India’s AI scenario has officially entered its second phase. After two years of experimentation, hackathons, and boardroom demos, 2026 is the year Indian enterprises are moving from GenAI pilots to full-scale agentic AI production systems. Searches for “Agentic AI India,” “GenAI enterprise India 2026,” and “AI deployment India” are surging — and for good reason.

As AI systems evolve from conversational assistants into tool-driven and action-oriented platforms, a standardized way to connect Large Language Models (LLMs) with backend capabilities becomes essential. Directly coupling prompts with APIs leads to tight dependencies, security risks, and poor scalability.

When building AI agents with Large Language Models (LLMs), there are several proven patterns that help create more intelligent and reliable systems. LangGraph provides excellent tools to implement these patterns. Let's explore the most common agentic workflows that you can use to build powerful AI applications.

The way we search the web is evolving faster than ever. For years, browsers like Chrome and Safari helped us access the internet — but they remained largely passive tools. Enter Comet Browser, an AI-powered innovation by Perplexity AI that’s turning the browser into an intelligent digital companion.