Stories, craft notes, and engineering deep-dives from the team.
The build log of a tool that turns a prompt into a finished, narrated, on-brand video. We write about the things that actually moved the needle - voice markup, image consistency, render pipelines, honest pricing.
Introducing VideoCue - the AI video tool we wanted to use
Five minutes of cinematic, narrated, on-brand video from a single prompt. Here's what we built, why, and who it is for.
Anatomy of a 5-minute AI narrative: "Your Life as One Coffee Bean"
A full teardown of the reference render - 8,420 characters of V3 script, 40 Nano Banana images, three music stems, a 3-pass ffmpeg render. With receipts.
Writing for V3: ElevenLabs voice markup we actually use
A working set of V3 audio tags, pacing rules, and chunking strategies - pulled from the coffee video script. The conventions that survive contact with real production.
POV vs. omniscient narration: choosing the right narrator
The narrator you pick decides the video before the first frame is generated. A working framework for choosing POV, omniscient, or interviewer - with three worked examples.
Style anchoring: how to keep 40 AI images consistent
A reference frame, a style suffix, and a discipline. The protocol we use to hold a single visual language across forty Gemini frames in a five-minute video.
The 3-pass ffmpeg pipeline behind every VideoCue render
A walk through the render container: image-to-clip with Ken Burns motion, concat with crossfades, overlay-plus-audio-plus-watermark. And why we shell out to Python from Laravel.
Pricing AI video honestly: what each minute costs
A line-item cost breakdown of a 5-minute AI video - voice, images, music, render - and an honest comparison to a freelancer, Runway, and a stock subscription.
From script to upload in under an hour: a creator's workflow
A minute-by-minute walkthrough of producing a 5-minute narrative video, end to end, in 59 minutes - using a single creator, one topic, and a stopwatch.
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