Just a placeholder for now...

The distance between a strong demo and a reliable product is usually not model quality alone. It is system quality.

A practical rule I use is this:

$$\text{Operational Quality} = f(\text{measurement},\text{constraints},\text{feedback})$$

If one term is missing, the system drifts.

Baseline stack

export type EvalRecord = {
  promptVersion: string;
  model: string;
  score: number;
  latencyMs: number;
  timestamp: string;
};

export function releaseGate(records: EvalRecord[]): boolean {
  const avgScore = records.reduce((sum, item) => sum + item.score, 0) / records.length;
  const p95Latency = records.map((item) => item.latencyMs).sort((a, b) => a - b)[
    Math.floor(records.length * 0.95)
  ];

  return avgScore >= 0.84 && p95Latency <= 1600;
}

This gate is simple, but it keeps the team honest about tradeoffs.

Practical takeaway

Treat prompts, retrieval settings, and models as versioned code. Then make quality and latency regression checks mandatory before deploy.