Building a Multi-Tool Gemma 4 Agent with Error Recovery
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Implementing hybrid search strategies is a critical step in building modern RAG (Retrieval-Augmented Generation) systems , especially when shifting from prototype to production-ready solutions.
Keyword search breaks the moment a user types something a document doesn’t literally say.
I have been experimenting with the OpenAI Agents SDK, and it has quickly become one of my favorite ways to build agentic AI applications.
Here is the number that defines the current state of things:
You have probably spent time learning how to prompt AI well.
Search works well when users know exactly what they are looking for, but it breaks down when intent is described in natural language.
Most
Large language models (LLMs) now power everything from customer service bots to autonomous coding agents.
Agentic loops in production can be synonymous with high costs, especially when it comes to both LLM and external application usage via APIs, where billing is often closely related to token usage.