How We Hire Engineers Who Think in Both AI and Web3

Frequently Asked Questions

01.What does it mean to hire an engineer who thinks in both AI and Web3?

It means the engineer can reason about a system end to end: where an AI model or agent makes a decision, and where that decision needs to settle on chain with finality, auditability, and cost controls. They understand that an AI agent recommending a trade is a different engineering problem than an AI agent executing one, and they design guardrails accordingly rather than treating the two disciplines as separate hires bolted together.

02.Why is this hybrid skillset harder to hire for in 2026 than a year ago?

Because the two talent pools are shrinking toward each other from opposite directions. Weekly crypto code commits fell roughly 75 percent since early 2025 as experienced developers moved toward AI projects, while demand for AI engineering skills grew sharply over the same period. The overlap, engineers who stayed in Web3 while also going deep on AI systems, is a small and shrinking group relative to overall demand.

03.What should founders test for instead of relying on résumés alone?

A scoped take-home or paired session where the candidate designs a system with an AI decision layer and an on-chain settlement layer, then explains the failure modes at the boundary between the two. Résumés list technologies; this exercise reveals whether the candidate has genuinely reasoned about where an autonomous decision needs a circuit breaker before it touches real value.