Architect

Architectural review for AI coding agents prevents goal misalignment by enforcing strict role separation between architect and implementer roles, requiring pre-dispatch pre-flight documentation, and conducting post-implementation adversarial audits with blocking verdicts to catch wrong-shape work early.

The best way to manage architectural review for high-stakes tasks is enforcing mandatory checkpoints, including a user-reviewed pre-flight document before dispatch and a post-implementation adversarial audit with blocking verdicts to catch goal misalignment early and prevent costly rework.

Maintain architectural discipline across multi-dispatch project work streams by using long-running series support features like truncation recovery, tracked finding closure workflows, and series-mode tallying to enforce strict review guardrails throughout the entire implementation process.

Yes, this architectural review approach works for high-stakes software engineering tasks including new dependency additions and subsystem replacements where incorrect implementation is costly to reverse, enforcing goal alignment checks and strict role separation to prevent architectural drift.

Strict role separation between architect and implementer roles matters because it avoids rubber-stamping work and ensures honest, adversarial review of all AI coding agent output, preventing architectural drift and costly rework from literal request implementations.