AI/ML Resources

Git Blame Isn’t Enough: Building Verifiable Provenance for AI-Generated Code

AI-generated code needs verifiable provenance linking intent, context, models, edits, approvals, commits, and artifacts across the software lifecycle.

September 30, 2026

by Uthej Mopathi

CORE

· 1,641 Views · 3 Likes

Meta Wants to Run Your Business With AI — Microsoft and Salesforce Have a New Rival

Meta launches Enterprise Platform, bringing Muse, Business Agent and AI tools to companies as it takes on Microsoft and Salesforce.

September 30, 2026

by Ai Cerrudo

· 1,542 Views · 1 Like

Engineering Self-Healing SQL Pipelines With LLMs: Validation, Guardrails, and Safe Recovery

Build self-healing SQL pipelines where LLMs propose repairs while deterministic validation, guardrails, and execution controls protect production systems.

September 30, 2026

by Uthej Mopathi

CORE

· 1,206 Views · 3 Likes

OpenAI ‘o’ Leak: What We Know About ChatGPT’s Always-On Assistant Before DevDay

OpenAI may be testing an always-on ChatGPT assistant called “o,” with leaked references pointing to possible email functionality and ChatGPT Pro placement.

September 29, 2026

by DZone Staff

· 2,855 Views · 2 Likes

A Deep Dive into the Microsoft Foundry Document Intelligence SDK: From PDF to Structured Data

A hands-on guide to Microsoft Foundry Document Intelligence SDK for extracting text, structured fields, and document data from PDFs for RAG and AI pipelines.

September 29, 2026

by Jubin Soni, FBCS

CORE

· 6,560 Views · 3 Likes

Mistaking Code Production for Engineering Progress: AI Productivity Myths Part 1

In this article, you will learn why lines of code generated are almost meaningless as a measure of AI-assisted development.

September 29, 2026

by Gaurav Gaur

CORE

· 1,382 Views · 2 Likes

AI Coding Is Moving From Trusting the Model to Constraining What It Can Do

AI coding is shifting from trusting models to constraining them with permissions, tools, and deterministic checks. BUBAS applies the same idea to business logic.

September 28, 2026

by Peter Verhas

CORE

· 1,149 Views · 1 Like

From Giant Prompts to On-Demand Skills: Build an Extensible AI Agent With Progressive Disclosure

Progressive disclosure replaces giant prompts with lightweight skill summaries and on-demand instructions, keeping AI agents focused and extensible.

September 28, 2026

by Akhil Madineni

CORE

· 1,456 Views · 3 Likes

The Agent Changed Its Plan Mid-Run: Reconciling AI Decisions With Completed Temporal Activities

Reconcile AI plan changes with completed Temporal Activities using versioned plans, idempotent execution, and compensation rather than retroactive rollback.

September 28, 2026

by Akhil Madineni

CORE

· 992 Views · 3 Likes

Why Incident Response Needs Memory, Not Just Intelligence

LLMs are excellent at reasoning, but effective incident response depends just as much on remembering previous incidents and organizational operational context.

September 28, 2026

by Akshay Pratinav

· 1,009 Views · 1 Like

Software Quality Habits and AI

Software quality depends on daily habits. Learn how small habits compound and how AI can strengthen quality while weakening engineering judgment.

September 25, 2026

by Stelios Manioudakis

CORE

· 2,676 Views · 3 Likes

Can Your Team Name the Work It Already Runs With AI?

The AI Workflow Inventory gives teams a shared list of recurring AI work, creating the foundation for A3 delegation decisions.

September 25, 2026

by Stefan Wolpers

CORE

· 2,106 Views · 3 Likes

Locking Down the Enterprise: Data Security Patterns for AI Integrations

Learn how to secure enterprise data in AI systems using data classification, access controls, encryption, vendor controls, prompt security, and output validation.

September 25, 2026

by Balaji Venkatasubramaniyar

CORE

· 1,710 Views · 1 Like

How Multi-Agent Systems can replace most of Manual ML Validation decisions - The Karpathy Loop Approach

This framework employs autonomous agents to run experiments against predefined metrics, determining success or failure without human input

September 24, 2026

by Amey Farde

· 2,064 Views · 1 Like

Building an AI Agent That Converts Production Failures Into Regression Tests

AI agents can transform production telemetry into deterministic regression tests that reproduce failures and verify fixes automatically.

September 24, 2026

by Uthej Mopathi

CORE

· 1,922 Views · 3 Likes

Track Brand Visibility Across AI Answer Engines with Python

A self-hosted way to track a brand's mention, citation, and share of voice across AI answer engines — sampled on a schedule so you follow the trend, not a single answer.

September 24, 2026

by Nadia Mohamed

· 1,521 Views · 1 Like

When Your Chatbot Can Talk Its Way Into the Scoring Engine

If you are building a system that both evaluates people and talks to them, assume the two functions will entangle unless you deliberately separate them.

September 24, 2026

by Somnath Banerjee

· 1,474 Views · 1 Like

Integrating LLMs into iOS Applications With Swift Using ONNX Runtime

This article explores how to integrate an ONNX transformer model into an iOS application using Swift. It covers loading and running models with ONNX Runtime.

September 24, 2026

by Kagan Girgin

· 1,450 Views · 1 Like

An Enterprise AI Governance Checklist for Software Teams

A seven-point governance checklist for engineering teams, with automated CI/CD pipeline gates for model registration, bias testing, and drift detection.

September 24, 2026

by Mohanaraman Namasivayam

· 1,572 Views · 1 Like

RAG Is Not Enough: The Rise of Enterprise Knowledge Graphs for AI Systems

Enterprise AI needs knowledge graphs alongside RAG to enable relationship-aware, explainable, secure, and contextually accurate retrieval and reasoning.

September 24, 2026

by Uthej Mopathi

CORE

· 2,281 Views · 3 Likes

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