We Used to Crimp Cat5e Cables. What Should We Learn in the AI Era?

The rise of AI does not make network fundamentals obsolete. But building everything by hand is not the same as understanding how it works. The engineer’s value is moving from performing each construction step to defining the goal, making choices, validating results, and combining systems effectively.

I used to make my own Cat5e cables

Years ago, I built my home LAN while reading Japanese magazines such as Software Design.

I measured the run, cut the cable, stripped the jacket, arranged the wires by color, inserted them into an RJ45 connector, and crimped it. If the link did not work, I checked the wiring and tried again. Cat5e was as far as I went with handmade cables.

That experience was valuable. A link would fail to come up, the expected speed would not appear, or the connection would drop when the cable moved. Troubleshooting those failures made it clear that a network does not exist only in a configuration screen. It rests on a physical layer.

But as speeds increased and quality and validation requirements became more demanding, making every cable by hand was no longer always the best choice. Today, choosing a reliable, factory-terminated cable that fits the use case is normal.

Not making it yourself does not mean not understanding it

Using finished LAN cables did not make the fundamentals unnecessary.

• What speed and cable category does the connection require?
• Are the length and installation method appropriate?
• Is a problem in the cable, port, device, or configuration?
• If replacing the cable fixes the symptom, how do you isolate the actual cause?

The hands-on work moved to a different place. The ability to assess requirements, choose the right component, and validate the result became more important than crimping the connector itself.

This is not abandoning the technology. It is using a mature layer as a foundation and moving on to the problem above it.

AI is bringing the same change to infrastructure work

AI can generate Terraform definitions, firewall rules, WireGuard configuration examples, and monitoring scripts. Work that once began by reading pages of documentation and looking up syntax can now begin with a short prompt.

Does that mean there is no longer any value in writing a configuration one line at a time?

It depends on the goal.

There is still enormous value in building a small learning environment, breaking it, and repairing it. Evaluating AI-generated configuration still requires a grasp of IP addressing, routing, NAT, DNS, firewalls, cryptographic keys, and other fundamentals.

In production, however, rebuilding everything from scratch is not proof that learning has taken place. Blindly trusting generated configuration is risky, but so is assuming that a configuration must be correct because you typed every line yourself. What matters is whether you can explain and validate what you are trying to achieve, which assumptions it depends on, and how it can fail.

Newton’s value was not in making an apple fall

The story of Newton and the apple is famous. In the Royal Society’s account of William Stukeley’s record, Newton is said to have reflected on gravity after seeing an apple fall while sitting in a garden. Even if parts of the story were embellished over time, what it represents is clear.

People had seen objects fall long before Newton. The valuable step was not dropping another apple. It was asking why it fell and connecting an event on Earth to a broader law.

Engineers in the AI era face a similar challenge.

If the central measure of skill is whether you wrote an entire configuration file by hand, you can spend your time reproducing the act of dropping the apple. The more important ability is to observe the result, question its assumptions, and generalize the lesson so that it applies to other problems.

Rebuilding the wheel to learn, and using the wheel to work

Reinventing the wheel is not always a waste.

Build a wheel once, and you can learn about load, friction, materials, and failure. If existing wheels cannot meet a new requirement, designing another one may be justified. Building DHCP, DNS, or a VPN in a network lab can serve the same purpose.

But a job that moves cargo to a destination does not require you to make new wheels before every trip.

For learning, you may deliberately rebuild a component. For operations, you can use proven components and services and spend your time on the requirements unique to the system. These are different decisions.

A home VPN can become a foundation to use, not a project to build

For a long time, building a home VPN was an achievement in itself.

You opened a router port, configured dynamic DNS, and managed WireGuard keys and configuration. If the connection failed from outside, you investigated double NAT, CGNAT, IPv4 over IPv6, IPv6 firewall rules, and other possible causes. A home VPN remains an excellent way to learn networking.

But was building the VPN server the thing you actually wanted to accomplish?

• Reach a NAS or development environment at home while away
• Send internet traffic from a trip through your home connection or a family member’s connection
• Reach an administrative environment that allows the public IP address used by your home connection, together with appropriate authentication
• Use your own devices and services across locations

If these are the goals, the VPN is a foundation rather than the finished work. Time previously spent building and maintaining that foundation can go toward what you intend to accomplish with it.

Infrastructure engineering is moving up a layer

AI and managed services do not make lower-layer knowledge unnecessary. The more you rely on generated output and external services, the more carefully you must decide what to delegate and where your own responsibility begins.

The following abilities are becoming more important:

• Define the problem before introducing a technology
• Identify assumptions about connections, devices, locations, and applicable terms
• Map trust boundaries across authentication, keys, network paths, and operators
• Design observability and rollback for failures, not only the normal path
• Validate the output of AI and services with evidence
• Connect technical decisions to the result the user needs

The emphasis moves from memorizing commands to reasoning about design, and from proving that you can build something to deciding whether it should be maintained as a custom system. Engineering work is not disappearing. The place where it creates value is changing.

What HomeGrid VPN removes, and what it does not

HomeGrid VPN does not turn networking into magic. It uses a hub-and-spoke design in which remote devices and Grids at locations such as a home connect to a Cloud Hub. Traffic travels through the Cloud Hub and a Grid, then reaches the internet through the connection where that Grid is installed. When a Grid at home is the exit, the traffic actually leaves through the residential ISP connection. The Cloud Hub is a relay on the path, not the Internet Exit.

Because each Grid uses an outbound connection to the Cloud Hub, the design does not normally depend on IPv4 port forwarding or dynamic DNS on the home router. It removes some of the construction requirements that users previously had to take on whenever they wanted to operate a home VPN.

Other decisions remain: what traffic to carry, which location to use as the exit, who should have access, whether you have the subscriber’s permission when using a connection contracted by a family member or someone else, and whether the intended use complies with applicable terms. Using a residential connection as the exit does not guarantee access to or use of any particular service.

Understanding how HomeGrid VPN works matters. Reimplementing that system from scratch is not every user’s goal.

What do you really want to accomplish?

The experience of making a Cat5e cable was not wasted. Neither is building a home VPN once or writing a configuration without AI. Each can help turn an abstract mechanism into something you understand.

But there is a difference between using that experience to move up a layer and using it to remain on the same one.

Every time we stop doing a task by hand, it can feel as though we are losing a technical skill. Yet when we started using factory-terminated LAN cables, we did not abandon networking. We became able to build and use larger networks through more dependable components.

The same is true of AI and services. The question is moving from “Can I build every part myself?” to “What do I really want to accomplish with this foundation?”