AI agents

The Security Architecture Behind Reliable AI Agents

A practical guide to AI agent security architecture: least privilege, untrusted input handling, sandboxing, tool gating, observability…Continue reading on Towards AI »

NVIDIA Researchers Argue Your AI Agent Is Overpaying 10–30x.

A position paper says small language models should run most agent calls.Continue reading on Towards AI »

What to Teach When AI Becomes the Compiler

Natural language is collapsing the expertise required to operate professional computing engines, but it does not collapse the expertise required to warrant their results. Education therefore has to move from teaching operation alone toward teaching specification, verification, and recovery.

The Hidden Architecture Problem Behind AI Agents

What Satya Nadella’s recent essay and research on agent failures reveal about building trustworthy AI architecture

An AI Agent Turned a Net $784K Into $5.3M of Debt. One Diff Catches It.

Building a Production-Grade Dimensional Model on Snowflake with Cortex Code using Skills

How I designed, audited, and expanded an e-commerce star schema using an AI-powered skill — and what I learned about letting the machine enforce Kimball principles.

Zero Trust Architecture for MCP

[Playbook] Zero Trust Architecture for MCP An engineering blueprint for implementing On-Behalf-Of OAuth 2.1 and SPIFFE workload identity. Cover visual featuring a physical Causal Interaction studio …

Microsoft Just Shipped an AI Agent Feature Whose Entire Job Is Not Trusting the Agent

Microsoft Just Shipped an AI Agent Feature Whose Entire Job Is Not Trusting the Agent Copilot Studio’s new “Hooks” are a quiet admission that agent judgment cannot be trusted with anything that …

OAuth 2.0 Token Exchange — Laying the Foundation for AI Agent Authorization

OAuth 2.0 Token Exchange — Laying the Foundation for AI Agent Authorization Background In a previous article, I walked through the three most common OAuth 2.0 grant flows: Authorization Code Flow …

The Summer AI Agents Started Knocking on Government Doors

OpenAI’s own agents wandered i⁠nto US and Aus​tralian government‍ websites, b⁠orrowi​ng keys stra​ngers had left​ lying around online…Continue reading on Towards AI »

What If Enzo Ferrari Was Blamed for Something His Car Did? The AI Agent Authorization Problem

AI agents can now make decisions, call tools, change systems, and act on their own. When something goes wrong, who is actually responsible?

We Connected a WordPress Site to AI Agents Through MCP. Here’s What We Had to Fix

More than 40% of all websites run on WordPress, according to W3Techs [1]. Over the past year, those sites gained a standard way to work with AI agents. WordPress 6.9 introduced the Abilities API, WordPress 7.0 added an AI Client to core, and the official MCP Adapter plugin turns registered…

Running an AI Agent Harness and 30Billion Parameter Mixture-of-Experts Model for Agentic Coding

AI Agents have changed daily software development. At the office, developers now have access to private frontier AI Models and a private frontier AI Agent Harness right in our IDEs.

10 GitHub Repositories That Will Make You Dangerous at AI Agents

Courses, runnable projects, agent tutorials and production playbooks, all open source and freeContinue reading on Towards AI »

How Does AI Game Merging Actually Work?

AI game merging can mean a content port, two live games linked by passthrough, or a rebuilt runtime. See what each route connects and what a demo proves.

TAI #225: OpenAI’s DevDay: Cheaper Intelligence, Unfinished Agents

TAI #225: OpenAI’s DevDay: Cheaper Intelligence, Unfinished Agents Also, Gemini 4 Argon, GPT-6.1 Sol, Dots, NVIDIA DGX Spark 64GB, Microsoft MAI-Transcribe-2-Streaming, and Cohere Embed 5. What …

An AI Agent Workflow That Survives kill -9: Inside Microsoft Agent Framework’s Latest Update

A reproducible crash test, then AG-UI, Foundry memory, and Hyperlight CodeAct in .NET and Python, with the one guarantee each feature…Continue reading on Towards AI »

AI Agent Evaluation: A Practical Guide with a Working Application

An end-to-end guide to deterministic checks, retrieval metrics, human review, LLM judges, and regression testing, with practical examples from a local multi-agent RAG application.