Blog

Build Simple AI Agents — Deploy Your Agent In previous parts - Your AI Prototype is Ready. Now What? From POC to Production. Building a brilliant AI agent prototype is just the first step. The real challenge—and the real value—lies in deploying it effectively into a live...

🚀 What Is Context Engineering? And why is it the next must-have skill in the AI world? Context Engineering is the art and science of giving AI the right information at the right time — so it can make accurate, intelligent decisions. In real-world AI systems, especially...

AI in Education: Transforming Learning & Skills Artificial Intelligence is reshaping how we learn, teach, and prepare for the future. It’s driving two parallel revolutions: 𝟏. 𝐀𝐈 𝐢𝐧 𝐄𝐝𝐮𝐜𝐚𝐭𝐢𝐨𝐧 – 𝐒𝐦𝐚𝐫𝐭𝐞𝐫 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐒𝐲𝐬𝐭𝐞𝐦𝐬 Personalized learning...

Where are you focusing your IT energy for the agentic future? With predictions that 50% of tech spend will be on AI agents, it's time to look beyond the hype at the underlying structure. Rewiring for agentic AI means looking at your entire IT ecosystem: ➡️ Is your Data clean and...

Full Stack of a RAG System Retrieval-Augmented Generation (RAG) is one of the most practical ways to make large language models more reliable. But behind the scenes, a full RAG system has many moving parts. Think of it as an iceberg the frontend is visible, but most of the...

Today, I’m sharing some bittersweet news: I’ve decided to move on from my role as 𝐏𝐫𝐢𝐧𝐜𝐢𝐩𝐚𝐥 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 at Ally Bank. My time here has been transformative. Working at the intersection of 𝐀𝐠𝐞𝐧𝐭𝐢𝐜 𝐀𝐈, 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐭...

Agentic AI vs AI Agents, What's the Real Difference? Let’s break it down in system terms: 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬: These are rule-based or goal-directed components that perform single, predefined tasks using hardcoded tools and static workflows. ➜ No planning ➜ No autonomy ➜ No memory...

Chunking is the unsung hero of RAG systems. Everyone talks about retrieval. Few talk about how you prepare the data you’re retrieving. But here’s the thing: If your LLM gives vague, irrelevant, or hallucinated answers—it’s often not the model’s fault. It’s the chunking. Let’s...

LangChain just dropped something big: Open Deep Research an autonomous agent built for long-form, reliable research. This is not just a wrapper around web search. It is a modular, multi-agent system that scopes, investigates, and synthesizes knowledge with real structure....