The rise of ‘Vibe Coding’ and what that means for FreightTech

“I saw the business from the other side. I was part of a founding team, and we raised a ton of capital from venture capitalists to build an insurtech back in the day before that was even a word that people used, and most people just thought we were a little crazy,” Loser said.

The firm raised its first fund in early 2021 and focuses on “full-stack businesses” operating in complex legacy industries including health care, financial services and trucking. Logistics represents roughly one-third of the portfolio.

The Market Has Bifurcated

The venture landscape has shifted dramatically since 2021, Loser said. The crypto, non-fungible token (NFT) and metaverse hype collapsed in 2023 and 2024, giving way to what he called “an increasing recognition that real businesses with real business models and real-world applications actually mattered.”

“On one hand, you’ve had a group of investors that really are getting bigger and bigger and targeting a smaller and smaller number of mega AI companies,” Loser said. “And then on the other extreme, I think there’s a recognition that the aperture is a lot wider than it used to be in terms of these questions about what is a business that’s venture-backable.”

Floating Point isn’t competing with the billions flowing into OpenAI or Anthropic. The firm targets founders applying technology to transform specific industries.

“What gets us very excited as early-stage investors is the way that some of this technology advancement that’s been so rapid has unlocked completely new economic models for very old industries,” Loser said.

Software Is No Longer the Moat

The rise of “vibe coding” and AI tools has fundamentally changed what creates sustainable competitive advantage.

“It’s still a skill, but in the world of vibe coding, it’s just not that hard to build an elegant piece of software,” Loser said. “And so the real moat, the real sustainable competitive advantage, comes from everything around that.”

That means real-world assets, operational workflows, regulatory capital and complexity. The firms that win will design the entire business model around new technology, not just layer software on top of legacy operations.

“It used to be if you had the best, prettiest software, you could win all the clients and get lock-in and dominate a market. And that just isn’t true anymore,” Loser said.

Floating Point Case Studies: Trucking and Insurance

Nevoya exemplifies the fund’s thesis. The company is building a trucking operation optimized for electric vehicles (EVs) to fundamentally change the economics of freight.

“You’re turning a mostly variable cost gas-type cost structure into mostly fixed cost. The trucks themselves are expensive, but then the electricity is de minimis,” Loser said. “And so all of a sudden you have an asset utilization problem much more so than a variable cost structure problem.”

That means running three drivers around the clock on expensive Tesla Semis rather than letting diesel trucks sit overnight. The result: dramatically lower per-mile costs without relying on a green premium.

Catena, a more recent seed investment, operates as what Loser called “Plaid for trucking telematics” — a data infrastructure layer connecting providers with users across the ecosystem.

“Ten years ago, that would have been a project for IBM with 1,000 engineers, and they’d take a decade to do it. Today, a couple of very talented people can do that in a few weeks,” Loser said.

Ledgebrook, an insurance business, used autonomous AI agents to scale underwriting of complex specialty policies. The company grew from zero to more than $100 million in annual recurring revenue (ARR) in two years.

Why Incumbents Can’t Adapt

Large publicly traded companies face structural barriers to reinvention, Loser said. Salesforce made human sales teams more efficient but never replaced them. The current AI moment demands something more radical.

“To say, ‘Hey, maybe we don’t need this huge salesforce, and maybe we’re actually going to replace them with an AI system or go in a completely other direction to reach our customers’ — it’s a much bigger ask. It’s a scary ask,” Loser said.

That creates opportunity for nimble startups.

Another opportunity comes from taking advantage of overlooked side effects stemming from these new technologies. Take automobiles, for instance.

“For all that people talk about Henry Ford, and obviously Ford and GM, a lot of money was made off the actual cars. I think you can make an argument that the biggest, most successful company that was built on the technology of the automobile was Walmart,” Loser said. “That intuition of, okay, I don’t have to make a car. I have to see how the world is different when everybody has a car and figure out what can I build in that new, different world to create something really special — that’s where I think some of the most transformative companies get built.”