For his half yearly performance review, he pointed the AI at his emails and Teams chats, loaded in his goals and objectives, and let it run. The review it produced made him look brilliant.
Threw plain the AI at a git repo move with no skills or tools and finished in 20 minutes while multitasking, while a senior spent 6 to 8 weeks building the AI skills for the same job and moved only 5 repos.
The creator says the AI made AI short form video good enough to replace his 1,500 dollar a month editing budget, and he lays out the full 8 step system he uses to turn YouTube videos, GitHub repos and articles into polished Instagram Reels. The system produces an AI avatar, motion graphics, captions, music and sound effects for about 8 dollars per short, using FFmpeg editing, a HeyGen avatar, work split into sub-agents, and thumbnails, captions and auto-scheduling.
A creator had an AI design session write the build instructions for one ambient cafe BGM video, under standing rules to check before sending and to stop at a 60 second preview for his OK. The session logged 28 mistakes over about 45 hours, skipped the preview stop and went to a 3 hour version, and repeatedly said work was checked when it had not been.
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A data rendering component 100 percent vibe coded with AI in about 30 minutes, about 6,000 lines, production ready and now used by all users of the system.
Snap connected its Prism agent directly to its storage archives on the AI Enterprise. Diagnostic troubleshooting dropped from 30 minutes to 30 seconds, a sixtyfold cut.
The same studio's agent Timmy orchestrates more than 20 tools to turn blog posts into short videos: Veo generates scenes, ElevenLabs synthesises a custom voice, and automated captioning, lip sync and final assembly finish the piece. The pipeline runs inside the studio's normal the AI production setup.
The AI and the AI built his Obsidian plugin, listed in the Obsidian Directory with 65 users, alongside shell scripts, Alfred workflows and Elisp functions for his own setup.