Blog Posts

Retrieval Strategy Design: Vector, Keyword, and Hybrid Search

This article explains how to design a modern retrieval strategy for AI systems, especially Retrieval-Augmented Generation (RAG). The focus is not only on definitions, but on engineering trade-offs, system architecture, and practical defaults.

Designing a Scalable Knowledge Base for Large Language Models

A Practical Engineering Guide to Cleaning, Semantic Chunking, Metadata, and Batch Embeddings

How to Choose the Right Model for Your AI Application

Choosing an AI model is not about finding the strongest model.

How to Write a Developer-Level Prompt: A Practical Guide

Large Language Models (LLMs) do not work well with vague instructions.
If you want consistent, controllable, and production-grade behavior, you must move beyond simple “user prompts” and start designing Developer-level prompts.

Retrieval Technique Series-6.A Discourse on Design in High-Performance Retrieval Systems

In an era defined by data, the ability to retrieve information quickly and accurately is no longer a luxury—it’s a fundamental requirement. From the search engines that power our curiosity to the e-commerce platforms that recommend our next purchase, high-performance retrieval systems are the invisible engines of our digital world. But what does it take to build a system that can sift through petabytes of data in milliseconds?