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I Built a Sci-Fi "Universal Translator" for the 2026 Hackathon

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The Problem: Why Do Translators Sound So... Dead? 💀 We’ve all used translation apps. You pour your heart out, say something meaningful, and the app spits back a robotic, monotone voice that sounds like a GPS from 2005. The vibe? Instantly killed. For the 2026 Hackathon , I wanted to build something different. I didn't want a tool that just swaps words; I wanted an agent that understands context and speaks with feeling . Meet LingoVoice AI .  The Tech Stack: The Best of Both Worlds   To build a "Next Level" agent, I needed the best tools for two specific jobs: The Brain (Context): Lingo.dev . Most APIs just translate text literally. Lingo.dev understands context , technical jargon, and cultural nuance. The Voice (Emotion): Murf AI Gen2 . These aren't standard text-to-speech voices. They breathe, pause, and have specific accents (like Enrique for Spanish or Baolin for Chinese). But there was a catch.   My backend logic was in Python (Flask) . The Lingo.dev SDK is...
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10 Voice Agents in 10 Days: How I Survived the Murf AI Challenge

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They say thousands start, but only a few finish. Specifically, in the Murf AI Voice Agents Challenge , only 321 builders crossed the finish line. I just became one of them. For ten straight days, I committed to "building in public." My goal wasn't just to make Hello World demos; I wanted to push the boundaries of what real-time Voice AI can do building agents that remember context, handle complex business logic, and recover gracefully when APIs fail. Here is a breakdown of my journey, the technical hurdles I overcame, and why consistency is the ultimate engineering skill. 🚀 The Mission The challenge was simple but grueling: Build 10 functional AI Voice Agents in 10 days. My toolkit: Voice: Murf Falcon (for ultra-low latency TTS). Brain: Google Gemini (for reasoning and intent extraction). Frontend: LiveKit / Custom React UIs. Backend: Python (Flask/FastAPI). Here is how my architecture evolved from simple scripts to complex, fault-tolerant systems. Phase 1: Foundati...
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🧠 How I Built a Sudoku Game Using Amazon Q CLI — With Just Prompts!

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What happens when you mix a strong idea with a smart AI CLI? You get a fully working game — without writing a single line of code yourself. Here's how I, Kavya Trivedi , built a complete Sudoku game using Amazon Q CLI , step by step. 🚀 Quick Links 🎥 Watch the Game in Action 📦 View the Source Code on GitHub 📲 See the LinkedIn Carousel Post 💡 Why I Built This As a developer passionate about trying emerging tools, I, Kavya Trivedi , recently explored Amazon Q CLI , a GenAI-powered CLI by AWS that helps developers build applications with natural language. I was curious: Could I actually build something real — like a game — just by describing it? Could GenAI handle logic, UI, and interactivity? So I put it to the test. The result? A complete Sudoku game — no manual coding required. ⚙️ Setup Phase — The Toughest Part Getting started with Amazon Q CLI wasn’t easy. I spent nearly 2 hours setting things up — here's what I did: Signed up for an AWS Builder ID ...
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