AI/ML Resources

Phantom APIs Are Eating Your Attack Surface, and Most Security Teams Are Still Looking the Other Way

Undocumented phantom APIs are creating hidden security risks. Learn how AI-generated endpoints evade reviews and expand attack surfaces.

June 23, 2026

by Igboanugo David Ugochukwu

CORE

· 2,687 Views · 1 Like

Connect Existing Data to AI Retrieval: How to Build Production-Ready Search Without Rebuilding Core Systems

Step-by-step tutorial building AI retrieval over existing data systems using a thin layer, covering workflow design, indexing, evaluation, and RAG pipeline.

June 23, 2026

by Jubin Soni, FBCS

CORE

· 7,206 Views · 2 Likes

The Breach Was Never at the Door

OAuth tokens and AI agents can bypass traditional security. Learn from Microsoft and Salesloft breaches why behavioral monitoring matters.

June 23, 2026

by Igboanugo David Ugochukwu

CORE

· 1,982 Views · 1 Like

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

Free VS Code extension for Azure AI Foundry agent traces into your editor as an interactive timeline — see tool calls, token costs, and conversation replays.

June 23, 2026

by Jubin Soni, FBCS

CORE

· 6,533 Views · 2 Likes

How to Classify Documents in C#

In this article, we discuss the advantages and challenges of implementing AI document classification for C# pipelines and discuss some solutions.

June 23, 2026

by Brian O'Neill

CORE

· 1,060 Views · 1 Like

Data Governance Checklist for AI-Driven Systems

A practical checklist for evaluating AI data readiness, covering data quality, governance, lineage, access controls, retrieval systems, and ongoing monitoring.

June 23, 2026

by Abhishek Gupta

CORE

· 2,155 Views · 3 Likes

Foxit MCP Server: Give AI Agents Direct Access to 30+ PDF Tools via Model Context Protocol

Foxit MCP Server gives any AI agent direct access to 30+ PDF tools for conversion, OCR, merge, and compare via the Model Context Protocol.

June 22, 2026

by Lucien Chemaly

· 2,176 Views · 1 Like

The Reliability Gap: Why Enterprise AI Keeps Failing After It Already Works

Enterprise AI often fails after launch due to behavioral drift, stale context, and trust erosion — not model quality or benchmark accuracy.

June 22, 2026

by Igboanugo David Ugochukwu

CORE

· 1,449 Views · 2 Likes

When Valid SQL Was Still the Wrong Answer

A personal project exploring why AI-generated SQL isn't always trustworthy and how semantic context, validation, and governance improve analytics accuracy.

June 22, 2026

by Anusha Kovi

CORE

· 1,721 Views · 2 Likes

Keeping AI-Powered BI Honest: A Human-in-the-Loop (HITL) Playbook

AI-generated SQL can look right while being wrong. Learn how human-in-the-loop workflows build trust through reviews, approvals, audits, and escalation paths.

June 22, 2026

by Nithish Shetty

· 1,343 Views · 1 Like

Offline Evaluation of RAG-Grounded Answers in LaunchDarkly AI Configs

Run an offline Playground eval with a cross-family LLM judge and use failing rows to separate retrieval issues from generation problems and judge noise.

June 22, 2026

by Scarlett Attensil

· 984 Views · 1 Like

Generative Engine Optimization: How to Make Your Content Visible to AI

Generative engine optimization (GEO) helps content get cited by AI tools like ChatGPT and Perplexity using structure, authority, and semantic clarity.

June 22, 2026

by Sibanjan Das

· 1,490 Views · 1 Like

GenAI Isn't Solving the Problem Most Development Teams Actually Have

We optimized for code-generation speed while the real bottleneck — cognitive overhead and knowing where to make changes — remained completely untouched.

June 19, 2026

by Gaurav Gaur

CORE

· 2,954 Views · 13 Likes

Testing Strategies for Web Development Code Generated by LLMs

LLMs can quickly generate web application code, but AI-written code may contain security vulnerabilities. This article reviews testing methods for LLM systems.

June 19, 2026

by Sandesh Basrur

· 2,897 Views · 2 Likes

The Cross-Lingual RAG Problem Nobody Is Talking About

RAG works beautifully in English. For the other 6.5 billion people, it is quietly failing — and the AI community has barely noticed.

June 19, 2026

by Janani Annur Thiruvengadam

CORE

· 1,535 Views · 3 Likes

Jakarta NoSQL: Why JPA Is Not Enough for the AI Era

Jakarta NoSQL provides a familiar Java programming model while preserving the strengths of document, graph, key-value, and AI-driven vector databases.

June 19, 2026

by Otavio Santana

CORE

· 2,889 Views · 2 Likes

Your AI Coding Agent Can't Steal What It Never Had: The Docker Sandbox Isolation Story

Docker Sandbox runs AI agents in microVMs. The API key never enters the sandbox — the host proxy authenticates on the agent's behalf.

June 19, 2026

by Shamsher Khan

CORE

· 3,000 Views · 2 Likes

When Your Documentation Manages Itself: mdship and AI-Assisted Markdown

Learn how to generate documentation using an LLM with mdship, and how to ensure that the prompts, which are now the source documentation, do not get lost.

June 18, 2026

by Peter Verhas

CORE

· 3,123 Views · 4 Likes

AI Is Finding Bugs Faster Than Enterprises Can Patch — Here's What Data Security Teams Should Do

Three structural shifts enterprise data security teams should make in 2026, based on verifiable data and a decade of experience building protection products.

June 18, 2026

by Priyanka Neelakrishnan

· 2,221 Views · 2 Likes

Context Rot: Why Your AI Agent Gets Worse the Longer It Works

Adding more tokens to an LLM's context window quietly degrades output quality, even well before the window is full. This is context rot.

June 18, 2026

by Vineet Bhatkoti

· 2,183 Views · 2 Likes

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