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Technical onboarding for new leaders has been transformed. Instead of relying on engineers for ad-hoc explanations, a CPO can now use AI tools to have "long conversations" with the codebase, gaining a deep understanding of the technical architecture quickly and without interrupting the team.

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Field engineers can bypass documentation limitations by querying the entire codebase with AI tools like Claude Code. This provides detailed, step-by-step answers that public docs lack, directly addressing complex customer problems and reducing reliance on the engineering team.

To improve communication with engineering, PMs should use AI to analyze their company's actual codebase. Asking the AI for a high-level architecture diagram or to explain a component is a practical way to learn the system and develop a shared language with developers.

The job of a CPO is profoundly changing with AI. It's no longer about delivering features customers request. Instead, it's about deeply understanding customer problems to collapse entire workflows and design new outcomes (e.g., "get paid faster"), leveraging technology in ways customers haven't imagined.

Product managers can use coding agents like Codex for self-service technical discovery. Instead of interrupting engineers with questions, they can ask the AI about the codebase, feature status, or implementation details, increasing their autonomy and team efficiency.

C-level executives with a technical past, like GitHub's COO, are using AI to build their own internal tools. This allows them to apply their unique blend of business and technical expertise to solve problems directly, bypassing traditional workflows and increasing their effectiveness.

PMs can use AI agents connected to their codebase to explore technical feasibility and iterate on ideas. This serves as a 'digital tech lead,' saving immense time for senior engineers who were previously burdened with speculative 'how hard would it be?' questions from product managers.

AI tools reduce the communication overhead and lengthy handoffs that traditionally separated product and engineering. By streamlining the path from idea to code, AI makes the combined Chief Product and Technology Officer (CPTO) role more viable, enabling a single leader to manage both functions effectively.

AI tools are democratizing software development, shrinking teams, and blurring roles. CPOs can no longer be pure strategists; they must embrace a "builder" mindset and actively code to lead effectively in this new environment, as their teams will expect them to.

To truly understand AI's capabilities and limitations, CPOs and other leaders must get their hands dirty. Monumental's CPO spent time coding front-end prototypes with AI tools. This direct experience prevents leaders from making uninformed demands and helps them guide their teams more effectively.

With AI, codebases become queryable knowledge bases for everyone, not just engineers. Granting broad, read-only access to systems like GitHub from day one allows new hires in any role (product, design, data) to use AI to get context and onboard dramatically faster.

New CPOs Can Onboard Faster by Using AI to Interrogate the Company's Codebase | RiffOn