Twelve AI personas review every architecture decision, deploy, and data model change. They disagree by design — the friction is the quality control.
Built by one person. Reviewed by twelve.
These advisors are AI-generated personas, not real individuals. Each represents a distinct domain of expertise — designed with deliberate tension pairs to prevent groupthink and ensure rigorous, multi-perspective analysis.
Learn how the advisory system works →Architecture reviews happen on a regular cadence. Before each review, a bundle generator compiles the full codebase, infrastructure, and documentation into a single reviewable artifact. The board grades the platform on a letter scale and produces specific findings with severity ratings.
Design reviews happen for any significant change — new data models, new Lambda functions, new MCP tools, new CDK stacks. The relevant sub-board convenes, and each persona evaluates the change through their specific lens.
Incident response happens when something breaks. Jin leads triage, Yael checks for security implications, and the full board contributes to the root cause analysis.
The disagreement is intentional. Viktor will say "don't build this" while Raj says "build it faster." Priya will push for architectural purity while Dana pushes for cost efficiency. The tension between them produces better decisions than any single perspective could.