{
 "slug": "edit-mock-client-call",
 "name": "Mock client call",
 "category": "preset",
 "group": "Edit styles",
 "media": [
  "video"
 ],
 "checked": "2026-11-13",
 "effect": "The viewer meets the problem as an overheard conversation before the solution is drawn.",
 "use_when": "System walkthroughs, consultation demos, case explainers, proposal videos.",
 "phrase": "a recreated video call: the client speaks first and names the problem, then the expert shares a screen and draws the system live, with speaker-labelled captions under it",
 "pitfalls": [
  {
   "text": "The client speaks first, in her own words. The expert opening, or a narrator stating the problem, is the listed failure.",
   "evidence": "practitioner",
   "source": "Director Chair measurement of a published short, Oct 2026"
  },
  {
   "text": "It explains a whole system but is not saved like a list: 2.8 percent of plays saved at 0.6 times the account's median.",
   "evidence": "measured",
   "source": "Director Chair measurement of a published short, 23 Oct 2026"
  },
  {
   "text": "A real client, a real person's face or a real vendor's logo needs written consent. Recreate a neutral call window.",
   "evidence": "practitioner",
   "source": "Director Chair measurement of a published short, Oct 2026"
  }
 ],
 "per_model": [],
 "external_refs": [],
 "licensed": [],
 "site_names": [],
 "related": [
  "layout-switch",
  "speaker-tag-captions",
  "drawn-as-spoken",
  "format-screen-led"
 ],
 "rights": "own-work",
 "evidence": "measured",
 "source": {
  "url": "https://www.tiktok.com/@pro.glitch/video/7695647708438220045",
  "note": "Our own reading and measurement of a TikTok by @pro.glitch, posted 12 Oct 2026. The clip is a third-party reference and is not shown; the words here are ours"
 },
 "body": "## Measured on the reference\n\n| What | Value |\n|---|---|\n| Length | 287.8 s |\n| Aspect | 9:16 |\n| Visual changes per 10 s | 4.31 (mostly the captions) |\n| Median segment | 1.9 s |\n| First visual change | 1.57 s |\n| First spoken word | 0.0 s |\n| Spoken words per second | 2.88 |\n| Loudness, integrated | -14.2 LUFS |\n| True peak | -1.4 dBTP |\n| Sound floor | -42.2 dBFS |\n| Face in sampled frames | 61 percent, top third (two cartoon tiles) |\n| Plays, saves | 3,445 plays, 2.8 percent saved (read 23 Oct 2026) |\n| Against the account's median | 0.6 times |\n\n## The recipe\n\n1. Recreate a call window in 9:16: a title bar with both names and a running timer, the active speaker's tile outlined, a toolbar at the bottom.\n2. Frame 0: the client's tile large, with a two-line title card naming the problem. The client says the first line.\n3. During the conversation keep two stacked tiles, client above and presenter below, about a third of the height each.\n4. When the presenter says they will draw it, switch to two small tiles on top and a shared drawing board below; draw each element stroke by stroke as it is named.\n5. Captions in a band under the screen with a speaker tag above each line.\n6. Keep real scene changes to about one every 6 to 8 seconds; the captions carry the faster rhythm.\n7. Close on the presenter's tile with the offer. Voice at -14 LUFS, no music under the dialogue.\n\n## Not for\n\nQuick tips, anything under 90 seconds, product beauty, emotional stories, a real client without consent.",
 "shown_with": null,
 "url": "https://directorchair.ai/preset/edit-mock-client-call",
 "markdown": "https://directorchair.ai/preset/edit-mock-client-call.md",
 "prompts": {
  "chat": "Give me a production plan: the shots or scenes in order, what each one needs, and the edit settings, for a short video about [your product], for [your audience]. The technique is mock client call: the viewer meets the problem as an overheard conversation before the solution is drawn. How it works: a recreated video call: the client speaks first and names the problem, then the expert shares a screen and draws the system live, with speaker-labelled captions under it. It is right for: system walkthroughs, consultation demos, case explainers, proposal videos. The client speaks first, in her own words. It explains a whole system but is not saved like a list: 2.8 percent of plays saved at 0.6 times the account's median. Be concrete: numbers, seconds and settings, no theory. Ask me one question first if something you need is missing."
 },
 "licence": {
  "code": "MIT",
  "text": "CC BY 4.0",
  "third_party": "Clips and card texts inside a \"licensed\" block belong to their makers and are shown with permission and credit."
 }
}