Scoring Rubric Design for Open-Ended Generation Tasks
Rubrics decompose quality into verifiable criteria, replacing opaque scalar scores.
Priya Venkateswaran
CRM Confessions — Page 2
Eval Harness Architecture
Eval Harness Orchestration With Open-Source Frameworks
Turn eval harnesses into production gates using the right framework and orchestration topology.
Latency and Throughput Benchmarking Inside Eval Harnesses
The harness, not the model, drives latency and throughput.
Casimir Wojcik
More From CRM Confessions
Integrating Eval Harnesses Into CI/CD for ML Model Releases
Blocking eval gates in CI/CD catch model failures before production.
Priya Venkateswaran
Determinism and Reproducibility in Automated Eval Pipelines
Model stochasticity breaks the reproducibility assumption that powers engineering gates.
Nkechi Oduya
Regression Testing Pipelines for Iterative Model Releases
Catch model degradation before production with automated gold-set testing.
Priya Venkateswaran
LLM-as-Judge Calibration and Bias Auditing
How miscalibrated LLM judges quietly shift baseline quality scores in production systems.
Nkechi Oduya
Benchmark Validity for Multilingual and Code-Switching Models
Current benchmarks mismeasure multilingual AI ability.
Casimir Wojcik
Synthetic Data Generation for Low-Resource Eval Scenarios
Synthetic test data helps teams catch AI failures before production reaches real users.
Casimir Wojcik
Eval Set Coverage Metrics Beyond Accuracy
Accuracy masks which failure modes your eval set actually covers.
Priya Venkateswaran
Version Control and Lineage Tracking for Eval Datasets
Eval datasets drift silently from production; version control and lineage tracking catch it.
Priya Venkateswaran
Domain Shift Detection in Training vs Evaluation Distributions
Models drift silently in production when training and real-world data diverge.
Casimir Wojcik