For someone trying to enter technology from outside the usual career pipeline, the field can feel unsettled: AI is changing how people work, tools rise and fall, and it is hard to know what to learn first. Mika Flowers’s September 18, 2026, DEV Community post approaches that anxiety as a personal reflection—not a forecast about hiring or proof that the industry is uniquely unstable. Its practical advice is to start with problems you care about, use tools you can understand, and make your earlier experience legible to a technical audience. Read Flowers’s post on DEV Community.
Start with a problem, not a fashionable stack
Flowers illustrates the point with KeyFlip, a Linux utility they built to disable a laptop’s built-in keyboard when an external keyboard is connected. They used Python and GTK4 because those tools served the specific project. The example is not a recommendation for a particular setup or a claim that those technologies are the best choice for everyone; it shows how a concrete annoyance can give a beginner a reason to choose and learn tools.
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That changes the question from “Which framework is trending?” to “What is something I want to make easier, and what would help me do it?” A small, understandable project can give you a more useful learning path than trying to predict which tool will remain popular by the time you finish a tutorial.
Use AI without giving up ownership of your code
Flowers says they use AI while building, but do not want to ship code they cannot explain. Their standard is personal and practical: they want to understand the work well enough to discuss and defend a pull request, including in an interview. As Flowers puts it, “What I don’t do is ship code I can’t explain, because that’s not developing, that’s just outsourcing the part where I learn anything.”
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This is advice about how Flowers wants to learn and work, not evidence that AI use is inherently harmful or that every employer evaluates candidates the same way. For a learner, the useful test is whether AI assistance leaves you able to describe what the code does, why it fits the problem, and what you would change if it failed.
Translate earlier experience into technical-language examples
Flowers draws on work outside conventional technology roles: years managing a Trader Joe’s, front-desk work, and running a TikTok LIVE community. In the post, Flowers says that community reached 50,000 followers and involved managing 16 moderators; those figures are part of the author’s personal account, not independently verified statistics.
The résumé lesson is to explain the responsibilities behind a role rather than assume its title will speak for itself. Flowers’s examples point toward coordination, operations, and responding to difficult situations—experience that can be described in terms a technology team may recognize. Be specific about what you actually did, the people or processes you coordinated, and the challenges you handled; do not claim technical work you did not perform.
Choose the problems you want to work on
Flowers does not argue that the technology sector will settle down, nor does the post establish what the next five years of hiring or AI development will look like. The closing thought is instead a choice about direction: “So the real question was never "how do I avoid the chaos." It’s "which chaos do I actually want to debug for the next five years."”
For someone starting out, that means you do not have to solve uncertainty before you begin. Pick a domain or problem that holds your interest, build something small enough to understand, and learn the tools that help you move it forward. Flowers sums up the point neatly: “The stack is not the plot twist you think it is.”
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