Multicoin Bets Internet Labor Markets Drive Crypto Adoption

Internet Labor Markets — that's the phrase Multicoin Capital is betting will define crypto's next chapter. The investment firm's thesis is blunt: the next hundred million crypto users will earn their first tokens, not buy them. It's a clean narrative. Whether it holds up is a different question.

What Are Internet Labor Markets?

How does the Internet Labor Market model work in crypto?

Internet Labor Markets refers to decentralized networks that pay participants in tokens for contributing work, resources, or expertise — not for speculating on price. The model flips the default onboarding path. Rather than converting dollars to crypto before touching any protocol, users show up, do something verifiable, and get paid. According to Multicoin's own investment thesis, the firm sees ILMs as a distinct category capable of pulling in users who would never self-identify as crypto investors.

Rohan Sengupta, who outlined the framework, put it plainly in a recent interview: "The reason people get their first crypto in the future won't be because they bought it. It'll be because they earned it." That's either a genuinely transformative insight or a very polished way of saying: speculative buying has a ceiling, and Multicoin needs another growth story. Probably both.

The idea is simple. There are two ways people enter crypto — they either buy in or they earn in.

From DePIN to Human Judgment — Where Does This Lead?

The ILM concept builds on DePIN — decentralized physical infrastructure networks — which already reward participants for contributing hardware resources like wireless coverage or mapping data. Solana has been the dominant home for DePIN experiments, and the Internet Labor Markets thesis extends naturally from that base. But Sengupta argues the next phase goes beyond plugging in hardware. "The system moves from just plugging in hardware to people doing more active work — contributing judgment, effort and time," he said.

That shift matters. Passive resource-sharing is relatively easy to verify on-chain. Active human judgment — labeling data, identifying bugs, evaluating quality — is messier and harder to formalize. The ILM model depends on blockchain infrastructure making that verification automatic and payment instant, cutting out the invoices and approval chains that slow traditional freelance work. Whether the verification layer is actually robust enough for complex cognitive tasks remains the technical question nobody has fully answered yet.

Grass is the most-cited current example. Users install software that shares unused internet bandwidth — that bandwidth then gets used to scrape data for AI model training. Participants earn tokens. It's a functional loop, and it sidesteps the buy-first requirement entirely. Sengupta sees this as just the beginning: "The next phase is not just scraping data, but humans applying discretion — labeling data, judging quality — in ways that only humans can."

Is This Really About Crypto — Or About AI?

Here's the angle that deserves more scrutiny: the ILM thesis is as much an AI story as a crypto story. Sengupta explicitly argues that AI increases demand for distributed human contributors. As companies automate their core operations, they still need people for tasks that require real-world judgment and verification. AI may shrink headcount on core teams, he contends, but it expands the need for on-demand, globally sourced contributors.

That's an interesting bet — and possibly the right one. But it also means ILMs' success isn't really in Multicoin's hands. It depends on AI adoption curves, on companies actually trusting decentralized contributor networks for sensitive tasks, and on token incentives staying attractive enough that workers don't drop off when prices fall. Those are three separate bets layered on top of each other.

Multicoin Capital manages a multi-billion-dollar token hedge fund and raised $422 million for a venture fund backing early-stage blockchain startups as of January 2022. The firm has skin in this game — it's not publishing theses for fun. Which means the ILM framework is also a signaling mechanism: Multicoin is telling founders what kinds of projects it wants to see, which shapes what gets built.

Someone starts a company to source something the market needs, and 50,000 people around the world can get paid for producing that labor.

What Does This Mean for Crypto Holders?

If ILMs become a real onboarding layer, the downstream effects on token markets are worth thinking through. New users who earn tokens — rather than buying them — are net sellers by default. They receive tokens as compensation and may cash out immediately. That's different from a speculative buyer who holds, hoping for appreciation. Early DePIN projects saw exactly this: contributor sell pressure kept prices suppressed even as user counts grew.

The model works cleanly for the network's utility metrics. It looks messier for anyone holding the token expecting price appreciation from growing user adoption. Sengupta's vision of a global labor marketplace is compelling. But compelling visions and strong token performance have historically had only a loose relationship in crypto.

The question isn't whether Internet Labor Markets are real — early implementations suggest they are. The question is whether they create the kind of users crypto needs: people who stick around, build on-chain history, and eventually become buyers too. Or whether they just create a new class of earners who extract value and leave.