From Skeptic to Believer: Can Claude Actually Write Code That Works?

You know the feeling. It’s 1:00 AM, you’re staring at a screen, and a semicolon—or worse, a subtle logic error—is holding your entire project hostage. Your coffee’s gone cold, and your patience is even colder.

For years, we’ve been hearing the whispers, then the shouts, about AI. “It’s coming for your job.” “It’ll write all the code.” We’ve all used (or fought with) the first wave of assistants. They’re good for boilerplate, maybe a little Stack Overflow copy-pasting, but ask them to understand the architecture of your app? Forget it.

So when the buzz started around Anthropic’s Claude, I was, to put it mildly, skeptical.

Another day, another AI model claiming to be the next revolution.

But the buzz wouldn’t die down. I kept seeing anecdotally impressive examples. Developers I respect were saying things like, “No, you don’t get it… this one feels different.”

My skepticism was battling my curiosity. Curiosity won. I decided to really kick the tires, to put Claude through the wringer not as a tech journalist, but as a developer. I wasn’t interested in marketing demos. I wanted to see if it could handle the messy, frustrating, and complex reality of actual coding.

This isn’t a list of features. This is the story of how I went from rolling my eyes to, well, something a lot like “wow.”

First, Why Bother? What’s Claude’s “Secret Sauce”?

Before we get to the tests, you have to understand why Claude is even in this conversation. It’s not just “another GPT.” Anthropic (the company behind it, founded by ex-OpenAI folks) has been playing a different game.

Their big, flashy feature? The context window.

If you’re not a deep-in-the-weeds AI nerd, “context window” is just a fancy term for “memory.” Most AI models have the memory of a goldfish. You can have a great conversation, but if you ask it to refer to something you said 20 messages ago, it’s gone. Poof.

In coding terms, this is a disaster. You can’t just feed it one 50-line function and expect it to understand your system. A real app is a web of dependencies, inherited classes, environment variables, and style guides.

This is where Claude 3 (and its predecessors) made me sit up straight. We’re talking context windows of 200,000 tokens, and now even reports of 1 million tokens.

In plain English? You can dump your entire codebase (or at least, a massive chunk of it) into the chat. You can upload your package.json, your main App.js, your utils.py, your CSS module, and then ask the question.

It’s the difference between asking a stranger for directions and asking someone who has the entire city map memorized. This, I thought, might actually be a game-changer.

Putting It to the Test: From “Hello, World” to “Oh, Wow.”

I decided to run a gauntlet of tests, starting simple and escalating to the kind of stuff that makes me want to pull my hair out.

Test 1: The Boilerplate Buster

• The Prompt: “Write a simple React component for a contact form. It should include fields for name, email, and message. Use functional components and hooks for state management. Oh, and add basic Formik and Yup validation.”
• The Result: Nailed it. In seconds, I had a clean, modern, and—most importantly—correct React component. It imported useState, set up the initial state, handled the onChange events, and even scaffolded the onSubmit. The Formik/Yup part was the real test, and it structured the validation schema perfectly.
• My Grade: A. (This is the new “table stakes” for AI. I expected this.)

Test 2: The Logic Puzzle (The “Can it think?” Test)

• The Prompt: “I need a Python function. It should take a directory path as input, recursively scan all subdirectories, and find all .log files that have been modified in the last 24 hours. Then, it should compile the contents of these log files into a single combined_errors.txt file, but only include lines that contain the word ‘ERROR’.”
• The Result: This is where things got interesting. It didn’t just dump code. It thought like a developer. It used the osand datetime libraries. It correctly handled time zones (a common pitfall). It used a try...except block for file I/O, which I didn’t even ask for. The code was clean, commented, and it worked on the first run. I sat back and just stared at it for a second. That would have taken me 20 minutes of Googling and testing. It took Claude 10 seconds.
• My Grade: A+. This wasn’t just pattern matching; this was synthesis.

Test 3: The Refactor Nightmare (The “Real Job” Test)

• The Prompt: I uploaded a real, ugly, 300-line function from an old project. It was a monolith of nested ifstatements, mixed concerns, and zero comments. We all have these functions. We all fear them. My prompt: “Refactor this. Make it more efficient, readable, and follow SOLID principles. Specifically, break it up into smaller, single-responsibility functions. And add docstrings, for God’s sake.”
• The Result: This was the moment. It didn’t just add comments. It fundamentally re-architected the logic. It identified three distinct “concerns” within my spaghetti code and broke them out into separate, pure functions. It replaced a messy loop with a more Pythonic dictionary comprehension. It added type hints and full “numpy-style” docstrings explaining what each new function did, its parameters, and what it returned. It even provided a “before and after” summary explaining why it made the changes. It was… beautiful.
• My Grade: A++. I felt a genuine pang of “Oh, this thing is good.”

Test 4: The Vague, Annoying Bug

• The Prompt: “I have a problem. My app feels slow. I’m uploading a 5MB image to my server, and the UI just freezes until the upload is done. How do I fix this? I’m using JavaScript on the frontend.”
• The Result: It didn’t give me one answer; it gave me a strategy. It immediately identified the problem as “synchronous blocking” on the main thread.
  1. The Fix: It explained asynchronous programming and provided a clean async/await example using fetch to handle the upload.
  2. The UI/UX Improvement: It then suggested, “While the upload is happening, you should give the user feedback.” It generated code for a loading spinner that appears when the request starts and disappears on success or error.
  3. The “Next Level” Step: It then added, “For very large files, you might also want to show an upload progress bar.” It provided the code to use the XMLHttpRequest object (or a library like Axios) to listen to onUploadProgressevents and update a progress bar.

It solved my stated problem, then solved the two follow-up problems I hadn’t even asked about yet. This wasn’t a “coder”; this was a “senior developer.”

The Good, The Bad, and The… Weird

After weeks of this, I have a clear-eyed view. It’s not magic, but it’s a hell of a tool.

The Good:

• The Context Window is Everything: Being able to upload my entire API documentation or component library and ask questions about my own code is the single biggest leap in AI coding.
• The Ultimate Pair Programmer: It doesn’t get tired. It doesn’t judge my “stupid” questions. I can “rubber duck” debug with it at 3 AM, and it will patiently talk me through the problem.
• Kills the “Grunt Work”: Writing unit tests. Generating documentation. Refactoring messy code. This is the 50% of our job that we all put off. Claude loves it.

The Bad:

• It Can Be Confidently Wrong: It’s still an AI. It can “hallucinate” a solution that looks perfect but is subtly, fundamentally flawed. It might invent a library function that doesn’t exist. You must still be the senior dev in the room. You are the reviewer, not just a typist.
• Niche Frameworks & Bleeding-Edge Stuff: If you’re working with a brand-new, version-0.2.1 framework, Claude might be just as lost as you are. Its knowledge is vast, but it’s not “up-to-the-minute.”
• Architectural Laziness: It’s so good at fixing your messy code that it can make you a lazy architect. It’s easier to ask Claude to “fix this 500-line function” than to design it properly in the first time. That’s a human trap, not an AI flaw, but it’s real.

So… Are We All Out of a Job?

I have to be honest. After the “Refactor Nightmare” test, I had a brief, cold flash of existential dread.

But the more I used it, the more that feeling faded and was replaced by something else: leverage.

No, Claude is not going to take my job. But it is going to change it. It’s not an engineer; it’s a force multiplier. It automates the drudgery, not the creativity.

It frees me from fighting with syntax and lets me think about the architecture. It handles the “how” so I can focus on the “why.” It lets me prototype an entire idea in an afternoon instead of a week.

The developers who will be “in trouble” are the ones who refuse to adapt. The new critical skill isn’t just writing code; it’s prompting, reviewing, and integrating AI-generated code. Your job is shifting from “bricklayer” to “architect who has a team of tireless, lightning-fast bricklayers.”

I came in a skeptic, ready to write another “AI hype is dumb” post. I’m walking away a believer. Not in a robot uprising, but in the single most powerful tool I’ve ever added to my stack.

It’s not a gimmick. It’s the new normal.