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Having worked on Reinforcement Learning, it’s always fascinating to see how it’s being applied in the world of LLMs. If you’re curious about how RL powers modern LLM agents, especially in areas like reward modeling, and policy gradients here are a f

Give me 2 minutes, I will tell you How to Learn Reinforcement Learning for LLMs A humorous analogy for reinforcement learning uses cake as an example. Reinforcement learning, much like baking a cake, involves trial and error to achieve a desired ou

LLM Post-Training: A Deep Dive into Reasoning LLMs This survey paper provides an in-depth examination of post-training methodologies in Large Language Models (LLMs) focusing on improving reasoning capabilities. While LLMs achieve strong performance

🔥Models & Agents: DeepSeek’s Next‑Gen Push 🔥 DeepSeek targets end‑2025 for a new model with advanced agent capabilities – aims for multi‑step autonomous actions and adaptive learning . 🤔 Why It Matters – More capable agents could automate resear

If AI’s rapid pace feels overwhelming, trust me-everyone feels it. New models, new papers, new frameworks… it’s impossible to keep up with everything. And the good news is-you don’t have to. What actually helps is a clear path, not more noise. So I

Most people miss these principles while building AI agents. I’ve explained everything that you should keep in mind. 1. Never run an agent without clear context. 2. Define who the agent is and what it is responsible for. 3. Always log inputs, action

Real Agentic AI is a multi-layered system, where each layer solves a specific challenge from reasoning to compliance: 1. LLM (Core Reasoning) – Handles language understanding and generation. Alone, not enterprise-ready. 2. RAG (Retrieval Layer) – G

Deconstructing How Agentic AI Actually Works We’ve all experienced what Large Language Models can do — but Agentic AI is the real leap forward. Instead of just generating responses, it can understand goals, make decisions, and take action on its own

Data scientist, Data analyst, AI engineer, or AI agent builder? Which one is best? I've explained below. 1. 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 This field teaches you how to 𝗮𝗻𝗮𝗹𝘆𝘇𝗲 𝗱𝗮𝘁𝗮, 𝗯𝘂𝗶𝗹𝗱 𝗠𝗟 𝗺𝗼𝗱𝗲𝗹𝘀, 𝗮𝗻𝗱 𝗱𝗲𝗽𝗹𝗼𝘆 𝘁𝗵𝗲𝗺 𝗶

4 powerful loops that power Agentic AI. Here’s the easiest explanation of how each one works. 𝗔𝗚𝗘𝗡𝗧𝗜𝗖 𝗟𝗢𝗢𝗣𝗦 Agentic Loops explain how AI agents think, act, learn, coordinate, and improve over time using structured cycles. 1. 𝗖𝗼𝗹𝗹𝗮