Discover the three invisible security risks facing every LLM application and the guardrail solutions that protect against them.
Author Archive | Vinod Chugani
The 2026 Time Series Toolkit: 5 Foundation Models for Autonomous Forecasting
Foundation models replace traditional forecasting with pretrained transformers that enable zero-shot predictions on unseen data.
Mastering LLM Tool Calling: The Complete Framework for Connecting Models to the Real World
Learn the three-pillar framework for building production-ready LLM agents using data access, computation, and actions tools.
7 Agentic AI Trends to Watch in 2026
Discover the seven emerging trends reshaping agentic AI in 2026, from multi-agent orchestration to production scaling challenges.
Beyond Short-term Memory: The 3 Types of Long-term Memory AI Agents Need
Discover the three types of long-term memory that transform AI agents from simple chatbots into autonomous systems that learn and adapt.
From Shannon to Modern AI: A Complete Information Theory Guide for Machine Learning
Connect Shannon’s 1948 insights to modern machine learning through entropy, information gain, cross-entropy, and advanced AI applications.
The Complete AI Agent Decision Framework
A systematic framework for choosing the right AI agent framework and pattern for your specific use case.
Building ReAct Agents with LangGraph: A Beginner’s Guide
Build ReAct agents with LangGraph using hardcoded logic and LLM-powered reasoning to create adaptive AI systems.
The Machine Learning Practitioner’s Guide to Fine-Tuning Language Models
Learn when fine-tuning makes sense, which parameter-efficient methods to use, and how to avoid common pitfalls.
The Machine Learning Practitioner’s Guide to Agentic AI Systems
Learn how to transition from traditional machine learning to agentic AI with practical frameworks, projects, and resources.