I started using Codex to learn DevOps… now I’m wondering what exactly I’m learning 😂
A QA engineer is learning DevOps by building a personal project, gaining hands-on experience with Git, TypeScript, Playwright, testing, CI/CD, and architecture. They are using Codex, an AI tool, and are now questioning the exact nature of their learning. Their current strategy involves manually building new concepts step-by-step, while leveraging AI agents primarily for reviews, repetitive tasks, and error detection, and they are interested in how others approach this learning method.
Why this oneThis post uniquely highlights a developer's real-world struggle to balance AI assistance with genuine skill acquisition, unlike typical reports focusing solely on AI's benefits or drawbacks.
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- 09/08, 18:38 UTC+0
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- 09/09, 17:00 UTC+0
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I’m a QA engineer trying to move into DevOps, so I started building my own project to get hands-on experience with Git, TypeScript, Playwright, testing, CI/CD, and architecture.
Today I decided to try Codex. I gave it access to my local repo and explained what needed to be done.
The thing inspected the code, found the problem, modified the files, added regression tests, cleaned up Git line-ending issues, ran all validations, and created the commit—while I continued doing my actual job.
Then it just came back with a clean summary of everything it had completed.
Absolutely incredible… but also: what the hell am I supposed to learn now? 😂
For those learning DevOps or software engineering while using coding agents: how do you balance the productivity boost without outsourcing the entire learning process?
My current idea is to build new concepts manually, step by step, and use agents mainly for reviews, repetitive work, and catching mistakes. Curious how others approach this.