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Practical Knowledge

Real problems.
Practical solutions.

Field-tested IT knowledge, troubleshooting guides, and free tools for professionals and people learning to build with AI.

AI Development · Infrastructure

From an idea to a deployed web service

AI can write code, but a continuously developed and operated service also needs a working environment, source control, repeatable builds, deployment, and verification.

Remote user → Windows PCWSL2 / Ubuntu → Codex CLI, Node.js, GitGitHub commit / push → connected build and deploymentPublic website → verify the result
This is a practical pattern, not the only or universally optimal setup. Choose the tools and boundaries that fit your context.
What we document

Useful detail over search-shaped filler

Good guides should explain symptoms, logs, context, the applied change, how it was verified, what to watch for, and how to roll back when possible.

InfrastructureNetworkingSecurityTroubleshootingAutomationAI DevelopmentFree Tools
A working principle

AI writes code.
Operating a service is another problem.

The gap between those two moments is where environment setup, version control, deployment, observability, and careful verification matter.

What comes next

We will expand this area when a guide has a concrete problem, a verifiable procedure, and enough context to be genuinely useful. We do not publish empty guides just to fill a category.

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