Category: Emerging Technologies

Introduction: Off-the-shelf embedding models work well for general text, but domain-specific applications often need better performance. Fine-tuning embeddings on your data can dramatically improve retrieval quality—turning a 70% recall into 90%+ for your specific use case. The key is creating high-quality training data that teaches the model what “similar” means in your domain. This guide… Continue reading

Introduction: Not all queries are equal—some need fast, cheap responses while others require deep reasoning. Query routing intelligently directs requests to the right model, index, or processing pipeline based on query characteristics. Route simple factual questions to smaller models, complex reasoning to GPT-4, and domain-specific queries to specialized indexes. This approach optimizes both cost and… Continue reading

Introduction: LLM applications are notoriously hard to test. Outputs are non-deterministic, quality is subjective, and traditional unit testing doesn’t capture the nuances of language generation. Yet shipping untested LLM features is a recipe for embarrassing failures—hallucinations, off-brand responses, or security vulnerabilities. This guide covers practical testing strategies: deterministic unit tests for prompt templates, evaluation suites… Continue reading