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Stop Trying to Make ChatGPT Edit Your Videos

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Using ChatGPT to edit videos via a single prompt fails because video editing is not a text problem — it involves pixels, waveforms, timestamps, and codecs that LLMs cannot natively access. The right approach is a multi-stage pipeline where the LLM handles only language tasks (segmentation reasoning, script rewriting) while purpose-built tools like yt-dlp, Whisper, and FFmpeg handle media processing. Key engineering principles covered: composition over generality, hiding LLMs behind adapters to avoid vendor lock-in, making pipeline stages resumable and idempotent with background job queues, and keeping humans in the review loop. The author built a product called VolfPack implementing this pipeline.

    #llm#backend#chatgpt
Jul 24•8m read time•From towardsdev.com
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Turning a 90-minute podcast into ten shorts isn’t a prompt problem. It’s a pipeline problem — and the difference matters for anything you build with AI.What “make a short” actually meansThe fundamental mismatch: tokens vs. samplesWhat you actually build insteadThe LLM belongs behind an interfaceThe unglamorous backbone: durable jobsWhere humans stay in the loopSo I built the pipeline, not the promptThe takeaway, stated as a principle
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