Why You Can't 'Manage' Code You Don't Understand

Source: Dev.to

Context

A common question in the age of AI is: “If AI writes the code, do developers just become Product Managers?”

The answer is No, and the reason lies in The Principle of Contextual Authority.

• Product Managers primarily own the Problem Space (user needs, market fit, value).
• Engineers primarily own the Solution Space (architecture, reliability, maintainability).

If a PM doesn’t understand the market, they build the wrong product. If an Engineer doesn’t understand the system, they build a fragile product.

The “How” Contains the Risk

When a developer delegates to AI without maintaining ownership, they are trying to outsource the Solution Space. The story becomes: “The AI handles the ‘how’, I just handle the ‘what’.” But the how contains the technical risk you can’t outsource.

• The how determines if the database locks up under load.
• The how determines if the security model is valid.
• The how determines if the system can be extended next month.

If the engineering team delegates the how to AI without maintaining deep understanding, the codebase becomes a liability. The team doesn’t become PMs; they become custodians of technical debt they can’t reason about.

The Contractor Trap

When you delegate a task to an AI because you don’t understand the code (or don’t want to deal with its complexity), you are acting as a Contractor. You use the AI as a shield against complexity. The AI produces a “black box” patch that closes the immediate ticket, but you can’t predict its impact on the rest of the system.

Doing this repeatedly erodes your mental model of the software. You become a “Product Manager of Code”—someone who can describe what they want, but can’t reliably explain why it works or when it will fail.

Unlike a real Product Manager who relies on an engineering team to ensure structural integrity, you’re relying on a model that (without strong feedback loops) is optimized for plausible output, not system guarantees.

The Architect of Agency

The best strategy for scaling is not to become a manager of black boxes, but to become an Architect of Agency. Use AI to execute, but rigorously audit the output against your mental model. Trade the low‑leverage work of syntax generation for the high‑leverage work of System Verification.

This requires Ownership‑Preserving Delegation. Don’t demand “trust me” output. Demand an audit trail: tests that pin behavior, clear invariants, notes about trade‑offs, and a narrative diff you can reason about before you accept the change.

You don’t lose ownership by delegating; you lose ownership by stopping to look.