Skip To Main Content
Mithilesh Kumar on Muck Rack

Mithilesh Kumar

As seen in: Medium, SAGE Publishing, Outlook (India), Financial Express, DEV Community, International Journal of Antennas and Propagation, Canadian Journal of Infectious Diseases & Medical Microbiology, Dialnet - Universidad de La Rioja, Economic and Political Weekly, The Cureus Journal of Medical Science and
Is this you? As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work. Claim your profile

Get in touch with Mithilesh

Contact Mithilesh, search articles and posts on X, monitor coverage, and track replies from one place.

Learn more about Muck Rack

Actions

Share this page

Is this you?

As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
Claim your profile

Articles

Why Basic RAG Fails in Production and How Adaptive Query Routing Fixes It

|
By Mithilesh Kumar
| DEV Community
Most developers build Retrieval-Augmented Generation (RAG) pipelines assuming every user query needs a vector search. In production, this naive approach fails in three distinct scenarios: Simple Queries: "Hi", "Who created this bot?", or general knowledge queries don't need expensive vector database lookups. Ambiguous Queries: Vague user questions lead to noisy retrieval, diluting the LLM's context window with irrelevant chunks.
Open in Who Shared Issue with article?

Building Scalable Multi-Agent Workflows & RAG Pipelines with LangGraph and FastAPI

|
By Mithilesh Kumar
| DEV Community
Building fully autonomous AI systems requires moving beyond simple linear prompts to robust, stateful agentic workflows. In this article, I share my core architecture for engineering Multi-Agent Systems and Retrieval-Augmented Generation (RAG) pipelines using LangGraph, FastAPI, and Python. Why Agentic Workflows and LangGraph? Traditional LLM applications often struggle with complex, multi-step execution paths.
Open in Who Shared Issue with article?

A Hybrid Feature Fusion for Retinal OCT Image Classification using Traditional and Deep Learning Methods

|
By Nagendra Singh, Mithilesh Kumar, Singh Yadav
| Dialnet - Universidad de La Rioja
IdiomacatalàDeutschEnglishespañoleuskarafrançaisgalegoitalianoportuguêsromână
Open in Who Shared View Duplicates (689) Issue with article?
See all 1,115 licensed articles (1,120 Total)