Introduction

Have you ever wished you could quickly grasp the key points of a lengthy YouTube video without watching the entire thing? That’s exactly the problem I set out to solve with FastForward IQ. In this article, I’ll take you on a journey through the creation of my MVP (Minimum Viable Product) that summarizes YouTube videos. Whether you’re a fellow developer looking to build your own SaaS product or just curious about the process, I hope you’ll find some valuable insights here.

Table of Contents

What is FastForward IQ?

FastForward IQ is a web application that uses AI to generate concise summaries of YouTube videos. Here’s how it works:

1. Users paste a YouTube video URL into the app.
2. FastForward IQ fetches the video transcript using the YouTube API.
3. The transcript is processed by an AI model (currently Claude) to generate a summary.
4. Users receive a concise summary of the video’s key points.

This tool is particularly useful for:

• Students needing to quickly grasp lecture content
• Professionals staying updated on industry talks
• Anyone wanting to decide if a longer video is worth their time

You can try it out yourself at FastForwardIQ.com - new users get 10 free summaries to start!

The Tech Stack: Why These Choices Matter

1. Next.js: The Swiss Army Knife of Web Development

When it came to choosing a framework, Next.js was a no-brainer. It’s like the Swiss Army knife of web development – versatile, powerful, and packed with features that make both frontend and backend development a breeze.

Here’s a peek at how I structured my pages:

// On the landing page (index.js)
const Home: NextPage = () => {
  return (
    <LandingLayout>
      <Hero />
      <Features />
      <WhyUs />
      <HowItWorks />
      <UseCases />
      <CallToAction />
    </LandingLayout>
  );
}

// On the dashboard page
const DashboardPage: NextPage<DashboardPageProps> = ({ user }) => {
  if (!user) {
    return null; // This shouldn't happen due to redirect in getServerSideProps
  }

  return (
    <AppLayout>
      <Dashboard />
    </AppLayout>
  );
};

This structure allowed me to clearly separate the public-facing landing page from the user dashboard, making the codebase more manageable as the project grows.

2. DaisyUI: Because Life’s Too Short for Ugly UIs

Let’s face it – building a beautiful UI from scratch is time-consuming. Enter DaisyUI, a plugin for Tailwind CSS that’s like having a professional designer on your team. It allowed me to create a sleek, responsive interface without getting bogged down in CSS details. For a solo developer or a small team, this kind of efficiency is gold.

3. NextAuth.js: Simplifying the Authentication Maze

Authentication is often a pain point in web development, but NextAuth.js made it surprisingly painless. I implemented both magic link sign-ups and Google login, giving users flexible options without spending weeks on security implementations.

Here’s a simplified version of my NextAuth setup:

import NextAuth from 'next-auth';
import Providers from 'next-auth/providers';

export default NextAuth({
  providers: [
    Providers.Email({
      server: process.env.EMAIL_SERVER,
      from: process.env.EMAIL_FROM,
    }),
    Providers.Google({
      clientId: process.env.GOOGLE_CLIENT_ID,
      clientSecret: process.env.GOOGLE_CLIENT_SECRET,
    }),
  ],
  // Additional configuration...
});

Pro tip: If you’re interested in a deep dive into NextAuth, check out my detailed article: Authentication in Next.js with NextAuth

4. Prisma + PostgreSQL: A Dynamic Duo for Data Management

For data persistence, I chose the dynamic duo of PostgreSQL and Prisma. Prisma’s type-safe queries have saved me from countless potential bugs, making database operations feel almost too easy.

Here’s a snippet of my Prisma schema:

model User {
  id             Int       @id @default(autoincrement())
  email          String    @unique
  summariesUsed  Int       @default(0)
  summariesLeft  Int       @default(10)
  // Other fields...
}

model Summary {
  id        Int      @id @default(autoincrement())
  videoId   String
  content   String
  userId    Int
  user      User     @relation(fields: [userId], references: [id])
  // Other fields...
}

This setup allows me to easily track user activity and manage summaries, providing a solid foundation for future features.

5. AWS SES: Ensuring Your Emails Actually Arrive

For transactional emails, I integrated Amazon Simple Email Service (SES). It’s like having a reliable postal service for your app – ensuring that important communications (like those magic login links) actually reach your users.

Here’s a peek at my email sending service:

import { SESClient, SendEmailCommand } from "@aws-sdk/client-ses";
import * as handlebars from "handlebars";

// ... (SES client setup)

interface SendEmailOptions {
  from?: string;
  to: string;
  subject: string;
  text?: string;
  html?: string;
  htmlTemplate?: string;
  templateData?: any;
}

export async function sendEmail(options: SendEmailOptions): Promise<void> {

  // Email building logic

  await ses.send(new SendEmailCommand(params));
}

This setup allows for flexible, template-based emails that are crucial for user engagement and authentication.

The Core Feature: YouTube Video Summarization

Now, let’s talk about the star of the show – the video summarization feature. This is where things get really interesting (and a bit challenging).

Currently, I’m using the YouTube API to fetch video information and transcripts. These transcripts are then fed into Claude, an AI model, to generate summaries. However, I’m constantly exploring ways to improve this process:

1. API Exploration: I’m looking into using Llama 3.1 (either the 405b or 70b model) as an alternative to Claude. The key question here is whether a smaller context size could still provide high-quality summaries, potentially improving performance and cost-efficiency.

2. Redundancy Planning: To ensure reliability, I’m considering implementing a fallback mechanism. The idea is to have two different APIs available, so if one fails, the system can automatically switch to the other. This kind of redundancy is crucial for maintaining a smooth user experience.

3. Continuous Improvement: The world of AI and natural language processing is evolving rapidly. Staying updated with the latest models and techniques is an ongoing process, and I’m excited to see how it will enhance FastForward IQ’s capabilities.

The Business Side: User Quotas and Future Plans

Currently, new users receive 10 free summaries upon sign-up. This quota system serves two purposes:

1. It allows users to experience the value of the service without any upfront commitment.
2. It provides me with valuable usage data to inform future business decisions.

Looking ahead, I’m considering a few options:

• A credit system where users can purchase summarization credits
• A monthly subscription model, possibly with rollover for unused credits
• A combination of both, catering to different user needs

The goal is to find a balance that provides value to users while ensuring the sustainability of the service.

Deployment: Keeping It Simple and Scalable

For deployment, I’m using a VPS (Virtual Private Server) with Dokku. This setup gives me the flexibility of a cloud platform with the cost-effectiveness of a VPS. If you’re interested in the nitty-gritty of this deployment process, check out my article: Deploying Next.js to a VPS Using Dokku

Challenges and Solutions

Building FastForward IQ wasn’t without its hurdles. Here are a few challenges I faced and how I overcame them:

1. Handling Long Transcripts: Some YouTube videos have extremely long transcripts that exceed the token limits of AI models. To solve this, I implemented a chunking system that breaks long transcripts into smaller, manageable pieces and then combines the summaries.

2. API Rate Limits: Both the YouTube API and AI model APIs have rate limits. I implemented a queueing system to manage requests and avoid hitting these limits, ensuring a smooth user experience even during high traffic periods.

3. Balancing Accuracy and Speed: Users want accurate summaries, but they also want them quickly. I’m constantly tweaking the prompts and exploring different AI models to find the right balance between summary quality and generation speed.

Conclusion: Lessons Learned and The Road Ahead

Building FastForward IQ has been an exciting journey, full of learning experiences:

1. MVP Mindset: Starting with a core feature and gradually expanding has allowed me to validate the concept without overcommitting resources.

2. Flexibility is Key: Choosing a flexible tech stack like Next.js has made it easier to adapt and evolve the product as I learn more about user needs.

3. User Feedback is Gold: The free quota system isn’t just a business model – it’s a valuable source of user insights that will shape the future of FastForward IQ.

4. Continuous Learning: From exploring new AI models to considering different business models, this project is a constant learning process.

As FastForward IQ evolves, I’m excited about the possibilities. Whether it’s implementing new summarization techniques, exploring different pricing models, or adding new features, the journey is far from over.

Have you built an MVP recently? Or perhaps you’re in the planning stages? I’d love to hear about your experiences and insights in the comments below. And if you’re curious about trying FastForward IQ, give it a spin and let me know what you think!

Remember, every big idea starts with a small step. So if you’ve got a project in mind, take that first step – you never know where it might lead!