The Future of Network Engineering Is Bigger Than Networking
Networking fundamentals become more useful, not less, when engineers use them to understand cloud, security, observability, automation, and the systems around the network.
Blog
Posts on technology, work, systems, and decisions.
Some posts will be technical. Some will be more reflective. The common thread is trying to notice what changed, what held up, and what is worth thinking through again.
Self-Service Networking Should Expose Intent, Not Configuration
Good network automation asks consumers for the outcome they need, then derives the implementation details the network already knows how to provide.
You Should Define Your Segmentation Policy First
Durable segmentation starts by defining required communication and its consequences before choosing how to enforce it.
Network Automation Does Not End at Deployment
Network automation is not complete when the configuration deploys. It also needs evidence that the network, applications, and security controls behaved as intended.
What Architects Actually Produce
Architecture produces diagrams and documents, but its more consequential outcome is often the shared understanding that helps an organization make decisions and move work forward.
Have You Thought of an Architect as a Lead Engineer? There's More to It Than That.
Architects get expected to act like lead engineers with a wider scope. The job is usually something else, and the difference tends to show up in small, easy-to-miss moments.
AI Can Write the Architecture Document. It Cannot Create Alignment.
AI can make architecture documents easier to produce, but alignment still depends on shared understanding, visible trade-offs, clear ownership, and people making a decision together.
AI-Assisted Network Engineering Is Not Network Automation
AI can help network engineers reason, draft, and review, but it does not replace deterministic automation, testing, or the engineering judgment that makes infrastructure changes safe.
Relaunching vStaub
Why this site is starting small: infrastructure, AI, architecture, career observations, and the useful experiments that keep changing how I think.