Evaluation-Driven AI Development
Treating evals as first-class, continuous tests for AI features.
Shipping an LLM feature without a living evaluation suite is the single most common root cause of AI product failures we see. Evals-as-code, run in CI, should be non-negotiable before any model or prompt change ships.
Signals behind this placement
- —Shipping an LLM feature without a living evaluation suite is a recurring root cause in post-incident reviews.
Sequencing
Enables Agentic Workflows, Small Language Models (SLMs), Reasoning Models, Autonomous Coding Agents, Synthetic Data Generation
Evaluation-Driven AI across other industries
Treating evals as first-class, continuously-run tests gating every model or prompt change.
Evaluation-Driven Clinical AI
Continuous, clinically-validated evaluation suites gating every model change.
Evaluation-Driven AI for Credit Decisioning
Continuous, fairness- and accuracy-tested evaluation suites gating every model change.
Evaluation-Driven AI for Predictive Maintenance
Continuous evaluation suites validating predictive-maintenance model accuracy over time.
Evaluation-Driven AI for Recommendations
Continuous evaluation suites validating recommendation and ranking model quality.
From the Technology & SaaS Emerging Technology & Innovation Radar, Edition 2026.1, published 2026-10-01.
An independent, industry-agnostic radar curated by Shailesh Kumar.