The Seven Laws of Software Engineering in the Age of AI and "Vibe Coding"
The speed of software development has never been more breathtaking. With AI tools like GitHub Copilot completing our code and ChatGPT architecting solutions in seconds, the pressure to "just code" and ship features is immense. We've entered an era of what some call "vibe coding"—a development flow driven by intuition, velocity, and the satisfaction of seeing things work quickly.
This new reality is powerful. But what is its hidden cost?
Recently, we've seen clear examples of this cost. The social app "Tea," which gained rapid popularity, suffered a massive leak of its users' private images. This isn't an isolated case but a symptom of a culture that, in its rush to launch, often leaves fundamentals behind. Security, scalability, and maintainability are deferred to "later"—a "later" that, for Tea's users, came far too late.
This forces us to pause and revisit the foundations. Decades ago, timeless principles were established to guide the construction of robust, quality software. In the age of AI, these "seven laws" have not become obsolete; on the contrary, they have become more crucial than ever. They are our beacon to navigate the fog of speed.
The Seven Timeless Laws and the Trial by Fire of Modernity
Let's analyze each of these principles and reflect on their relevance in today's landscape.
First Principle: The Reason for Being (Add Value)
- The Law: A software system exists for one reason: to provide value to its users.
- Reflection in the AI Era: AI can generate features in the blink of an eye, but it has no concept of "user value." It doesn't understand business context, customer pain points, or product strategy. In the "vibe coding" culture, it's tempting to add features just because AI makes it easy. This principle forces us to act as curators. Our most important question shifts from "Can we build this?" to "Should we build this?"
Second Principle: KISS (Keep It Simple, Stupid!)
- The Law: All design should be as simple as possible, but no simpler.
- Reflection in the AI Era: AI tools, if not well-guided, can generate overly complex and verbose solutions. They might spit out complicated design patterns for simple problems. Elegant simplicity is not the default for a machine; it's the result of deep human thought. "Vibe coding" often results in quick hacks—solutions that work now but create a maintenance nightmare. True simplicity requires effort and discipline, roles that the developer must now take on with even more seriousness.
Third Principle: Maintain the Vision
- The Law: A clear vision is essential to the success of a software project.
- Reflection in the AI Era: AI has no vision. It is a tactical tool, not a strategic one. A project guided solely by AI prompts and the flow of "vibe coding" runs the risk of becoming a "hodgepodge of incompatible designs," just as the principle warns. AI can build the walls, but the architect (the developer, the tech lead) must have the complete blueprint in their head. Without this human-driven vision, the system disintegrates into a set of disconnected features.
Fourth Principle: What One Produces, Others Consume
- The Law: Always specify, design, and implement knowing that someone else will have to understand, maintain, and debug your work.
- Reflection in the AI Era: This is perhaps the most violated principle in the age of AI. When Copilot generates an obscure block of code, who is responsible for documenting it? Who ensures it's readable? The answer is: you are. The developer who "accepts" the suggestion is the producer. The Tea app case is the ultimate consequence of this principle's failure. The developers produced a system, and the "others" (the users) "consumed" the consequence of their lack of care: the exposure of their data. Code is not just for the machine; it is human communication.
Fifth Principle: Be Open to the Future
- The Law: Design systems that can adapt to change, solving the general problem, not just the specific one.
- Reflection in the AI Era: AI is trained on the past and present. It is excellent at generating solutions for well-defined problems based on existing patterns. It is not good at anticipating the future or designing for flexibility in the face of the unknown. The "what if?" question remains a profoundly human task. "Vibe coding" focuses on the "now." It falls to the software engineer to think about the "later," designing systems with loose coupling and high cohesion that can evolve.
Sixth Principle: Plan Ahead for Reuse
- The Law: Reuse saves time and effort, but it is not automatic; it requires planning.
- Reflection in the AI Era: It's easier to ask AI to generate the same type of code in five different places than to stop and think, "Wait, should this be a reusable component?" AI can inadvertently encourage duplication over abstraction. Planning for reuse is an act of architectural design, something that requires the macro-level vision only a developer can provide.
Seventh Principle: Think!
- The Law: Clear, thoughtful thinking before acting almost always produces better results.
- Reflection in the AI Era: This is the final and most important principle. The greatest promise and the greatest danger of AI and "vibe coding" is that they allow us to act without thinking. They give us the illusion of progress by generating code, when in fact we might just be digging a deeper hole, faster. A software engineer's real job isn't typing; it's understanding the problem, analyzing trade-offs, designing a solution, and then implementing it. AI can automate parts of the implementation, but it cannot (and should not) replace the analysis.
Conclusion: AI is a Brilliant Intern, Not the Architect
The seven laws of software engineering are not a brake on speed; they are the guardrail that keeps us from driving off a cliff. The Tea app's data leak was not a failure of technology but a failure of principles. It was the direct consequence of not thinking about what was being produced, who would consume it, and failing to maintain a vision of quality and security.
AI tools are like an incredibly fast and talented intern, but one with no experience, no context, and no sense of responsibility. They can produce a lot of code, but it's up to the senior engineer (you!) to review, simplify, ensure quality, and, above all, think.
In the age of AI, our value as developers is shifting from the ability to write code to the ability to guide the generation of code with wisdom, vision, and an unwavering commitment to these fundamental principles. Speed is a means, not an end. User value, simplicity, vision, and quality remain the true north.
