DEV Community: Fame

I’m Building a Cozy Ambience App in React (Sounds, Presets & Chat)

Fame — Thu, 07 May 2026 16:55:51 +0000

I’ve been building a cozy ambience app with React. The idea started pretty simple: a space where you can mix ambient sounds like rain, wind, coffee shop noise, and fire crackling to help you focus or relax while working or studying. Over time, it started evolving into something more interactive and structured than I originally planned.

Right now it’s still early (around 5–10% done), but the core experience is already forming. It’s not meant to be a heavy productivity tool or anything overly complex. The focus is more on mood — creating a calm, minimal environment that feels slightly immersive and easy to stay in.

The main system so far is the ambient sound engine. Each sound runs independently, and you can adjust volumes in real time to build your own mix. On top of that, I’ve added a preset system, which lets you save and switch between different ambient setups. So instead of manually tuning everything every time, you can quickly switch between different moods like focus, sleep, chill, or whatever you create yourself.

The UI is split into a main ambience area and a side panel where presets, controls, and future features live. The design direction is soft and slightly glassy, aiming to avoid anything harsh or distracting, keeping the focus on the atmosphere itself rather than the interface.

I also started experimenting with real-time weather integration. The idea is to subtly influence the ambience based on the user’s environment, so the soundscape feels more connected to what’s happening outside. It’s still not fully refined, but it adds an interesting dynamic layer to the experience.

More recently, I added a basic chat system. It wasn’t part of the original plan, but I wanted to explore adding a lightweight interaction layer inside the app. It’s not meant to turn it into a social platform — more like a quiet, optional space where interaction exists without breaking the mood.

On the technical side, audio handling is fully client-side using React state and refs. Each sound has its own instance and volume control, which works well for now, but will likely need restructuring as the project grows. I’ve also started moving toward proper database querying instead of frontend filtering so the system stays scalable as features stack up.

One thing this project has made clear is how quickly “vibe-based” apps become complex under the hood. Even small things like smooth audio blending, transitions, and UI softness matter a lot if the goal is to create a calm, usable experience instead of something cluttered.

It’s also been a lesson in not overengineering too early. A lot of the initial work was trying to design everything upfront, but the project has naturally evolved as I build it step by step.

Next steps are improving the preset system so it feels even smoother to create and switch environments, refining the chat feature, adding custom sound uploads, and polishing the overall UI and flow. The long-term goal is to create a space that you can open anytime and instantly feel a shift in mood — something simple, calm, and consistent.

I'm 14 and I'm Building a Desktop API Client with a Built-in AI Panel — Here's Where I'm At

Fame — Mon, 06 Apr 2026 10:21:01 +0000

I'm 14 and I'm Building a Desktop API Client with a Built-in AI Panel — Here's Where I'm At
I've been coding for 8 months. Self-taught, no bootcamp, no CS degree. Just me, my laptop, and way too many late nights.
I had a simple idea: what if your API client had an AI assistant built directly into it? Not a browser extension, not a separate tab — just right there while you're testing endpoints. You send a request, something breaks, you ask the AI panel without ever leaving the app.
That's PingPaddle. And I'm currently 45% of the way through building it.

The Stack

Electron + React + Vite for the desktop app
Node.js + Express for a CORS proxy backend
Python + FastAPI for the AI backend
Groq API for the AI model
CodeMirror + Prism for syntax highlighting

What's Built So Far
The core client

Color-coded HTTP method dropdown — GET, POST, PUT, DELETE, PATCH each have their own color so you can glance and know
Full request builder with headers, body, params
Status / time / size indicators on every response

Response analytics

Live response speed chart — tracks ms across requests with a smooth curve
Response size tracker alongside it
Both visible at a glance, no digging through menus

(screenshot above — that chart is fully working)
Response viewer

Syntax-highlighted JSON and HTML responses
Large HTML responses load in a sandboxed iframe instead of nuking the viewer
Tabbed response headers viewer alongside the body

Request history

Every request logged with method, URL, and status code
Color coded — green GET, the works
Searchable and re-loadable

(screenshot above — history panel in action)
CORS proxy

Runs on localhost:3000/proxy so browser-side restrictions don't block you
Built with Express, handles the boring stuff so you don't have to

The AI panel

Groq-powered chat sidebar baked directly into the app
You're mid-request, something's off, you just ask — no context switching, no tab hopping

What's Still in Progress

Collections and saved requests
Environment variables
A scroll-driven panel transition using Framer Motion that I have fully mapped out in my head — it's going to look clean
General polish and stability

I’m 14 and Building My Own API Client — Now 25% Complete with AI Integration and Performance Insights

Fame — Tue, 31 Mar 2026 12:48:34 +0000

I’m 14, and over the past months I’ve spent a lot of time exploring API tools. They’re powerful and widely used, but I kept feeling the urge to build something that was truly mine — a tool designed around how I think about APIs, requests, responses, and performance.

Using existing tools taught me a lot, but building my own taught me even more.

So I started creating my own API client from scratch.

Why I Started Building My Own Tool

While working with APIs, I realized that sending requests is only part of the process. Understanding what happens behind the scenes — headers, cookies, response timing, and payload sizes — is where the real learning happens.

I wanted:

Full control over the workflow
A deeper understanding of HTTP behavior
A tool that I could experiment with and improve continuously
A platform to integrate new ideas like AI assistance and performance visualization

That curiosity pushed me to start building my own client instead of relying entirely on pre-made tools.

Current Progress — 25% Complete

Right now, the project is about 25% complete, and it already supports a strong set of core features. Reaching this point has taken a lot of testing, debugging, and iteration.

Even at this stage, the client can already handle many essential API tasks reliably.

What My API Client Can Do Right Now
Core Features
Sending HTTP requests (GET, POST, PUT, DELETE, etc.)
Handling request bodies and parameters
Parsing JSON and HTML responses
Viewing and managing headers
Cookie handling and inspection
Request and response history tracking
Measuring request time and response size
Displaying detailed response information

These features help me understand exactly what’s happening during each API call instead of just sending requests blindly.

AI Integration — Making Responses Easier to Understand

One of the most exciting parts of the project is the AI integration.

Instead of showing only raw technical data, the client can explain what the response means in simple language.

How It Works
A request is sent to an API
The server returns a response
The response data is processed
The AI analyzes the response
A human-readable explanation is generated

This turns technical output into something easier to understand, especially for beginners learning APIs.

Performance Insights and Planned Visualizations

Another area I’m focusing on is performance visibility.

Right now, the client already tracks:

Request duration
Response size
Data transfer details

Next, I plan to add:

Graphs for response time trends
Request size comparisons
Data usage monitoring
Performance pattern detection

These features will make it easier to spot slow endpoints, large payloads, or unusual behavior.

Challenges I Faced While Building This

Building this project hasn’t been easy, and that’s what made it valuable.

Some of the biggest challenges included:

Parsing different response formats (JSON, HTML, text)
Managing cookies and headers correctly
Designing a clean and responsive interface
Handling errors and edge cases
Keeping the application stable while adding new features

Every problem forced me to learn something new.

Why Building This at 14 Matters to Me

Starting early gives me time to experiment, fail, and improve.

At 14, I don’t have pressure to make everything perfect. I can:

Try new ideas
Build ambitious projects
Learn from mistakes
Develop problem-solving skills
Understand real-world systems

This project isn’t just about coding — it’s about learning how software works from the inside.

What’s Next

The roadmap ahead is exciting.

Planned improvements include:

Interactive performance graphs
Expanded AI capabilities
Better UI and usability
More request automation features
Stability and performance optimizations

I also plan to release the tool publicly, gather feedback, and continue improving it based on real user experiences.

Building My Own API Client at 14: From Requests to AI-Powered Insights

Fame — Fri, 27 Mar 2026 14:20:27 +0000

Building My Own API Client: Why I Did It

I’m 14, and I’ve already spent a lot of time exploring API tools like Postman, Hoppscotch, Insomnia, and more. While they’re all powerful and useful, I wanted something that was truly my own. Using pre-made tools is great, but I often felt limited by their design and workflow. I wanted a tool that reflects how I think about APIs, handle requests and responses, and analyze data in ways that make sense to me. That curiosity and need for control inspired me to start building my own API client from scratch.

What My API Client Can Do

Even at this early stage, the client already supports a lot of features. It handles cookies, request bodies, JSON data, headers, parameters, HTTP methods, and keeps a history of all requests and responses. It also measures request and response size and timing, giving detailed insights into API performance. This makes it easier to understand exactly what’s happening behind the scenes with each API call, instead of just sending requests blindly.

Planned Features and Visualizations

The project is currently about 20% complete, but the roadmap is exciting. I plan to add interactive graphs to visualize request size, response speed, and data capacity, so performance trends are easy to spot. I’m also integrating AI features that can automatically explain responses, suggest smart autofills for requests, and guide users through complex endpoints. The goal is to make API testing and exploration faster, smarter, and more intuitive.

Why Build It at 14

Building a project like this at 14 has been an amazing learning experience. It gives me a head start in understanding web development, API design, and performance optimization. Each bug, limitation, or challenge is an opportunity to improve my problem-solving skills and creativity. Starting early means I can experiment freely, try new ideas, and learn faster than if I waited.

Looking Forward

This API client is more than just a tool—it’s a platform for learning, experimenting, and pushing the limits of what I can create at my age. I’m excited to keep developing it, adding features, improving performance, and eventually having a full-fledged client that I can truly call my own. It’s a journey that’s teaching me so much about coding, design, and problem-solving, and it’s only just beginning.

I'd love to hear your thoughts — whether it's feedback on the features, suggestions for what to build next, or just your experience with API tools in general. Drop a comment below, it genuinely helps me improve. And if you're curious to try it out, stay tuned — PingPaddle is coming soon.