jury-system

Synthetic validation allows you to evaluate product prototypes by aggregating judgments from diverse persona profiles. It simulates 100-500 votes to estimate overall resonance and feasibility, generating structured JSON results and human-readable jury reports.

Synthetic jury validation is a method to assess PRD resonance by simulating diverse persona judgments. It aggregates 100-500 synthetic votes across stratified user roles, outputting structured JSON for relevance and usability alongside human-readable reports.

Yes, synthetic validation scales user research by simulating 100-500 votes from stratified persona profiles. You define roles, tech comfort, and AI attitudes to mirror real user diversity, generating consensus thresholds and iteration logs.

You set up personas for scenario evaluation by defining stratified profiles that include user roles, tech comfort levels, and AI attitudes. This mirrors real user diversity to accurately estimate product resonance and feasibility.

Synthetic validation outputs structured JSON files containing resonance, relevance, and usability metrics. It also generates human-readable jury reports and iteration logs in markdown format to track consensus thresholds and changes.

Synthetic validation should not replace real user testing when high-fidelity behavioral data is required. It estimates resonance and feasibility using aggregated persona judgments, making it better for fast, scalable concept validation than final usability testing.