Whisper.cpp app nails alignment, rendering

This is where the project stops looking like a transcript toy and starts looking like a serious subtitle production pipeline.

• –Forced alignment with roughly 10–20 ms timing is the standout; that’s the part most transcription tools still treat as “good enough.”
• –Styled rendering, transparent alpha output, and overlay/MOV export make it useful for editors and post-production, not just SRT generation.
• –The product’s moat is shifting from speech recognition to output control: speech-to-text gets you in the door, but visual fidelity is what makes it stick.
• –The biggest constraint now is not engineering, it’s founder bandwidth and monetization strategy; a free-only promise limits options unless donations or sponsorships appear.
• –If it stays bootstrapped, the cleanest path is probably a narrow, high-value niche with strong community pull rather than a generic transcription-app arms race.