How to Evaluate a Retrieval-Augmented Generation System
A RAG assistant can fail at retrieval, at reasoning or at answering. Evaluating each stage separately is the fastest way to improve quality.
Insight topic
Research Notes insights
Notes on experiment design, evaluation methods and feasibility work. Articles in this topic are written for leaders and practitioners who need practical, evidence-based guidance.
2 articles in Research Notes
Writing a Proof of Concept That Actually Decides Something
Many AI proofs of concept end in a demo and a shrug. A short charter written before the build turns them into decisions.
Topic guide
Understanding research notes
Research notes share methods from applied research: experiment design, evaluation, feasibility and proofs of concept. They are written to help teams produce evidence that supports real decisions.
FAQ
Key questions about research notes
What is applied research in AI?
Structured investigation into whether and how an AI approach can solve a specific problem, ending in a recommendation for engineering or further work.
What makes an experiment trustworthy?
A clear question, success criteria and baselines agreed before results, realistic test data kept separate from development and honest reporting of failures.
Is a negative research result useful?
Yes. Evidence that an approach does not work, backed by analysis, prevents far larger investment in building something that would fail.
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