84 | AI-Powered Content Marketing: Building an AI Automated Content Funnel That Sells 24/7

0:00Hello and welcome to Leveraging AI, the podcast that shares practical ethical ways to leverage to improve efficiency, grow your business, and advance your career. This is Isar Maitis, your host, and we got a really fun and important show for you today. We all know that creating valuable content and distributing it in a strategic way, meaning the right content on the right platforms at the right time, can drive a lot of value and can drive business growth and leads. The problem in that statement is that generating a lot of high-value content in the right format across multiple platforms is really time consuming.

0:37Like anything from doing the research on pinpointing the exact target audience to creating multiple formats of the types of content that it will fit the right platform to distributing it across these platforms, scheduling it, and so on. It's just a lot of work. The good news is that using AI and other automation tools can make this entire process significantly shorter and more effective, still achieving the results for which it's done, which is driving leads, creating additional influence, and growing your business. Our guest today, Aaron Steele, is the founder and CEO of Engin, which is spelled E-N-D-G-N, but sounds like a car engine or a growth engine, if you want, is a content lead generation ninja.

1:23And what he does is he helps business owners and influencers and content creators to generate 3 ,000 plus leads every single month by creating this social media posting machine. And so when I saw his stuff and the content that he's posting, I was very excited. And that's why he's here today. Aaron, welcome to Leveraging AI. In the next few years, AI technology will change our world dramatically. Whether you are a business executive trying to catapult your business forward, or just somebody who refuses to be left behind and want to advance your career, this is the show for you. I'm your host, Isar Maitis, a serial entrepreneur and an AI enthusiast.

2:11You'll hear invaluable practical tips from innovative business leaders, AI practitioners, and some of the brightest AI minds in our world today on how you can leverage AI in ethical ways to advance your career and grow your business.

2:29Thanks for having me. I'm glad to be here. And I'll say one more thing. If you didn't pick the accent from the first sentence, he's in Australia and he's a real trooper because it's like after midnight for him and we're recording a podcast episode. So kudos for that. No worries. Let's really dive right in. I know there's a very structured process, teach people and help people put in place let's just follow your process step by step if i want to create more content and have it very well targeted to my audience what are the steps let's start in the beginning yeah sure so it's it's been a bit of an iterative process over the last little while about finding the best way to to produce and scale that content so i guess the important thing to to note with content is this is ai generated content like we're not trying to hide that but i guess the key difference is that we do a lot of work i guess you could say pre-production work and get lots and lots of context and training data to use in order to make sure that the AI content that we produce actually sounds like you and is modeled on best practices on what to post, how to post and that sort of thing.

3:49We've really taken a lot of the guesswork out of that whole process and really just step people through. So what that looks like from a client's perspective is we have, it's very important that we capture the true natural speaking voice of our clients so that it's not just polished writing that they've that they've used chat gpt to answer questions in a form it's literally having a conversation like this whether it's live or like through the use of voice forms where we pre-record the questions and we get them to actually respond like this so that we can actually capture the transcript of how each individual talks because that's really what we'll separate what we believe separates us from other agencies out there which are utilizing content creation through ai is they're they're not really they focus i feel like they're focusing more on the technique of producing lots of content as opposed to quality content and so when you once you go through the quite a lengthy process of answering like really in-depth questions and my business partner she is the master of this like I focus more on the the technical execution and the distribution side and she focuses on like the content quality vertical and so she really spends so much time and effort getting like extracting all the sorts of information out of people so that we have so much rich content to work with when we're actually creating the posts for them.

5:31So let's say once we've completed everything, we've gone through and we've got - May I pause you for just one second? Yeah, sure. What kind of questions are being asked? So let's say I want to do this myself and I don't want to hire an agency. What kind of questions are being asked that I can practically ask myself and then answer in a natural voice so I have that information? So what are the kind of questions that you guys are asking in order to, I would say, qualify what is the tone that this person usually speaks at yeah so we don't have a set question list it's bespoke to every client that we work with so we based on what they have what we know about them already we'll guide the questions based on that but it's it really dives into like their thoughts feelings passions like what how they see the world how they see their business how they see their customer what the actual everyday life is of the customer i can even bring up a few i'll sanitize them a few examples of the sort of questions that we ask in a moment but it's yeah it's really trying to bring out that conversational tone it's basically asking people about their business and having them respond about their business but from a very personal perspective yeah i would say we we mesh the the business side of things with also the personal brand side of things as well so like where we don't generally work with really big corporate clients it's more sort of the small to medium size where there is definitely still a personal brand element to it a lot of the time and so yes we can ask lots of questions about their business but also we want to know about them as well so because they're going to be the ones who are posting the or are going to be the name and the face on the content, whether or not it's them posting it or not.

7:20We want to make sure that it's unique and it's personable and it sounds them and it's not just going to get lost in a sea of AI-generated content. Yeah, it can be hard to answer what sort of questions because it really depends on each client. No, but I think I understand. You're talking about personalizing or humanizing the business, right? It's hearing from the person about their passions and about their business through their personal lens. And then you capture that. So you capture that as a transcription of these recordings? Yep. Yeah, so transcribe it. Yeah, so literally word-for-word transcriptions of what they say.

7:57So we're looking for the phrasing, the tone of voice, the way they talk, the vocabulary, that even the we'll like get the ai to intentionally mimic the perhaps incorrect sentence structure that they might use because everyone talks it's all jumbled unless you're very good at speaking like we will talk a bit all over the place and using lots of words like that and we're not we're not saying like we will get the ai to write and all that sort of thing like filler words but we want to really capture the unique tone and quality of that person so it definitely sounds like them because i think i'm sure you can as well it's very easy to spot things that have been written by an untrained gpt4 let's say absolutely yeah okay cool so we have a transcription by the way which tool do you use to transcribe the meetings or the calls or the so we use got a couple different things that we're working with the main one that we use is probably voice form so that's a it's a bespoke tool not bespoke it's a tool that we is built for that purpose but they didn't build it for us but it's yeah like literally like any other kind of form but you just click record and you record your responses and it captures the transcript live and it can also prompt them for additional responses based on what they give you.

9:31So it has an AI component, which we're working with them on to intelligently ask more questions based on what they give us. It's a really cool bit of software that we've hooked up with the last few months, which is pretty exciting. Otherwise, we just use standard Zoom recording or something. Yeah, and then transcribe it. Okay, so what do you do with the transcription? so what's step two yeah so step two we have we've just moved over to make instead of zap yes okay we have a transcription pdf so everything goes into a giant pdf that we save so all existing information we just compile it like the transcript is the the largest part but any like website information or anything that we can get we compile it into a giant pdf and this is two 300 pages this pdf oh wow yeah like it's not small and so obviously we need a larger context window for that so anthropic claude is great as well as google gemini because it has a million gemini pro 1.5 it's the verge of endless at this point yeah it's well it's definitely not endless not the way i've used it but yeah so we take that pdf and basically i'll get it to i'll attach it to a form which i'll submit with the client's name bit of background here's the form i submit that and from there the make scenario or automation will use python to extract the text from the pdf like the ocr because if you usually we're working with so much text that you can't just dump it into a spreadsheet it's there's too many characters so we have to bypass that limitation by using that pdf and then And yeah, so we use a bit of Python to extract the text out.

11:20And then I've just recently cooked up a way to have conversation history with Anthropic by the API. So at the moment, if you're on the web browser and you're using Claude Opus or something, obviously you've got a conversation history. but if you ever want to use it with the API, basically every time you prompt it, it forgets what you've said and you have to waste a shitload of tokens. Like I've got a massive bill with Anthropik this month because I've been running huge amounts of tokens through it. But we've just, in the last few days, successfully built conversation history into the clawed API interface that we're using, which is just like passing a post request or something.

12:06we can there's a function within the api to recall there isn't oh there isn't no so how are you doing we're using i have to ask my developer but lang chain i think they have a function that we're using to store conversation history and it captures it's like a middleware build a line that captures the history of everything that was said exactly i'll be honest and say i don't know exactly how it works yeah it's fine by the way i don't think i'll get it and i don't think the audience will either but it was custom built for you it's not like a tool i can go and use tomorrow no that's right happy if people are interested happy for them to get in touch with me and definitely ways that we can make that work for people but and it's interesting it does keep a conversation summary ongoing as well and i was trying to i was debugging with it and was asked asked it for a conversation summary and it was basically just whined to me about how the human kept asking for information without providing it and because I was trying to get like the variable through so that it could read the text and it wasn't working and it kept oh we're being polite but it keeps asking for the same thing it was just yeah it's amusing how it had a bit of a sook to me about it not doing its job but yeah and so from there once we get that conversation history in which I haven't tested that heaps yet because it's only been the last few days.

13:36We then run multiple different scenarios in conjunction. So that'll split off into one prompt, which says, okay, here's the text from the PDF. Here's all the context you need. Here's a very considerable prompt about how to write, say, a LinkedIn post. here's some templates that we want you to model your response on and that'll produce a linkedin post below that it'll be doing the same thing for say an email newsletter based on the content that we've got and just go through the list of all the different content types basically and facebook instagram twitter like we do tweets in there as well and this is all utilizing the writing style that we've given them like two, 300 pages of context of.

14:27So when you're actually producing these articles and blog posts and Facebook posts, it actually genuinely sounds like them, but you literally can't tell. Like I've even got it to write YouTube video scripts for YouTubers out there, excuse me. And yeah, you couldn't even tell that it was written by Anthropik, not him, because it was, yeah. So I want to pause you just for one second because there's two gaps, at least in my mind, that I want to understand how you're doing. So that 300-page document is basically just reference for whatever AI model, and because it's so long, it probably has to be either, like you said, Cloud 3 or Gemini Pro 1.5.

15:08For those of you who don't understand what we're talking about, these AI engines have a limitation in the amount of memory they have in each chat or in each API call, if it's on the API side, and it's limited to, It's called tokens, but a token is about 0.7 words. So OpenAI just actually increased theirs to 128 ,000 tokens in GPT-4 Turbo. That means about 100 ,000 words. Cloud3 has 200 ,000 tokens, which is about 150 ,000 words. So it's just a lot more words. And Gemini 1.5 Pro, which to get to it is not the regular Gemini, but like their back-end tool that you can play with. it's like a sandbox to test their new tool.

15:53It's not the formal release, but it's available and it's working is a million tokens, which about 750 ,000 words. So if you want to push a 300 page document through, then you need the larger context window. So that's like on that. But so this is only the reference, right? This is only, this is the style, the tone, the voice. This is how we speak. This is okay. How do you pick the topics, the content you're going to generate? Okay. So So I understand now we have the reference on the tone, but what are the actual topics that you generate? And so let's start with question number one. How do you decide the topics of the content?

16:30Yeah, so a couple of different ways. For example, I haven't asked for permission to mention his name, so I won't, but there's a fairly well-known YouTuber in the AI space that I'm working with, and we take an extract, or sorry every time it'll automatically send the transcription to us and we use that transcription as the topic so we've already got the context library of how he talks based on 150 video transcripts that's a big document and we've already got the transcript from the most recent video and we say hey here's the existing history of how he sounds here's the the topic that i want you to talk about and then we just push that through the rest of the mechanism and it will create the content based on that video but that's one way that we do it so one option is basically you start with a one type of piece of content and really just use your engine to yeah pun intended to repurpose it to all the other different options and usually i assume start with whether it's that client or another with a live sorry with a video recording because that can be converted to basically anything yeah yeah so yeah there's i guess there's the ideation stage which was it's an ongoing development i suppose so but you can like the very early days the way i had this set up was i would just get chat gpt to say i'd say to look i'm an ai entrepreneur ask me 10 questions so that I can answer them like I'm on a podcast.

18:14And then I just recorded myself and each of the answers to those 10 questions was a different topic. And that's what I pushed through. And that was the content right there. Now I am a bit more sophisticated than that, but not much. I, yeah, like we'll get still using AI a lot of the time to generate content ideas, but using more like book style titles rather than just a blank title. And it will generate the content based on the hook and the existing content. But before we get to that stage, we also have, I've got a robot that will every day based on our context and like it has an understanding of what we do or what the client does, it will generate different keywords and it will then go and scrape the Google search results as well as like a variable keyword like opinion or news or whatever.

19:14There's a few different things that we use and it will take the contents of the search results that it gets back from those and then compile keywords and topics from those. So it's an ongoing thing that happens every day basically then it creates more content topic ideas and then it will reflect on that and then ask provide questions to respond to about those as well so that's like an ongoing thing that is dynamic that depends on what we tell it to search for basically but yeah so it's and is that done through what tools do you use in that process like for this curation of ideas yeah so i'm still using make for that so i plug in browse ai which is just like a web scraping interface and so you have a whole stack of pre-trained robots as they call them and so you can say i just want to have it like a google search robot and you just put in the keywords that you want and tell it how often you want it to go and collect those search results and it goes and does it or you can connect it on make and it will integrate with the rest of your processes so i had that scheduled for every day and then it just pushes the search results through based on what chat gpt or claude or whatever we're using in that particular use case tells it to so yeah it's pretty pretty handy tool there's you know i'm sure there's ways we could build like a bespoke wet scraping application using python but i'm happy with this at the moment yeah so for those of you who don't know what make is or what zapier that was mentioned earlier these two platforms are probably the biggest most commonly used automation platforms in the world today and they're basically the glue between everything and everything on the internet so you can take data from any it's not any platform but they have literally now tens of thousands of platforms they're already connected to.

21:17So you can take data from one source, let's say Google search and push it into ChatGPT and then get the output from ChatGPT and put it in Google Sheets and then take the data from Google Sheets and aggregate it and send it to a PDF, like literally anything to anything, your CRM, your email marketing automation tool, like whatever tools you have most likely are already in there. And you don't need to be a developer to actually make those connections. It's basically telling you the type of data you want to bring. First name, last name, topic, idea, content, like whatever it is you want to pull. And then it knows how to send it correctly between all these different platforms.

21:52So it enables people who are not developers to build really cool and sophisticated multi-step automations like Aaron just mentioned. So you can take the data from, you tell it what to search at what frequency with one platform, you take the content from that, throw it to ChatGPT. It knows how to summarize it. It puts it into a Word document that is saved to a Google Drive that can then trigger something else. So you can build all these things that can dramatically reduce the tedious work that you otherwise would need to do just by copying stuff and moving it around and converting it to different formats.

22:26Yeah, absolutely. And just to make note of, I agree, yes, you don't need to be a developer, but you really don't need to be a developer full stop. And this is still a bit of a controversial opinion, but I've built a lot of stuff with Python and I am definitely not a developer and it's just by working with multiple language models like ChatGPT and Claude and just saying this is what I want to do. Like I literally sketched out the diagram. Like I've got background in business analysis and all that so I'm not completely clueless with how to represent technical ideas but I sketched out a diagram like a data relationship model of how I wanted the software to work and said, this is, gave it to Claude and said, this is what I want.

23:13Can you code it up in Python for me? And then got it to walk me through how to host it on my own device and then put it up into Heroku. And then I got 90 % of the way there. And then I said, okay, I don't want to do this anymore. I gave it to a developer who was like, oh, and fixed it. And yeah, so like you can go a long way And the gap between developer and non-developer is getting smaller and smaller with these tools. I agree with you 100%. I'm just like you. I've never written a line of code in my life. And I'm doing really cool stuff. Short, like I'm not recreating FIFA 2025 or something like that.

23:54But for daily small applications that do stuff that I need, I create code with Claude and ChatGPT regularly. And when it fails, I go back to it and tell it what happened. I'm like, okay, this is what happened. It's giving me error 0361, blah, blah, blah, blah, blah. And then I tell it this, oh, okay, try this code instead. And then it's giving me a new piece. And I don't have a clue where the code is good. I don't know how to read it, but I'll try. And usually within four, five, six attempts of back and forth, it will build something that's actually working and doing what I need it to do. Yeah.

24:27And the next iteration of that workflow, though, is agent or agentive workflows, which I've been working with as well. So instead of your eye writing in, going back and forth between the code and the language model, you can set up a big, like a smart, expensive language model like Opus Claude, sorry, Claude Opus, and giving it the instructions of what you want it to do. and then it passes that task to a smaller developer model, sorry, a smaller language model, and then they can bounce back off each other and they're able to test it. You can equip it to test the code and it can test it and review it and do all that stuff itself very fast and then it will spit back out once it's done the working code that you would have had to have gone back and forth manually and now it's taking care of that process for you and that applies not just code but like content and all kinds of things like the agentive workflow is is the next big thing i think absolutely the only one who thinks that as well no no absolutely it's going to be probably as big as a jump as chat gpt was when it first came out when real agents will work properly.

25:47But let's go back to our thing. I think I threw us on this. So quick summary, you train the model by giving it a lot of background on how the person talks by literally letting the person talk. So that's step one. Step two, you figure out what is the content you want to create, either by content that person is already creating or the company is already creating, or by doing an iterative process with some automation that goes to the internet and looks for specific topics that are relevant to the industry, the target audience, the time, the month of the year, like whatever other information is relevant to your industry and your audience.

26:29And then you have the ideas for the content. Then you feed that into all of this together into Claude or GPT 1.5 Pro. And then it spits out multiple pieces of content that are relevant to whatever was created. can you share the exact prompt you're using in those tools can you open it up and say okay this is what you do because i think it will give people a very good context on the how and not just what yeah no totally i'll if you give me for just opening my browser up just quickly i'll read out some of what yeah that would be awesome and the just while i'm doing that so the process i've set up an interface let's say app.engine.com so app.endgn.com i've built like a sas platform where you can go in there and you can do all that exact process that we just discussed yourself you can upload your context yourself your writing style yourself and you can edit your prompts and edit your writing strategies templates everything that we do behind the scenes and you can connect up your social accounts to it and you can just push content out that way and or people just pay like a sass fee yeah yeah also pay us like it's pretty pretty hands-off like some of the clients that i work quite closely with i will build a similar kind of workflow with for them but it'll be specifically for them with their own prompts and all that kind of thing so it's we bypass the sas part and just hook it straight into their socials but um and then yeah there's like a an approval kanban board that all the posts land on which you can go in and just drag it over which are approved um okay so i've got a make scenario here called blog generator which so this generates a so this is i won't give too many details because this is for a specific client yeah just go beep every time there's a name of a person that will be fine or a business yes So we go, this will generate like a five-day challenge, a blog post, free assets like a newsletter, a quiz and social media posts all in one.

28:59So a five-day challenge. Let's pull up the prompt for that. All right. You are an expert ghostwriter. Your job is to first conduct an extensive review and analysis of the content of this document, taking care to note the unique style of writing, speaking, turn of phrase, content expertise, and manner of speaking. And then it gives the variable for the PDF and put that in quotation brackets. Now that you have become the name of the client and understand their style of writing, interest, experiences and verbal mannerisms, your job is to create a five day challenge related to their business aimed at coaches and consultants doing two to five million dollars in revenue who are at a growth friction point.

29:45challenge should educate participants how lost profits are impacting their business and so it goes through some pretty context specific stuff about the client i'll skip through that but basically yeah most importantly write it exactly how name of client speaks drawing on the unique story insights and way of speaking to build connection and credibility make it interesting exciting and highly valuable and actionable the goal is for participants to think if this is free content the paid workshop must be amazing and then in capitals do not sound like an ai do not respond with anything other than a requested text no preambles no conclusions no pleasantries i do that because ai always has a habit of saying okay sure here's the i'm like no i don't want that and i don't want the like here's the thing that i've just written for you like it always tries to do that i'm like no i don't want that like just give me the text give me the thing yeah because it'll find its way into the post otherwise and it's you have to then cut it out with a like the structured text extraction module with gpt and it's just a pain so i'm always yelling at it and being mean to the the language models but they're pretty useful so question question two questions about this one so this is running it on claude you said so this yep so that's the claude uh opus three prompt yep and the follow-up question now that i know that it's running on claude and i know what you're sending is does it actually do it every time like one of the things that i see like i have a lot of gpts that are running for my business and so on so it's a similar thing right it's a gpt is just a fancy recurring standout standard prompt right that's what it is with some background information the the problem that i'm running into is that every now and then it will not do exactly what you tell it to do at least the way i see it on chat gpt i've never tried to run something regularly on clod just because gpt's currently only run on chat gpt so do you see it that sometimes it will write that extra stuff or these kind of things it's pretty good usually like i haven't encountered too much of that like i have i do put in place like that attentive workflow as well so i'll get it to check its own work after this so that and i'll say here's the criteria make sure it doesn't have the preamble make sure it doesn't do this doesn't do that does this it meets this criteria and if not loop it back and get it to do it again.

32:15Oh, so you send the outcome of this through make to a different conversation. Yep. Verify that it's really doing what it's supposed to do. Yeah. And I use a less expensive model than Opus. Yep. Because, yeah, Opus is not cheap. And yeah, like I'll get it to loop back on itself a few times if it needs to. and basically there's eight approval gates and if it approves it the first time, it goes off and it goes to get scheduled. But it has eight chances to get it right basically before we get to the very end. If it still can't get it right after eight pieces of constructive feedback, it still just goes through to the scheduling part and just flags as we couldn't get it right sort of thing, but that hasn't happened.

33:08so that's probably just being over engineered but so i want to i want to now explain to the people what we're just saying and as far as pricing and so on so each and every one of these models when you run them through an api which is what aaron is doing so he's not going and copying stuff into the chat that you usually go to he's sending it through an api call which is multiple tools that can do it or even through make and zapier and a 10 like all these tools can talk to the apis There's a tool I really like that you may or may not know that is actually pretty cool. That's called Open Router. And what Open Router enables you to do is just like a hub of all these large language models through APIs.

33:48And you can connect just to Open Router and then call more or less any large language model through an API. So you have one API connection and then you can call by name whichever large language model you want to use. The other thing that it shows you the pricing for each one. So to put things in context of what Aaron said, that Cloud3 Opus is very expensive. It's the most expensive tool out there, both in the content that it's getting in. So you're sending it content, such as those 300 pages, as well as in content coming out. And again, to put things in perspective, an open source model, a good open source model like Mistral 7B, which is the name of a large language model, costs 12 and a half cents for a million tokens.

34:32So we spoke about what are tokens. So 12 and a half cents for a million tokens. And Claude 3 Opus is$75 for the same million. US dollars as well. So it hits us even harder. So it's just to put things in perspective, that's obviously about what, like 700 times more expensive than running it on Mistral. The quality is there and the context window is there. But like Aaron saying, there's ways to trick it. If you want to just test the content, you don't have to run it through a$75 dollars, a million tokens like option, you can run it through cheaper options. And the trick here is always to optimize quality and cost, right?

35:11So you want to have the right tools for the right thing that do a good job. It doesn't have to be the best job. You just have to be good enough job to get the job done. In this particular case, good content that drives leads to a business. If you can do that for$0.25 instead of$75, that's a good way to do it. So picking up different steps and running it through different of these lenses in order to get a good outcome is a brilliant way to optimize both for quality and for cost. So kudos. Yeah. Great idea. Yeah. That's why I'm so excited about getting conversation history working with the Antropic API as well.

35:53because one of the reasons I was getting hit so hard with API costs was because if I wanted to generate 10 posts with 300 pages of context for each post, I was getting hit for all the tokens every single time I ran it. Now that I've got a conversation history component, I can just run that context once. And then just like you do on the web browser, just keep hitting the same conversation and it remembers the context. and it doesn't need to be reminded or starting a new one every time. So it's significantly cheaper than the way it's set up by default. I'm pretty excited about that, to say the least.

36:35Makes perfect sense. Yeah, yeah. Okay, so now we have figured out the tone. We have figured out what the content that we want to create. We have created the content. We check the content. And then you said it goes to scheduling. I assume, again, that's a connection through Make that goes to a scheduling software, whichever one the client uses or that you use. I don't know which one you're using. I use Metrical because they allow us, basically from an agency perspective, they allow us to connect up to 25 brands on the price point that we're on, which means each brand can connect basically all of their socials.

37:14And we built a little integration so that when we, because everything goes over the Airtable when it's like ready to be published when an Airtable record or a post gets approved it will get pushed to a auto list which I love in in Metrical so my like I'm not I've got Hootsuite as well but I don't use it anymore because you still had to specify the schedule every time you wanted to post it whereas in Metrical I can just set up predefined times and times of day frequency days of the week and it'll just act as cues that i can just send 100 posts to and it will just host them at the predefined times which is great it's one less thing i have to think about so yeah that's the tool i use i'm not sponsored by them or anything like that yeah no it's i i love this kind of advice this is real life real people real use cases that's the best advice there is yeah that's and then yeah like it's that's that's the written component of the post i also have an image component so linkedin i will collect like 150 180 roughly like selfie type images of myself or the client or they can be more photo shoot type images and just have those set up in a google drive and i'll just get make to collect to produce a random number and then like use that number to determine which photo it pulls and then just post that photo with the the post on linkedin and that's a really basic use case for it but yeah we also can use tools like creator mate which is like video publishing which with dynamic text and images and videos I use that to create like carousel style posts on LinkedIn and the other one that we use for still images is switchboard canvas or switchboard.ai I'm not sure what they're actually called but switchboard.ai I think is the the name of the actual site but again that is like dynamic images and text if i'm the way i would use that is i go in and i set up these templates and you can actually connect canva within switchboard ai and do the design in canva and then just delete the text out of the design pull it back into switchboard and then like position dynamic text boxes where the original text was and then you can pull it out from make or it doesn't integrate with make directly so i'd have to use the api but in zapier you just pull whatever text you want dynamically straight onto the image and you can do like quotes or whatever and it's yeah it's a really good tool which doesn't get talked about enough but it makes the whole image component of socials automatic as well yeah a little bit of a very very cool i i have a question for you did you try using one of the image generators apis in order to generate images based on the text in the actual yep post yes i do this manually now i've never tried to do it through the api but i would use let's say i use chat upt to have the whole conversation on a post i want to write or a presentation I want to make, I will ask it for recommendations on what might be a great graphics for this kind of audience with this exact post.

40:58And then it gives me three ideas. I'm like, oh, I like number two, go create it. Or I like number two, but I want to add this and that. Then they will go and create the image for me. So did you try that like at scale through the API? Yep. So I've got two ways that I do that. So the LinkedIn way that I do it, or it doesn't have to be LinkedIn, but I was trying to be a bit less creative on LinkedIn. But I just connected to the Unsplash API, which is like a stock images site and would get like GPT 3.5 to do a quick summary, get it to review the post that was written and just say, I need you to spit out five keywords.

41:40And then I would just pass those keywords through to Unsplash, get it to select a random page so I don't get the same image every time and then just pull that stock image based on the content of the post. So you're using stock photos and you're not generating AI images on the fly per post. I've done both. So yeah, I also would use, I use Dali a little bit, but I think I've moved over to mid-journey and playing around with stable diffusion as well. But yeah, same kind of thing, using the content to generate posts and then I just have a retry function where if I don't like what it's come up with, I just click a button or drag it into the retry column or something and it'll get rid of the picture and come and do another one.

42:29Yeah, I've done multiple different ways to generate those images. I guess it depends on what the clients are looking for. I think people are still a bit scared of doing AI images, but like mid-journey version six, you basically can't tell anymore that it's AI. It's incredible. I want to summarize quickly because you just mentioned a word that makes a lot of sense to me and you mentioned it before. And I want to add a little more context about it, about the Kanban board and the columns. So reading between the lines of what you're saying, there's a Kanban board that really shows the human operator what's happening in the process that all these AIs are doing in the backend.