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Building with AI: agent architecture, harnesses, and the engineering practices behind production systems for the IT channel.

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AI Engineering articles

AI EngineeringJul 8, 2026

Agent RBAC: Five Ways to Scope What an Agent Can Do (And When to Use Each)

Role-based access control for agents is not user RBAC with a new label. An agent acts, so its permissions are a matrix of what it can see, suggest, and execute. Here are the five strategies, when each fits, the tradeoffs, and how to implement them in Claude Code, Codex, and your own harness.

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AI EngineeringJul 1, 2026

The Verify Step: Why Agents Fail in Production (And How to Catch It Before the Customer Does)

The verify step is where an agent proves the work actually happened before anyone calls it done. It is the single cheapest addition to a harness and the one that separates a demo from something you can run near a customer's quote, ticket, or data.

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AI EngineeringJun 24, 2026

The Model Is Not the Moat. The Harness Is.

Enterprise AI strategy is shifting from model selection to the harness around models: routing, fallbacks, context, permissions, memory, observability, and review.

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AI EngineeringJun 16, 2026

What Is an Agent Harness? (And Why It Matters More Than the Model)

An agent harness is everything wrapped around the model that makes it reliable: the loop, tools, context management, guardrails, and the verify step. Here is what that means in plain terms, and why it decides whether AI agents actually work in the IT channel.

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