Vibe Coding Without a CS Degree

I have no Computer Science (CS) degree. I have never written a line of production code in my life.

I built a Severance calculator that 45,000 people saw on LinkedIn and thousands visited from around the world. I built a F.I.R.E. calculator because I didn't like any of the others that I found online (they were either incomplete, had a bunch of Ads, or you couldn't save your work). I have built market simulations, quizzes, and interactive tools that live on my site and that real people use to make real decisions.

None of it would exist without AI. And none of it was easy.

This is not a story about how AI does everything for you. It is a story about what happens when someone who thinks in systems but cannot write them suddenly has a collaborator who can.

I Was Frustrated

I did not start with a strategy. I started with a specific frustration.

When Severance became a cultural moment, I noticed something most of the conversation was missing: most people watching the show had no idea what a severance agreement actually does. It is not a parting gift. It is a contract. (READ: Severance Packages - 6 Terms to Negotiate) You are trading your right to sue your employer for a check, and several pieces of that contract are negotiable.  Areas such as the amount, the non-disparagement language, the timeline, the outplacement support.

I wanted to build something that made that real for people. Not just a blog post. A tool. Something where you enter your salary, your years of service, your state, and walk out the other side with a number and a negotiation playbook.

The problem: I cannot code.

So I described what I wanted to an AI, in plain English, the same way I would brief a contractor. I explained the logic. I explained what the user experience should feel like. I explained what the output needed to do. And then I iterated, back and forth, until what appeared on the screen matched what was in my head.  (By far, the hardest part was ensuring the mathematical equations and logic were strong and as accurate as possible!)  Within a few hours, I had built something I could not have built.

What 45,000 Views Actually Taught Me

When I shared the Severance calculator on LinkedIn, the post reached 45,000 views. Thousands of people from around the world found their way to my site. Many reached out directly. What surprised me was not the volume. It was the specificity of the feedback.

People were not just impressed by the tool. They were grateful for the "Your Negotiation Playbook" section. They said things like: I had no idea I could push back on that. Or: I signed one of these last year and I wish I had known this. I was really excited as it was meeting people at their specific situation.

Token Walls

If you've hit a token wall you know it sucks.  If you haven't, it's basically like hitting a paywall on a news site after you read the first paragraph of an article and are dying to read the rest.

For me, is typically shows up deep in a build where the AI and I are working well, we are something like 80% of the way through something genuinely complex and the AI is holding the context of everything I've built so far (i.e. the structure, the edge cases, the decisions you made two hours ago about how a specific calculation should behave, etc.). And then you hit the token limit.

The context window closes and the momentum breaks. The AI you are now talking to does not know what the one from two hours ago knew.

I have paid for premium access specifically on Claude so I can build without that ceiling, and I still hit it. When it happens I feel a quiet, resigned frustration. Actually, to be honest, sometimes I feel rage...especially if I am running out of tokens because of poor code or mistakes the AI is making.  I feel like I shouldn't be charged for the AI's mistakes. 

The real cost of vibe coding is having to rebuild the context, re-explain decisions and commands, etc. The big looser is me because I lose time and money. This is the real cost of vibe coding, and it is underreported. The tools are extraordinary. The infrastructure is still catching up to the ambition of what people are trying to build with them.

Building An AI Agent

After enough broken builds and repeated mistakes, I stopped treating AI like a search engine I happened to talk to. I started treating it like a team member who needed proper onboarding.

Every serious project now lives in a dedicated Claude Project. I maintain structured Markdown files that encode my style guide, my brand rules, my cover image guide, my code preferences, and the decisions I have already made so I do not have to make them again. I have built multiple AI Agents for specific repeatable tasks.

The difference was immediate and noticeable because the AI stopped forgetting. The builds stopped drifting and the outputs stopped requiring me to re-explain things I had already explained a hundred times.

I am calling this the Operator Stack: the combination of Projects, structured MD files, and task-specific Agents that turns a capable AI into a consistent collaborator. It is not a product. It is infrastructure and the quality of that infrastructure is what separates vibe coding that scales from vibe coding that frustrates.

The next step is moving the most complex builds into Skills, structured capability files that encode not just preferences but procedures. When a project is complicated enough that a style guide alone cannot carry it, Skills are the only option. That is where I am heading.

The Same Shift Is Happening at Work

None of this is separate from my day job. I work in enterprise software sales at Adobe, and the same AI-driven shift that changed how I build tools for my site has changed how I build strategy documents for customers.

Account plans used to be a synthesis exercise: gather data from multiple sources, extract what matters, frame it for the audience, and write something coherent under real time pressure. That process has not disappeared, but its ceiling has changed. AI now lets me synthesize more data, more quickly, into documents that are actually personalized to the customer's situation rather than templated to save time.

Whether I am building a Severance calculator or a customer strategy document, the rule is identical: AI does not replace the thinking. It amplifies the reach of the thinking. The operator who brings real judgment and domain knowledge is more valuable than ever. The operator who thinks AI does the thinking for them will produce exactly what AI produces on its own, which is competent, generic, and forgettable.

There is a larger implication here that I keep coming back to. The tools that used to require a developer, a designer, and a budget are now available to anyone who can think clearly about a problem and describe it precisely. (Read: Why Project Managers Are The Real Heavyweights) That changes who gets to build things. A sales professional, a nurse, a teacher, a small business owner with twenty years of domain expertise and zero coding background can now put that expertise into functional form. The access gap between having an idea and being able to build it has never been smaller. What you do with that access is still entirely on you.

What Vibe Coding Actually Is

It is a new category of creative leverage for people who think in systems but never learned to write them.

I think in sales cycles, in customer journey logic, in financial frameworks, in the mechanics of how people make decisions under uncertainty. Vibe coding did not give me that. What it gave me was the ability to express it in functional form, in tools that run, that people use, that do something a paragraph cannot.

The question worth sitting with is not whether you can code. It is whether you have something real enough to build.

Key Takeaways

• Vibe coding is not a developer shortcut. It is creative leverage for people with domain expertise and no coding background.
• The Operator Stack (Projects + structured MD files + AI Agents) is what separates consistent, scalable builds from sessions that drift and break.
• Token walls are the most underreported real cost of vibe coding. Paid access reduces the ceiling. It does not eliminate it.
• AI amplifies the reach of real thinking. It does not replace it. Generic inputs produce generic outputs regardless of the tool.
• The same shift that changed how I build personal tools has changed how I build professional strategy documents. Bring the judgment, let AI expand what that judgment can produce.
• Moving complex projects into Skills is not an optimization. For sufficiently complex builds, it is the only viable architecture.

FAQ

What is the Operator Stack?

The Operator Stack is a framework for building a consistent AI collaboration system. It combines three layers: dedicated Claude Projects that hold context per topic, structured Markdown files that encode style rules, brand decisions, and build preferences, and task-specific AI Agents for repeatable workflows. Together they replace freestyle prompting with infrastructure that does not forget, drift, or require constant re-explanation.

Why does vibe coding break down without a system?

Without structured context, every new conversation starts from zero. The AI does not know your brand rules, your prior decisions, your code preferences, or what you built last session. The result is inconsistent output, repeated mistakes, and builds that drift away from what you intended. The Operator Stack solves this by giving the AI a stable, persistent briefing before any work begins.

What are Skills and why do they matter for complex builds?

Skills are structured capability files that encode not just preferences but full procedures for a specific type of complex task. Where a style guide tells the AI how to write, a Skill tells it how to execute a multi-step build: what to check first, what decisions to make when, and what the output should look like at each stage. For projects too complex for a style guide alone to carry, Skills are the only architecture that holds.

About the Author

Martin Goetzinger has spent his career in enterprise software sales, helping large organizations such as Apple, Microsoft, and Verizon connect data, insight, and action. His work focuses on transforming how businesses measure success and create customer value through technology.

Outside the enterprise world, he writes about the five forces he believes are reshaping everything: AI, blockchain, energy, personalized health, and robotics. Not from a purely technical lens, but from a human one as to how these technologies will redefine work, wealth, and well-being.

He is based in the U.S. and publishes at www.MartinGoetzinger.com.

Disclaimer

The views expressed in this article are the personal opinions of the author and are provided for informational and educational purposes only. Nothing in this article constitutes investment advice, financial advice, legal advice, or any other form of professional advice. Do not make investment or financial decisions based on the content of this article. Always consult a qualified professional before making decisions that affect your finances, business, or livelihood.