Why run_command () doesn’t belong in your first network agent
A flexible tool pushes the hardest safety decision into runtime. Narrow tools make that boundary explicit.
The AI Network Engineer by Packt
Where AI meets production networks
Live Last read · last published · next check
Latest posts
Your agent said everything looks fine. Scroll up.
A tool-using agent produces two outputs. Only one of them is evidence.
Valid JSON can still be wrong
There are two gates between a model’s output and your workflow. Most teams only build the first one.
Don’t let AI troubleshoot from a single signal
Before an agent recommends a network change, make it prove the diagnosis.
The rule your AI agent is probably missing
A context contract tells an agent what it knows. A stop condition tells it when not to continue.
Your AI agent needs a context contract
Fresh context helps. Knowing which context to trust matters more.
AI workflows need more than prompts
Two hands-on sessions on Claude Code, GitOps, and platform engineering, plus a quick test for safer AI workflows.
Before you build an MCP skill, ask this
A quick test for deciding which network workflows are ready for agents.
Could someone else run your MCP server if you weren't around?
Six issues ago, this newsletter didn't exist yet. A workshop called Build Intelligent Networks with AI did, and it's why you're reading this now.
AI Infrastructure & Agentic Workflows Start with Better Engineering
Three hands-on sessions for platform, network, and Linux teams trying to make agentic workflows useful without making them reckless.