Implementing Hybrid Semantic-Lexical Search in RAG
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.
Building Context-Aware Search in Python with LLM Embeddings + Metadata
Keyword search breaks the moment a user types something a document doesn’t literally say.
How to Build a Multi-Agent Research Assistant in Python
I have been experimenting with the OpenAI Agents SDK, and it has quickly become one of my favorite ways to build agentic AI applications.
Agentic Programming: A Roadmap
Here is the number that defines the current state of things:
Prompt Engineering for Agentic AI
You have probably spent time learning how to prompt AI well.
Building Vector Similarity Search in PostgreSQL with pgvector
Search works well when users know exactly what they are looking for, but it breaks down when intent is described in natural language.
Choosing the Right Agentic Design Pattern: A Decision-Tree Approach
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LLM Observability Tools for Reliable AI Applications
Large language models (LLMs) now power everything from customer service bots to autonomous coding agents.
Implementing Prompt Compression to Reduce Agentic Loop Costs
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.
Implementing Permission-Gated Tool Calling in Python Agents
AI agents have evolved beyond passive chatbots.