Insights

Plain-language explanations of the AI terms we use—and why they matter.

safety

What Are AI Safety Guardrails?

A quick, plain-language overview of safety guardrails—filters, limits, and design patterns that keep AI outputs useful and appropriate.

Read4 min • 2025-11-08
observability

Observability for AI Features

Observability gives you the lens to see how AI features behave: inputs, outputs, latency, cost, and quality signals.

Read5 min • 2025-11-08
workflow

Human-in-the-Loop AI Explained

Not everything should be fully automated. Human-in-the-loop lets you mix efficiency with judgment.

Read3 min • 2025-11-08
rag

RAG (Retrieval-Augmented Generation) Basics

RAG combines retrieval and generation so answers stay grounded in real, approved content instead of guesswork.

Read6 min • 2025-11-08
nl

Natural Language (NL) Interface Patterns

NL interfaces let users express intent directly. The challenge is shaping ambiguous language into reliable actions.

Read5 min • 2025-11-08
experimentation

A/B Testing Prompts: A Plain Guide

How to compare two prompt versions fairly so you improve quality without guesswork.

Read4 min • 2025-11-08