Code is cheap. Like, ridiculously cheap. Writing code has never been faster or easier, and if that statement makes you uncomfortable, you're probably still treating lines of code like they're sacred manuscripts instead of sticky notes.
Here's the thing: if you're not using AI for coding, you're not being principled - you're being left behind 🏃♂️. And no, I'm not saying you need to let AI touch your production environment (though why not?). But at minimum, you should be familiar with models, agents, and hell, why not build one yourself? It's like refusing to use a calculator because you're good at mental math. Congratulations on your skill, but the rest of us have moved on to solving harder problems.
Vibe Coding Is Real ✨
You can build entire applications exclusively using AI. But here's where people get confused: they conflate the tool with the responsibility.
Are you hacking together a weekend project? Great, let AI run wild 🚀. Contributing to a production codebase? You're still the gatekeeper of what goes to main.
The code might be cheap, but your judgment isn't.
The endless discussions about AI coding everything and developers losing ownership? They're missing the point entirely. If you're asking "how do I judge if the code is good?" the answer is: Can you not read code? 🤔 Did you forget that skill the moment Claude started typing? You're still responsible for every line that ships. AI just does the busy work and frees you up for the actually interesting problems - the ones that require thinking, not typing.
The Gap Problem 🕳️
But here's where it gets interesting. There's a paper showing that all AI models share the same fundamental deficiency. When you leave out information and ask AI to fill the gap, it can't. Not won't - can't. It's architectural, baked into how transformers and attention mechanisms work. LLMs are brilliant with large datasets but terrible when data is absent.
So when you ask AI to "implement this feature" without specifying exactly how, you're leaving gaps. And AI will fill those gaps - not with what you wanted, but with whatever its training suggests is statistically likely.
You wanted AI to read your mind, and instead it read the internet. 🌐
Then you complain that AI did things you never asked for. But you also didn't ask for anything specific.
Extract the Capability 🎯
This is the crux: The more guidance you provide, the better the result. We're past the point of questioning model capability. The models are capable. The question now is: How do you extract that capability? It's like the early days of ChatGPT before the Q&A format - the emergent intelligence was there, but it was hard to talk to it properly.
Use Plan Mode 📋
Take Claude Code's plan mode. The initial prompt is everything. Let the model explore your codebase, research APIs, understand the landscape. That plan becomes the north star for implementation. You can adjust it, refine it, then tell Claude to code until it's done.
AI in the loop, not AI in charge. 🔄
Build Guardrails 🚧
You need guardrails. Type-checking, linting, tests - these aren't suggestions, they're requirements. AI doesn't know it made mistakes. It needs feedback in the form of errors and warnings.
- Teach it to run type checks; it will correct its own mistakes ✅
- Teach it to write tests and run them until they pass 🧪
- The feedback loop is what makes AI useful instead of dangerous ⚡
A Real Example 📸
I recently implemented a design from a screenshot. My first attempt? Horrible. Claude couldn't match what I was seeing. So I stopped, thought about the gaps I was leaving. My final prompt:
"Inspect the image very carefully. It's a screenshot of a web page section. Identify the individual elements on the page. Describe in detail what you see. Then explore the current implementation and make any necessary changes to match the design in the image. Refer to the design system for a consistent design language across the page. Do not use the colors from the image. Ultrathink."
That's it. One paragraph of specific instructions instead of "make it look like this." Claude nailed it 100% on the first try 💯. No screenshots, no puppeteer feedback loops. Just clear communication and one made-up word to trigger its reasoning capabilities.
The Bottom Line 💡
The message is simple: Use AI. For your side projects, your experiments, your production code where it makes sense. I love working with Claude Code, not because it replaces me, but because it amplifies me.
The developers who get this are already moving faster than you can imagine. The ones who don't are still debating whether it's "real programming." 🙄
And if you're still worried about job security, think about what hasn't changed:
- Good code still needs to be recognized as good ✨
- Gaps still need to be filled with intention, not accidents 🎯
- Someone still needs to own what ships 📦
That someone is you. Only now you're not typing - you're directing. 🎬
