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The Breach Was Never at the Door

Jun 23rd 2026, 15:00 by Igboanugo David Ugochukwu

I've lost count of how many breach disclosures I've read where the first sentence is some version of "no evidence the perimeter was compromised." It used to strike me as corporate hedging. Now I read it as the whole story, hiding in plain sight. The perimeter wasn't compromised because, increasingly, nobody bothers attacking it. Why would they, when the back door is propped open by a token nobody's looked at since the engineer who set it up left the company?

That's the pattern I want to walk through here — not as a hypothetical, but as something that's now happened, in public, with named victims and dated timelines, twice in the last eighteen months at a scale too big to wave away.

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I Built a VS Code Extension to Debug Azure AI Foundry Agents Without Leaving My Editor

Jun 23rd 2026, 14:00 by Jubin Abhishek Soni

The Problem

Azure AI Foundry has a genuinely great portal. You can see your agent runs, the tools it calls, the messages it sends and receives, and even a breakdown of token usage — all in a clean UI.

But here's what actually happens when you're building an agent locally:

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How to Classify Documents in C#

Jun 23rd 2026, 13:00 by Brian O'Neill

A functional automated document processing pipeline typically needs to know what type of document it’s dealing with before it can do anything useful with it. The extraction logic that determines when it’s dealing with an invoice, for example, is different from the extraction logic for a tax form, and the routing rules for a contract are clearly different from those for an ID document. Classification is what makes downstream automation possible when there are multiple unique input types.

Building reliable classification logic, however, is no simple task. It’s easy to create something brittle, and much harder to create something dynamic and flexible that works reliably in the majority of cases. In this article, we’ll look at why classification breaks down at scale, and we’ll examine what it actually takes to build and maintain a reliable solution in C#. Towards the end, we’ll walk through a dedicated API that handles classification across a wide range of document formats using AI without requiring a specially trained model for each document type.

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Data Governance Checklist for AI-Driven Systems

Jun 23rd 2026, 12:00 by Abhishek Gupta

Editor’s Note: The following is an article written for and published in DZone’s 2026 Trend Report, Cognitive Databases, Intelligent Data: Unified Infrastructure for Vector Search, AI-Optimized Queries, and Hybrid Workloads.

Many teams find governance gaps only after a retrieval system surfaces stale or unauthorized content in production. Models, agents, and retrieval workflows all depend on enterprise data. Before any of that data reaches an AI system, teams need to know where it originates, how it’s integrated, whether it meets quality expectations, what context enriches it, who can access it, and how it changes over time.

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