Claude API

Anthropic Publishes Quantitative Case Study on Prompt Engineering for Long-Context Recall

Anthropic shares a quantitative case study evaluating prompting techniques to improve Claude's recall over 75,000–90,000 token contexts. Two techniques are tested: extracting reference quotes before answering, and providing few-shot examples of correctly answered questions. The study uses Claude Instant 1.2 on a government document dataset constructed via a 'randomized collage' method, with multiple-choice Q&A pairs generated by Claude itself. Results show measurable recall improvements over a baseline prompt, with methodology and notebooks shared publicly.