DEV Community: Yash oberio

I Built a Haunted Spirit Board That Talks Back (Hacktoberfest Week 4)

Yash oberio — Tue, 27 Oct 2026 13:20:15 +0000

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 4: Ghost in the Machine

What I Built

I built Spooky Spirit Board — a browser-based AI horror experience that lets users summon a virtual ghost and ask it questions.

The idea was to bring the classic spirit-board experience into the browser using AI, eerie background sounds, and creepy voice effects.

Press Summon, ask a question, and see what the spirit has to say. 👀

The goal was to create something more atmospheric than a regular chatbot — a small AI experiment that feels like a supernatural encounter.

Demo

🌐 Live Demo: https://www.machinehaunted.tech/

🎥 YouTube Walkthrough: https://youtu.be/4dIK9k4LRrc

Code

yashexc2002 / spooky-spirit-board

This is a Next.js project bootstrapped with create-next-app.

Getting Started

First, run the development server:

npm run dev
# or
yarn dev
# or
pnpm dev
# or
bun dev

Open http://localhost:3000 with your browser to see the result.

You can start editing the page by modifying app/page.tsx. The page auto-updates as you edit the file.

This project uses next/font to automatically optimize and load Geist, a new font family for Vercel.

Learn More

To learn more about Next.js, take a look at the following resources:

Next.js Documentation - learn about Next.js features and API.
Learn Next.js - an interactive Next.js tutorial.

You can check out the Next.js GitHub repository - your feedback and contributions are welcome!

Deploy on Vercel

The easiest way to deploy your Next.js app is to use the Vercel Platform from the creators of Next.js.

Check out our Next.js deployment documentation for more…

View on GitHub

How I Built It

I built this project using a lightweight, browser-based AI approach:

Framework: Next.js, React, TypeScript, and Tailwind CSS.

AI Framework: Transformers.js.

AI Model: Xenova/LaMini-Neo-125M.

Inference: Web Workers keep model processing separate from the main UI thread.

Audio: Web Audio API for the creepy atmosphere and sound effects.

Deployment: Vercel with a custom .tech domain.

Why Does Open Innovation Matter?

Open-source AI gave me the freedom to experiment with models and customize how the ghost behaves without depending on a hosted, closed-model chat API for every response.

Running inference in the browser also made this project a fun experiment in client-side AI.

I could change the model, tune the generation settings, and build my own response-handling logic. The trade-off was clear: smaller models are faster for this experiment, but they don't always generate reliable answers.

Open innovation gave me the flexibility to experiment, learn from failures, and build something creative with the tools available.

The Spirit of It

A normal chatbot answers questions. I wanted this one to make you hesitate before asking the next question.

Combining AI, sound effects, and a dark atmosphere turned a small web development experiment into something much more fun to build.

The machine isn't haunted. At least, that's what I keep telling myself.

Give it a try — if you dare!

Prize Categories

I'm entering the Best Use of a .tech Domain category, provided my domain meets the challenge's eligibility requirements.

🌐 https://www.machinehaunted.tech/

🦥 I Built "Bed-Rot Coder" to Write Code Without Leaving My Bed (Hacktoberfest)

Yash oberio — Fri, 23 Oct 2026 21:24:55 +0000

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady

What I Built

I built the Bed-Rot Coder—a voice-first, local AI coding agent designed for the ultimate lazy weekend. Why sit at a desk when you can code from your bed?

Bed-Rot Coder allows developers to embrace "bed-rotting" without sacrificing their side-hustles. You simply press a button on your phone or laptop, speak your logic (e.g., "Create a Python script to check if a number is even or odd"), and the AI transcribes your voice, processes the prompt, and streams the generated code directly to a sleek, dark-mode web console. No typing, no IDE setup, just pure, lazy productivity.

Demo

Code

yashexc2002 / bed-rot-coder

Markdown

🦥 Bed-Rot Coder

Speak your code. Stay in bed.
A Next.js full-stack voice-to-code AI agent for Hacktoberfest.

🛌 The Concept: "Slow and Steady" Theme

Why should you even work on a desk? Bed-Rot Coder was developed for developers that want to enjoy "bed-rotting" while still maintaining productivity. All you have to do is to hit record, speak out your logic (for example, "Write a python script that calculates Fibonacci sequence"), and an AI will transcribe your voice, process your logic and produce your code within a sleek dark-mode console webpage.

✨ Features

🎤 Voice-First User Interface: No typing needed. Click, speak, and stop.
⚡ Webpage-First Approach: No need to store anything locally. Code is displayed right away on the UI.
🧠 Agentic AI Logic Processing: The Mastra Agent framework with Google Gemini (Flash) AI.
🗣️ Accurate STT Integration: Integrates with ElevenLabs scribe_v1 for perfect transcription of speech.
…

View on GitHub

How I Built It

I built this project using a modern, fast tech stack centered around open-source AI frameworks:

Agent Framework: Mastra (@mastra/core) orchestrated the entire AI logic.
LLM Engine: Google Gemini (gemini-1.5-flash) via the Vercel AI SDK.
Transcription: ElevenLabs JS SDK (scribe_v1) for flawless Speech-to-Text.
Frontend/Backend: Next.js 16.4.3 (Turbopack), TypeScript, and Tailwind CSS.

The Architectural Pivot:
Initially, I forced the Mastra agent to use a write_file_tool to save the generated code locally. However, this caused massive latency (sometimes hanging for 10+ minutes) and unnecessary agent looping. I performed a surgical "Webpage-First" pivot: I removed the disk-writing dependency, set the Mastra agent to maxSteps: 1 to prevent loops, and streamed the output directly to the UI. I also downgraded from gemini-3.8-flash to gemini-1.5-flash to gracefully handle Free Tier rate limits (429 errors).

Why Does Open Innovation Matter?

Open innovation was the only reason I could fix my latency issues. Because Mastra is an open-source framework, I wasn't locked into a black-box workflow. When I realized the disk-writing tool was slowing down my agent, I was able to inspect the agent's harness, completely rip out the tool, and re-wire the core loop to a single-step inference (maxSteps: 1).

An open-based approach allowed me to swap models instantly when I hit quota limits and completely customize how my agent behaves locally, keeping the processing fast and free.

The Lazy Payoff

This project took my coding friction from 100% down to 10%. By squashing the initial 15-minute wait-time bug down to a 2-second generation time, I no longer have to get out of bed to test a quick logic idea. I actually used it this week to generate basic Next.js API boilerplates while literally laying down. Just click, speak, copy, and sleep!

Prize Categories

I am submitting this project for the following partner categories:

Best Use of Mastra (Used @mastra/core to orchestrate the AI agent logic and prompt execution)
Best Use of ElevenLabs (Used the JS SDK and scribe_v1 to give the agent flawless voice-transcription capabilities)****