Last updated July 25, 2026
I edited a fishing video from the ChatGPT mobile app without touching a timeline
The real prompts, screenshots, corrections, and tools behind a 31.7-second vertical video I edited with Codex and HyperFrames from my phone.
How the video was made
Aaron gave Codex one Google Drive video, ten fishing photos, a screenshot of a Codex fishing report, and access to his existing video brand system.
Codex transcribed the source, selected three spoken sections, assembled a five-scene 1080 by 1920 HyperFrames project, and returned review MP4s to the ChatGPT mobile app.
Aaron reviewed each cut on his iPhone and sent specific visual corrections until the final 31.7-second edit was ready for X, Instagram, and TikTok.
Tools in the workflow
The workflow used ChatGPT mobile remote, OpenAI Codex, Google Drive, GitHub, HyperFrames 0.7.71, FFmpeg, FFprobe, OCR, MiniMax CLI, and a licensed Melodie music track.
MiniMax music generation failed because the connected account had no active token plan, so the final edit used music Aaron had already licensed through Melodie.
Keep going
Sources and references
Short answers
Did Aaron edit the video in a traditional video editor?
No. Aaron reviewed the video and sent corrections through the ChatGPT mobile app. Codex changed and rendered the HyperFrames project on his Mac.
What did HyperFrames do in this workflow?
HyperFrames handled the code-based timeline, scene composition, on-screen graphics, captions, photo timing, transitions, checks, and final MP4 render.
Can this workflow create a version for native social captions?
Yes. The project includes a native-social export that removes the music and narration captions while preserving Aaron's voice, river audio, story graphics, and timing.