{
  "id": 15994213,
  "title": "How I decide what to fix in my AI video workflow",
  "url": "https://urgent.news/2026/10/22/how-i-decide-what-to-fix-in-my-ai-video-workflow",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-22T03:00:07.000Z",
  "source": {
    "name": "e27",
    "slug": "e27",
    "url": "https://e27.co/how-i-decide-what-to-fix-in-my-ai-video-workflow-20261018/"
  },
  "original_language": "en",
  "account": "When crafting AI-assisted video workflows for TikTok commerce creators, I faced issues with storyboard-generated scripts. To remedy this, I initially asked a language model to refine the storyboard generation prompt. If the outcome was still insufficient, I would switch models and regenerate the sequence. This process is distinct from writing individual scripts and aims to create a reusable method for future projects, eliminating the need for manual corrections. My responsibilities encompass product selection and content creation to drive sales. My workflow involves product discovery, competitor analysis, storyboard creation, visual production, editing, and publishing. I utilized crawling tools to gather category-trend data and applied GPT and DeepSeek to evaluate product candidates and analyze competitive videos. Generation models converted storyboards into clips, which were subsequently edited in CapCut and uploaded to TikTok. A coordinating agent assisted in assigning and monitoring tasks across specialized agents. While reviewing a storyboard, I evaluate three factors: logical connections between scenes, appropriate pacing of narrative and shots, and sufficient detail for the image-generation stage. If the storyboard is weak, I first attempt to improve the prompt by asking a language model to revise the instructions. I then regenerate the storyboard and recheck the three criteria. If this approach fails, I switch to another language model and rebuild the entire sequence. Depending on the issue, I may make adjustments or automate the first draft, but continue to manually edit certain aspects. Throughout the process, agents independently review their outputs, and the coordinating agent scrutinizes selected results before forwarding them. I also cross-check certain tasks using various models. Despite producing coherent outputs, I must ultimately verify the suitability of the product and video intentions. If problems arise, I analyze the process to determine whether the input was unclear, the prompt led the model astray, or if another model would perform better. Direct corrections or adjustments to instructions or workflow may be necessary. In one instance, an AI music-video project encountered difficulties due to multiple layers of client approvals. While AI streamlined the production process, the client's multiple approval levels required personal discussion and negotiation. Ultimately, I must determine acceptable output thresholds, pinpoint problem areas, and devise corrective actions. If these factors remain ambiguous, I maintain closer supervision over that stage. This evolution in my daily workflow has reduced script, image, and clip creation from scratch. My current focus involves comprehending requirements, selecting optimal models, scrutinizing outputs, and addressing unresolved issues.",
  "summary": "While building an AI-assisted video workflow for a TikTok commerce creator, I ran into a problem with the storyboards generated by a language model. The scripts covered the product, but the shots were not tight enough for the short videos we wanted to make. I could rewrite the scenes myself. Instead, I first asked a […] The post How I decide what to fix in my AI video workflow appeared first on…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}