Frameworks -> LangGraph, CrewAI, AutoGen Harnesses -> Claude Code, Cursor, Codex A framework helps “you” build agents. A harness runs them. Frameworks provide building blocks for creating AI Agents, like Tool calling, Memory management, Mu...

NVIDIA GPUs helped train LLMs that are now helping design the next generation of NVIDIA GPUs. Yes, there is something recursive happening here. Nvidia trained internal LLMs: ChipNeMo and BugNeMo on decades of proprietary chip-design data. T...

Because learning is rarely a linear process It is more like layering. The more we revisit a topic, the more it sinks in. The first time we learn something, it’s just an introduction. The second time, patterns start becoming visible. The third...

You decide it’s time to “do something with AI.” A use case is found. A team is formed. Budgets are locked. Timelines approved. And then someone asks: “Who’s going to manage this project?” Let's discuss it in this video. Watch the complete v...

Hiring Agentic AI Engineers? This one question you could ask to separate the real talent from others. Agentic AI engineering isn’t just about calling APIs or writing flashy prompts. It’s about building real solutions that work for real users....

I am an accidental teacher. About 3 years ago, I discovered I have a knack for teaching, and since then, I have been teaching. Over this time period, I realised there’s one highly underrated trait: Asking questions. Not to test learners. No...

Most teams do. Because realistically: You don’t have time to review every edge case Security audits are expensive and slow And if something really critical existed… surely someone would’ve caught it by now Right? Here’s the uncomfortab...

Let an AI agent work on your machine and things can go wrong fast: Accessing files it shouldn’t Leaking secrets Running destructive commands Modifying things you never intended So teams do the obvious thing: Add guardrails But Guardrails insi...

Unless you’ve been completely offline lately, you have probably heard about OpenClaw. For those new to it, OpenClaw is an open-source, configurable agent framework The good thing is it runs locally and gives AI Agents real operational capab...

In this episode, Jigyaasu and Saral explore what practical safeguards actually help: delimiters, proxies, JSON validation, moderation APIs, LlamaGuard, and more > Next episode: The AI Leadership Playbook Previous episodes: 0. Basics of AI - ht...

Let's build a fun project to make AI agents do stand-up comedy The idea is to learn "multi agent collaboration" in Autogen. The first AI Agent will crack a joke, and another agent will create a counter-joke on the punchline Let's laugh and...

OpenAI is trying something very different from traditional search ads. According to Sam Altman, “Ads on search engines make money when a search fails. If search engines gave you the best answer, there’d be no reason to buy an ad above it.” ...

Prompt Caching: Stop paying for the same prompt twice. Problem: A prompt is an integral part of any Gen AI or Agentic AI application. However, the problem occurs when the prompt becomes too large. Bigger prompts = higher cost every single cal...

Employees are feeding sensitive data into Copilots and AI tools at massive scale. Most of it happens through unmanaged personal accounts, invisible copy/paste flows, and non-federated logins. Traditional DLP tools don’t even see it. A ne...

The problem Most AI models write text one word at a time. That keeps answers good, but makes them slow. Some models try to write everything at once to be faster. But then: they lose memory efficiency the text feels less connected compute cos...

AI Agents are powerful, but without security, they’re also dangerous. In this episode, Jigyaasu learns why AI Agent security isn’t just a technical concern, but a leadership and business imperative. From prompt injection and hallucinations to dat...

Over the years, LLMs have become great at understanding training text and images. But things fall apart when we move to new data type. For example, medical scans, or sensor data. Training an LLM on these new data types usually needs thousa...

But what if the next phase of AI doesn’t isolate us? What if it brings us together? Picture this. It’s 3:00 AM. You’re talking to an LLM about a relationship problem that strangely feels like debugging code. The model pauses and asks: “Do...

But what if the next phase of AI doesn’t isolate us? What if it brings us together? Picture this. It’s 3:00 AM. You’re talking to an LLM about a relationship problem that strangely feels like debugging code. The model pauses and asks: “Do...

Through humour, simple analogies, and real-world examples, Jigyasu and Saral explore: What MCP Servers are and who builds them How MCP makes AI Agentic systems scalable, maintainable, and safe What is Google's A2A and more > Next episode: AI Age...