Start as a focused service that audits a buyer's SDLC, selects 2 to 3 high-value agent workflows, configures the tools, writes usage policies, builds evaluation checklists, and trains teams through real tickets. The first delivery package should produce concrete artifacts: approved AI coding workflows, repo-specific agent instructions, secure sandbox patterns, PR review gates, test-generation procedures, and a monthly adoption scorecard. Over time, the service can productize reusable templates, governance playbooks, benchmark harnesses, and lightweight internal tooling.

AI coding agents are moving from individual experimentation into company-wide engineering practice. The job signals show enterprises now care about governance, reliability, secure delegation, evaluation, and measurable productivity rather than demos.