Mrudul Gole, Head of Business Development at NodeOps, joined Exponential to trace the arc of a company that started as a blockchain validator and is now building the infrastructure layer for the AI era.
The conversation covered the evolution of decentralized compute, the unlikely synergies between blockchain and AI, and a bold prediction about what dev teams will look like in six months.
NodeOps began three to four years ago when its founders were running genesis validators in the Cosmos ecosystem and noticed a growing problem. Projects were selling node licenses to retail users who had no reliable way to actually run them.
"For any retail user it kind of became a painstaking process to spin up their own nodes," Gole explains. The company's answer was a one-click deployment console that abstracted away all the complexity — for five to ten dollars a month, anyone could have a live node. That product attracted 70,000 to 80,000 paid customers and was backed by a network of 80,000 compute providers NodeOps assembled globally to reduce its reliance on centralized cloud vendors.
When the node meta cooled and AI began consuming the industry's attention, NodeOps made a deliberate pivot. The infrastructure it had already built — a distributed network of compute, orchestration tooling, a global provider base — turned out to be exactly what vibe coders needed.
The result was CreateOS, a platform designed to take a developer from idea to production in a single continuous loop without context switching. Front end, back end, database, messaging queues, GPU access for model training — all of it deployable in one click. Alongside it, NodeOps launched a Router product, an LLM gateway giving teams access to open-source models like DeepSeek and Minimax at a fraction of what frontier APIs cost.
That router has given Gole a ground-level view of a trend he says most teams underestimate: "The performance gap between frontier models and open models is way narrower than most teams assume. The cost gap though is massive."
He also flagged latency as an underrated purchase driver. "I've seen teams switch models not because quality improved but because it felt faster." On the blockchain-meets-AI side, Gole is watching two areas closely: agentic payment flows built on stablecoins like USDC, and the move by major centralized exchanges — Binance among them — to expose their APIs through MCPs, opening their systems to AI-driven trading for the first time.
His candor extends to the limitations of the space. A lot of the AI-blockchain conversation, he notes, remains at the concept level, and token-incentive dynamics can distort development priorities. Smart contract security, though increasingly accessible to smaller teams with AI coding tools, still requires vigilance — and Gole sees AI agents as a natural fit for continuous monitoring work that humans find tedious.
Looking ahead, Gole's bold bet is a near-term shift in how small dev teams are structured. "For mostly small dev teams, they will have at least one AI agent running as a permanent part of their workflow — not as a tool they open occasionally, an actual participant of the team."
Watching infrastructure, handling deployments, flagging issues, escalating to humans only when genuine judgment is required. That transition from tool to teammate, he argues, is already underway — and it is arriving faster than most enterprises are prepared to admit.
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