Record · corpus.blog/posts/01a0b654-6676-724b-bc48-04fbe17ee824

LLM evaluations: Tutorial and best practices

launchdarkly.com · published 6 January 2026

A record is what was published and who pointed at it. The text of the post is not held here: read it at the source, or at its Wayback capture.

Read the post at launchdarkly.com Wayback capture

0blogs citing

First cited: —
Most recent: —
Rank this month: not ranked
Links from this post: 35
Words captured: 6,132

Cited by

No blog we hold has cited this post yet.

Links from this post

Link

Host

AI model deployment: Best practices for production environments Read at the source ↗

launchdarkly.com

https://www.bbc.com/travel/article/20240222-air-canada-chatbot-misinformation-what-travellers-should-know

bbc.com

Catch AI hallucinations before they break user trust Read at the source ↗

launchdarkly.com

https://artificialintelligenceact.eu/

artificialintelligenceact.eu

https://leginfo.legislature.ca.gov/faces/billTextClient.xhtml?bill_id=202520260SB53

leginfo.legislature.ca.gov

LLM pricing comparison: Tutorial and best practices Read at the source ↗

launchdarkly.com

The Complete AI Experimentation Guide: Test, compare, validate, and ship safely Read at the source ↗

launchdarkly.com

MLOps lifecycle: Stages, workflow, and best practices Read at the source ↗

launchdarkly.com

LLM RAG Tutorial: How to Build a Reliable Retrieval Pipeline Read at the source ↗

launchdarkly.com

https://arxiv.org/abs/2403.04132

arxiv.org

https://en.wikipedia.org/wiki/All_models_are_wrong

en.wikipedia.org

https://arxiv.org/abs/2410.07137

arxiv.org

Online evals: LLM-as-a-Judge Read at the source ↗

launchdarkly.com

Prompt versioning & management guide for building AI features Read at the source ↗

launchdarkly.com

Advancing red teaming with people and AI Read at the source ↗

openai.com

https://www.anthropic.com/research/team/frontier-red-team

anthropic.com

https://blog.google/innovation-and-ai/technology/safety-security/googles-ai-red-team-the-ethical-hackers-making-ai-safer/

blog.google

https://arxiv.org/abs/2603.05399

arxiv.org

https://arxiv.org/abs/2607.08535

arxiv.org

https://huggingface.co/datasets/abisee/cnn_dailymail

huggingface.co

LLM observability: Tutorial and best practices Read at the source ↗

launchdarkly.com

Observability is not enough Read at the source ↗

launchdarkly.com

https://launchdarkly.com/platform/agent-control/

launchdarkly.com

What Are Feature Flags? Read at the source ↗

launchdarkly.com

https://launchdarkly.com/docs/home/agentcontrol/offline-evaluations

launchdarkly.com

https://launchdarkly.com/docs/tutorials/offline-evals

launchdarkly.com

https://launchdarkly.com/docs/home/agentcontrol/online-evaluations

launchdarkly.com

Online evals in AI Configs is now GA Read at the source ↗

launchdarkly.com

https://launchdarkly.com/docs/tutorials/when-to-add-online-evals

launchdarkly.com

https://launchdarkly.com/docs/home/releases/guarded-rollouts

launchdarkly.com

Adaptive Triggers: AI that corrects itself in production Read at the source ↗

launchdarkly.com

LLM inference optimization: Tutorial & Best Practices Read at the source ↗

launchdarkly.com

https://launchdarkly.com/case-studies/hireology-ai/

launchdarkly.com

https://launchdarkly.com/policies/privacy/

launchdarkly.com

https://go.launchdarkly.com/UnsubscribePage.html

go.launchdarkly.com