Hybrid Search & Agentic RAG for Enhanced Data Retrieval

Building robust AI systems for information retrieval presents a recurring challenge: balancing precision and recall. Retrieval-Augmented Generation (RAG) frameworks have emerged as a powerful solution, allowing language models to generate responses grounded in real-world data. However, traditional retrieval methods often struggle with messy, mixed-type data or exact keyword queries. This is where Hybrid Search and Agentic RAG come into play, transforming our approach to dat

Javith Abbas

1 day ago3 min read

RAG

I've been contemplating this blog since 2024, and here I am, finally putting pen to paper in 2026. Remarkably, my understanding of Retrieval-Augmented Generation (RAG) has remained consistent over the past two years. This reflects the depth of research I've conducted since 2023. RAG has fundamentally reshaped our perception of Large Language Models (LLMs) and their limitations. It’s time to share my journey, insights, and practical experiences with this powerful architecture.

Javith Abbas

1 day ago4 min read

Demystifying LangGraph State Management: Reducers, Overwrites, and Supersteps

When I first started working with LangGraph, I was struck by its unique approach to state management, which deviates from the typical global state mutation model found in many frameworks. Instead of directly modifying a shared state variable, LangGraph nodes return explicit updates that are applied to a central state. This design fundamentally alters how state evolves during graph execution, and it took me some time to fully grasp its nuances. In this post, I’ll break down L

Javith Abbas

2 days ago4 min read

Navigating Subgraph Persistence in LangGraph: Journey from Pitfalls to Best Practices

I often find myself diving headfirst into coding, driven by excitement and curiosity, sometimes neglecting to fully grasp the underlying mechanics of the tools I use. This approach has led to both triumphs and frustrations. Recently, while delving deeper into LangGraph, I encountered another one of those "WHAT THE HELL" moments that compelled me to step back, learn the fundamentals, and gain insights that I believe can help others avoid similar pitfalls. In this post, I’ll s

Javith Abbas

2 days ago4 min read

LangGraph Checkpointers in Action: Lessons Learned from Distributed Deployments

Today, I found myself deep in a technical challenge, anticipating issues but driven by the excitement of discovery. As a developer, I’ve learned that hands-on experience with tools often provides more insight than any documentation or tutorial. This time, my focus was on LangGraph Checkpointers a mechanism for managing state in distributed workflows. What began as a casual experiment turned into an enlightening journey into state persistence, distributed systems, and the comp

Javith Abbas

6 days ago3 min read

Plan and Execute Design Pattern: Agentic AI Systems

When I began working with large language models (LLMs), I was amazed by their ability to generate human-like text and tackle complex queries. However, I quickly recognized a crucial limitation: while LLMs excel at producing coherent output, they struggle with intricate, multi-step problems. They resemble brilliant improvisers but lack the structured approach necessary to navigate the hidden complexities of real-world tasks. This realization led me to Agentic Design Patterns

Javith Abbas

Feb 154 min read

Exploring Routing Design Pattern: Agentic AI Systems

Why Routing Matters When I first began building multi-model AI systems, I quickly discovered that routing was not merely a technical detail, it was the backbone of the system's efficiency and scalability. Routing dictates how queries are processed, balancing cost, accuracy, and latency to optimize the system's "thinking budget." Without effective routing, you risk overloading expensive models with trivial tasks or missing the mark with lightweight models that lack the capabil

Javith Abbas

Feb 154 min read