These days you can prompt Claude to generate a working feature in twenty minutes. File uploads, database queries, API calls; the code appears, it runs, it looks right. But if you've never owned a mature architecture, AI-generated code becomes a liability you don't know how to manage.

You don't know how the pieces fit together, what breaks first under load, or how to go from works locally to deployed securely and ready to scale.

A developer recently put it well:

"I barely write code from scratch anymore. AI can handle a big part of that, incredibly fast. But interestingly, the job hasn’t become easier."

A few years ago the trap was tutorial paralysis. With LLMs, it just looks different: the code runs, but you didn't decide how it's structured.

The tools have changed, but the problem remains: when we hand over decision-making, whether to tutorials or to LLMs, we keep getting stuck.

Before: tutorial hell

Tutorials are good at one thing: showing you that code works. They walk you through syntax in a logical order and give you working code to follow. Automate the Boring Stuff, CS50, a Udemy course, all solid resources. They do what they promise, but it's often biased towards the happy path.

What they don't teach:

  • How to break an app idea into features small enough to actually build.
  • Which feature to build first and why.
  • How to structure a project so it doesn't collapse past a thousand lines.
  • How to use Git and GitHub to save your work and work effectively with other developers.

These aren't advanced topics per se. In practice though, they have so much more nuance and ambiguity.

The result: someone finishes a Django tutorial, sits down to build something real, and spends two hours stuck on a decision the tutorial never prepared them for.

As Mike Tyson once said:

"Everybody has a plan until they get punched in the face."

That's the blank page syndrome. Every decision has already been made for you in a tutorial. When you open your own project, you feel lost.

Now: vibe coding hell

LLMs have made this more pronounced. You can prompt your way to working code faster. But to go from prototype to something real and high quality, people still hit a wall, just differently. Instead of "I cannot replicate the syntax after consuming tutorials," now it is:

  • "I can vibe code but I've never owned an architecture end to end; if it breaks in production, I'm guessing"
  • "I know there are couplings between parts of my system but I don't fully understand the infrastructure beneath them"
  • "I've set up logs, tests, and audits, but I don't feel confident interpreting what they're telling me"
  • "I can't keep one part of the system consistent when another part changes"
  • "Deploying my app to the cloud is still a black box to me, even with AI"

The code runs. But you didn't decide how it's structured, and you can't foresee what breaks when it grows. You're executing without deeper understanding.

The gap is the same

Both traps share one root cause: someone else made the decisions.

Tutorials gave you syntax and a happy path to follow. Vibe coding with AI gives you code and a design to accept. Neither forced you to decide what to build first, how the data should flow, or what your architecture will cost you in six months.

Being deliberate is hard. AI is designed to feel fast, intuitive, and effortless. That pull is System 1 thinking by design. But real architectural ownership requires System 2 thinking: the slow, deliberate, and often frustrating "productive struggle" of weighing trade-offs.

When the AI removes that struggle, the knowledge doesn't stick. I see this all the time in coaching:

"The hands-on approach made all the difference. Building something real made Rust click in a way that tutorials never could — and honestly, it's made me a better Python developer too." - Vikas Z

It's the decision-making muscle we need to keep training to really own the code we write. To better understand System 1 vs 2 thinking, read Thinking Fast and Slow.

The solution isn't more prompts

More prompts will make you better at prompting. If the goal is to own what you build, that's not the skill you need. You need to learn how to make decisions about your project, how to structure it, and how to maintain it.

Working on your real project with someone who's done it before gives you that. Not abstract lessons, but your actual code, your actual decisions — feedback on why something will break, how to structure it better, or what to build first and why.

Vibe coding is fast at output. But it can't tell you which problem to solve first, why your architecture will hurt in six months, or that you're modeling the whole thing wrong. It also can't ask you why you made that decision, and that question is often where the real learning happens.

Vibe coding doesn't have to be a trap; it can be a power tool. But that only happens when you use the AI to augment your decisions rather than replace them. A power user prompts for a feature, but then pauses to ask: 'Why did you choose this pattern?' or 'How does this change our database load?' They use the generation speed to test architectural hypotheses and apply critical thinking.

From prompts to software architecture

Start with a problem worth solving. I usually scratch my own itch or look at what people are complaining about in forums. If the problem belongs to someone else and it's real enough, they might pay for it.

Don’t get bogged down in documentation or jump straight into prompts. Start with the design: How does data flow? What are the main features? Plan before you prompt.

If you need help, reach out to me. In one or two sessions you stop prompting and start thinking in architecture, and how to own your project end to end. I give you deep feedback on your code and design, not lessons in the abstract. You learn to make those decisions yourself, and feel confident in them, instead of relying on the model to tell you what to do next.

That's 1:1 coaching. Here's what it did for Ryan:

"My Python coaching, however, gave me the ability to 'see under the hood.' Because I understand the core principles of Python and Django, I can effectively direct the AI. Without coaching, you're just a passenger; with it, you're the navigator who actually understands the map."

Ryan went from building alone to directing AI agents with confidence for a business that now supports his life in the Bahamas. If you're ready to stop being a passenger in your own codebase and start navigating with a map you actually understand, let's talk.