About Kavriq

Kavriq is an attempt to explain modern AI, especially Agentic AI, from first principles with an engineering mindset.

Most AI content focuses on tools and surface-level abstractions. Kavriq takes a different approach: understanding how systems work, how they are built, and how they behave in real settings.

About the Author

I am Ravi Shankar, a software engineer working on AI systems and developer platforms.

Kavriq is where I document what I am learning and building in AI, with a focus on clarity, depth, and practical understanding.

Background

I graduated in Computer Science from NIT Allahabad and have worked across startups and large-scale engineering environments.

My experience includes product startups such as THB, Urban Company, Flynote, and Trinkerr, followed by platform and infrastructure engineering at Oracle. I currently work in AI engineering at Salesforce.

Learning

• Mathematics for Machine Learning Specialization — Imperial College London
• Mathematics for Machine Learning and Data Science Specialization — DeepLearning.AI

Philosophy

Kavriq is built on a simple idea:

Understanding systems deeply is more valuable than chasing tools.

The goal is not to keep up with trends, but to build a mental model that lasts.