Compliance
Deploying LLMs in Regulated Industries: The Eval Requirements You Can't Skip
Healthcare, financial services, and legal teams face stricter LLM output standards. The eval criteria that map to those requirements.
Fyntune Notes
On LLM evaluation, production AI quality, and prompt engineering in the real world.
LLMOps
Running Evals Across Multiple Models: A Practical Comparison Strategy
How to structure eval runs when your team is comparing GPT-4o, Claude 3.5, and Gemini on the same task — without drowning in result tables.
LLM Evaluation
Using LLM-as-Judge: When It Works and When It Doesn't
The appeal of LLM-as-judge for open-ended evals, its calibration challenges, and how to combine it with deterministic criteria.
Prompt Engineering
Eval-Driven Development: Writing Tests Before You Write Prompts
Flipping the workflow: define your quality criteria first, then iterate prompts until evals pass.
LLMOps
Foundation Model Ops: Five Things Teams Get Wrong When Switching Models
Model swap does not equal drop-in replacement. The quality assumptions that break silently when you change from GPT-4 to Claude.
LLM Evaluation
LLM Regression Testing: A Practical Guide for ML Platform Teams
Building a regression baseline, choosing eval criteria by feature type, and interpreting delta scores.
LLM Evaluation
Semantic Similarity vs Exact Match: Which Eval Approach Fits Your Use Case
When exact-match scoring masks real quality improvements and when semantic similarity misses genuine regressions.
Integration
Adding LLM Evals to Your CI/CD Pipeline in an Afternoon
Step-by-step guide to wiring Fyntune into GitHub Actions and GitLab CI so every PR triggers an eval run.
Safety & Guardrails
When Guardrails Fail Silently: Three Patterns We See Most
The most common ways guardrail failures slip past manual review and what automated eval catches that humans miss.
LLM Evaluation
LLM Eval Metrics That Actually Matter in Production
Semantic similarity, factuality, coherence, and guardrail compliance — ranked by correlation with user satisfaction.
Prompt Engineering
Prompt Versioning: What Git Taught Us About Managing LLM Prompts
Treating prompt changes like code changes — branching, diffing, rollback. The workflow ML teams are building.
LLM Evaluation
Detecting Hallucinations in Production LLMs Before Your Users Do
How systematic eval suites catch factual drift that A/B tests miss, with concrete eval criteria examples.