How would you improve AI response accuracy?

Signal to interviewer

I can improve AI accuracy by designing governance and execution layers explicitly, so policy decisions and inference mechanics evolve independently without breaking reliability.

Clarify

I would define accuracy for this product context: factual correctness, instruction adherence, or domain-grounded precision. I would identify highest-impact error classes and whether failures stem from retrieval, reasoning, or orchestration.

Approach

Use control plane versus data plane analysis. Control plane sets routing rules, confidence policies, escalation thresholds, and safe fallback behavior. Data plane executes retrieval, context ranking, generation, and post-generation validation. Improvements are prioritized by which layer contributes most to observed error classes.

Metrics & instrumentation

Primary metric: verified correctness rate on representative production samples. Secondary metrics: contradiction incidence, citation support coverage, and corrected-answer turnaround. Guardrails: latency budget breaches, over-refusal rate, and user trust complaints. Instrumentation: route selection logs, retrieval hit quality, confidence calibration curves, and validator outcomes.

Tradeoffs

More validation and multi-step routing improve correctness but increase cost and latency. Aggressive refusal policies reduce harmful errors but can lower perceived helpfulness. Tight policy controls improve consistency but may reduce flexibility on novel queries.

Risks & mitigations

Risk: hidden routing regressions after policy updates; mitigate with shadow evaluation and canary gates. Risk: stale retrieval corpus; mitigate with freshness monitors and re-index triggers. Risk: validator blind spots; mitigate with adversarial test sets and periodic reviewer audits.

Example

In an internal knowledge assistant, low-risk FAQ requests use a fast path, while policy-sensitive questions route to a high-validation path with mandatory citation checks and contradiction scanning.

90-second version

Improve accuracy by splitting the system into control and data planes. Use control logic for routing and safeguards, data logic for retrieval and generation quality, and optimize each with targeted telemetry and validation.