Tag: software process

AI coding agents are turning software work into management work: engineers now have to manage intent, context, agent output, teammate coordination, stakeholder evidence, and long-term maintenance.

Outcome: Defined a public operating model for engineers and consultants who need to coordinate human teammates and AI agents without producing artifacts that create hidden technical debt.

Why teams using Claude, GPT-style coding agents, Cursor, and Copilot often get unstable app work when requirements, versions, conventions, tests, and handoffs are implicit.

Outcome: Defined a docs-first assistant workflow that turns requirements, pinned stack choices, task slices, review loops, tests, and Git checkpoints into a repeatable way to ship with AI without surrendering architecture control.