# How to Vibe Code Your Own Final Round AI (and Stop Paying for It)

> AI interview preparation and live assistance platform

- Site: https://finalroundai.com
- Category: AI Career & Productivity
- Platforms: macOS app, Windows app, Web app
- Verdict: **Serious undertaking** (38/100 vibecodeable)
- Estimated effort: 6+ weeks of grueling native systems and audio debugging

## Verdict

Build a personal web-based mock interview coach and resume generator in a few weekends, but expect immense frustration trying to replicate the sub-second live desktop overlay.

The web dashboard, mock interview loop, and prompt generator are straightforward side-project territory. However, building the core 'Stealth Mode' feature—a native desktop overlay that captures system audio, talks to an STT API, queries an LLM, and renders floating text that evades screen-sharing capture on Zoom and Teams—is a brutal systems engineering challenge. If you just want to pass your own interviews, buying a month of the real product is vastly more rational than writing low-level platform overlay code.

### What you can't replicate

- Their viral user acquisition loop and 10 million registered user base
- Battle-tested OS-level window flags that bypass screen-sharing hooks across every corporate meeting platform
- Edge-optimized low-latency audio capture pipelines built for cross-platform audio routing

## What it does

An all-in-one AI interview assistant and prep platform offering mock interviews, resume builders, and a stealth live desktop copilot for real-time answers during video calls.

### Core features

- Web dashboard for resume generation and mock interview configuration
- AI mock interview engine with speech-to-text and simulated persona dialogue
- Native desktop overlay application ('Stealth Mode') running invisibly during video calls
- Real-time audio capture loop streaming interviewer questions to an STT pipeline
- Context-aware LLM prompt router combining user resumes, job descriptions, and live transcripts
- Post-interview analytics tracking speech clarity, engagement, and structure gaps

## The business

### Pricing

- Free Plan: Free — Limited trial tier with restricted session lengths and monthly mock limits.
- Starter / Entry: $25/mo — Annual commitment tier for standard job seekers.
- Monthly Pro: $90-$150/mo — Month-to-month flexibility for active interview loops.

### Funding

$6.88M raised.
- Seed Round (~January 2025)
Investors: Uncork Capital

Founded 2024.
Team size: 11-50.

## The hard parts

- Low-latency audio pipeline: capturing, transcribing, contextualizing, and rendering live answers within 2 seconds without awkward pauses
- Stealth overlay mechanics: creating a translucent native desktop window that stays pinned over full-screen IDEs or browsers without being captured by screen-sharing hooks in Zoom/Teams
- Real-time transcription synchronization and robust noise cancellation in messy conference room audio
- Dynamic prompt engineering fusing dense resume context and coding problem descriptions into structured STAR outputs on the fly

## How to vibe code Final Round AI

### Prerequisites

- macOS / Windows (Free): Required to build and test the native desktop overlay application.
- Node.js (free): Runtime environment for the Next.js web dashboard and Tauri build tooling.
- GitHub (free): Source control and repository hosting.
- Cursor ($20/mo): AI-native code editor for rapid feature iteration.

### Recommended AI tools

- Claude Code: Exceptional at scaffolding full-stack features, database schemas, and complex API integration loops.
- Cursor: Unmatched for day-to-day UI component composition and quick diff reviews.

### Stack

- Frontend: Next.js + Tauri (for the hybrid desktop wrapper shell)
- Backend: Next.js API Routes / Server Actions
- Database: Turso (SQLite at the edge for storing user resumes, session logs, and prompts)
- Auth: better-auth
- Payments: None (personal use clone)
- Other: OpenAI API (Whisper STT + GPT-4o for live response generation), Tailwind CSS

### Hosting

- Vercel (Hosting the Next.js web dashboard and API endpoints): $0/mo
- Cloudflare (Turso database hosting and edge caching): $0/mo

### Build guide

1. **Scaffold Next.js Dashboard and Database Schema** — Initialize a Next.js project with Tailwind CSS, configure Turso SQLite via Drizzle ORM, and set up user authentication using better-auth. Create tables for user profiles, resumes, target roles, and interview logs.

```
Create a new Next.js 16 project with TypeScript and Tailwind CSS. Configure Turso SQLite as the database using Drizzle ORM. Implement better-auth for secure email/password authentication. Create database schemas for users, resumes (storing parsed text and role targets), mock interview sessions, and transcript logs. Ensure clean folder organization with a dashboard layout for managing job profiles.
```

2. **Build the Resume Analyzer & Job Target Setup** — Build an interface where users can upload resumes, paste target job descriptions, and configure their interview persona (e.g., Senior Software Engineer, Product Manager). Integrate an LLM endpoint to parse and structure resume text into actionable context blocks.

```
Build a resume upload and parsing dashboard view in Next.js. Implement file dropzone support for PDF/TXT resumes. Use an AI API endpoint to extract structured sections (experience, core skills, key projects). Add a job description input form that pairs with the resume to build a comprehensive interview context prompt for downstream LLM calls.
```

3. **Develop the AI Mock Interview Simulator** — Implement an interactive mock interview practice mode where the AI asks role-specific questions via text or speech, evaluates user responses using the STAR method, and generates structured feedback reports.

```
Create an AI mock interview practice module. Build a chat-style interface where the LLM acts as an interviewer, asking tailored questions based on the user's uploaded resume and job target. After 5 turns, trigger an evaluation engine that scores the user across speech clarity, engagement, and structure, displaying a detailed breakdown report with actionable improvements.
```

4. **Configure the Tauri Desktop Wrapper Shell** — Set up a Tauri desktop application project wrapping the web dashboard frontend. Configure window flags to create a frameless, transparent overlay window capable of staying pinned on top of other applications.

```
Configure a Tauri v2 desktop wrapper project around the Next.js frontend. Set up native window configuration to create a lightweight, frameless, transparent overlay window that stays always-on-top. Implement hotkeys to toggle visibility so the window remains unobtrusive during development testing.
```

5. **Implement Real-Time Audio Capture and STT Pipeline** — Integrate system audio capture capabilities inside the desktop app, streaming audio chunks to OpenAI Whisper or Deepgram for real-time transcription of incoming interviewer questions.

```
Implement local system audio capture within the Tauri desktop application. Set up a background worker that chunks microphone and system audio streams, sending them to the OpenAI Whisper API in real-time. Display the incoming transcribed text stream in a floating live transcript box inside the overlay window.
```

6. **Build the Live Interview Copilot Assistant Loop** — Wire the live transcript stream into an optimized LLM router that dynamically injects the user's resume context, job description, and the latest question to generate concise, structured bullet-point answers within 2 seconds.

```
Build the live Interview Copilot processing loop. When a new transcribed question arrives from the audio pipeline, combine it with the cached resume and job description context. Send an optimized, low-latency prompt to an LLM endpoint configured for structured JSON output. Display the resulting bullet points, code snippets, or STAR framework answers instantly inside the floating desktop overlay UI.
```

### Cost vs paying

**Starting costs (one-time):**

- Cursor Pro subscription: $20
- Initial LLM & STT API credits: $20
- Total: ~$40 one-time

**Ongoing costs (monthly):**

- Vercel / Cloudflare / Turso free tiers: $0
- Pay-as-you-go LLM/STT usage during interviews: ~$5-15/mo
- Total: ~$10/mo

- Paying for the SaaS instead: $25 - $150/mo
- Build time: 45-60 hours
- AI tool credits: $40 (Cursor Pro + Claude API credits)
- Break-even: 1 month of active interviewing

## Sources

- [Final Round AI Official Website](https://finalroundai.com)
- [Final Round AI $6.88M Seed Funding Announcement](https://www.prnewswire.com/news-releases/final-round-ai-secures-6-88m-in-seed-funding-302345678.html)