Welcome back to TechTalks with Manoj — the show where architecture meets intelligence, and innovation meets real-world execution.

In this episode, we’re unpacking one of the most important shifts in AI today: the move from Agent AI — task-focused bots — to Agentic AI — autonomous systems that plan, adapt, and collaborate.

This isn’t just about smarter assistants. It’s about a new paradigm where AI becomes a strategic partner in product development, customer journeys, and decision-making.

Here’s what we’re breaking down:

* What actually separates Agent AI from Agentic AI — and why it matters

* Real-world use cases, from password bots to AI product managers

* What developers and architects need to rethink in design, state, and orchestration

* The shift in infrastructure: memory, vector stores, identity, and trust

* How you can start small — with agents — and scale toward agentic maturity

* And what the rise of the “Agentic Web” means for the future of your stack

If you're building systems today — and planning for tomorrow — this one’s for you.Let’s dive in.

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Welcome back to “TechTalks with Manoj” — the show where cloud, code, and cutting-edge ideas meet real-world impact.

In this episode, we decode the bold vision Microsoft unveiled at Build 2025: a future where AI isn’t just a Copilot — it’s an autonomous agent capable of navigating tools, APIs, and even the open web.

At the heart of this transformation lies a new architecture stack:From infrastructure to models, from orchestration to open protocols like MCP and NLWeb — Microsoft’s stack is evolving into a full agentic platform.

Today, we’ll break down:

* What “Agentic Web” really means and how it differs from traditional web apps

* The evolution from Copilot to fully autonomous systems

* How MCP and NLWeb open up new frontiers for agent-native development

* The implications for Azure, identity, trust, and enterprise adoption

* And what builders like you need to know to stay ahead

This isn’t just keynote hype — it’s a call to rethink your tech stack for an AI-native future. Let’s get into it.

Thanks for reading! Subscribe for free to receive new posts and support my work.

Welcome to another episode of “TechTalks with Manoj”, where we break down real technology for real-world builders.

Today’s deep dive is all about the Model Context Protocol, or MCP — a powerful open standard that’s quietly reshaping how AI models plug into tools, APIs, databases, and live systems.

MCP solves one of the oldest integration headaches in software architecture — the dreaded “N×M” connector explosion. It introduces a protocol-driven way for LLMs to securely access tools, resources, and prompts — without bespoke glue code for every system.

Whether you're building enterprise copilots, AI-powered IDEs, or context-aware customer assistants, MCP is the missing link between your models and your operational stack.

In this episode, we’ll explore:

* What MCP actually is and why it matters

* How it compares to REST, LangChain, and other tools

* Key architecture concepts like Tools, Roots, and Sampling

* Real-world use cases in software, healthcare, finance, and more

* And finally — how to get started with MCP in your own projects

This isn’t theory — this is the protocol layer that lets AI talk to your real systems, with security and scale built in.