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"Is AI Going to Replace Us?" — Transcript

by MoreMozi · 12,726 words · 1,831 segments · language en · Watch on YouTube

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0:00And so I'm going to break this into
0:01three pieces. All right, AI hygiene be
0:03very quick workflows. Uh and then AI
0:06assets. All right, that's the that's the
0:09that's the deal. All right, so AI
0:12hygiene. Um many of you guys do not
0:16follow AI hygiene and for some reason
0:18you don't know about this. Okay. Um you
0:21want to start a new chat for every new
0:23topic. So, when I first started using AI
0:25a long, long time ago, I basically had
0:27an neverending one chat that just kept
0:29going forever and ever. And I talked it
0:31was like, "Hey, I've got this weird spot
0:32on my arm. What's that?" And then I was
0:34like, "Hey, how do I change this light
0:36bulb in my car?" And then it was, you
0:38know, after that it's like, "By the way,
0:39write me some copy." And like the AI
0:41probably thought I was a psychopath and
0:42it would be correct. Um, but I don't
0:44want it to know that. I wanted to infer
0:46that. So for every time that you want to
0:50ask anything that is not related to the
0:52the question before you want to start a
0:54new chat. All right? So just for
0:55everybody number one.
0:58Next the more iterations and or feedback
1:01loops you provide within the same chat
1:04the better the outputs will continue to
1:06be. And so your fourth answer uh on a
1:10string is going to be superior to the
1:12first answer. Again the big C word is
1:14context. All right. Can we get a
1:16favorites chat? I don't even know what
1:17that means, but that that's what we're
1:19looping here. All right. So, if you have
1:21you have your initial prompt that you
1:23added your big context uh to it then
1:26might ask you some more questions, then
1:27you give that feedback and then it gives
1:29you an output and then you give output
1:30on that feedback. That next thing it
1:32gives will be significantly better than
1:34if you just took the first thing it gave
1:36you. Okay. So, if you want to increase
1:38the quality of the outputs, increase the
1:40number of iterations within each window.
1:42All right. Next,
1:45uh, verify facts and figures of outputs.
1:47We we try to make sure as, you know, we
1:48minimize hallucinations as much as
1:50possible, but like you for sure like if
1:52they have if there's numbers in there or
1:53it says a study, make sure that um that
1:56you just double check it. Um, one
1:59important point that I will make here
2:01and this kind of references Kenan's
2:02story is that like at the end of the
2:04day, decision- making is still yours,
2:07right? You cannot outsource thinking.
2:08You'll still be rewarded by the quality
2:10of your judgment and your taste. So what
2:12we want to really have AI do is
2:13outsource the typing, right? Like if you
2:15know what you want to type and you
2:16already have the ideas, you can just
2:18have someone else clack clack clack
2:19clack on the keys. All right? So
2:21outsource the typing, not the thinking.
2:24Next, the big thing here is that the
2:26idea is still the alpha. So your idea
2:28from a content, from a sales message,
2:30from an offer, the idea is still the
2:32alpha. That is still where the highest
2:34returns come. Not necessarily the the
2:37collateral. Now the cloud is a part of
2:38it to describe or or or execute or
2:40implement against the alpha. Um but the
2:43idea is still the core thing and I'll
2:44show you what I mean in a second. Okay.
2:46So that's AI hygiene. Please start new
2:48chats when you have a new idea. The more
2:50iterations you have within a chat, the
2:51higher the the quality of the output.
2:53Verify facts and figures. Don't
2:54outsource your thinking. Only the typing
2:56and the idea is still the thing that
2:57matters most. Okay. Now this gets into a
3:01little bit higher level for those of you
3:03who are who have teams. Okay. And if you
3:05don't have teams, then this will still
3:06apply to you. So just um it's just a
3:09different way of organizing uh
3:10workflows.
3:15Okay, let's rock. So
3:19here's a big idea for you. Who here has
3:22heard the term SOP? Standard operating
3:25procedure. Who has heard SOP before?
3:27Give me a gives me an SOP in the chat if
3:30you've heard of SOP.
3:32Okay.
3:35Yes, you guys have heard of SOP. What I
3:38want you to do is in your brain
3:41translate SOP to prompt. It is the same
3:46thing. Think about what it I want to
3:48give you, my employee or myself, our
3:51standard operating procedure for some
3:54task, right? We give them a standard
3:56operating procedure. What do you think a
3:58prompt is?
4:01You're giving them the operating
4:02procedure to get an output. And so the
4:06prompt is the SOP. And so when you think
4:08about it from that perspective, you will
4:10realize that most of y'all's prompts are
4:12too short. You're trying to uh outsource
4:16work to an employee with one sentence.
4:19And so like everything worth doing in
4:21life, it still takes work. Now, I'm
4:24going to talk about the leverage that
4:25this creates later, but big picture, you
4:28still have to do you have to do some of
4:31that thinking work up front to get
4:33higher quality outputs. Like, you still
4:35you can be dumber than you were before
4:37and still be kind of successful, but you
4:39get significantly more returns when
4:41you're smart and work hard. Now, the
4:43rich get richer still.
4:47Now,
4:50when we want to have repeated workflows,
4:52so you have things that occur every
4:54single week within your business. You
4:55make a certain amount of content. You do
4:56a certain amount of outreach. You send a
4:58certain amount of emails. Um, you send
5:00voicemails. You have, you know, RFPs
5:02that you respond to. Um, you have emails
5:05that happen in in and out every day. You
5:07have Slack messages. All of these things
5:09are are that happen on a regular basis,
5:11right? What you want to do is create
5:14standardized prompts for repeated work.
5:17So inside that AI folder that we had, we
5:19had business context which was one
5:21folder. The next folder that we would
5:23have is SOP prompts. Okay. So inside of
5:28those SOP prompts is where we want to
5:30put the prompts for repeated work. Now,
5:34if you're not sure what those are yet,
5:36at the very least, create a list of the
5:39things that you do on a regular basis.
5:41Now, if you don't know how what that is,
5:43then what you'd want to do is a time
5:45study where you can look at what you
5:46spend your time on in a given week and
5:48then block it out at 15 minute slots and
5:50you can see where you spend your time.
5:52Now, the vast majority of that stuff um
5:54is stuff that is repeated. And so, all
5:57we have to do is spend onetime work.
5:59Remember I said onetime work, forever
6:00payoff or forever time saving. onetime
6:03work, actually really thinking through
6:04what our SOP would be if we wanted to
6:06hand this off to an employee. What would
6:08it really be? And then that becomes the
6:10basis for the prompt for the AI in the
6:12future.
6:14Yes, ADHD wins again. Okay.
6:18So, you want to store these centrally in
6:19that folder. And if you're the one using
6:22them, um, you can save it into a master
6:24doc with tabs. For those who use Google
6:26tabs, that's one way of doing it. If you
6:27just like love having master docs, I
6:29tend to be a psychopath who likes like
6:30one doc to rule them all. Some of you
6:32guys like folders, that's up to you. I'm
6:33a big like one doc that has a zillion
6:35tabs guy. That's me. Um, but it's up to
6:37you. Now, most of you, um, like if you
6:40really think about what this would
6:41translate for a role is, you might have
6:42like a customer success manager and
6:44there might be 15 tabs and each of those
6:46tabs relates to one of 15 tasks that
6:48they have to do and the prompt related
6:50to that task. Is this making sense? And
6:53if you're not sure what an SOP looks
6:54like, I will show you. I will show you.
6:57Okay? I will show you. Don't worry. We
7:00good so far? Yes. All right.
7:05Now, um, if you are also solo working,
7:08here's an alternative method of
7:09implementing it within your business. If
7:11you have repeated calendar blocks, so if
7:13you're somebody who does time blocking,
7:14which I'm a big advocate of, which is
7:16you block your calendar for when you're
7:17going to do work, um, you can put the
7:20prompt inside of the calendar block so
7:22that when you see it on your calendar,
7:23the prompt is already there and you can
7:25make it a repeated event. All right. You
7:27can also do this for a new employee. You
7:29can time block their time and inside of
7:31their calendar event is the prompt that
7:33they would use to do the work.
7:35Pretty slick, right? Okay. Can I give
7:38you an example? Yes, I will give you an
7:39example of an SOP in a second. All
7:41right. And so what you want to do is you
7:44then can train the team on using those
7:46SOPs, those prompts, rather than just
7:49saying, "Hey guys, use ACQAI. Use the
7:52LLM, right? Go use them." It's like
7:54that's not helpful for somebody. just
7:56like saying go make emails, they need
7:59more context so they can make them the
8:01way you want them to be made. And to be
8:03clear, this is just like uh this is just
8:05using AI like any other machine with a
8:08checklist.
8:15And so the end result here of this
8:18second second little portion here is
8:21that you have a prompt repository. you
8:23have an area where your SOPs are saved
8:26and these become even more powerful new
8:28wage SOPs. So think of prompts as just
8:322.0 SOPs 2.0, right? And so your
8:35business functionally is run by a series
8:37of prompts. There is work that must be
8:40done. There is a way to do that work and
8:42we save the prompts for how to do that
8:44work properly.
8:48Okay?
8:50If you do it many times, then it means
8:52you should only do it once and do it
8:54right and then replicate it. I'm gonna
8:56say that again. If you do the same thing
8:58over and over again, then you should do
9:00it one time, right? So that you don't
9:01have to do it again over and over again.
9:05Brian, how do we know when to update the
9:07prompts? When you stop getting outputs
9:09that are good.
9:12Okay, now this may be the the meiest
9:16part of today. Okay. And I said I was
9:18going to keep today shorter and that's
9:20because this is already a shitload of
9:21work. All right. So I like my goal here
9:23is just like I want you to actually do
9:24this. Okay.
9:27This is the bigger one. All right. So
9:30big picture, we got our context window
9:31101 and 2011. That's what we did first.
9:34Next, we make sure we follow our AI
9:36hygiene. We start new chats. We iterate
9:38more times within the chat in order to
9:39get better outputs. We're good on that.
9:42Then for the repeated tasks that we do
9:43within the business, we start creating a
9:46prompt repository SOP list. And you can
9:49do this by RO and you can do it on their
9:51calendar, you can do it within a Google
9:53doc or you can do both. So people know
9:55exactly what steps to follow in order to
9:58do the work.
10:00Now the third piece here is AI assets.
10:04All right, this is this is going to be
10:07probably the besides the context window.
10:10This will be the highest ROI. So I
10:11probably put the SOP thing I just said
10:13as as third highest ROI. This would be
10:15the second highest ROI thing that we
10:16will do today. Okay.
10:20So we already have the folder of AI
10:23assets. So we have our business our
10:25business context number one. We have our
10:27SOP or prompt repository number two. And
10:30then number three we have AI assets.
10:32Sorry. We have um I mean you could call
10:34them I guess it's AI assets within AI
10:36assets but um
10:38I guess probably have to call a
10:39different name. Um you call it data
10:42sources if you want to. Um but
10:46call it data sources for for right now.
10:48Sorry I I I messed that up by saying
10:49calling the same name twice. Um
10:52data sources. All right. That's what the
10:53folder will be. Now
10:56what you want to do is go by function
10:58and gather the assets. Now what does
10:59that mean? Okay. So what we do is we
11:02will export the things that you have
11:04already done. So the big advantage that
11:06you have especially the longer you've
11:07been in business is that you have done
11:10stuff you have worked and that work has
11:13created output. That output is data.
11:16That data can be used to create more
11:18data like it in the future.
11:20So
11:22you should have a place where you have a
11:24source that has all of the data of the
11:26work that you've already done so that it
11:28can help you create more work that looks
11:30like that.
11:33So this is a sample list of assets that
11:35I would start with.
11:37If those of you who tweet, I would put
11:39all of your tweets which you can export
11:41in one button on X. You export every
11:43single one of your tweets and that
11:45becomes boom your prop. that becomes,
11:47excuse me, a data source. Number one, I
11:50put all my tweets all time data source.
11:53Real quick, I'm going to show you the
11:54exact 10-stage road map from zero to 100
11:57million plus that less than 1% of
11:59companies finish. I've now done multiple
12:01times. And so, I can say with a lot of
12:02confidence that these are the stages as
12:04headcount increases that you need to get
12:06through. And I broke each of these down
12:08by eight different functions of the
12:10business, what the constraint feels
12:11like, like what are the symptoms of it
12:13when you're going through it, and then
12:14what steps we actually took to graduate.
12:16And we've done this across software,
12:18physical products, uh, service
12:20businesses, brickandmortar, all of this,
12:22and it works. And it's my gift to you.
12:24It's absolutely free. And so the links
12:25in the description, just enter your info
12:27and it'll spit it right back to you. All
12:28free. Number two, if you've sent any
12:32emails to your list over the last
12:33however many years of your of your
12:35customers, take those emails and then
12:38put all of them in one document, one
12:39master doc that just has the emails that
12:42you've ever sent. Now, alternatively, if
12:44for each of these that I'm giving you,
12:46if you have certain emails that you
12:48like, you can use those emails, right?
12:52If you like an e-commerce store that
12:53sends a certain type of email or or
12:55whatever, you could just search all
12:57those, then export, and then boom, you
12:59have another data source.
13:03By the way, the calendar prompt is not a
13:04prompt. It's just you paste in the
13:07prompt and you just put it in the
13:09description of the calendar event. um so
13:10that when that person clicks the time
13:12they can see the prompt, they can import
13:13the prompt, they can do it, they can use
13:14it. So it's not like a special thing.
13:17I'm just saying it's a different way of
13:18organizing it.
13:20Another asset that you should probably
13:22have for those of you who have sales
13:23teams, you probably have SDRs or
13:25setters, right? You probably have those
13:27calls recorded. You already have this
13:29stuff. Take your top 10, top hundred if
13:32you want recordings, the transcriptions
13:34of those calls, and then we want to make
13:37that another data source. Now, what I'm
13:39putting in the bold next to this as
13:41we're going through this is what you can
13:42create from these assets, right? So, if
13:45I have my top 10 sets of all time
13:48transcribed, I'm going to give you the
13:49prompt momentarily that you can use to
13:51transform that into the golden standard
13:53of your SDR script. If you have your uh
13:57email newsletters that you've done in
13:58the past, that helps you create your
14:00future newsletters. If you have your all
14:02your exposts and tweets that you've done
14:03in the past, that helps you create
14:05future expost and tweets.
14:08If you have your top 10 closing calls
14:10recorded, this will help you create your
14:12VSSLs. It'll create your emails, it'll
14:14create your follow-up, create your
14:15closer script. So, what do I use for
14:17extracting uh transcriptions if it's in
14:19a different language than English? I
14:20mean, I don't think it matters the all
14:22the LLM speak the same language. They
14:23they're universal. They're they're large
14:25language models. You can speak in
14:26whatever language you want.
14:28Um,
14:30if you have uh lead nurture uh
14:32sequences, uh you can export all of
14:34those things and then say, "Hey, this is
14:36my current lead nurture. How could I
14:38improve this? How could I make this
14:39better? Output superior versions of the
14:41lead nurture." So, I'm going to keep
14:43going through these because I know that
14:44like SDR means setter, the person who
14:46qualifies leads. Um, I'm going to keep
14:48going through these, but the the big
14:50takeaway that I want everyone to have
14:52from this is that you already have these
14:55data sources. you have already done this
14:57work and so it's so the advantage that
15:01all of us who have done work in the past
15:02have for using AI is that you can get
15:06the AI to sound like you because you
15:09have done stuff. So I'll uh I'll pause
15:12real quick. Who here in the chat has
15:14seen content on the internet and been
15:16like this was written with AI? Just give
15:20me a give me a give me an eyeballs
15:22eyeballs emoji if you've seen AI content
15:26on the internet just like words just the
15:28words not even the videos just the words
15:31yes
15:32of course now the question is why
15:38why is it AI content? How can we tell
15:41that it looks like AI content?
15:45The reason we can tell it's AI content
15:47is because AI sounds like a a melting
15:51pot of the internet.
15:53And so AI sounds like the internet. And
15:58so if you want So AI doesn't sound like
16:00AI. AI sounds like us
16:03if we had no personality. And so if you
16:06want the AI to have a tone, have a a
16:09pattern of speaking, have a certain
16:11cadence that it that it communicates in,
16:14the advantage that you have, all of us
16:16who have actually done work is that you
16:18can use the work you did and say, "Don't
16:20sound like you, sound like this."
16:24And then it will use that and pattern
16:26match to create the output that you
16:29want. And so AI doesn't like if people
16:31like because I hear this a lot like like
16:33AI can only make stuff that sounds like
16:34AI. No, AI sounds like AI if you give it
16:37no context. You have given no asset, no
16:39data source to work off of. Then it's
16:41just going to fabricate from the large
16:43data set that it has which is the
16:44internet. And so that's why these
16:46filters, that's why we start with these
16:48context uh up front so that it can know
16:51what pattern to match with the outputs.
16:56But wait, there's more. Thank you, Lee.
16:58Okay. And so for each of these that I'm
17:00showing you here, it's you've got the
17:02data source and then we've got the thing
17:04that we can create from the data source.
17:05And I'll give you the pro I'll show you
17:06the prompt stuff in a second, okay? But
17:08each of these, this is the relationship
17:09I want you to see is that like if we
17:10have if we have sales recordings,
17:12there's lots of stuff we can do with
17:13that. We can improve a gold standard
17:15script. We can make a video sales letter
17:17taking the best closes we have. We can
17:19take those sales scripts, put them into
17:20emails. We can do it, make it into
17:22follow-up. all of these first ass these
17:25assets or these data sources can create
17:27further assets and data sources in the
17:29future. Okay. Um if you want to help if
17:32you if you're like hey I want to make
17:33better content use transcripts from
17:35YouTube videos that you like
17:39and yes uh hi May or Jamie um I'll show
17:42you how to do the the tone blueprint in
17:44a like we'll do that at the end.
17:47Uh transcripts from YouTube videos that
17:49you like. Great. We take those
17:51transcripts and then we feed it in and
17:53that gives us more videos like this. All
17:55right? And I'll show you again the more
17:56tactical ones, but this is I just want
17:58to give you conceptually the idea here
17:59so it can get your get your juices
18:00flowing because every single one of you
18:02right now, you guys tweet, you write
18:05emails, you have you have salespeople,
18:07you have VSSLs, video sales letters, you
18:09have emails, you have follow-up, you
18:10make content, you make all this stuff,
18:13right?
18:14And if you're not using this to make
18:16that, then you're not you're not using
18:18the ACQA to the at all the same degree
18:21that you could be and getting way more
18:22out of it. Okay. Um product FAQs, right?
18:26That transforms into sales page copy,
18:28VSSL, FOB, lead long-term nurture, uh
18:31customer support transcripts. So, when
18:33we're thinking about this folder that
18:34we're talking about, we've got our
18:35assets, we click in, we've got our
18:36context, right? We have our SOPs and
18:39prompts for the repeated work we do in
18:41the business. And then we have the data
18:42sources that those SOPs and prompts are
18:45based off of. Are seeing how this all
18:47put together.
18:49If I can
18:52is there an overhead cam that's on? If
18:54there isn't, then worry about it. I can
18:56use my hands.
18:57>> There's no Okay. Okay. So then pay close
19:01attention to my hands.
19:05We're going to double click on this
19:07first folder which is your AI assets.
19:10Inside you will have three folders.
19:12Folder number one is your business
19:14context. That is all the data that
19:16you're going to have on your business.
19:17Folder number two is you're going to
19:19have your prompt repository, your SOP
19:22repository. These are the prompts that
19:24dictate how you do the work you do on a
19:26regular basis in your business. These
19:28are instructions.
19:30The third folder is going to be the data
19:32sources. This is what these prompts will
19:36reference to pattern match to create
19:38outputs.
19:41All right.
19:43Does everyone get all three of those
19:47everyone? Everyone with me so far? Yes.
19:52Business context.
19:56SOP repository
19:58data sources.
20:00That's it. It's all we're doing. Your
20:02SOPs are the things you do and how you
20:03do them. Business context is what you've
20:06already done and the description of your
20:08business.
20:09And your data sources are where you are
20:13gathering, you're exporting data from
20:15things you've already done. Your tweets,
20:16your emails, your STR recordings, your
20:18sales recordings, your existing email
20:19sequences, uh video transcripts,
20:21transcripts of videos you like, emails
20:22you like, right? Content you enjoy,
20:25product FAQs, reviews online, customer
20:27support transcripts, all of that stuff.
20:29All of those are data sources.
20:34your best performing ad copy
20:38to give you a few others. If you've got
20:40high engaging uh social media posts that
20:42you like or have seen from other people,
20:44keep a one, you know, one doc that has
20:47the the post that you like the most.
20:48That rhymed. Uh your website copy in and
20:52of itself is an asset, right? It's a
20:55data source that it can pull off of,
20:57which can also give you page
20:58improvements, copy improvements, ad copy
21:00from there, emails from there. If you
21:02have blog posts or articles that you
21:04enjoy, those become data sources. SOPs
21:07and internal process. Some of you guys
21:08already have some SOPs. Great. Now, I
21:11will I don't know if I'm going to hit
21:13that memo system.
21:15I I think I might I might blow someone's
21:17gasket, so I might not do that one right
21:18now. I think it's going to it's going to
21:19melt some minds. Okay, we'll just move
21:22on to the next one. Um onboarding
21:23scripts for customers or employees,
21:25right? These are all things that you
21:27have.
21:30pitch decks and webinars, slide decks
21:32that you have, all of these new data
21:35sources, top performing email sequences,
21:40guys. Are you guys with guys with me on
21:41this? You want that that repository to
21:46be rich with the highest quality data
21:48you can. And the higher the quality that
21:50you curate with those sources, the
21:54higher quality the AI will pattern match
21:56to create outputs. And the more complete
21:59the context, the more specific and
22:01personalized they'll be to your
22:03business. And the more detailed the
22:04prompt, the more they will follow the
22:06instructions, give you the output you
22:07want. That's how all three of these
22:09things work. All right? It has to know
22:11what your business is about. It has to
22:15have good data that it can base off
22:16saying, "This is what it looks like when
22:17it's right." And it has to get clear
22:19instructions on exactly what you want.
22:20When you have all three of these things,
22:22you can put them together and make
22:24banger outputs. And so things only sound
22:27like AI when you don't have a baseline
22:29to train it on. So AI sounds like the
22:31internet. But if you train it on the
22:32work you've done, it sounds like the
22:33work you've done.
22:37Yes, I will give you guys examples. I
22:39want to give you I want to walk through
22:40this first. Okay. And so these are the
22:43most common things that people are using
22:46uh to get outputs with ACQA.
22:49So people are looking for sales scripts.
22:51So right now many of you I know because
22:54I've talked to you guys many of you need
22:56one or more items on this list right so
22:59who here um actually what do we have we
23:02got 12 items on the list who here say on
23:05number one to 12 how many of these
23:07things you know you could do better at
23:11than you are right now
23:13you could do better on one of them do
23:15better on two of them five of them all
23:1712 put a number 1 through 12 of these
23:19things are on this sales scripts 12 12 a
23:23lot of twelves okay that was not
23:25actually where I was going for that but
23:26that's good to know that a lot of 12
23:27three right a lot of twelves five a lot
23:31of twelves
23:33um some four seven six okay use a lot
23:36this is brilliant okay cool so the
23:38reason I bring this up is that this this
23:42now gets to the crux of the issue of
23:44like what separates ACQ AI from kind of
23:46the generic AI right which is that for
23:49many of you. These 12 things are the
23:52majority of how you make money, right?
23:54You make content, you run ads, you do
23:57outreach with words and videos and
24:01media, and then those people become
24:03engaged leads. And then you give them
24:05more information via sales scripts and
24:08video sales letters and webinars. And
24:11then with that extra information, they
24:12then make an informed decision and then
24:15purchase your stuff. And then after that
24:17they get more information from you in
24:19some way, right?
24:22And so it's not that do you have this or
24:26not have it, it's how much do you have
24:27and how good is it? And this is why the
24:30difference between a 225 batter and a
24:31300 batter is such an important point.
24:35So the whole idea here is that we're
24:36trying to make the asset HQI that can
24:39help improve the quality of these things
24:41as they come out based on all the things
24:43that we've trained it on. Now this is
24:44clearly just on assets. There's
24:46obviously, you know, offer strategy,
24:48there's decision-making, there's things
24:49like that that it also is trained on.
24:51But for many of you, when I look at the
24:52top use cases that you guys have, these
24:55are the these are the big use cases you
24:56guys use it for. All right? So, if many
25:00of you guys did say at least one of
25:01those things is something that you could
25:02improve on. Okay. The reason this is
25:05important, why this matters is that if
25:07more better is how you grow, this allows
25:10you to do that. You no longer have an
25:12excuse because you now have tremendous
25:15leverage. And I just found this little
25:16infographic that I thought was funny.
25:17All right. Boss, leader, introvert,
25:19introvert with AI, right? I just thought
25:22it was cute. And so, some of you guys
25:24asked, "How do I use this?" All right.
25:27How do we put out so much stuff and how
25:30do we keep the quality high? Here's how
25:32we do this. So, Mosy Minute used to take
25:35me between 60 90 minutes per email. And
25:39so this generates, put this in context,
25:41this generates about 20% of the revenue
25:43of ACQ, uh, the advisory practice. All
25:46right?
25:48Now, it takes four hours for me to make
25:5016 emails. So, basically, one half day
25:52per month, I sit down and I write all
25:54the emails for the month. And so, I get
25:57So, this gives me 4x leverage
26:00using what I just outlined. I've got my
26:02business context. Again, what are the
26:04three pieces here? I probably should
26:05have put a slide up, so I apologize.
26:07There's three big pieces. We have
26:09business context. We have the rules of
26:12engagement. We have how we do the stuff.
26:14And then we have the stuff we base it
26:15on, our data sources. Those are the
26:18three things that you need to have to
26:19use AI. Well, and so using all three of
26:22those things, I wrote the Mosy Minute
26:24for a very long time before using AI.
26:26And so then I said, great. And I'll tell
26:29you, it's like AI does not come up with
26:30the idea though. This is a big one. AI
26:33does not come up with the idea. It will
26:35take the idea that I have and say, "Hey,
26:38um, I want to write uh, uh, a mosy
26:41minute based on this core offer
26:43structure. This is why it's cool. This
26:44is why I think it's awesome. Turn this
26:46into an email that looks like these ones
26:48and follows that structure and then it
26:49gives me the output and then I tweak and
26:51edit it. Thank you. I appreciate that."
26:54That I still spend time on it. It's just
26:55the difference is that I get more time
26:57back. So many of you guys think in terms
26:59of automation when you really should
27:01just be thinking in terms of leverage
27:03and amplification.
27:05I want to say this again because I think
27:06it's a really important point.
27:09Many people want to sell you an
27:11automation and it's and hey it's sexy as
27:13hell. Automation sexy but more
27:16realistically what you will get is
27:17amplification not automation. You will
27:19get more leverage not infinite leverage.
27:22True automation is infinite leverage
27:24right? It's it's it just it continues to
27:27run. It never has to get checked. It
27:28never breaks. It always improves. That
27:31is uncommon. What is far more common is
27:34that something that used to take me 60
27:35to 90 minutes now takes me 15 to 20
27:38minutes.
27:40Real. So, I'm getting 4x. Thank you,
27:42Kevin. I appreciate that. Um, and to be
27:44fair, Kevin, it's not AI. It's me. It's
27:48my idea. It just helps me type the words
27:50faster um and give examples faster,
27:53right? So instead of me sitting there
27:54being like all right what example do I
27:55want to use here it just gives the
27:56example I'm like great it already it
27:57already used the idea that I had it
27:59applies it right and so they're not AI I
28:03take the emails that I have already
28:04written that write that I write like me
28:07I have the idea that's me I say go make
28:09this similar to that it gives me the
28:11output and then I still edit it and
28:13tweak it right and the tweets for
28:14example that start the email with those
28:16are tweets that I pull from somewhere
28:17else right and so all of this is
28:19leverage all right Next, um, tweets
28:24themselves used to take me about an hour
28:25and a half a day. And to give you
28:27context on this, it gets 20 to 30% of
28:29all of our content comes from tweets.
28:31All right? And so now it takes me about
28:3390 minutes a week. So basically, I'm
28:35seven times more efficient. I haven't
28:37automated this. It's not AI making my
28:39tweets. Is that it will help me generate
28:41ideas from which to iterate to make
28:43tweets that are good. Right? So if I
28:45could just purely say, "Hey, make me all
28:48these tweets and I copy paste them." It
28:50it wouldn't work. I like believe me I'
28:51like doesn't work right but it can give
28:53me inspiration uh and ideiation to base
28:56off of to then make my stuff happen
28:57faster because before this I just sit
28:59there and be like all right and I would
29:02scroll I would scroll X I'd scroll uh
29:04social media and usually I would just
29:05wait until I felt an emotion about
29:07something and then be like why do I feel
29:08this way and then I would respond to
29:11that content as my tweet right
29:15and technically Stephen no it's not
29:17still written by AI because I'm still
29:18still editing a lot of it um it would
29:20assisted. Um, if it's pure AI, it's
29:23different. So, which is a a specific
29:26difference, by the way, from a from a
29:27copyright perspective. Um, so next is um
29:33YouTube, right? So, videos used to take
29:35two hours for video for me and this is
29:37like where 40% of lead flow comes from,
29:39right? So, now it takes 15 minutes per
29:41video. And so, what's interesting is
29:42that many of you will take the word AI
29:44and think, "Oh, bad quality." And that's
29:45because you don't know how to use it.
29:46It's also because you don't have
29:48existing resources. This is a big point.
29:50is a big deal.
29:52You are rewarded for the work that you
29:54have done.
29:56My minute emails are bangers because I
29:58wrote a shitload of bangers. My tweets
30:01are good because I already wrote 6,000
30:03[ __ ] tweets before I did this. 6,000.
30:06All right, I'm at 7,000 now. 6,000 was
30:09just me, right? And so it has a huge
30:12datab bank data source to pull from to
30:15give inspiration in terms of sentence
30:16structure, in terms of ideiation that
30:18allows me to go work a lot faster. And
30:20so I gave my estimated Yes. I I do a lot
30:23of work, Dylan.
30:26Yes, Emil. Exactly. I put 6,000 in and
30:28said, "Learn from this right
30:32now." Um,
30:35if we're going through here, notice not
30:37all of the amplification is the same,
30:39right? I got 4x leverage on emails. I
30:42got 8x on YouTube.
30:45Different, right? And the key point
30:47here, big big point. It's the idea.
30:51The idea is the leverage. The ultimate
30:54alpha is the idea. And so it's not going
30:57to come up with the mosy minute because
30:59it can't have my experience. And so I
31:02know some of the questions that I'm
31:03going to get around this are like, is AI
31:05going to replace us?
31:07eventually not for a while but the main
31:11reason is that because AI cannot live in
31:13real life and cannot get real life
31:15experiences and so those experiences are
31:17the alpha that's the idea that's the
31:19learnings those learnings those stories
31:22those narratives it can then flesh out
31:24but the core idea is yours that is the
31:27essence of it and so this is how this is
31:30how I've scaled what I do is like I can
31:33take the core the core value and then I
31:37can amplify
31:38It's not automated. It's just amplified.
31:41You guys digging this? Is this making
31:43sense?
31:48Correct. Moritz a is not AI is not
31:51original yet. It does. It's like a
31:52remixer, right? Exactly. For now, it
31:56will get better in the future, but for
31:57now, it it more or less remixes. And so,
32:00the idea is what I want to Okay, I can
32:03now articulate this well.
32:05What we are trying to remix is our
32:08language patterns, our sentence
32:09structure, the format of the video. I'm
32:12gonna have an intro, I'm gonna have
32:13three main points, I'm gonna have
32:14stories, whatever, right? The format,
32:16the structure, that is what AI is very
32:19good at replicating
32:21the essence of it, the core value that's
32:24being created. It sounds like very
32:25amorphous language for me. Um,
32:26fundamentally, the good [ __ ] right,
32:29that's inside that still is going to
32:31come from you. Which is why a beginner
32:33who just tries to turn out AI content
32:35still doesn't win because they have no
32:38idea. They have no experience. They
32:40haven't done anything. And the AI can't
32:43do it for you. Can't live your life for
32:45you. Can't have the experience for you.
32:47So, you have to do stuff like I've
32:49always said and then take the stuff you
32:50did and you talk about it. AI just
32:52allows you to talk about more of it
32:54faster.
32:56Yes, Rayon.
32:59We can amplify. That's the goal here.
33:02All right. Um, memos used to take me at
33:04least four hours per memo. Um, now they
33:07take me probably an hourish,
33:11right? Um, maybe a little less than
33:13that. I don't know. Maybe maybe was
33:15maybe a little aggressive on that one.
33:16Probably still takes me about an hour.
33:17Um, so it was 4x lever 8x. Scripts for
33:21sales guys. My god, that would take me a
33:22long time. Um, and now we can write
33:25scripts much faster for new offers, for
33:27portfolio companies, for anything,
33:28right? is we get significantly more
33:30leverage.
33:32And so I'm bringing this up for you guys
33:33to show you that like how do I use AI to
33:36make YouTube videos. It's going to be
33:38more structure and ideiation. Um and
33:41then honestly I have a skill set which
33:43is that I've developed over many years
33:44which is that I can riff on topics in a
33:46way that's interesting and I know syntax
33:48and rhetoric that people find engaging
33:51being real. Um so my stuff isn't
33:54scripted and that's what also makes it a
33:55lot easier. Um, so for me it's much more
33:57like what are the what are what are the
33:59interesting prompts that drive response
34:01around a topic and that is easier. So
34:03like I still so the way I use AI is
34:06actually to prompt me to say interesting
34:09things. Actually that's probably the
34:10easiest way for me to say this like the
34:12tweets for me is that it prompts me to
34:15respond to things which helps me
34:17ideulate on interesting things to say
34:19faster. It does not say, "Hey, Alex, say
34:21this."
34:24Now, for for scripts, yes, you can use
34:27it to create sales scripts. All right?
34:28So, that's what we're going to get into
34:29next. All right? And so, yes, VSSLs used
34:32to take a full day, and now you can do
34:33them really quick. Okay?
34:36So, the part that many of you guys have
34:38been waiting for. So, big picture, we've
34:40we've broken this down into number one,
34:43we have our business context. Number
34:45two, we have our SOP repository of how
34:49we do [ __ ] And I'm going to give you
34:50examples of this in a second. And number
34:52three, we have our data sources, right?
34:55Which is stuff that we've done in the
34:56past that it can reference to make more
34:58stuff like it. Okay. What if you're not
35:01confident about the quality of your
35:02current content? Excellent question,
35:04Casper. I will give you use cases for
35:06how to improve this.
35:09Yeah, AI uses me the way other people
35:11use AI. Yes, I get AI to prompt me.
35:13Okay, so the goal here is we use past
35:16work to make future work. So this is the
35:17overarching step process. So number one
35:20is you get assets, you separate them
35:22clearly. So what I mean by that, so
35:23let's say uh let's say you got 10 sales
35:25call transcripts. You just got to make
35:27sure that each sales call is clearly
35:28delineated like space space star start
35:31star begin script star start star begin
35:34third script star start star begin
35:36fourth script. All right as you go
35:38through. So you get your assets, you
35:41separate them clearly and then you
35:42upload them. All right. So this is the
35:43data sources we're talking about. So you
35:45upload that, you put your little paper
35:47clip, right? You upload it. Then you
35:50prompt, right? The prompt repository
35:52that I was referencing. I probably
35:53should have done step three instead step
35:55two first, but you get the idea. Okay?
35:58So you'll notice that the best outputs
36:01come from the best inputs. And when done
36:02right, these create prompt chains. And
36:04I'll explain what this means later. So,
36:07for example, if you have a sales
36:09recording but don't have a gold standard
36:12sales script, let me um let me send
36:16something. Hold on. Lis, can you pull
36:18something up um on
36:21on the screen? Can we go like back and
36:23forth between two screens? Is that
36:25possible?
36:31>> I I'm send you a doc because I want to
36:33show what the prompt looks like.
36:35um so that they can they can see it. So,
36:39just so you guys know, I'm going to give
36:40you Yeah, I mean, so believe me, this is
36:43like the oneonone training. I'm not
36:44going to do any more than this. Um I
36:46don't I don't want you to be
36:47overwhelmed. Again, before anyone gets
36:49too deep in this levels here, okay?
36:53Number one is get your context window
36:54right. Do 101 and 2011. Get that first.
36:57If you if you do nothing else but doing
36:59that, it's a W. The second thing you can
37:02do is just get your data sources.
37:05Everyone has them. There's there's no
37:07work that's really involved there
37:08besides you just capturing it. Just put
37:10it together. All right, that's the
37:12second big thing. The third thing is the
37:14prompt repository that references both
37:15of these things to create outputs.
37:19Thomas, there is a isn't there a limit
37:21providing context on every one of the
37:23platforms? There is, but this is why I'm
37:24saying try do things in word format and
37:27that'll dramatically decrease the size.
37:29If you're talking, it's 25 megabytes. If
37:31you're doing just words, you'll have
37:32more than enough. You could put a book
37:33as context with 25. Again, the key thing
37:35is you don't put images inside. Okay.
37:37So, I'm going to have my team um uh go
37:41through this. So, I had this originally
37:44as in the slide deck, but I think I'll
37:46just voice over it. I think it'll be
37:48more useful for everybody. Um yes, thank
37:50you, Buck. We worked on it. Um okay, so
37:53let's say right now, um you have some
37:57sales recordings. Okay, you have some
38:00sales recordings, um, but you don't have
38:02a unified script. So, your sales team
38:04doesn't have a unified script. So, what
38:06we would do is we would paste the
38:09transcript of the tender call recordings
38:10and then we would post this prompt
38:13inside of it, right? And so, it' be
38:15like, hey, this is the number one. This
38:17is for you guys. And I will give you
38:19guys a copy, my gift to you, of every
38:20one of these prompts, uh, as an email.
38:22Okay? So, you guys get an email with
38:24every one of these. Um, but I want to go
38:26through each of them so you understand
38:27how this works because fundamentally
38:28you've got stuff. We give it a prompt to
38:31make better stuff or analyze that stuff
38:33and improve it. That's it. All right.
38:36So, you're an elite B2B sales trainer
38:38and script doctor. I'll paste 10 full
38:39transcripts of successful sales calls
38:41that sold the same offer to the same
38:43type of prospect. Your job is to build
38:45one mother script from these calls by
38:47extracting only what actually moves
38:48itself forward and deleting everything
38:50else. Follow these rules. So, you can
38:52scroll up. So analyze these calls first.
38:55Identify common structure but best calls
38:57follow from greeting to close. Note the
38:58exact questions and phrases that
39:00consistently leads to open disclosure uh
39:02commitment and payment. Define the call
39:04structure. Build the script in clear
39:05sections with headings. Opening and
39:07rapport frame and agenda discovery.
39:08Transition to pitch offer and value
39:10stack. Handling three to five
39:11objections. Final close and next steps.
39:13All right. Booking. Bam. Bam. Right.
39:16Create the unified script. Use only
39:18lines that appear in multiple winning
39:19sales calls or are clearly essential
39:21glue. Remove filler, small talk, or
39:23stories that don't directly help the
39:24sale. Keep language single. Keep
39:26language simple, direct, and
39:28conversational. Third to sixth grade
39:29reading level. Uh, keep the core pitch
39:31portion short enough to be said in under
39:32five minutes at a normal pace. Where
39:34useful, include questions the rep should
39:36ask verbatim, and notes about intent or
39:37tone. Uh, output format, a short
39:39overview of the structure in bullet
39:41form. Uh, final word for word script
39:43organized by section headings. Bullet
39:44list of the top 10 most powerful phrases
39:46or lines you pulled from the calls.
39:47Remember, prioritize clarity, brevity,
39:49and closing power. Delete everything
39:50that doesn't help prospect decide and
39:51buy. All right. So, this is what you can
39:54take your transcripts and turn it into
39:57sales scripts. Transcripts. Sales
40:00scripts. Transcripts. Sales scripts.
40:06This is cool, right? This is pretty
40:08sweet, is it?
40:11Yes. Dope. Dope [ __ ] Okay, cool. So, I
40:17said I was give you guys examples. Like,
40:18we're gonna This is This is the meat.
40:20All right. This is the meat. All right.
40:22I know transcripts are pretty sexy. All
40:24right. So, now let's say you uh want to
40:27write more emails. So, right now, you
40:28know, you should be following up, right,
40:30with your leads.
40:32You know, you should be following up
40:33with your leads. You know, you should
40:34have a newsletter because Alex said he's
40:36getting 20% of his revenue just from
40:37spending one half day a month. And
40:38you're like, "Man, if I spent one half
40:39day a month and I and I got an extra 20%
40:41revenue, uh, that would make me money."
40:43And I would say I agree with that. Uh
40:45and you should do that. So how do you do
40:47it? All right. Uh this is a newsletter
40:50style and uh and so basically you're
40:52going to analyze newsletter and
40:54generate. So it's both. So you're an
40:56expert copyrer narrative strategist.
40:57You'll notice the same structure for all
40:59these. You give them the role, you have
41:00the task, you give rules, and you give
41:01output. It's kind of the four the four
41:04kind of structure for good prompting.
41:06All right. So you're an expert
41:07copyriter, narrative strategist. Train
41:09to analyze writing samples, extract
41:10voice structure, style patterns, and
41:12reproduce them with new ideas while
41:14maintaining the same feel and reader
41:15impact. I'll provide my past email
41:17newsletters that performed well. Your
41:19job is to learn the voice, tone, pacing,
41:20narrative structure, rhetorical
41:21patterns, and call to action style from
41:23these examples. Analyze my past so
41:25tasks. Analyze my past winning
41:27newsletters. For all newsletters, I give
41:28you to extract voice profile, writing
41:30ticks, narrative structure, format, and
41:31patterns, persuasion mechanism, CTA
41:33style. Provide concise but complete
41:35descriptions of the style you infer.
41:38Next,
41:39build a reusable newsletter template
41:42using the patterns above. Create a
41:43generalized structure for my winning
41:44newsletter style, including opening hook
41:46style, story and modern pattern,
41:47teaching framework, pacing and rhythm
41:49rules, closing style. This becomes the
41:51newsletter blueprint. Three, generate a
41:53brand new newsletter after analysis when
41:55I give a new topic idea. So, this is
41:57this is the alpha, right? Remember guys,
41:59I was like, you still have to come with
42:00the idea. So you say, "Hey, I want to
42:02write," So, uh, I want to write a
42:04newsletter on some stuff that roofers,
42:08you know, so people who own roofs, uh,
42:10or people who have leaky pipes,
42:11whatever, that they can, uh, do avoid
42:14having leaky pipes in the winter. Easy.
42:16So, I want to have this specific thing,
42:18this core story or core element that
42:20happened. And I'm going to say, "Hey,
42:22that's the story." And I say, "Great."
42:23Boom. Put in my template. Go run it.
42:26Right? And then it's going to fill in
42:27the gaps uh, within that structure. is
42:29going to take that story and amplify it
42:31so that it actually finishes follows the
42:33structure that I want. So then the
42:34output will be one full newsletter match
42:36the same style use the template um and
42:38then it should feel like I wrote it and
42:40so then it has rules. So, some of you
42:42guys never copy phrasing from old
42:44newsletters. Learn the style, not the
42:45words. Newsletter must be 100% original
42:47content in my voice, right? That's why
42:49the key idea is so important. If you
42:50actually just ask it to just write
42:53newsletters for you guys, it will suck.
42:55I'm just telling you, it will suck. It
42:57does not work. If you give it the idea,
43:00then you will have a valuable a valuable
43:02insight. Keep theruct structure
43:04consistent. Never break character. Um,
43:06and if you need more samples to refine
43:08the model, ask. Yes, Simon, I'm gonna
43:10give you all these my gift to you. All
43:12right. Uh, and then this is output
43:14format. So, you can just scroll past
43:16this.
43:17Okay. So, here's another one. So, let's
43:20say you have notice it's like if you
43:23have this, then you can do this, right?
43:25So, uh let's say you've got a uh
43:28um you're you're getting you're getting
43:30stuck on rebuttals, right? You're like
43:32people are are are not buying from you
43:34and they're coming up with objections,
43:35right? So, we say, "Great. Let's help
43:38solve this. We're going to upload our
43:40transcripts, right? And now we're just
43:42going to focus on the objections. So,
43:44you're an expert sales and objection
43:46handling strategist. You specialize in
43:47reviewing failed sales calls,
43:49identifying the core objection patterns,
43:50and turning them into clear, repeatable
43:52objection handling playbooks. The input:
43:54I'll provide you with one or more failed
43:56sales transcripts. Each transcript may
43:57include hesitation, fill words, messy
43:59phrasing, or incomplete responses. Your
44:00job is to extract and clean the
44:02insights. Task: Identify the primary
44:05objection each call. So, reach I give
44:07you give you the primary objection.
44:08Secondary objection, quote the exact
44:10lines from the transcript that signal
44:11the objection. Summarize the objection
44:13in one clean sentence. Two, propose
44:15strong objection handling sentences. So
44:17for each objection, write three to five
44:18short, powerful objection handling lines
44:20the salesperson could say next time.
44:22These must be conversational,
44:24non-confrontational, confidence
44:26building, framed around value, clarity,
44:27and reducing perceived risk, including
44:29both softening statements and direct
44:31reframes. Three, build a consolidated
44:34objection guide after processing
44:35multiple calls across all transcripts
44:38you analyze. Create a running playbook.
44:40Identify all objections that appear more
44:42than once. Cluster them in the top 10
44:44most common objections. And for each of
44:45the 10, give a clean definition of the
44:48objection. List example phrases
44:49customers say and provide three to five
44:51objection handling lines. Provide the
44:52root cause behind the objection. Fear,
44:53confusion, misalignment, timing, money,
44:55and then format the final guide in a
44:56clean way that can be copied into your
44:58training manual.
45:01Right. Okay. There's more output. I'm
45:05not gonna read the output formats for
45:06you guys, but that's because then it you
45:07just tell it how you wanted to, you
45:09know, deliver the thing. So, you scroll
45:10the next one. Okay. Um, so next one. One
45:15of you guys said earlier, I wish there
45:16was like some sort of uh writing style
45:18analyzer, right? This is what it looks
45:21like. So if you've written stuff
45:23anywhere via Slack, via email, blog
45:26posts, uh any any any content you put
45:29out, you can deduce your writing style
45:33and then you can feel you can you can
45:35put inputs in so it doesn't sound like
45:37AI, it'll sound like you. All right, so
45:39role is you're a world-class writing
45:40style analyst. Your job is to dissect
45:42the style of a given text so it can be
45:43reverse engineered or reused. Focus on
45:45how it's written, not what it says. I'll
45:47paste sample writing after this prompt.
45:48Analyze it deeply and systematically.
45:50Number one, highle snapshot. So overall
45:53style summary, author persona, and then
45:55primary goals of the writing. Next, give
45:57me the voice and tone, formal, informal,
45:59direct or indirect, conversational or
46:00authoritative. Uh tone shifts. Does it
46:03stay consistent or does it change? Any
46:05notable moments where a tone becomes
46:06intense, emotional, humorous, serious?
46:08Relationship to the reader. Is this
46:09because it's their peers, expert, coach,
46:11storyteller, teacher, or something else?
46:12Is the voice empathetic, challenging,
46:14supportive, or confrontational?
46:15Structure and flow. Number three, how is
46:17the text built? All right. So overall uh
46:20structure pattern. So is it hook, story,
46:22lesson, framework, CTA? Are there
46:23distinct sections or acts? Is there
46:25opening? Is there closing? Is there
46:26logical flows? Right. How we work
46:28through this stuff. Sentence uh sense
46:31level style. So drill into how sentence
46:33are written. So sentence length and
46:34rhythm, syntax and construction,
46:36punctuation habits, use of questions,
46:38right? Diction and word choice. We
46:41scroll through this. Do Yeah. Is there
46:43repetition? Are there analogies? Are
46:44there metaphors? Are there rhetorical
46:46devices? Notice how much detail there is
46:48on this one. We're trying to get the
46:50we're trying to get the true essence of
46:52the writing. Most of you guys are just
46:54saying sound like me. We have to be
46:57specific. That's the idea. It is a it is
46:59a machine, right? So, you give it
47:01machine-like instructions. Imagine you
47:03gave this to a human. The the what's
47:06interesting about this is that a human
47:08would have a very hard time maintaining
47:09all this context in their mind when
47:11they're trying to write. A robot can.
47:13And that's what makes this powerful.
47:16Cool. Okay. Keep uh keep roll for me. So
47:20stall and rules the checklist. You can
47:22keep going
47:24and then emulation sample and then we
47:26have the output format again. All right.
47:28And so then this becomes our next thing
47:31um that you can complete like completely
47:34plug in to anything else.
47:37Yes, this is talking to an autistic spe
47:40specialist, right? [laughter]
47:43Um real talk. Everything I do I take
47:45from that perspective more um when I
47:47give instructions that's the whole point
47:52um you can use these uh prompts
47:54obviously in HQAI which is what I'm
47:55talking about but fundamentally so like
47:57I'm like I have I want everyone to win
48:00that's my whole goal here um I use all
48:03the LLMs including including ACQAI
48:07use ACQAI the most for my own business
48:09strategy questions because it pulls from
48:11the most context of business a business,
48:14right? Rather than like this is pulling
48:16from blogs on Wikipedia and stuff like I
48:18want stuff that is the most applicable
48:20for a small business which you know for
48:22our purposes will be you know zero to
48:23100 million. Um and so especially
48:27strategy questions especially like
48:28offerbased questions pricing questions
48:30sales flow sales process it's
48:33exceptional at very good with sales
48:35process. Uh yeah don't sell GPT sound
48:37like me again. Yes, please don't. Okay
48:40so with each of these other ones you can
48:41get the idea for how much depth there is
48:42here. I'm going to just read the um the
48:44headlines um so that you can get an idea
48:47for how this works. So, um for some of
48:50you guys, you guys have sales
48:52transcripts and recordings, which if you
48:53don't, please do that first, but you
48:55don't have VSSLs. You can take your
48:56sales transcripts and say, "Hey, you're
48:58top top tier direct response writer and
49:00sales strategist. You specialize in
49:02converting long-term sales
49:03transcriptions into polished high
49:05converting VSSLs."
49:07So you upload the document containing 10
49:09successful sales calls and your job is
49:10to extract persuasion patterns,
49:12emotional beats, objection overcomes,
49:14promises made and transform uh and
49:16transformations described and convert
49:17them into a cohesive cinematic VSSL
49:19script. And so many of you guys need to
49:22just take this, take your 10 sales
49:23calls, use this to transform them into a
49:26VSSL script, and then read the damn
49:28script. All right, let's go to the next
49:29one. Just scroll all the way to the next
49:30one.
49:34Okay. So, uh, number six. So, uh, sales
49:38call manager, sales call feedback
49:39analyzer. So, this is a big one. So,
49:41many of you guys have sales teams and
49:43you're too lazy to give sales, uh, sales
49:46feedback. So, you can have the team one
49:48of two things. One is the sales manager,
49:50if that's you, you take their
49:52transcript, feed it in, and say, "Hey,
49:53give feedback as like give me the
49:56feedback on this sales script as though
49:57you're a master salesperson."
49:59So then when you go into your
50:00one-on-one, you can say, "Hey, this is
50:01what you need to work on." And then you
50:02can roleplay it. Now, if you need to do
50:04that for the whole team, you can do
50:05that, too. Guess what else you can do?
50:07You can have the team get their own
50:08feedback on their own sales call. Or you
50:11can take your own sales script and get
50:12your own feedback from a master
50:13salesperson,
50:17right? Okay. Let's go to the next one.
50:24Okay. So, if you like specific style of
50:28YouTube videos, right, you're like, I
50:30like this style. I like this structure.
50:32Um, take YouTube videos you like and
50:36paste it in. And then you would include
50:38what you want it to be about. And then
50:40it would pattern match to make a video
50:41that's about a new topic with your idea
50:43with that general structure and tone.
50:46Right? So, you're a world-class YouTube
50:48script analyst and creator. You study
50:50video transcripts to extract structure,
50:52tone, pacing, narrative, mechanics,
50:53emotional beats, comedic timing, if any,
50:55hooks, story arc, CTA patterns, and
50:57signature sty stylistic choices. I will
50:59upload one to five transcripts from
51:01YouTube that I like. Your job is to
51:02analyze them, extract the style,
51:03structure, tone rules, build a reusable
51:06script template. Four, when I give you a
51:08new idea, generate a brand new script
51:10using that template matching the exact
51:12feel of the original videos, but with
51:13completely new concept.
51:16Dallas, how do you get transcripts from
51:18YouTube? You literally there's a button
51:20on videos on YouTube to get them. Like
51:22literally it's lally a button. So in the
51:25description you hit see more and if you
51:28scroll there'll be a button that says
51:29see transcript and then you can just
51:31copy it. It's like you don't have to
51:33have a tool. You can just like YouTube
51:35gives you the transcripts. So you copy
51:38two or three of those and make sure
51:39again with when you whenever you have
51:40multiples make sure that you delineate
51:42star star you know number one star star
51:44star number two star star number three
51:46as you keep going. Okay,
51:48great. Do I prefer HQA for writing copy?
51:51Yeah, I mean I use it. Um,
51:54I'm biased though. So, um, yes. Uh, I
51:59like it for writing copy. Again, I like
52:01I'll be honest, like I use everything. I
52:02use everything. I use HQI the most
52:04around offer, pricing, sales flow, copy.
52:08It's probably the big four that I use it
52:10the most for. Um,
52:12but anyways, let's keep going. So, uh,
52:15this would then output, um, YouTube
52:17stuff from past YouTubes that were good.
52:20So, keep going. Okay. Uh, shorts script.
52:24So, for those you that's that's the
52:25longs format. This is if you have a
52:27shorts format. So, either take the your
52:29best performing shorts or take shorts
52:31that you like that you like the style of
52:33and then you insert those into our data
52:36source and it already has the context
52:38window of your business. And so then you
52:39say, great. Boom. Here's the prompt.
52:44You're a world-class short form content
52:45analyst and creator. You break down
52:46YouTube shorts, Tik Toks, reels, and
52:48understand their hook style pacing,
52:48emotional beats, jump, cut, rhythm,
52:50punch line, and timing, creator voice.
52:51Upload one to I will upload one to four
52:53uh one to five short form transcripts,
52:55videos I like, you analyze the
52:56transcripts, exact structure and tone
52:58and pacing rules. Build a reusable short
52:59script template. And when I give a new
53:01idea, generate a brand new short form
53:03script using that style. Final script
53:05must feel indistinguishable and vi from
53:07the original content while containing
53:09completely new content.
53:12All right, let's go to the next one.
53:18I like Gemini for images. For those of
53:20you curious, I like Gemini and GPT for
53:21images. Um,
53:25I like
53:28I use those I use a lot for images. I
53:30use GPT a ton for like personal
53:32questions. So, more like health stuff.
53:35Like if I like I'll give you a real
53:37story. My uh microwave kept getting this
53:39child lock on it. So, I took a picture
53:41of it and I said, "Can I how can I
53:43remove this?" And it was like, "Oh, this
53:44is series E17722.
53:47Here's the owner's manual. It says this
53:49is how to remove it." I was like,
53:50"Great." Stuff like that. I use it for
53:52those types of things. Um, I use Grock
53:55for anything that I want to not have any
53:58kind of political agenda woven into it.
54:01So, anything that I have that I want to
54:03ask Grock about is like more like edgy.
54:07[laughter] if I have like hypothetical
54:09questions that I don't need the GPD to
54:10judge me, u I'll ask rock. Um, so yeah,
54:14that's that's like what I use those ones
54:15for. All right, back to this. So, uh,
54:18many of you guys, uh, need lead magnets.
54:21Okay, so many of you guys have videos,
54:23have content that you've made in the
54:25past. You take those transcripts, uh,
54:28you take those SOPs, you take those
54:29assets that you already have, and then
54:31you plug it in to create a lead magnet
54:33for your business.
54:36So you're world-class content strategist
54:37and direct response marketer. You
54:38specialize in transforming video content
54:40into high converting lead magnets
54:41designed to create demand, build
54:42authority and generate in leads. I will
54:44upload one to three videos or
54:45transcripts of content I like. It may be
54:47educational, motivational tactic or
54:48story based. You will take this tone,
54:51structure, frameworks, insights and
54:52teaching patterns and then build a
54:53master lead magnet based on those
54:54patterns but with new original content
54:56aligned with my topic and audience.
55:01Yes, Morates. Exactly. If you want to be
55:02the sole emperor of the world, how would
55:04I go about this? Exactly. Okay, so
55:06that's if you have this stuff and need
55:08lead magnets. Let's go to the next one.
55:12This is the last this is the second to
55:14last main one and then I'll show you the
55:15last kind of advanced thing. And I think
55:16we're I think that probably have enough
55:18minds melted for the day. Um so uh once
55:23you have the lead magnet, like once you
55:25give a mouse a cookie, it's going to ask
55:27for some milk, right? So once you have
55:29the lead magnet, what do you need next?
55:30You need the follow-up for that lead
55:31magnet. And so you say, "Hey, you're an
55:33elite email and SMS conversion
55:34copywriter. You specialize in turning
55:35lead magnet downloads into booked sales
55:38calls using this big stack. I will
55:40upload my lead magnet PDF or text. Your
55:43job is to read it, extract the
55:44messaging, and create a compelling or
55:46sorry, complete follow-up system that
55:47converts readers into book calls.
55:50Right?
55:54That's the idea. So, some of you guys
55:55have lead magnets. You're like, "Oh, it
55:57doesn't work. No one books calls." It's
55:58like, well, have you asked it to make an
56:00idealized um
56:03uh follow-up sequence? Right, that's SMS
56:07and email that's proven for that
56:08specific lead magnet.
56:12That's what this helps you do. Okay,
56:13let's go to the next one.
56:17Okay. Uh,
56:20keep going. Keep going. Okay, offer
56:21architect. So, this is one of the big
56:23ones for you guys. Um, this is one of
56:25the like based on the use cases that
56:27we've already pulled from the AI, this
56:28is one of the biggest ones that you guys
56:29use it at most commonly. Um,
56:33so this is going to be a little bit
56:35different. So 11 through 14, the ones
56:37I'm going to show you are actually a
56:39prompt chain. All right. So what's the
56:41difference here? So the first 10 I
56:43showed you were more or less like if you
56:45have this, you know, basically use this
56:47prompt plus your context plus the data
56:49source to get a good output. Right?
56:50That's the idea.
56:5211 through 14 basically stacks or loops
56:55the output to create the input of the
56:57next one. Okay, so output one becomes
57:00input two in output two becomes input
57:04three output three becomes input four.
57:06All right, this is the best you ever
57:08spent. I'm glad Daniel glad to hear
57:09that. Okay, so this is the offer
57:12architect. So some of you guys like need
57:13to sell more stuff or people aren't
57:14buying as much as you want. And so this
57:17is what we'd start with. So you're an
57:18offer architect, worldclass strategist.
57:20If you think like pricing economist,
57:22behavioral psychologist, blah blah blah
57:23blah. Your job is to absorb any offer I
57:25upload and turn in more powerful, more
57:27irresistible, higher converting, higher
57:28profit, and more defensible offer. So,
57:31I'm going to read this one in total
57:32because I think it's important and then
57:33we'll go to the other ones. All right.
57:34So, step one, analyze my current offer.
57:36When I upload my offer, extract core
57:38promise, mechanism, value drivers,
57:39tangible outcomes, intangible outcomes,
57:41time to result, effort required, risk,
57:43pricing structure, guarantees, bonuses,
57:44delivery model, avatar, sophistication
57:46level, how it's currently positioned
57:47versus the market. Then create a
57:50diagnostic report showing strengths,
57:52weaknesses, missing elements,
57:54marketability, risks.
57:58That's step one. Step two, now build a
58:01more irresistible version of my offer.
58:03So offer enhancements, add or improve,
58:05guarantee bonuses, fast action
58:07incentives, delivery upgrades, reduce
58:08steps or complexity, increase time to
58:10value, uh increasing perceived
58:12certainty, increasing tangibility, uh
58:14social proof or evidence, insert
58:15recommendations, value stack, right?
58:18I'll go through all I'm just going to
58:20skip that one. Okay. Pricing
58:21architecture. Here's optimal pricing.
58:23Here's our anchor pricing, middle,
58:24entry, bundles, hybrid pricing, payment
58:26plans, etc. Step three, add upsells,
58:28down cells, or cross sales. This is
58:29optional. Boom, boom, boom, boom, boom.
58:32Step four, build the grand slam offer
58:34version. Create a completely new
58:36rearchitect version of my offer that is
58:38clear, simple, dramatically blah blah
58:39blah blah blah. Keep going through. Um,
58:42include the title, one sentence is
58:43promised, target avatar, primary
58:45mechanism, delivery model, what they
58:46get, line by line, bonuses, guarantees,
58:48pricing, reasoning behind the pricing.
58:49That's a key one, by the way. Uh, and
58:51CTA framing. Step five, high converting
58:53offer, positioning, messaging. So now
58:55give the elevator pitch, headlines,
58:57risk, reversal statement, mechanisms.
58:59Keep going. Step six, now we have the
59:01output format and we can skip the
59:03output. So is each step a new prompt?
59:05No, this is one prompt. This is the
59:07thing is like you guys are putting like
59:09two sentence prompts in and somehow
59:10expecting it to write a book for you.
59:12Like let me give you let me give the let
59:14me give the way it works. The longer the
59:17prompt, the shorter the output.
59:20The shorter the prompt, the longer the
59:21output.
59:24It's kind of like the shorter the
59:25question, longer the answer. Like what's
59:26the meaning of life? Very short
59:27question, very long answer. If I said if
59:30you are a you know uh you know old white
59:34American man born in this time married
59:37to this person here's a book about that
59:39person what is that person's meaning of
59:40life it might be a sentence
59:43the idea is the more context you give
59:44the more it narrows the answer so many
59:46of you guys probably let me let me know
59:47in the chat actually if you guys get
59:49annoyed when you put a simple question
59:52in and you get like two pages of answers
59:54you're like I just needed [ __ ] yes or
59:55no Right.
59:58Do I ever get tired of cranking so much
1:00:00value? Ryan, it's a great question. Um,
1:00:03I don't know. I'll tell you. We'll we'll
1:00:05find out by the end of the day. Um, yes,
1:00:07you guys get that. I get super annoyed,
1:00:09too. Why do you think that is? Short
1:00:11prompt, long response. Long prompt,
1:00:14short response.
1:00:17That's what it is. You have to give more
1:00:19context so that it answers exactly what
1:00:22you want. It doesn't know what you want,
1:00:23so it just gives you a ton of answers,
1:00:24hoping that one of them matches.
1:00:26Okay, now remember what we just did
1:00:30number 11 is that we got the new offer,
1:00:32right? The output was the offer. Yes,
1:00:34I'm tired of it now. Thanks, baby. So,
1:00:36we got the So, remember output, input,
1:00:38output, input. So, the the output of
1:00:41prompt 11 was the prompt of number 12.
1:00:45So, we now have our offer. What do we
1:00:48need? We need our sales page copy
1:00:50generator. So, we say, okay, I have my
1:00:53offer. Now, I got to write the copy. So
1:00:54your world class copyriter specializes
1:00:56in writing high converting sales page
1:00:57based on a clear structured offer. So I
1:00:59will paste my offer architect output
1:01:02including all of these things. So we
1:01:04take the output and we paste it in as
1:01:06the input and then scroll. We can just
1:01:09scroll all the way. That's fine. And
1:01:10then it's going to output all these port
1:01:11portions. Now the output of that one is
1:01:14going to be our sales page. And so we
1:01:16say hey with the output of our offer
1:01:18architect I want you to also create my
1:01:20sales call script. Right? Because we
1:01:22have our architect. You gave us the
1:01:23output. We say, "Great. You're a
1:01:24world-class sales trainer and call flow
1:01:26architect. You turn offers into high
1:01:28converting sales call scripts. I will
1:01:29paste my offer architect output. Your
1:01:31job is to create complete sales call
1:01:32script that a rep can follow." Boom. Now
1:01:34we have our sales call script off of
1:01:36number 11.
1:01:38Yes. The chain prompt. Yes. And then
1:01:41number 14. Great. Now that we have our
1:01:43offer and that we have our sales page
1:01:44and we have our call script, what else
1:01:46we need? We need our VSSL. So we take
1:01:48our offer architect. We put the output
1:01:50in and then boom, we have our VSSL. And
1:01:52so just like that, when you can chain
1:01:55these together, you can build out entire
1:01:58marketing universes
1:02:00the way you want it. And the key point
1:02:02of all of this stuff, guys, is the three
1:02:05wheels I started this whole day with,
1:02:07which is we have to have the 47
1:02:10questions of context around your
1:02:11business, right? And so you say, "Now
1:02:12I'll paste my offer. Create the VSSL
1:02:14using the structure buff." Right? So
1:02:16whenever you see those things at the
1:02:18bottom, that's where you clearly
1:02:19separate. That's where star start star.
1:02:21And then you put the put the inputs,
1:02:23right? Um, [snorts]
1:02:24so all of these will work if you have
1:02:27wheel number one, complete context for
1:02:29the business. Wheel number two, great
1:02:31props, which is what we're saying, clear
1:02:33instructions to follow. And then rule
1:02:34number three, the data source that it
1:02:36can pull from to make good quality
1:02:39outputs. Those are the three wheels of
1:02:41making AI work significantly better.
1:02:44People can tell the difference between
1:02:45truly automated work, which is why
1:02:47nothing I have sounds like I mean
1:02:49doesn't nothing I have sounds like AI,
1:02:51right? I just use it because it helps
1:02:54you get more.
1:02:58That's the game, right? The game is more
1:03:00now. That's the game. If you can do 10
1:03:03times the work, which is the part that
1:03:04you guys I think many of you guys are
1:03:05missing is like every one of you should
1:03:07be able to 10x your output with this and
1:03:09still keep your quality the same. That's
1:03:11the key. If you like I know a bunch of
1:03:13you guys are like I love Moy Minute. Me
1:03:14too. I spend time on it. I just don't
1:03:16spend 90 minutes like I used to. I spend
1:03:17like 20. Now if some of you are like
1:03:20well he only spends 20 minutes on it
1:03:21now. Well I don't know. I do Q&A things
1:03:23that are five minutes and people pay a
1:03:25lot of money to do stuff like that,
1:03:26right? And so like
1:03:29I just don't have to waste my time on
1:03:32lower value work. So, if I know what the
1:03:35core idea that I want to talk about is,
1:03:37once the core idea is there, fleshing
1:03:40out some of the words and the sentences
1:03:41and transitions and like bolding the
1:03:42stuff like that stuff is a pain in the
1:03:44ass. It takes time. It's not valuable,
1:03:46right? The value is in the idea. The
1:03:48values in the narrative, the val value
1:03:50values in the story. That's the value.
1:03:51Value is in the experience. And that's
1:03:53what everyone who's watching this, you
1:03:54guys, you have the experience. You guys
1:03:56are doing stuff in the real world. You
1:03:58need to document that. That's what the
1:03:59data sources are for. We have to have
1:04:01these data sources so that you can have
1:04:02something that's unique, right? We want
1:04:04to use the AI like a workhorse, right?
1:04:07Use it like a workhorse, not to make
1:04:09your decisions for you. Real quick, I'm
1:04:11going to show you the exact 10stage road
1:04:13map from zero to 100 million plus that
1:04:16less than 1% of companies finish. I've
1:04:18now done multiple times and so I can say
1:04:19with a lot of confidence that these are
1:04:21the stages as headcount increases that
1:04:23you need to get through. And I broke
1:04:25each of these down by eight different
1:04:27functions of the business. what the
1:04:28constraint feels like, like what are the
1:04:30symptoms of it when you're going through
1:04:31it, and then what steps we actually took
1:04:33to graduate. And we've done this across
1:04:35software, physical products, uh,
1:04:37service, businesses, brickandmortar, all
1:04:39of this, and it works. And it's my gift
1:04:41to you. It's absolutely free. And so the
1:04:43link's in the description. Just enter
1:04:44your info and it'll spit it right back
1:04:45to you. offering.

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