Software development is no longer what it was just a few years ago. With the widespread adoption of artificial intelligence tools such as ChatGPT, Claude, Gemini, and Copilot, developer habits have transformed radically, to the point where many now rely on AI at nearly every step of the software development process.
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In a satirical overview, a tech report highlights what it describes as the "Seven Deadly Sins" that have become part of a programmer's daily life, reflecting the degree of their reliance on AI—sometimes at the expense of traditional software engineering principles.
1. We No Longer Memorize Theory—AI Handles It
In the past, developers were expected to master concepts like Object-Oriented Programming (OOP), Functional Programming (FP), design patterns, and database theory.
Today, many simply describe the problem to an AI, leaving it to choose the programming language, framework, or even the appropriate architecture for the project.
The report, originally published by InfoWorld, notes that deep knowledge remains important, but it is no longer applied in the same way as before the emergence of AI models.
2. Developer Documentation Is No Longer the First Stop
Reading official documentation for libraries and software tools was long a fundamental step when encountering an issue.
Today, the scenario is different; a developer copies the full error message and pastes it into a chatbot, expecting a solution within seconds instead of debugging, reading documentation, or searching Stack Overflow as was previously standard practice.
In fact, some AI-powered development environments now automatically suggest fixes before the developer even begins searching independently.
3. Running the Project... Without Fully Understanding What Is Happening
The report notes that many developers now rely on AI to generate databases, configure servers, write infrastructure-as-code files, and even establish security rules.
While everything may appear to run correctly, several developers do not fully comprehend how these components function or why they were selected—which can turn into a problem later when system modifications or fixes are required.
4. AI Writes the Code... Then Tests It Itself
One of the most controversial phenomena is that developers now ask AI to build the application, then return to the very same tool to generate quality assurance tests for it.
The author describes this scenario as akin to a student writing exam questions and then grading their own answers, since the tool that generated the code is the same one verifying its correctness.
Although this can boost test coverage metrics, it does not necessarily guarantee the detection of all bugs or flawed assumptions.
5. Design Documents Completed in Seconds
Preparing design documents or technical architecture diagrams no longer takes days as it used to.
AI can produce professional documents, illustrations, and flowcharts in seconds, giving technical teams a more organized appearance.
However, the report warns that a polished presentation does not always guarantee accurate content; these documents can conceal core errors that only surface after project implementation begins.
6. "Vibe Coding" Has Become a Reality
Although many developers publicly criticize what is known as "Vibe Coding," they practice it in secret.
Instead of writing code line by line, describing an idea to AI is now sufficient for it to generate user interfaces or large portions of the application in seconds. This gives developers a sense of speed and creativity, but it can diminish their deep understanding of what was actually built.
7. When Everything Fails... A Battle with the Chatbot Begins
If the AI makes a mistake, many developers do not revert to traditional debugging.
Instead, they rewrite the prompt repeatedly, adding more constraints and instructions, and altering their phrasing in hopes of getting a different answer.
The author describes this process as having evolved into a "battle of wills" between the developer and the AI, where the former continues tweaking instructions until achieving the desired result, without always understanding the underlying root cause of the issue.
A New Era... And a Blacker Box
The report concludes by emphasizing that programming has entered a completely different phase compared to a few years ago.
In the past, programmers were the sole individuals who understood how the systems they developed functioned. Today, AI models participate in writing major portions of the code—to the extent that even the developer themselves might not fully grasp every detail produced by the tool.
Al Arabiya
