrics has nothing to do with fundraising: Generalist has grown to 43 people, yet not a single technical employee has left in two and a half years. He attributes that in part to a culture where engineers develop deep expertise without being pigeonholed into one narrow problem forever.

If you want to work on the full stack required to give machines general intelligence in the physical world, come meet Pete at the showcase.

Juan Lozano, Founder of Mariana Minerals

AI infrastructure, electric vehicles, modern energy, and defense all depend on critical minerals like copper and lithium. The problem is actually getting them out of the ground. Mining and refining remain notoriously slow industries, with major projects often taking years to permit, build, and bring online. Mariana is trying to rebuild the minerals industry as a software-first operation.

Juan Lozano came to Mariana after building and scaling machine learning systems at Affirm and Kite. At Mariana, software isn’t just an analytics layer sitting on top of a traditional mining company. Its internal platform, MarianaOS, spans the entire operation: software for building projects, running mines, and optimizing refineries. MineOS uses physics-informed world models and reinforcement learning to coordinate mining fleets, while PlantOS uses sensing and RL to continuously optimize mineral processing.

And they’re already putting it to work in the real world. Mariana is operating Copper One in Utah and building Lithium One in Texas, with MarianaOS already deployed across both sites. The company says it compressed Copper One’s typically multi-year acquisition, permitting, and restart process into months, while Lithium One is on track to become its first designed-for-autonomy greenfield refinery less than three years after Mariana was founded. This month, Mariana announced a $310M Series B led by Khosla Ventures, bringing total parent and project capital raised to roughly $400M.

If you want to build software and AI where the output is measured in tons of copper and lithium rather than tokens, come meet Juan at the showcase.

Alex Modon, Founder of Unlimited Industries

Unlimited’s manifesto opens with the line “We used to build.” Their argument is that construction hasn’t just failed to keep pace with software—it has developed incentives that actively resist speed. Cost-plus contracts, billable hours, rigid design freezes, and endless change orders reward caution and delay rather than better outcomes. Unlimited is rebuilding that system, with the goal of making physical infrastructure move at the pace of software.

Unlimited is an AI-native, vertically integrated engineering and construction company using small, engineering-led teams and software to actually deliver factories, data centers, energy infrastructure, and other large projects. Unlimited uses AI to generate hundreds of thousands of design permutations, drastically cutting feedback loops, iteration time, and overall cost.

The approach is already producing real results. Unlimited has compressed pre-construction engineering that traditionally took six months into a few weeks and identified redesigns that cut projected capital costs by more than 50%. The company raised a $12M seed co-led by Andreessen Horowitz and CIV. When we had dinner at Unlimited’s office this summer, the pace was tangible: team members arrived from calls, disappeared to run models, and came back to the table—welcoming, but visibly eager to get back to building.

If you want to help restore our ability to build ambitious things in the physical world, come meet Alex at the showcase.

Apply to attend our next SF Startup Showcase and meet these founders in person.

The Ground-Floor Myth

Engineers often tell us they want to join a company at the ground floor. The instinct makes sense. Join early enough and your equity could be meaningful. You get to shape the product, influence the culture, and say you were there before the company had a proper logo.

But early and high-upside are not always the same thing. The ground floor comes with the risk that the building never gets built, the product may not work, and the market only exists in the fundraising deck.

There’s another compelling moment: when a company has real traction, customers, and evidence that it’s working—but still has an enormous amount left to build.

A billion-dollar valuation can sound like the party is over. Sometimes it means the product finally works and the party got a liquor license.

After the Signal Is Clear

On a recent podcast, Founders Fund’s Brian Singerman described a new perspective on venture investing: the hardest part is not only finding the winners early. It is continuing to recognize the winner after it stops looking early – Founder’s fund put roughly one-third of a fund into Palantir at a $1 billion valuation.

The same principle applies to choosing where to work.

An engineer considering SpaceX or Anthropic after the product and market were credible might have worried they missed the ground floor. But equity does not need to start cheap to become valuable. FYSK featured Anthropic in February 2023, when it was worth roughly $5 billion. It was not exactly hiding in a garage. Today, Anthropic is valued at $965 billion. Holding ownership constant, $100,000 of equity maps to roughly $19 million today. The ground floor was gone. Apparently, almost none of the upside was.

Serval and Owner are far from being companies with three people and a deck. They have products, customers, and incredible momentum. But the larger markets they’re pursuing are far from finished. It’s time to change your mindset from “What has already been done” to “How much is there left to do.”

General Matter

General Matter may be the clearest example.

Scott Nolan founded the company to rebuild America’s domestic nuclear-fuel capabilities. It is focused on uranium enrichment and advanced nuclear fuel production, one of the most important bottlenecks facing the next generation of nuclear energy. The company has secured a $900 million Department of Energy task order and raised $50 million in a round led by Founders Fund.

A meaningful amount has already been proven.

But the hard work is not over. General Matter still has to build complex physical infrastructure, develop and operate enrichment technology, navigate a heavily regulated industry, and help restore a critical part of the American industrial base.

That is not getting in after the adventure. That is the adventure.

The best startup jobs are not always at companies nobody has heard of yet.

Sometimes they’re at companies everyone can see are working—but few people understand how far they still have to run.

Apply here if you’re interested in dinner with General matter or future FYSK dinners.

A company’s website can tell you what it builds. It can’t tell you that a hardware engineer liked Flow enough to leave his job for a company that would let him use it. Or that the right person to reinvent construction may be an aerospace engineer. Or what keeps a healthcare team working late when the work stops being theoretical.

That’s why we started hosting dinners.

Unlimited Industries

Our first dinner of the Summer was at Unlimited’s office with Alex Modon and Tara Viswanathan.

Their manifesto is about making the physical world move faster. Their office felt like proof they meant it. Team members arrived from calls, disappeared to run models, and returned to the table—genuinely welcoming, but visibly eager to get back to building.

In between moments like an attendee realizing he and Tara were from the same hometown, Alex and Tara shared Unlimited’s progress. They’re already compressing processes from months into weeks, but were candid about the thing AI cannot shortcut: credibility. Until you have completed enough projects, knowing the best way to build something is not the same as being trusted to say so.

Flow Engineering

Next was Pari Singh of Flow Engineering.

Pari told two wild stories you will not find about Flow online. In one, a hardware engineer changed jobs because his company would not let him use Flow. In another, Flow was rejected after a long product evaluation—only for the engineers to push leadership to reopen the decision. Flow came back and won.

The company names stay at the table.

Pari described Flow as the kind of family that argues, works through the issue, then hugs it out. That tracked: intense but warm, and caring enough to disagree properly.

Healthier

Then we had dinner with Parth Bhakta of Healthier. They’re building an AI reasoning platform for oncology—bringing together fragmented medical records, imaging, genomics, research, and clinical guidelines into recommendations patients and doctors can actually evaluate.

The views of the Bay Bridge were incredible, the dinner was delicious, but the personal stories are what stuck.

A friend of a founding team member once called them after his father was diagnosed with cancer. He had great doctors. He still needed help. It’s the kind of call that makes staying late feel different.

Parth made the point that hard things are interesting precisely because they are hard. The team seems to attract people who are empathetic without needing to make a production of it. They are not working toward some distant hypothetical impact.

Someone needs the product now.

You can learn plenty about a company online.

You cannot search how the team argues, what makes them stay late, or whether the room feels more interesting two hours in.

For that, you have to come to dinner.

Apply here to join our dinner series if you would rather catch the vibes in person than read our reconstruction.

Play FYSK Builder deck

Make eight fast choices, draw your engineering character card, and unlock the FYSK companies best matched to the way you build. Like Myers-Briggs (but way shorter!) the game takes about two minutes and reveals where you thrive, how you work, and the particular form of technical wizardry you bring to a team.

Your result comes with its own:

BUILD ENGINE
How you turn ideas into working things.

BATTLECRY
The phrase your coworkers have heard 4,000 times.

INSTINCT
What your brain does before the meeting has technically started.

HABITAT
The environment where your powers become most powerful.

Resist the urge to add this card to your LinkedIn certifications. Actually never mind…do it. LinkedIn could use some more adorable, colorful, magical animal cards!

Once you’ve taken the quiz, we find your people

This is where the personality quiz develops a useful side quest. Your builder type, preferred industries, and ideal company culture are matched against every company that has presented at Founders You Should Know. Years of exceptional startups curated for you by one highly opinionated matchmaking machine.

Unlock bespoke connections

When a match looks promising, ask FYSK for a private introduction. We’ll approach the founder, brag about you appropriately, and make the connection when there’s mutual interest. Learning that you are a highly evolved Infrastructure Beast is fun. But learning that your ideal team is already hiring is better.

Get in on the magic

Discover your engineering personality. Meet the founders you should know.

Play FYSK Builder deck

This only takes two minutes — unless you attempt to reverse-engineer the scoring system—which would also tell us quite a lot about you.

Bonus content: notes from my very first vibe-coded project!

This was my first time vibecoding and deploying an actual product. I know almost nothing about engineering, which made the process feel equal parts magical and frustrating. It reminded me of baking—an activity I do not love. There’s room to be creative, but getting anything into production requires following a long list of very exact instructions. Miss one step, and the whole thing refuses to rise. Except instead of a sunken cake, you get a 404.

A few things I learned:

The artwork needed an actual design system.
The first versions were all over the place, so I had to define a proper design file and keep refining it until the cards finally looked like they belonged in the same universe.

Ugh, ugly v1, or v25…

“Every FYSK company” turned out to require some human judgment.
The original database included companies that had been acquired or shut down. I asked Codex to scour public websites for a first pass, then manually reviewed and removed the ones that should no longer appear in the matches.

AI loves putting too much text on the cards.
Early versions were crowded, distracting, and full of lines no human would actually say. A large portion of the work was deleting things, simplifying the layout, and rewriting copy until it sounded like a person instead of a very enthusiastic machine.

What does the text in the little box windows even mean?

The badges took forever.
Getting them to feel culturally relevant, funny, distinctive, and actually connected to each engineering personality required many, many iterations. Apparently “make it cooler” is not a complete creative brief, despite my repeated attempts to make it one.

Deploying the game was the hardest part.
Because I had no idea what I was doing, I initially asked for the simplest possible setup and was guided toward Netlify with a private Airtable handling the backend storage.

Then the human in the loop—my husband, a seasoned vibecoder—suggested GitHub, Vercel, and Supabase instead.

What followed was a painstaking sequence of instructions, failed steps, screenshots uploaded to Codex, revised instructions, more screenshots, more revised instructions, and several moments where every button on the internet appeared to be in the wrong place.

Eventually, it worked (mostly!)

There are still bugs. Please report them (seriously!) Finding a bug is now part of the game.

Not the right Detail! Ironically we could use Detail to find the bugs…

The connections we made mattered, but both candidates had plenty of other options and closing them was entirely in the founder’s hands. We can lay up an introduction, but like a first date, what happens next depends on the people in the room.

The best founders understand that. They treat the interview process as a chance to build trust, create momentum, and show exceptional candidates why this is the company – and team – they should bet their career on.

How great founders win great people:

1. Speed as a weapon
   The fastest hiring outcomes we’ve seen are highly intentional. One founder closed an exceptional engineer within 48 hours of meeting him at a FYSK showcase. Another hired two engineers the week after we hosted a dinner for the company. And the founder we mentioned above closed both candidates within a week of our introductions.
   
   These founders were building companies, shipping product, talking to customers, and managing a hundred other priorities, but they treated promising candidates with urgency. They followed up immediately, created momentum, and made every next step clear.
   
   We know that is easier said than done. Recruiting is one of many things competing for a founder’s attention, and it is easy for a follow-up to slip. But exceptional candidates move quickly, and the founders who move with them are often the ones who win.

   
   A strong candidate should never be wondering when they’ll hear from you. If a candidate has to nudge you, the process has already lost momentum. Make it a goal to keep things moving whenever the ball is in your court.
   

2. Sell the dream, not the job description.
   Great founders do more than explain what the company is building today. They make the future feel tangible.
   
   They do not lead with, “We’re looking for a Python backend engineer.” Almost no one wakes up identifying as a Python backend engineer. They lead with the problem, the stakes, and the future someone could help create.
   
   Compare that with: “Energy is the foundation of every AI system. We’re working on uranium enrichment to unlock abundant, clean power—and if we succeed, the future of AI runs on infrastructure we helped make possible.” They might even add: “By the way, our backend is built in Python. Even if you do not know it yet, I’m sure you can figure it out.”
   
   The best engineers are looking for the opportunity to help build a generational company. They want to understand what this could become, why it matters, and why this team has a real chance of making it happen.

   
   3. Don’t make candidates play detective.
   Strong candidates will ask about revenue, growth, compensation, competition, risks, and the challenges ahead. Answer those questions clearly. Engineers notice when founders are evasive. We recently heard from a candidate who asked about compensation and was told the company was “competitive,” but was not given a range. When they pressed, the numbers shared felt surprisingly low relative to the company’s massive recent funding round. Their takeaway was harsh: the process ranked “bottom decile” on both compensation and transparency. They still agreed to continue the conversation but the founder had already created doubt that did not need to be there.
   
   If you are asking someone to devote years of their life to building alongside you, it is hard to earn that commitment while gatekeeping the information they need to evaluate the opportunity.

   
   Transparency during the interview process signals how you will communicate once they join and begins establishing the culture of the company before their first day.
   

3. Let your team do the selling.
   Candidates are evaluating the people as much as the company. Give them meaningful time with the strongest members of your team, especially the people they would work with most closely.
   
   We recently heard this from an engineer after meeting one of the FYSK-featured companies: “The idea was not an immediate ‘wow,’ but it also didn’t strike me as a bad direction. For me, it came down to the passion, charisma, and caliber/pedigree of the team. Once I met more people on the team, I was so much more excited about working there.”
   
   Exceptional engineers want to collaborate with exceptional peers. They want to know who they’ll be solving hard problems with, who they’ll learn from, and whether this is a group that will push them to do the best work of their career. People want to join the coolest, most interesting, most brilliant club they can get into.
   

4. Don’t lose on the offer.
   The strongest engineers are often considering several opportunities at once—and they rarely evaluate an offer alone. They share it with friends, former colleagues, founders, and other people who have seen dozens of competing packages.
   

   One engineer recently told us that while he was assessing his offer, a founder friend was blunt: the comp package he received was far too low, he was worth significantly more, and the alternatives were better. Because that friend had seen many comparable offers and knew him well, the feedback carried real weight.
   
   A low-ball offer, especially one with weak equity, can quickly remove you from consideration. Research the market and compensate early employees appropriately for the risk they are taking. Raising significant capital from a top-tier investor does not automatically make the opportunity feel derisked to a candidate.
   

   Early employees only get to make one bet with their time. Your offer should reflect the value of that bet.

And lastly…remember every candidate talks.

An interview process leaves an impression far beyond the candidate in the room. Treat every candidate as someone who will share the experience with 30 other exceptionally talented people (because they often will!). Engineers talk to their friends, roommates, partners, former colleagues, and to us at FYSK. When founders run a thoughtful, respectful process, word travels, and it becomes easier to attract even more exceptional people.

Because we’re often the connector, we care deeply about what happens after the introduction. The founders who consistently make candidates feel valued are the ones we’re most excited to keep introducing to great talent. Run a great process, and the flywheel starts to work in your favor.

Thank you to Camille Ricketts for chatting with me about this topic! For more of Camille’s musings on talent, company-building, and the occasional extremely important TV or movie recommendation, check out their newsletter, Early Days.

LinkedIn is fine, but personal websites are where the weird good stuff lives. AI has made building easier, which means the bar has moved. The most interesting people now show receipts: projects, writing, design taste, weird obsessions, half-finished tools, thoughtful essays, and GitHub rabbit holes.

That’s part of why personal websites are having a moment in the FYSK community. LinkedIn still has its place. It tells you someone’s title, company, school, and maybe whether they recently discovered the phrase “AI-native.” Helpful and fine. A little beige.

The personal websites we’ve seen show how the creator thinks. The best ones feel less like resumes and more like personal trophy cases: things built, people built with, ideas chased, side quests pursued, and tiny clues that make it clear there’s a human behind the keyboard.

Here are a few we loved:

Bryce Sandlund

brycesandlund.com

Bryce’s site proves he can’t be reduced to a LinkedIn headline. There are research papers, software projects, competitive-programming history, opinions on academia, AI writing, and old projects. There’s also beer brewing, music, and outdoor adventures.

Almost none of this would fit on a normal resume. The research is serious and substantial, but the site never flattens him into “person with publications.” You can follow links into reinforcement learning and AI, explore independently built products, see the competitive-programming community he’s participated in and supported, and then casually discover that he also makes tikis (Bryce if you’re reading this, I want one). The site gives you a much fuller picture of Bryce: not just what he has done, but what he notices, what he builds, and what corners of the internet his curiosity has colonized.

Harsha Karanth

harshakaranth.com

Our favorite part of Harsha’s site is the project section. The work is concrete, clickable, and pleasantly all over the place. There’s Notefolio, an investment journaling platform linked to the App Store. Cardiac AR, which points to research on collaborative mobile AR for cardiovascular surgical planning. There’s also an AI-powered employee onboarding platform with a video demo, an SEC 8-K stock predictor, and a mobile version of Egyptian Rat Screw – which we can only assume is safer for hands than the card-slapping original.

By the time you reach the line “reaching for the stars, one line of code at a time,” the pun feels earned. And for the record, we are pro-pun: Harsha makes a strong case that he is, in fact, a star.

Cooper Shea

coopershea.com

Cooper’s site makes you feel like you just dropped into someone’s workshop and realize they have five tabs open in their brain. He’s obsessed with questions around computational design, manufacturing, materials, AI, human cognition, and the messy process of turning ideas into physical things. Then you hit the projects tab and the builder brain fully reveals itself.

There’s a cleft palate orthodontic device for infants with Pierre Robin sequence, built through a Blender, nTopology, and Python pipeline that cut a manual process from 14 hours to 2. Right next to it is a Monstera leaf bottle opener, VR-sculpted in Gravity Sketch and post-processed in Fusion 360. The range is impressive. You get medical devices, aquaculture robotics, hydrogen systems, microneedles, ocean plastics recovery, and houseplant-shaped bottle opener. It’s a very specific flavor of builder energy: deeply technical, physically grounded, and just weird enough to be memorable.

The CV is tucked away at the end. After clicking through projects, theses, writing, and the homepage quiz — which took us way too long, no further questions — you eventually learn Cooper has a Stanford M.S. in Mechanical Engineering focused on Biomechanics and Thermodynamics. By then, the credential lands differently. Like “oh, that explains the houseplant bottle opener pipeline.”

Madhuri Bhavana

madhuribhavana.com

Madhuri’s site is a great example of a portfolio that shows not just what the final product looks like, but how the thinking happened. Her work is organized around real product problems: redesigning a complex virtual-machine creation flow at Nutanix, designing Amazon Easy for shoppers in emerging markets, and conducting research for Google’s AdMob platform.

The case studies do what good case studies should do and what many case studies heroically avoid doing: they show the actual judgment. They lay out the problem, users, research, insights, tradeoffs, and concept development alongside the final experience. You can see the difference between someone who can make a clean interface and someone who can make complicated systems more understandable, inclusive, and useful. That’s the real signal.

The best personal websites do something resumes and LinkedIn rarely do. They remind us there is a person behind the page. They show the projects behind the titles, the taste behind the work, the curiosity behind the credentials, and the side quests that make someone memorable.

That’s part of what makes the FYSK community special. Yes, the talent is exceptional. But the real magic is the density of curiosity, generosity, ambition, taste, and “you really built that?” energy in one place.

Thanks again for being a part of FYSK!

Have a personal website you’re proud of? Share it when you apply to the FYSK community!

Hungry to meet founders and can’t wait until the next showcase in September? Join FYSK and other jobseekers for an intimate dinner with six of our favorite founders. We chose these founders because their companies have incredible momentum: Over 130% YoY revenue growth, hundreds of millions in government support, backed by a16z, Sequoia, Founders Fund, and Nat Friedman – yet they’re still early enough for new hires to shape the direction of the company. Each founder is actively hiring and looking to connect with candidates from the FYSK community!

These dinners are intentionally small. They’re an exclusive opportunity to speak directly with the founder, a few early team members, and ~10-15 other engineers also interested in attending. You’ll have a chance to personally feel out company culture, understand the technical problems the team is working on, and maybe even make a new friend.

Here’s what attendees from our most recent dinner series had to say:

This Summer’s Menu

These teams are growing quickly. Now is your chance to join and have real ownership and an outsized impact.

Tara Viswanathan, Co-Founder of Unlimited

📅 July 16 | San Francisco

Unlimited is an AI-native engineering and construction company that leverages software and artificial intelligence to improve how factories, data centers, energy infrastructure, and other critical projects are designed and built. Tara and the team’s vision is to transform the delivery of large-scale infrastructure by combining AI, software, and engineering expertise.

Unlimited recently raised a $12 million seed round co-led by Andreessen Horowitz and CIV and is already delivering measurable results on industrial projects, reducing pre-construction engineering timelines from six months to a few weeks and identifying design optimizations that cut costs by over 50%.

Pari Singh, Founder & CEO of Flow Engineering

📅 July 21 | San Francisco

Pari is building Flow Engineering to accelerate the development of the world’s most important physical technologies. Flow helps engineering teams design, test, verify, and iterate on complex hardware systems dramatically faster, enabling companies building rockets, autonomous systems, energy technologies, and advanced manufacturing products to operate with software-like speed. The cost of software creation collapsed once AI could write code, and Flow’s bet is hardware engineering will undergo a similar transition.

Flow’s software is already deployed in many of the top next-gen hardware companies. Rivian evaluated 30 different tools and ultimately chose Flow. They started using Flow with only 40 users and grew to 1,500 in four months.

Parth Bhakta, Founder & CEO of Healthier

📅 July 23 | San Francisco

Parth is building Healthier, a trusted AI reasoning platform for high-stakes medicine, beginning with oncology. The company’s technology synthesizes fragmented medical records, imaging, genomics, clinical guidelines, research literature, and trial protocols into source-grounded recommendations that both patients and clinicians can understand and evaluate. Healthier’s products span patient-facing care navigation, AI-powered clinical decision support, and tumor board workflows designed to help providers make more informed decisions in complex cases.

We’re excited by the team and their early commercial traction. The team consists of advisors and operators from Stanford, UCSF, Mass General, Dana-Farber, UPenn, and Foundation Medicine. They recently hired a Chief Medical Officer who previously worked at OpenEvidence and City of Hope. It’s still early, but they already have pilots and partnerships with major oncology networks and institutions and several top cancer centers. The company recently closed a seed round led by a16z.

Rune Kvist, Co-Founder of AIUC

📅 July 30 | San Francisco

Rune is building AIUC, a company creating the trust infrastructure for AI. As enterprises deploy increasingly capable AI systems and autonomous agents, AIUC is developing standards, certification frameworks, and insurance products designed to help organizations evaluate and manage AI-related risk. The company is pioneering a new category of infrastructure intended to make advanced AI deployment safer, more transparent, and more accountable.

AIUC combines a strong founding team (experience spanning Anthropic, McKinsey, METR) with exceptional early traction. The company already launched the AIUC-1 standard, raised a $15M seed round, and is working with some of the most prominent AI companies in the world to define how enterprises certify, insure, and adopt AI agents.

Adam Guild, Co-Founder & CEO of Owner

📅 Date: tba | San Francisco

Adam founded Owner after helping save his mother’s small business and realizing how difficult it had become for independent businesses to compete online. Owner helps restaurants grow direct revenue, strengthen customer relationships, and compete against large chains using AI-powered tools and software infrastructure. What began as a mission to empower local business owners has evolved into a platform serving independent restaurants across the country.

Owner now serves more than 10,000 restaurants across the United States and recently raised a $120 million Series C at a $1 billion valuation.

Scott Nolan, Founder & CEO of General Matter

📅 Date: tba | Los Angeles

Scott founded General Matter to rebuild America’s domestic nuclear fuel capabilities. The company is focused on uranium enrichment and advanced nuclear fuel production, addressing one of the most critical bottlenecks facing the future of nuclear energy. As countries race to deploy next-generation reactors and strengthen energy security, General Matter is working to ensure the United States has the industrial capacity necessary to support a new era of nuclear power.

General Matter secured a $900 million Department of Energy award to help rebuild domestic HALEU enrichment capacity, and they recently raised a $50 million round led by Founders Fund, with Peter Thiel joining the board.

Interested in attending? Apply here and let us know which dinners you’d like to join!

Happy SpaceX IPO day! A multi-trillion valuation is a remarkable achievement by any measure, but our hot take is that among the most valuable legacies SpaceX leaves in its plume is its alumni founder network. SpaceX has become the launchpad for a new wave of founders building some of the wildest companies in the world.

Looking back, you can identify companies that shaped entire generations of entrepreneurship. Fairchild Semiconductor produced the founders who built Intel, AMD, and dozens of companies that became the backbone of Silicon Valley. PayPal (notably also founded by Elon!) became the training ground for founders who would go on to build Tesla, LinkedIn, Palantir, Yelp, YouTube, and countless others. These companies became environments that further shaped already talented people, helping them develop a new understanding of what’s possible. SpaceX is one of them.

Building rockets forces people to think across software, manufacturing, operations, supply chains, and energy systems at once. Few organizations force people to operate across so many disciplines simultaneously. But it’s also cultural. SpaceX had a reputation for assigning enormous responsibility to young people and expecting them to solve problems that most organizations would consider impossible.

The result is founders willing to tackle incredibly complex problems. Here are a few SpaceX alum founders that we’ve featured at our FYSK showcases and a couple others who made the news recently!

General Matter — Scott Nolan

As electricity demand surges and energy security becomes increasingly important, one of the biggest bottlenecks in nuclear power is fuel, not reactors. General Matter is focused on domestic uranium enrichment, tackling a deeply technical and highly regulated challenge that sits at the foundation of America’s energy future.

We featured General Matter at the most recent showcase. Scott is the type of founder we’re proud to feature: ambitious, deeply technical, and focused on a generational problem.

Base Power — Justin Lopas

The electric grid is becoming more complex by the year as AI data centers, electrification, and extreme weather put new pressure on aging infrastructure. Justin Lopas and the team at Base Power are building distributed energy systems designed for a grid that will be more resilient, intelligent, and decentralized than the one we have today.

We were excited to have Justin present Base Power at FYSK last October; building the infrastructure needed for an increasingly electrified world is both technically difficult and enormously important.

K2 Space — Neel Kunjur

For decades, satellites were treated as custom-built aerospace projects. K2 Space believes the future requires something different.

The company is building large, high-power satellites designed to support the growing demand for communications, defense, and national security capabilities in orbit. As space becomes critical infrastructure, K2 is helping build the backbone.

That thesis was validated this week when K2 was selected as a satellite provider for the U.S. Space Force’s Protected Tactical SATCOM-Global program.

Starcloud — Adi Oltean

Every founder ecosystem produces a few ideas that sound ridiculous at first. Starcloud is one of them.

Adi Oltean is building data centers in space. It’s a concept that feels pulled from science fiction until you remember that reusable rockets once did too. And Starcloud isn’t just talking about the future – the company launched a satellite carrying an Nvidia H100 GPU into space last November.

Starcloud recently raised a $170 million Series A at a $1.1 billion valuation, reaching unicorn status less than two years after graduating from Y Combinator.

A well-deserved congratulations to all SpaceX alumni for such a remarkable milestone! This is just a small sampling of a much larger set of ex-SpaceX founders to explore. We’re excited by the number of founders taking lessons learned from SpaceX to new problems and we look forward to seeing many more.

If you know (or are!) a SpaceX alum founder building in energy, defense, healthcare, or are focused on another foundational challenge, we’d love to get to know you!

We recently received this feedback from a long-time community member. She left her previous role to join a startup she discovered through the FYSK YouTube channel. Community members often ask us how to find the companies we’ve previously featured, and the FYSK YouTube channel is the perfect resource.

Go to the channel and watch a few founder presentations from a showcase you missed. If you find a mission or problem that resonates, don’t hesitate to reach out to us! Reference the video and explain what made you interested. Founders at this stage of their company care deeply about who joins them, and a genuine, specific message goes a long way.

If you’re actively looking for a job this summer and having FOMO because the next showcase isn’t until September, look no further.

Your summer watchlist here!!

The whole point of FYSK has always been to get the right jobseekers in front of the top founders at the right time. The showcase is often where FYSK members first discover companies they go on to work for, but the opportunity doesn’t disappear once the event ends. Since founders only present once, it’s easy to feel like you’ve missed your chance if you couldn’t attend live. Fortunately, that’s not the case — every founder presentation remains available on our YouTube channel. It’s a growing library of exceptional founders and startups you can explore whenever you're actively thinking about your next role.

You can find presentations from the founders of Cursor, Anthropic, Parallel AI, Exa, and dozens more. Those videos are still generating conversations today. Some of the people who watched those videos and reached out are now engineers, PMs, and designers at those companies.

Looking for your next role?

• Watch a few founder presentations.

• Find a company that genuinely excites you.

• Send us a note explaining why.

If there’s a strong fit, we’ll help make an introduction.

We look forward to hearing from you!!