Agents that work in operations need narrow tools, least-privilege access, human approvals and a full audit trail. These guides cover how we design them and how a project starts.
Human-in-the-loop only works if the approval step is fast, informed and honest. How to decide what an AI agent may do alone, what it must ask about, and how to keep approvals from becoming rubber stamps.
A step-by-step guide to exposing ERP data to AI agents through the Model Context Protocol: narrow tools, read-only credentials, validated inputs, and a safe path to writes.
Most AI readiness assessments end in a slide deck. A workflow audit ends with an agent running on your real cases and a go or no-go. What each one covers, what it costs, and what to ask for.
An agent harness is the software around a language model that gives it tools, context, permissions and a loop. Here is what goes into one, and why it decides whether an agent works in production.
More topics: AI agent harnessesClaude Code All insights
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