Himanshu Agarwal
PulseAugur coverage of Himanshu Agarwal — every cluster mentioning Himanshu Agarwal across labs, papers, and developer communities, ranked by signal.
-
AI Interview Prep: 300 Q&A on LLMs, RAG, and MCP for Senior Engineers
This guide offers 300 interview questions and answers for senior AI/ML engineers, focusing on Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Model Context Protocol (MCP). It covers foundational …
-
Claude AI and MCP integrate for advanced automated software testing
A new guide and ebook explore the integration of the Model Context Protocol (MCP) with Anthropic's Claude AI for automated software testing. The resources detail how Claude can understand user intent to generate tests, …
-
LLM Interview Questions Focus on Production Experience
This article outlines common interview questions for enterprise AI engineering roles, focusing on practical experience beyond theoretical knowledge. It covers topics such as LLM fundamentals, transformer architecture, a…
-
Promptfoo framework streamlines LLM testing for production QA engineers
Promptfoo is an open-source framework designed to address the unique challenges of testing Large Language Models (LLMs) in production environments. Unlike traditional software testing, LLM testing requires redefining 'c…
-
Enterprise LLM Engineering Guide Focuses on System Reliability and Security
This guide focuses on enterprise LLM engineering, emphasizing the creation of reliable, observable, and secure systems around large language models rather than just prompt engineering. It details core components, archit…
-
LLM Interview Guide for Experienced Engineers Focuses on Production Systems
This article provides a guide for experienced engineers preparing for interviews focused on large language models (LLMs). It highlights that modern LLM interviews emphasize practical production experience over theoretic…
-
AI integrates with enterprise systems via MCP, creating intelligent bridges
The concept of MCP (Multi-cloud Platform) is evolving beyond simple generation to act as an intelligent bridge between AI applications and enterprise systems. This integration allows AI assistants to perform complex tas…