Does AI Replace Technical Skill? The Honest Answer
Every time a powerful new tool enters networking, the same fear resurfaces. We heard it when scripting became mainstream. We heard it again with configuration management and infrastructure as code. Now the conversation has shifted to AI-native tools such as Cursor and Model Context Protocol integrations.
“Is this the moment engineers become obsolete?”
The honest answer is no. But the reasoning behind that answer is important.
AI Replaces the Typing, Not the Thinking
AI is exceptionally good at removing mechanical friction. It can generate a full BGP configuration in seconds. It can write automation scripts, summarise logs, and correlate monitoring alerts across systems. What it cannot do is understand your organisation’s intent.
It does not know why you selected a specific transit provider, what compliance obligations you must satisfy, how your change board evaluates risk, or the strategic trade-offs behind your architecture. That context exists in the engineer’s mind.
AI handles syntax. Engineers handle strategy.
It is similar to autopilot in aviation. The system manages routine flight conditions. The pilot remains responsible for judgment, especially when conditions change. Autopilot does not remove the pilot. It elevates the pilot’s responsibility.
Validation Is Becoming the Core Skill
We are entering a “trust but verify” era. AI generates. Humans validate, and validation requires expertise.
A less experienced engineer may review an AI-generated OSPF configuration and see nothing concerning. A seasoned engineer might immediately identify a dangerous redistribution policy, an incorrect area type, or a missing route filter that could leak prefixes.
The AI output is the same. The outcome depends entirely on who reviews it.
Mastery of fundamentals such as BGP path selection, OSPF behaviour, convergence mechanics, MTU consistency, and failure domain design becomes more critical, not less. AI does not understand your network’s unique edge cases. You do.
The Black Swan Problem
AI performs best when dealing with patterns it has seen repeatedly. Enterprise networks, however, often fail in rare and unexpected ways.
An obscure firmware bug. A cross vendor MTU mismatch causing intermittent packet drops. A control plane issue triggered only under a specific traffic burst at two in the morning. These scenarios are rarely documented and highly contextual.
When automation reaches its limits, first principles thinking takes over. Packet analysis. Route validation. Structured reasoning.
Technical skill remains the safety net when automation encounters the unknown.
What Actually Changes
The repetitive layers of the job begin to disappear. Manual CLI repetition, endless syntax lookups, copy paste configuration across dozens of devices, and tedious log scraping become automated. AI reduces mechanical effort and trivial mistakes.
What remains, and becomes more valuable, is architectural thinking. Designing resilient systems. Evaluating trade-offs. Identifying systemic risks before they reach production. Planning capacity with long term vision. Making sound decisions under uncertainty.
The role shifts upward.
Less typing. More thinking.
The Real Competitive Shift
AI will not replace engineers. Engineers who leverage AI will outpace those who do not.
The advantage belongs to professionals who understand networking fundamentals deeply, know how to guide AI precisely, and can rigorously validate outputs before deployment. The tool itself is neutral. Its leverage depends entirely on the operator.
AI is not replacing the engineer. It is replacing manual effort.
Your technical skills are not becoming obsolete. They are being elevated.
The real question is not whether AI will replace you.
The real question is whether you are ready to operate at the higher level it demands.
I would be interested to hear your view. Is AI lowering the skill requirement in networking, or is it raising the bar for what true expertise looks like?
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