LF#3 · Full script · "How AI Books My Calls While I Sleep (5-Step Setup)"
Engine: BOOK (speed to lead + AI setter). Draft only, nothing posted. Package (titles, thumbnails, description, chapters, pinned comment): PACKAGE.md.
Runtime ≈ 12:00 spoken (1,800 words at 150 wpm), ≈ 13 min finished with screen holds. Setup A, landscape, award wall, same chair as the VSL. Film in 9 chunks (one per # beat), 2 s pause between chunks.
Rules baked in: evergreen (no dates, no weekdays), no prices, no phone tiers, one CTA (the free session, mid-roll + end), proof only from brand-assets/proof-library/PROOF-INDEX.md (clients by first name, "Individual result. Not typical." said aloud), "Nikhil Sai" or "Nik", "you" never "you guys", no "live" claim for the session (say "my team in the chat"). Humanizer pass done.
1. Hook (yt-script hookscore.py, 5 written, top 2 kept)
| Score | Hook | Formula |
|---|---|---|
| ⭐ 52 | A lead filled out your form at 2 a.m. Nobody answered. By 9 a.m. they're on a call with your competitor. That's a setter problem, and I fixed it with an AI. | The Stake |
| 41 | Every lead you answer after five minutes is a lead you're paying for twice. Here's the AI setter that answers in sixty seconds and books the call. | The Reveal |
Winner uses the cold-open scene the viewer recognises (the 2 a.m. form fill) and names the cost before the fix. Same scale LF2's winner scored (44), so the opening below puts the stakes in the first line and the proof right after.
2. First 30 seconds, word for word
[SCREEN: black. Phone lock screen. One notification: "New lead · 2:07 AM · Form: Strategy Call"]
A lead filled out your form at two in the morning. Nobody answered. By nine, they're on a call with the business that replied first. That's a setter problem, and I fixed it with an AI.
[SCREEN: cut to Nik, award wall behind. Lower third: "Nikhil Sai · AI implementation"] (PROOF: C01)
I'm Nikhil Sai. I've trained over a hundred thousand business owners to implement AI live, and the one thing I set up in every single business first is this. An AI that answers every lead in under a minute, qualifies them, and books the call on the calendar. Mine's called Cassie.
[SCREEN: GoHighLevel conversation view, Cassie's reply at 2:08 AM, lead name blurred]
By the end of this video you'll have the five-step build, the exact prompt I give her, and the one number to track so you know it's working. Step four is where most people's AI setter falls apart, so stay for that one.
(≈ 0:00–0:38, 150 words)
3. Full script with retention beats
Legend: [SCREEN: …] editor insert · [LOOP OPEN] / [LOOP CLOSE] open question planted and paid · [PATTERN BREAK] change of rhythm, prop or framing · [PROOF] indexed proof moment · [CTA].
0:00 · Cold open + hook + promise + plan (0:38)
(the 150 words above, verbatim)
0:38 · Why speed is the whole game (≈ 1:10)
[SCREEN: a clock graphic. "Lead arrives" at 0:00. Markers at 1 min, 5 min, 30 min, next day]
Understand this. A lead is at their hottest in the first few minutes after they fill out the form. They're on your page. They're thinking about the problem. Their phone is in their hand. Every minute you wait, that attention drains, and by the next afternoon they've forgotten which form they filled out.
[SCREEN: the old-way timeline: "Form 2:07 AM → setter sees it 10:30 AM → first call 2:15 PM → voicemail"]
That's the old way. The setter starts at ten. Sees the lead. Calls at two. Voicemail. Leaves a note, "tried calling", moves on. You paid for that lead. You paid the setter. And you got a voicemail.
[SCREEN: the new timeline: "Form 2:07 AM → text 2:08 AM → reply 2:11 AM → booked 2:14 AM"] [PATTERN BREAK: fast cuts]
Here's what Cassie did with the same lead. Text at two-oh-eight. They replied at two-eleven, because they were still awake and still on their phone. Booked at two-fourteen. I was asleep. She was closing.
[SCREEN: Morgan's testimonial card, "Individual result. Not typical." footer] [PROOF: C39 Morgan] [consent pending]
Morgan set up this exact piece and his appointments got automated, in his words. Individual result, not typical. The point is the lead didn't wait for a human to wake up.
Now, there are five steps to build this. Step one is the one everyone skips, and it's the reason their AI sounds like a robot. [LOOP OPEN: why AI setters sound like robots]
(≈ 190 words)
1:48 · Step 1: Write her job description before you write a prompt (≈ 1:30)
[SCREEN: card "STEP 1 · THE JOB DESCRIPTION"]
You'd never hire a setter without telling them what the job is. Same with the AI. Before any prompt, I write a one-page job description, and it answers four questions.
[SCREEN: four lines appear one at a time]
Who is she talking to? Not "leads". A coach who runs a group program and wants to add high-ticket clients, who just filled out the strategy call form. That specific.
What does a good lead look like? Three qualifying questions. For us it's: what do you sell, what are you doing per month, and what's the one thing you want fixed first. If you can't write your three questions, you don't have a setter problem yet. You have an offer problem.
What's the one job? Book the call. Not sell. Not explain pricing. Not answer twenty questions. Book the call. Every message points there.
What does she never do? Never quote a price. Never promise a result. Never argue. If the lead gets rude, she hands off to a human.
[SCREEN: the actual job-description doc on screen, scrolling]
This is the actual document. The reason most AI setters sound like a robot is that the owner skipped this and typed "you are a helpful assistant" into a chatbot. The AI didn't know the job, so it did a generic one. [LOOP CLOSE]
Step two is the prompt, and I'll give you the whole thing.
(≈ 240 words)
3:18 · Step 2: The prompt (≈ 1:40)
[SCREEN: card "STEP 2 · THE PROMPT". Then the prompt text, full screen, scrolling slowly as Nik reads the headers]
Here's the prompt structure. It's in the description, you can copy it. Five blocks.
Block one, identity. "You are Cassie, the booking assistant for Nikhil Sai's team. You text like a real person on a phone. Short messages. One question at a time."
Block two, the goal. "Your only job is to book a strategy call on the calendar link. You do not sell, you do not quote prices, you do not explain the program."
Block three, the three questions, in order, one per message. And this part matters: "Ask the next question only after they answer the previous one. Never send two questions in one message."
Block four, the rules. "Reply within sixty seconds. If they ask about price, say the call covers that and offer two times. If they say they're not interested, thank them and stop. If they're rude or confused, say a team member will reach out, and tag the conversation for a human."
Block five, the voice. Three example exchanges, written the way I'd text. This is the block that makes her sound like us instead of like a bank.
[SCREEN: side by side, "generic bot" message vs Cassie's message to the same lead] [PATTERN BREAK: comparison]
Look at the difference. Left is the bot without block five: "Thank you for your inquiry! We would love to assist you." Right is Cassie: "Hey Sam, saw you grabbed the form. Quick one, what do you sell?" Same AI. One has a job description and examples. One doesn't.
Hear me out, the prompt isn't the hard part. Step three is where it has to live.
(≈ 250 words)
4:58 · Step 3: Wire it into the CRM (≈ 1:40)
[SCREEN: card "STEP 3 · THE WIRING". GoHighLevel workflow builder, screen recording]
I run this inside GoHighLevel because that's where the calendar, the pipeline and the texting already live. The wiring is one workflow, four pieces.
[SCREEN: workflow steps highlighted as he names them]
Trigger: form submitted. Any form, any ad, any landing page.
Action one: wait sixty seconds. Not instant. Instant feels like a bot. A minute feels like someone saw it.
Action two: the AI conversation step, with the prompt from step two loaded in, and the calendar link attached so she can offer real times.
Action three: when a booking lands, move the lead to "Booked" in the pipeline and send the confirmation. When she tags a conversation for a human, notify the team in a channel.
[SCREEN: the pipeline view, a lead moving from "New" to "Booked"]
That's it. If you use a different CRM the shape is identical. Trigger, short wait, AI conversation, calendar, pipeline update.
[SCREEN: Nav's testimonial card, "Individual result. Not typical."] [PROOF: C39 Nav] [consent pending]
Nav closed a twelve-and-a-half-thousand-dollar deal off a hundred and twenty dollars of ad spend, in his words. Individual result, not typical. That lead came in through a form and got answered fast. The wiring is what makes "fast" happen every time, including the ones that come in at two in the morning.
Now, step four. This is where I see most AI setters break, and it's never the technology.
(≈ 250 words)
6:38 · Step 4: The handoff rules (≈ 1:50)
[SCREEN: card "STEP 4 · WHEN SHE STOPS"]
The number one way an AI setter loses you deals is by not knowing when to stop. She keeps texting a lead who's already annoyed. Or she keeps asking qualifying questions to someone who already said "just send me a time". So I give her four stop rules, and they're all in the prompt.
[SCREEN: four rules, one at a time]
One. If the lead asks for a time, offer two times immediately. Skip whatever questions are left.
Two. If the lead asks anything about price, contracts or guarantees, she says the call covers that, offers times, and tags the conversation. A human reads it within the hour.
Three. If the lead says no, or stop, or not interested, she sends one message: "No problem, thanks for letting me know." Then she stops. No "are you sure". No "one last thing".
Four. If she can't understand the reply, after one clarifying question she hands off. Humans handle confused. AI handles clear.
[SCREEN: a real handoff example, lead asks "how much is it", Cassie replies, tag appears, team notification]
Here's one from last week. Lead asks how much. Cassie: "Good question, that depends on what we'd set up for you, which is what the call is for. I've got two slots open, which one works?" Tag goes to the team. The lead picked a slot. And if they hadn't, a human would have stepped in with context instead of starting from zero.
[SCREEN: Nik, straight to camera] [PATTERN BREAK: slower, flat]
My ex was a cold-calling team. We don't talk about it. The reason Cassie works isn't that she's smarter than a human setter. It's that she never forgets the rules, and she's awake at two.
[CTA, soft] If you want to see this whole build on screen, the prompt, the workflow, the handoff rules, there's a free session linked in the description. I'll come back to it at the end. Step five first, because without it you won't know if any of this is working.
(≈ 300 words)
8:28 · Step 5: The one number (≈ 1:20)
[SCREEN: card "STEP 5 · THE NUMBER". A simple two-column table: "Before" / "After"]
One number. Leads to booked calls. Out of every hundred leads that come in, how many land on the calendar?
Most owners I meet don't know theirs. They know how many leads they bought and how many sales they made, and everything in the middle is a feeling. So before you turn Cassie on, pull last month's leads and count how many booked. Write it down. Then turn her on and count again next month.
[SCREEN: our own dashboard frame, date range visible, numbers blurred except the two percentages] (PROOF: C34 framing; use our own numbers only, "Our own business. Not typical.")
In our own business, this is the number that moved first when we put AI on the leads, and it's the number that pays for everything else. Our own business, not typical.
And if the number doesn't move, you know exactly where to look: the job description, the prompt, the wiring, or the handoff rules. It's one of the four. It's never "AI doesn't work".
(≈ 190 words)
9:48 · What this replaces, and what it doesn't (≈ 1:00)
[SCREEN: two columns, "Cassie does" / "Humans do"]
Let me be straight about what this replaces. Cassie does first reply, qualification, booking, reminders, and the three a.m. shift. She does it in sixty seconds, every time, for every lead.
What she doesn't do is close. The sales call is still a human. Objections, pricing, the actual decision, that's you or your closer. And when a lead is confused or upset, that's a human too.
So the team stays. The part of the job that nobody does well at scale, the fast first reply, goes to something that never sleeps. Your setter, if you keep one, moves up to the calls that need a person.
(≈ 150 words)
10:48 · Recap + the one move this week (≈ 0:45)
[SCREEN: the five steps as a list, one highlighted at a time]
That's the five steps. Job description. Prompt. Wiring. Handoff rules. The number.
Here's your one move. Don't build all five this week. Write the job description. Four questions: who she talks to, what a good lead looks like, the one job, and what she never does. One page. If you can write that page, the rest is an afternoon. If you can't, you found your real problem, and it's upstream of AI.
(≈ 110 words)
11:33 · CTA (≈ 0:35)
[SCREEN: Nik, then the session link on screen as a lower third] [CTA]
If you want to see Cassie built on screen, there's a free session linked in the description. I go through the prompt line by line, the GoHighLevel workflow, the handoff rules, and my team is in the chat answering questions. You leave with your own job description written and the prompt filled in for your business.
It's free. Click the link under this video, pick a time, and bring the last ten leads that came in. That's the only prep.
I'm Nikhil Sai. Answer the lead before your competitor does.
(≈ 100 words)
4. Proof and screen-recording list (capture before the edit)
| # | What | Source | Notes |
|---|---|---|---|
| P1 | Phone lock screen, one form notification at 2:07 AM | staged on Nik's phone, demo sub-account | no real lead name |
| P2 | GoHighLevel conversation: Cassie reply at 2:08, lead reply, booking at 2:14 | demo sub-account, names blurred | must match the timeline said aloud |
| P3 | Old-way timeline graphic (form → setter → voicemail) | editor build | text on screen, no stock footage |
| P4 | The job-description doc, scrolling | ai-acquisition/ Cassie job description (export a clean copy) | no client names |
| P5 | The five-block prompt, full screen | PACKAGE.md §6 (same text as the description) | editor types it or screen-records the doc |
| P6 | Generic bot vs Cassie side by side | editor build from two real messages | |
| P7 | GHL workflow builder: trigger, wait, AI step, pipeline update | demo sub-account screen recording | ~40 s continuous |
| P8 | Pipeline: lead moves New → Booked | demo sub-account | |
| P9 | Handoff example: "how much is it" → Cassie reply → tag → team notification | demo sub-account, staged | |
| P10 | Our own dashboard, leads → booked, date range visible | our own GHL reporting, numbers blurred except the two percentages | caption "Our own business. Not typical." |
| P11 | Morgan testimonial card | brand-assets/proof/testimonial-morgan-reed-appointments.png | "Individual result. Not typical." footer, [consent pending] |
| P12 | Nav testimonial card | brand-assets/proof/testimonial-nav-ganesh-12500-on-120.png | same footer, [consent pending] |
| P13 | Award wall cutaway, 2 s | brand-assets/nik/nik-award-plaque-wall-01.png or live B-roll | C01 |
5. Shorts cut points (3, 9:16, captions burned in)
| # | In → out | First line on screen | Why it stands alone |
|---|---|---|---|
| S1 | 1:10 → 1:48 (old-way timeline vs Cassie timeline) | "Text at 2:08. Booked at 2:14. I was asleep." | the whole argument in 38 s, ends on "She was closing" |
| S2 | 6:38 → 7:40 (the four stop rules) | "The #1 way an AI setter loses you deals" | list format, each rule is a caption card |
| S3 | 10:48 → 11:33 (the one move: write the job description) | "Don't build the AI this week. Write this page." | clean instruction, ends on "upstream of AI" |
Each Short ends with "Full build on my channel" (no link in the Short, link in the comment).