Adoption does not require abandoning Jira, GitLab, or familiar harness configurations. It requires digitizing delegation: give agents identities, move execution into a shared runtime environment, preserve plans and traces, account for compute and human attention, formalize permissions, and make skill development a team activity.
A sprint then stops being a collection of issues that conceal personal sessions. It becomes an observable flow of runs, reviews, waits, and decisions. The team can address the actual executors, compare profiles, reproduce failures, and accumulate project memory.
The path to an AI-native company begins with data-driven agent production. First, the organization learns to see runs, attempts, cost, human involvement, and result quality. Only then can it make evidence-based improvements to pipelines, redistribute work between people and agents, and change the production process itself.
Agentic execution becomes part of the team process—not a developer’s personal magic.