90% improvement in AI output accuracy
Org-Wide AI Adoption at a Web3 Gaming Platform
Challenge
The company needed to go beyond developers using Copilot. Every function — Design, Finance, Executive, Technology, Marketing — needed to work differently with AI, but there was no shared framework. AI outputs were inconsistent, product engineering was drowning in scope churn, and leadership couldn't get straight answers from their data without pulling an engineer.
Approach
Rolled out a cross-functional AI adoption program covering five departments. Restructured product engineering around Spec-Driven Development to eliminate scope thrash. Built and deployed a Claude Skill Directory with prompt shaping patterns so every team used AI the same way. Placed an AI agent on top of the data warehouse so executives and analysts could ask questions and get answers without engineering involvement.
Result
AI output accuracy improved by 90% across the organization through shared prompt-shaping patterns. Engineering regained focus with Spec-Driven Development. Executives got direct, self-serve access to business intelligence through the warehouse agent. Alongside the AI work: built and shipped a Web3 gaming discovery platform and token launchpad.