Securing the Autonomous Frontier: A Guide to AI Identity
Author(s): Niraj Kumar Originally published on Towards AI. Imagine an AI agent, tasked with “optimizing cloud costs,” deciding that the most efficient path is to delete an underutilized production database. In the shift toward 2026, we’ve moved from simple chat interfaces to …
Unlocking Embedded Visuals from Documents Using Snowflake Cortex
Author(s): Krishnan Srinivasan Originally published on Towards AI. Most document AI discussions focus on text extraction, OCR accuracy, table detection, layout parsing. These are familiar themes. But many enterprise documents are not just text-centric. Inspection reports, audit documents, supplier catalogs, safety manuals, …
Breaking the Monolith: Architecting a Process-Based Sub-Agent Ecosystem
Author(s): Shreyash Shukla Originally published on Towards AI. Image Source: Google Gemini The “Generalist” Ceiling In the previous five articles, we architected a robust single agent. It has memory, tools, and user context. However, as we scale this agent to handle enterprise-grade …
Engineering the Semantic Layer: Why LLMs Need “Data Shape,” Not Just “Data Schema
Author(s): Shreyash Shukla Originally published on Towards AI. Image Source: Google Gemini The “Context Window” Economy In the world of Large Language Models (LLMs), attention is a finite currency. While context windows are expanding, the “Lost in the Middle” phenomenon remains a …
What OpenClaw’s Security Disasters Teach Us About the Future of AI Agents
Author(s): thamilvendhan Originally published on Towards AI. In January 2026, a weekend project by Austrian developer Peter Steinberger broke the internet. OpenClaw (originally called Clawdbot) — a self-hosted AI agent that lives in your WhatsApp, Telegram, and Slack — racked up 9,000 …
Where LLMs Belong in Agentic Systems: Gating, Approval, and Human-in-the-Loop Design
Author(s): Vahe Sahakyan Originally published on Towards AI. This article closes a four-part series on designing agentic AI systems. So far, we’ve focused on structure first. We separated agentic behavior from language models. We built workflows with explicit control flow, shared state, …
TAI #192: AI Enters the Scientific Discovery Loop
Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie This week, LLMs crossed from tools into participants in scientific discovery. OpenAI released a preprint, “Single-minus gluon tree amplitudes are nonzero,” in which GPT-5.2 …
The boring AI That Keeps Planes in The Sky
Author(s): Marco van Hurne Originally published on Towards AI. One of the ways I keep myself busy in the AI domain is by running an AI factory at scale. And I’m not talking about the metaphorical kind where someone prompts an AI …
The Roadmap of Mathematics for Machine Learning
Author(s): Tivadar Danka Originally published on Towards AI. A complete guide to linear algebra, calculus, and probability theory Understanding the mathematics behind machine learning algorithms is a superpower. Here’s the full roadmap for you.This article presents a comprehensive curriculum that guides readers …
Building an AI Agent with Long-Term Memory: ChromaDB + Ollama + TypeScript
Author(s): Jageen Shukla Originally published on Towards AI. How I Built a Customer Support Agent That Actually Remembers What You Said I built a prototype AI customer support agent with semantic long-term memory using ChromaDB (vector database), Ollama (local LLM), and TypeScript. …
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