Spec-driven AI Migration: How Nearly 2 Quarters of Work Was Completed in One Week

This post details a 'spec-driven AI migration' approach where Jira tickets are used as structured behavioral specifications for AI agents. The authors migrated over 100 GraphQL fetchers by defining detailed specs in Jira, which AI agents then used to generate migration code. Key contributions include: 1. Using Jira as a persistent, reviewable 'store of truth' for AI agent context, preventing context degradation across sessions or agents. 2. Shifting engineering focus from writing repetitive code to defining behavior, shaping context, and managing confidence. 3. Implementing layered verification: agent acceptance criteria, pre-review validation agents, and live traffic shadow testing. 4. Highlighting Jira tickets as a durable, structured prompt for agentic workflows, enabling parallelism and scalability.