Map the work and its constraints.
Work with sponsors, process owners and users to understand priorities, exceptions, existing software and data access. Establish a baseline for the work you want to improve.
Outputs to agree: a problem map, priorities, access findings and an implementation recommendation.
Define the working model.
Describe how people, information and software will interact. Decide what AI may do, where review is required, how systems connect and what a good result looks like.
Outputs to agree: target workflows, integration scope, responsibilities, evaluation cases and acceptance criteria.
Build and review working increments.
Develop the agreed applications, integrations and AI steps using our daily Codex and Claude desktop/CLI practice. Use Agentic Crews when specialist roles and handoffs help; define orchestration, review responsibility and failure handling. Review progress with domain users, including difficult cases and failures.
Outputs to agree: working software, review interfaces, tested integrations and documented limitations.
Prepare people and release deliberately.
Connect practical learning to the workflow. Test representative work, check permissions and practise exceptions. Agree release authority, recovery and the owner of everyday operation.
Outputs to agree: an accepted release, operating instructions and role-specific demonstrations.
Operate, improve and extend.
Review quality, cost, usage and staff effort. Test changes to models, instructions or integrations. Use evidence to choose further workflows and reuse foundations where they fit.
Outputs to agree: an operations plan, improvement priorities and a support or handover arrangement.