How I Coded ANOTHER Profitable App SOLO (step by step / from scratch / with AI)

Developed a tool that allows bulk downloading of video transcripts from YouTube channels or playlists. The purpose is to utilize YouTube video text data for training custom AI models.

Market research revealed competitors like YouTube Transcript.io exist, but a clear demand was confirmed with over 350,000 users. The strategy is to differentiate with a simpler pricing model and a cleaner UI.

Instead of an MVP (Minimum Viable Product), the SLC (Simple, Lovable, Complete) framework was adopted. The goal is to create a complete version 1.0 that provides value from day one.

The tech stack used is React, Next.js, Supabase, and Stripe. The AI tool Tempo was leveraged for setup, completing initial configurations that usually take several hours in under 10 minutes.

Tempo assists with documenting product requirements, UI generation, and code generation. The entire project can be managed across three tabs: Product, Design, and Code, with capabilities like importing Figma designs and generating code.

The launch strategy involved approaching target customers directly on niche subreddits and forums, in addition to common platforms like Product Hunt, Hacker News, and Twitter.

The opinion is that Product Hunt is not suitable for most indie hackers because it's a platform primarily for other founders, not general users. However, it offers value in terms of SEO backlinks and increased traffic.

The launch didn't go as viral as hoped, but it garnered 13 sign-ups and 6 paying customers. Revenue exceeded £200, proving that customers are willing to pay for the product.

Emphasized the value of sharing a realistic launch experience rather than an overnight success story, advocating for the importance of perseverance even without immediate results.

Moving forward, the focus will be on product improvement and growth, with the entire process planned to be documented and shared.