OntoGuard: I Built an Ontology Firewall for AI Agents in 48 Hours Using Cursor AI
Author(s): Pankaj Kumar Originally published on Towards AI. The $4.6M Mistake That Changed Everything Last month, a financial services company learned an expensive lesson about AI agents. Their automated refund processing agent — working perfectly in demos — made a catastrophic error …
From Power BI Dashboard to AI Agent in 30 Minutes: I Built the Tool That Unlocks 20 Million Hidden Ontologies
Author(s): Pankaj Kumar Originally published on Towards AI. A hands-on tutorial showing how to extract formal ontologies from Power BI models — and why I built it in 48 hours with Cursor AI Follow-up to: “The Power BI Ontology Paradox” [Image Caption]This …
OpenAI Shipped Eight Amazing Things in 72 hours
Author(s): JP Caparas Originally published on Towards AI. The Codex desktop app, Apple’s Xcode integration, Skills, Automations, and 500,000 downloads later Monday morning, OpenAI dropped the Codex Desktop App. By Tuesday, Apple announced Xcode 26.3 with native Codex integration. Wednesday brought the …
Beyond AI Tools: How I Architect Systems That Actually Run the Business
Author(s): Abdul tayyeb Datarwala Originally published on Towards AI. My journey building operational intelligence — and why most AI initiatives quietly die I’ve built AI-enabled systems that scaled revenue, cut operational cost by multiples, and replaced chaos with clarity. I’ve also watched …
Building State-of-the-Art Vision-Enabled RAG Pipelines (2026)
Author(s): James Loy Originally published on Towards AI. A practical, hands-on guide to multimodal retrieval with the Qwen3-VL ecosystem. In early 2026, the multimodal landscape shifted with the release of the Qwen3-VL-Embedding and Qwen3-VL-Reranker families. Built upon the state-of-the-art Qwen3-VL foundation model, …
Word Embeddings in NLP: From Bag-of-Words to Transformers (Part 1)
Author(s): Sivasai Yadav Mudugandla Originally published on Towards AI. Image generated with Microsoft Copilot · 1. Introduction: Why Computers Struggle with Language· 2. What Are Word Embeddings and Why Do We Need Them? ∘ The Map Analogy ∘ Why We Need Them …
Agents 2.0: AI Agents that Can Learn (6 Learning Types that Make Memory Persistent)
Author(s): Divy Yadav Originally published on Towards AI. What if your AI actually remembered you? We call them AI agents. Personal assistants. Digital helpers. Photo by geminiThis article discusses the limitations of current AI agents, which typically do not learn from past …
Microsoft vs Palantir: Two Paths to Enterprise Ontology (And Why Microsoft’s Bet on Semantic Contracts Changes the Game)
Author(s): Pankaj Kumar Originally published on Towards AI. A technical deep-dive into how Microsoft Fabric IQ actually implements ontology — and why it’s fundamentally different from Palantir’s approach 🚀 NEW: I just built OntoGuard in 48 hours — an ontology firewall for …
I tuned a 7B Model That Outperforms GPT-4 (Here’s How You Can Too)
Author(s): Gaurav Shrivastav Originally published on Towards AI. A practical guide to understanding and implementing model specialization for real-world applications Last month, I helped a startup replace their GPT-4-powered customer service system with a fine-tuned 7B parameter model. The results were surprising: …
Beyond Vision Language Action (VLA) Models: Moving Toward Agentic Skills for Zero-Error Physical AI
Author(s): Telekinesis AI Originally published on Towards AI. Vision Language Action (VLA) models are the hottest topic in Physical AI right now. If you are in the space of robotics or computer vision, your feed will be packed with it: massive funding …
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