Building GenLayer’s Docs from a Whitepaper
GenLayer had a product but no developer documentation. Just a dense whitepaper that described the protocol’s design and architecture. My job was to turn that into something developers could actually use.
The Challenge
The whitepaper was written for an academic audience. It described the protocol’s consensus mechanism, the role of validators, and the theory behind intelligent contracts. None of that was structured for a developer who needed to install the CLI, write a contract, and deploy it.
The gap between “here’s how the protocol works conceptually” and “here’s how to build something on it” was the entire documentation project.
50+ Pages in Nextra
I authored 50+ pages for the first version of the documentation, built in Nextra. This covered the full surface area a developer needed:
- JSON-RPC API reference for every available method
- CLI reference for the development tooling
- Getting started guides that took a developer from installation to running their first intelligent contract
- Conceptual documentation explaining the protocol architecture in developer-friendly terms
- Tutorials for building on the platform
Each piece required translating academic-style writing into clear, task-oriented content. A developer shouldn’t need to understand the consensus theory to deploy a contract. They should be able to follow the getting started guide and understand the theory later, if they want to.
In-App Error Messaging and UI Copy
Beyond the docs site, I collaborated with the product team to write in-app error messaging and UI copy for GenLayer Studio, the platform’s development environment. This meant understanding the developer’s workflow end-to-end: not just what the API did, but what errors they’d hit, what the messages should say, and how to guide them through recovery.
Bridging AI and Blockchain
GenLayer sits at the intersection of AI/ML and blockchain infrastructure. The documentation needed to make sense to developers coming from either background. A blockchain developer needed to understand how the AI validator consensus worked. An AI developer needed to understand how the blockchain execution model worked.
The result was a complete documentation site that could stand on its own as the primary onboarding resource for new developers.