General purpose agentic loop in 40 lines of Python
When rolling your own agent, tool calling comes with annoying plumbing (packaging up arguments from the…
Reasoning boosts search relevance 15-30%
In my previous article, I hypothesized reasoning agents work best with simple search tools. In agentic…
Agents turn simple keyword search into compelling search experiences
A traditional RAG system often looks like the search we’ve built for years. An LLM calls…
A Machine Learning-Driven Approach for Optimizing Hybrid Search
How to greatly improve your hybrid search results using machine learning to dynamically optimize hybrid search parameters for each query.
Grug-brained evals
Big brain spend months building perfect quality metrics. Grug brain no trust, and just want dumb labels from coworkers 👍/👎.
RAG’s big blindspot
RAG apps have a big blindspot – using actual user engagement to drive improvement. But its a hard problem. Let’s discuss!
AI-Powered Search: Revolutionizing Search for the AI Era
A quickly evolving search landscape, driven by the intersection of artificial intelligence, machine learning, and the…
Deep dive: Enabling pluggable storage in the OpenSearch vector engine
In 2019, OpenSearch introduced the Vector Engine, which supports three native engines: Non-Metric Space Library (NMSLIB),…
Semantic Search on Bonsai
Adding Semantic Search to Elasticsearch/OpenSearch with MistralAI Embeddings. This in the next installment in a series…
AI-Powered Search: Navigating the Evolving Lexicon of Information Retrieval
Based on Trey Grainger’s keynote at Haystack EU 2024 The field of information retrieval is experiencing…
