“The computer is the most remarkable tool that we’ve ever come up with. It’s the equivalent of a bicycle for our minds.” *— *Steve Jobs

*“The programmer, like the poet, works only slightly removed from pure thought-stuff. He builds castles in the air, from air, creating by exertion of the imagination.” — Fred Brooks, *The Mythical Man-Month *

“Programming is the art of telling another human being what one wants the computer to do.”* — *Donald Knuth, The Art of Computer Programming

“Any fool can write code that a computer can understand. Good programmers write code that humans can understand.” — Martin Fowler

Software is a manifestation of humans thinking in public. It’s our attempt to shape logic into form, to trap intent, ideas, imagination inside systems.

Then came vibe coding, the exhilarating, seductive experience of watching AI turn our whims into code, a website, an application. We recline in our chairs, coffee in hand, watching code appear line after line like magic, giving us a dopamine hit.

But beneath that rush lies something fragile. Code that appears viable breaks once put into production. Systems can’t be scaled or trusted, and teams end up spending more time debugging than shipping.

And the most dangerous part is that we become lazy and lousy. With seemingly viable code generated by AI, we stop thinking. We risk losing the precious software heritage that humanity has accumulated over the past few decades because vibe coding isn’t built to capture it.

Every organization’s internal system encodes years of ‘tribal knowledge’: business iterations, unwritten rules and institutional practices. The development of this system requires deep human consensus and experience. It’s the living memory of a company, a collective form of understanding that can’t be autocompleted by AI.

We aren’t rejecting vibe coding; its invention has opened the gates for millions of people who never dreamed of building software. But confusing convenience with craftsmanship is dangerous.

Therefore, we are calling for the alternative to vibe coding — serious coding, a disciplined programming practice that combines human intent with machine capability, with people’s understanding and ownership as the prerequisites.

The cost of vibe coding

Speed without precision is chaos. The problem of vibe coding is three-fold:

The productivity tax: AI-generated code is rarely production-ready. It demands debugging, refinement and human alignment that slows down real-world development, often taking longer than if it were written deliberately.

The technical debt spiral: When teams trust generated code blindly, they inherit artifacts they can’t comprehend. The results are untraceable bugs, brittle architectures and codebases that create future maintenance headaches.

The security abyss: Auto-generated code often comes with security vulnerabilities, lacking proper validation and secure practices that incurs huge costs down the road.

Human’s indispensable role

A.I.s can’t replace the human intuition acquired through learning and mastery for three reasons:

Fundamental competence: Even if AI-generated code keeps improving, humans still need to learn basic skills to be the vanguard of the work. Understanding algorithms, data structures and systems architecture remains the foundation. One cannot debug what they don’t understand.

Continuous learning: Serious developers adapt to new tools but should never outsource their understanding. Humans learn from machines, not lean on them.

Craftsmanship: Generating code is just the first step. Humans need readable code, modular design and proper testing for trust, collaboration and scale, all of which require people’s supervision.

Therefore, we are proposing a framework for AI coding and human involvement to coexist.

Humans + AI

AI is a remarkable collaborator, but we can’t assign it responsibility and ownership. We use AI to augment our work, not to surrender our expertise and agency. It’s a tool, not our replacement.

We use AI tools with discipline, for instance, always reviewing and understanding generated code and applying rigorous code review standards.

Serious programmers sign off their work. We stand behind what we ship. Humans should remain accountable for the intent, correctness and consequence of code. Ownership is what makes us humans.

A culture of trust

Serious coding requires building a culture of collective responsibility.

We need to advocate for adopting frameworks and procedures (e.g., security scanning and TRiSM practices) to validate AI-generated code.

Every line of code carries a value weight and must be traced back to a human agent. Providers of AI coding tools should be reminding users of ethical considerations like data privacy and safe deployment.

Society as a whole should build systems that educate, certify and continuously upskill developers in AI literacy and secure coding skills.

Realistic expectations

The myth of “push a button, code appears” is a new form of technical naivety. The goal should not be faster code but better understanding.

AI coding assistants get humans over the hump of pumping, but they don’t make software complexity disappear. The hard problems like architecture, tradeoffs and semantics remain solvable only by humans.

Software is not a static artifact but a living system that is complex and ever-evolving, requiring critical thinking and problem-solving from humans with mastery.

Velocity without deliberation leads to fragility. Teams and businesses should invest in sustainable AI coding practices rather than chasing short-term productivity spikes.

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The future of software development belongs to those who think deeply, build deliberately and stand behind the code they create with the help of AI. Serious coding is a commitment to a future where humans and AI can coexist to advance human flourishing.