Are you VIBE Coding?
Hey fellow coders! Are you VIBE Coding yet? Because I am having a lot of fun doing it. I am glad that I am not stuck in a coding dead end, spending hours on mundane tasks. You might be wondering how? It’s because I am doing Vibe Coding.
"VIBE Coding?" you might ask. Basically, it's like telling your computer what app or feature you want, in regular, everyday language, and it just… builds it for you. That's the vibe! The word Vibe Coding is coined by Andrej Karpathy.
Think of it as moving away from typing out endless lines of code with all those semicolons and brackets, and instead, having a more conversational, back-and-forth flow with an AI. You say, "Make me a simple game where a cat chases a laser pointer," and the AI starts generating the code. It's like having a super-smart coding buddy that gets your ideas instantly.
I’m doing this to:
- Move faster from idea → prototype → MVP.
- Stay in flow without switching mental contexts.
- Let AI supercharge my productivity with intelligent suggestions.
- Experiment and create with joy, not friction.
Who's This For?
Non-Techies: Yep, you heard that right! Tools are popping up that let people who've never written a line of code create simple apps or games by just describing what they want.
Developers: Even for pros, this is a game-changer. AI becomes your coding partner, helping with prototyping, UI design, and even debugging. It's like having a full-stack assistant right in your code editor.
Now you might be wondering how Amazon Q came into picture, right?
How to VIBE Code with Amazon Q CLI?
Amazon Q CLI is your new dev bestie on the terminal. It’s the developer companion CLI tool from AWS, and it’s not your average command-line utility. This one comes supercharged with generative AI, powered by the same tech that’s redefining how we write, think, and build. It’s like having an LLM-powered engineer sitting beside you on your terminal — helping you write, debug, and understand AWS workflows and code.
That’s what Amazon Q CLI brings to the table. It’s like combining the power of AWS with the intuition of a senior cloud engineer, all through natural language.
Installation & Prerequisites
To start VIBE Coding, let’s get your setup ready. It’s super simple and should take just a few minutes.
Step 1: Install AWS CLI (if you haven’t)
Head over to the official AWS website and download the CLI for your OS (Windows, macOS, Linux). Refer this to install AWS CLI: https://docs.aws.amazon.com/cli/v1/userguide/cli-chap-install.html
Step 2: Configure AWS CLI
Once you have installed AWS CLI, verify and configure AWS CLI. You’ll be prompted to enter:
- AWS Access Key ID
- AWS Secret Access Key
- Region
- Output format (choose json or yaml)
Step 3: Install Amazon Q CLI
Amazon Q CLI doesn’t have a native Windows version yet, but you can still use it on Windows through WSL (Windows Subsystem for Linux).
Install WSL: Follow https://learn.microsoft.com/en-us/windows/wsl/install to enable WSL on your machine.
Install Ubuntu: Get it from the Microsoft Store or via CLI
- Download & Install Amazon Q CLI for Linux: Use the official Linux zip package inside WSL. Refer to https://docs.aws.amazon.com/amazonq/latest/qdeveloper-ug/command-line-installing.html for details.
Configure AWS Login
Inside WSL, run: “q login”. Here select “Use for Free with Builder ID”. If you do not have Builder ID yet create it using your email.
Now you have to confirm the code in the browser by manually opening the link.
Once you confirm the code in the browser, you will have to allow the access to Amazon Q.
After allowing you will see this window. Congratulations, you have successfully downloaded Amazon Q CLI and are able to use it now.
Let's Build an App with Amazon Q CLI
Now that we have installed Amazon Q CLI, let's build an amazing project. Let’s create an application that gives FinOps best practices for different AWS Services.
Step 1: Type “q chat” command.
Step 2: Write your prompt and enter “y” to continue.
Step 3: It has created an “index.html” file and stored it in the folder. Type “y” to continue.
Step 4: It has created a “style.css” file and stored it in the folder. Type “y” to continue.
Step 5: It has created a “script.js” file and stored it in the folder. Type “y” to continue.
Step 6: It has also created a read.me file. Type “y” to continue
*Step 7: I have asked to deploy the app on AWS. *
There was some error while creating S3 Bucket. But it corrected automatically.
It has configured public access settings.
It has uploaded all the files into the bucket.
Step 8: FinOps app is successfully deployed on AWS
Step 9: Lets delete our resources so that we are not charged for this.
Later, I have also asked to create a read.me of all that we have done to keep record of it. I have also asked to create an architecture diagram of this. Although it has not created the diagram using AWS icons, the gist was correct.
So what are you waiting for? Go on and create your application using Amazon Q CLI. But there are few tips and tricks that you need to keep in mind while working with Amazon Q CLI.
Tips and Tricks
While Amazon Q CLI offers a powerful interface for generating code and managing AWS workflows, its effectiveness depends heavily on how you interact with it. Here are some best practices to help you make the most of the tool:
- Prompt Engineering: Be Specific and Clear
The quality of the output is directly related to the quality of your input. The more context you provide in your prompts, the better the quality of the code or explanation you receive.
For example:
- Better Prompt: Generate a Python Lambda function that writes user data to a DynamoDB table named 'users', with error handling and input validation.
- Poor Prompt: Make a Lambda for database.
By specifying the language, purpose, service involved, and additional constraints, you’re more likely to get a relevant, usable result.
- Troubleshooting: Use Q CLI as a Diagnostic Tool
When something breaks, there are a few different ways to approach the issue:
Prompt Q CLI with your error
You can paste AWS errors or logs and ask Q CLI for help diagnosing the issue.
Example:
Why is my Lambda function getting AccessDenied when writing to DynamoDB?
Cross-reference with AWS Documentation
While Q CLI provides useful output, always validate commands and recommendations against the official AWS documentation for production use.
Community Support
If you're stuck, explore AWS Developer Forums, GitHub issues, or Stack Overflow. These resources are valuable for resolving edge cases and getting community-validated solutions.
Precautions and Considerations
Not gonna lie - Amazon Q CLI is impressive. It’s fast, smart, and makes you feel like you have an LLM-powered intern who never takes breaks. But let’s keep it real for a second...
Is it perfect?
Nope. Not yet.
And maybe that’s a good thing - because we’re not just shipping anything. We’re shipping quality. And even though the AI might write code that runs, there are still some critical areas where you, the human dev, are irreplaceable.
Let’s break it down
1. Review: Always Read What the AI Writes
Amazon Q might generate a Lambda function, a policy, or an S3 command - but it doesn’t mean it’s 100% optimal.
- Does the logic actually match your use case?
- Is it readable, maintainable, or overly verbose?
- Does it align with your coding style?
Human review is non-negotiable. Treat AI like an eager intern. Smart, helpful, but not ready to commit directly to main.
2. Testing: Code That Runs ≠ Code That’s Reliable
Yes, it might deploy.
Yes, it might return a response.
- But does it handle edge cases?
- Does it break when inputs are unexpected?
- Did it cover retries, failures, timeouts?
You still need:
- Unit tests
- Integration tests
- Manual poking (aka: break things on purpose)
VIBE Coding is not "vibe & hope." It's "vibe & verify."
3. Security: Is It Safe to Use in Prod?
AI-generated IAM policies might be too permissive. Your Lambda code might forget to validate input or sanitize data. And don’t get me started on secret keys in code.
Security isn’t just about firewalls. It’s about:
- Principle of least privilege
- Input validation
- Data encryption
- Logging & monitoring
VIBE Coding without security = chaos in production.
4. Scalability: Will It Break Under Load?
Sure, Q CLI can spin up a basic app. But will that app:
- Handle 1000 concurrent users?
- Scale when traffic spikes?
- Handle retries gracefully under pressure?
Scalability is an architecture mindset, not just code.
Ask Q CLI to help with autoscaling or load balancing - but you need to know when and how to use those answers.
5. Debugging: When AI Code Goes Sideways
Let’s be honest: AI-generated code will break sometimes. Maybe the logic’s wrong. Maybe the syntax is off. Maybe it just… doesn’t work.
Now what?
Two options:
- Fix it manually (classic dev style)
- Prompt the AI smarter (next-gen dev style)
The new dev skill isn’t just writing code - it’s crafting good prompts, and understanding the answers.
The Future of VIBE Coding and Amazon Q CLI: What's Next?
The future is bright! As AI continues to evolve, we can expect even more powerful coding tools. Imagine AI that can design entire applications or write complex algorithms with a single command.
VIBE Coding with Amazon Q CLI is more than just a trend; it's a paradigm shift in how we write code. Embrace it, experiment with it, and expand your coding potential!
SOCIAL SHARE CARD GENERATOR