deep-plan

A zero-code architectural audit resolves technical ambiguities, defines invariants, and simulates physical file changes before implementation. You need this pre-implementation audit for complex refactoring, new feature development, and high-risk operations to mitigate architectural risks.

To ensure AI resolves ambiguities before coding, use an interactive pre-implementation audit that forces clarifying questions until all technical decisions are locked. This decision-first methodology requires explicit user input to resolve gaps in the proposed plan.

Define property-based testing invariants during the architectural audit phase by establishing mathematical properties, such as idempotency, that the final code must satisfy. This ensures your refactoring plan maintains strict data consistency and logic integrity.

Yes, you can preview exact file modifications through physical change simulation. This audit step analyzes data flow, complexity, and potential system side effects to show exactly how files will be altered before any actual coding begins.

Yes, this pre-implementation planning approach works for critical payment processing modules. It explicitly defines edge cases, error handling strategies, and data consistency requirements, ensuring architectural soundness for high-risk operations before any code is written.

The limitation of a decision-first methodology is that it requires interactive user input for ambiguity resolution and strict adherence to predefined audit templates. It is not suited for rapid prototyping or scenarios where skipping pre-implementation risk assessment is acceptable.