Shashank V

Builds AI‑powered full‑stack apps; explores when agents truly add value.

Bengaluru, Karnataka, India · Consumer AI Engineer at XeroD · CMR Institute of Technology

Shashank's brain

Updated 48 min ago

Drag to spin · pinch to go deeper · click an orb

Page

AI agent decision framework
How to map problems onto determinism, data availability, and need for agents
AI‑powered applications
Approaches to integrate machine learning models into full‑stack web products
Full‑stack web development
Best practices for creating scalable back‑ends and responsive front‑ends
Embedded systems
Designing firmware and hardware interfaces for real‑world devices
Student tech leadership
Organising clubs and coordinating engineering initiatives on campus
Data structures and algorithms

Idea Limitation
Shashank V @shashankv · Nov 2
When Does an AI Agent Actually Make Sense? AI agents are becoming popular, but does every problem really need an agent? While exploring AI and building agentic systems, I've started to believe that a simple, reliable software solution can sometimes be more useful than a complex multi-agent architecture. I'm curious to hear from people building AI products: 1. When do you choose traditional software over machine learning or AI agents? 2. What makes an AI agent reliable enough for real-world use? 3. Have you ever simplified an AI system and achieved a better result? I'd love to hear real project experiences and lessons learned.
Networking
Shashank V @shashankv · Nov 2
Yay, I joined ASX today. Looking forward to meeting folks on this platform to make meaningful connections.