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Case study

Web3 / AI

Goodhive.io

Web3 + AI product — live in production

At Goodhive, I work as a founding builder and senior product engineer on a decentralized recruitment platform. The product spans Web3 integrations, AI-assisted workflows, and a modern React/Next.js frontend — all shipped to real users in a fast-moving startup environment.

Next.jsReactSolidityWeb3Node.jsAWSAI
Role
Product Engineer
Problem focus
Making blockchain products feel human — and actually work.
View live product

The problem

Traditional hiring platforms are opaque, slow, and trust-heavy. Goodhive set out to make talent matching more transparent on-chain while still feeling approachable to non-crypto users.

The core challenge wasn't just blockchain — it was making complex systems feel simple, reliable, and fast enough for daily recruiting workflows.

My role & contributions

I own significant slices of the product across frontend, backend integrations, and Web3 touchpoints — often end-to-end from idea to production.

  • Designed and implemented smart contract integration flows with clear UX for wallet connection and on-chain actions
  • Built AI-powered product features that improve matching and recruiter workflows
  • Shipped scalable Next.js/React interfaces with performance and accessibility in mind
  • Collaborated async with a distributed team (Paris-based company, remote execution)

Technical approach

We use a modern full-stack setup: Next.js and React on the frontend, Node.js services, AWS/GCP for infrastructure, and Solidity/ethers for on-chain logic.

I prioritize incremental delivery — small, testable releases rather than big-bang launches — which fits startup velocity and reduces regression risk.

  • Component-driven UI with reusable patterns across recruiter and talent flows
  • API boundaries between Web2 services and Web3 providers kept explicit and observable
  • Feature flags and staged rollouts for higher-risk blockchain features

Challenges overcome

Web3 UX is unforgiving — failed transactions, network switches, and wallet friction can kill adoption. We invested heavily in error states, retries, and plain-language copy.

Balancing decentralization ideals with product pragmatism required constant tradeoffs: not everything belongs on-chain, and users care about speed first.

Outcomes

  • Production platform serving real recruiting use cases in Web3
  • AI features integrated into live product workflows
  • Sustainable full-stack ownership in a lean founding team

Interested in similar work? I'd love to hear what you're building.

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