Here are a few "hype-free" practical differences: 1. Run multiple AI agents at the same time Say: “Clean the backend, improve UI, and write tests.” Antigravity spins up several agents that actually execute these tasks side-by-side. VS Cod...

The Problem Most language models accidentally memorise private data - even if it appears only once. A phone number buried in a blog post, a home address mentioned in a forum, a unique email ID in a dataset… once a model sees it, it can quietl...

We know that LLMs are pre-trained models and therefore have a knowledge cut-off. And that's the reason they can't answer current affairs questions. So, let's build an AI Search Agent that can access Google Search using the API for current af...

Building an AI product ≠ Using AI in a product. One means AI is the heart of the solution. The other just adds AI to something that already works. You can know everything about models, prompts, benchmarks, inference speed But if you can’t fram...

Not many companies reveal the environmental impact of their AI models But French AI startup Mistral has disclosed the full environmental footprint of its flagship model, Mistral Large 2 123B parameters. Training the model emitted 20,400 metric...

For years, AI model creators treated the internet like an open buffet - a limitless source of data to train their models. But now, that buffet is closing. Publishers are blocking AI crawlers and demanding payment for access. Why? Wikipe...

Let us learn "AI Agent Evaluation" with humour. AI Agents can plan, reason, and act - but how do we know if they’re doing it correctly? What if you wanted to book a ticket to London, but the AI Agent booked one to Lisbon? We have to evaluate...

After 3.5 years of building, teaching, and breathing AI, I hit pause. Not because AI isn’t exciting anymore But because I am curious about what else the future is cooking. So I have started exploring some mind-bending frontiers of technology...

What makes an AI Agent truly personalised? Memory. In this episode of educational web series, Jigyaasu and Saral explore how AI Agents remember, learn, and personalise over time Next episode: Evaluation of AI Agents Previous episodes: What ...

AI agents can buy things on your behalf, right? but would you trust them enough to do so? The challenge: today’s payment systems assume a human is clicking “buy.” With agents in the loop, how do we make sure payments are: Authorized – Di...

Meta just launched LlamaFirewall – an open-source security system for AI agents. The goal is to protect agents from three big threats: 1️. Jailbreaking – malicious prompts that bypass safeguards 2️. Goal Hijacking – tricking an agent into foll...

Let us learn Multi-AI Agent systems with humour. Key takeaways: What Multi-AI Agent systems are How they work together step by step Real-world examples travel planning, customer support, content creation Next episode: AI Agents' Memory Previou...

Previous video was an experiment. This is actually the first episode of the "AI Agent" course. Hope it's worth your time! Next episode would be on - Multi AI Agents....

The problem with current educational content is that mostly its lecture style videos - one person is teaching, and then there are graphics around. I want to break away from that style and want to make educational content more fun and engaging. ...

Already in 20,000+ repos, it’s basically the README.md for AI coding agents. README.md → for humans intro, contribution guide, quick start AGENTS.md → for AI setup commands, testing workflows, coding style, PR rules By separating this con...

For Example: Traditional Phishing: “Dear Customer, your bank account is locked. Click here to reset.” Targeted phishing: “Hi Nikhilesh, this is Rahul from Winsaga Edutech’s partner team. Here’s the updated contract you requested yesterday, plea...

And building an AI tool isn’t simply throwing GPT at a problem. Yet inside companies, this is happening most of the time: Business says yes to an AI idea Tech rushes to build Misalignment begins Because later, every “Can you just add this...

The biggest problem with AI coding assistants is that they create a lot of “buggy code”. So, what’s the solution? Make AI learn to fix its own mess Alibaba built SWE-smith: an automatic bug generator + fixer that: Creates real bugs in GitHub...

Most companies are architecting multi-agent AI systems based on human teams. But then the problem with this approach is Agents skip asking for help when confused Roles get forgotten mid-task Communication breaks down Tasks get marked “done” wi...

Real-life use cases of AI other than Chatbots Imagine this: A drone flies over a farm and spots exactly where pests are located. A robotic sprayer then treats only those specific spots. No blanket spraying. No chemical overload. Just preci...