AI Operations: Using AI to Scale Your Work

Key Takeaways

I actually see AI not only being helpful for the stuff that I'm not good at but I see it even more so as a tool to scale what I am good at or like what my team is really good at like our core competencies today I'm very excited to be joined by Rachel Woods if you don't know who Rachel is she is an AI strategist and founder of divy up an agency that helps agencies develop their AI operations she's also the founder of of the AI exchange a membership for AI Ops professionals and Consultants she's also a former data scientist from Facebook and her course includes she has many courses but one of her courses includes prompting for AI operations another one is intro to AI operations Rachel welcome to the show how you doing today I'm doing great thanks so much for having me really excited for this I'm super excited that you're here so today Rachel and I are going to explore how to use AI to scale your work and we're coming at this from an operations perspective which I think is really exciting um before we get into this like I'd love to hear a little bit of your backstory how in the world did you get into AI uh start wherever you want to start yeah uh of course so I might have a little bit of a unique background in the space and that I've actually been in AI for a while um I kind of started my career out in uh the intersection between Ai and marketing actually um so my degrees are technically in marketing and then management information systems which is basically like fancy course words for uh data science and so uh I started my career at um Facebook actually working in their R&D Department literally doing AI in the ads ranking stack so like the perfect blend of marketing and data science um that was really where I kind of got both the marketing and AI uh bug if you will um and turns out that actually up being a really great launching pad for my whole career um in that job and that was you know a long time ago we were using Transformers which is the tea in GPT that now everybody knows we're actually using Transformers in the ads ranking stack so I was getting exposure to that technology using it and really like The Cutting Edge you know team and place um like Facebook and then um that's AIG just out of curiosity like help us understand what that meant for ads just because a lot of people listening are probably have been using Facebook ads or currently using Facebook ads just curious yeah I mean there are so many applications uh as you probably can imagine the whole ranking algorithm that picks what ad to show you or what post to show you is really really really complex um but I was working on a lot of projects where we were trying to understand the meaning in both the ad creative and also the ad copy and we were using Transformers to kind of do some of that learning and understanding and um you know one of the projects in particular I worked on was how to help small business ads learn faster so they if anybody's been in the ads manager your ads can exit the learning stage faster um so we we were just doing all kinds of uh really really exciting and and cool like R&D projects way back then with much worse versions of Transformers what we have today so it's been really amazing to also see like the technology evolve from that side cool so at what point did you decide to to leave Facebook and what came next so I've also been an entrepreneur kind of my whole life um when I was 15 I started my first business I had to get my dad to coign my business license um and so Facebook was amazing place to work but um I really knew I wanted to go do my own thing so I left and that's when I started um my previous company which was an e-commerce and marketing platform focused on the Alcohol industry and especially independent Wineries and again there with with that business we were using AI a lot uh in the um product and services we were providing including using early versions of GPT to write marketing emails for wineries we called it like TurnKey emails they ask us if it was magic like it just you know really fun um again the early versions of a lot of this stuff and so yeah I did that and then um ended up selling the business in 2022 and I really had this bug of like oh my gosh especially this flavor of technology is just so powerful for being able to help businesses operate and you know I as I'm sure many people who've uh done anything entrepreneurial you know like man doing business and operating business is so hard like there's just so much work that goes into that um and seeing that AI could be this amazing unlock um on a whim I decided to start a Tik Tok account talking about Ai and the usage in business uh in November 2022 oh good timing was literally like 30 days before Chachi BT came out um so like I got all of my like awkward dancing Tik toks out of the way I had a couple of like you know uh good videos on AI and stuff but then um yeah when chat came out and people really excited and interested um I just really leaned fully in and uh started creating content um and just trying to be a helpful resource for people as they're trying to navigate um and learn about this like amazing new technology that honestly I've been like pretty obsessed with for a while so so has Tik Tok been your primary platform that you've been creating uh video content on or have you been using YouTube and other platforms as well so haven't really YouTube is like the one platform that I haven't like gone super deep in but um yeah I do a lot of Tik Tok a lot of Twitter LinkedIn has been a really fun platform for me recently um I'm kind of everywhere uh but it's yeah that's been a totally new part of the journey as well so tell us kind of what you're doing today then so today um I have two businesses as as you mentioned in the intro um we have the AI Exchange which was created um again like kind of right when chbt came out to really be that educational resource and help people learn about how to use AI applied like inside business inside work um and that's where we started to really uncover this AI operations concept we were talking about it like in a brainstorming session with the whiteboard in like February of 2023 trying to figure out like what do you call this whole thing of like using AI to actually like do do the work and execute stuff and be like a you know not just a helpful intern but assistant and all all these things like what do you call that and so we started calling AI operations um and then alongside that we started doing a lot of different Consulting and work with a bunch of different types of businesses and um really ended up finding this amazing uh you know place like near and dear to my heart of working with marketing agencies and other like B2B Service uh agencies um and helping them figure out again like how do they take what AI is really good at and complement their teams and their work and their operations so that they can scale you know and have a much more big impact and so um that's what we do with divvy up is that's our agency where we actually like come in help you with your business um and get to do a lot of really amazing like implementation projects um uh alongside with that what an incredible story and journey there are a lot of people listening right now who are using Ai and learning to use AI because this is called AI explored and much of what they're probably doing is things like creating content or helping them with their messaging and some of their marketing but when it comes to an operations side of thing things make the case to everyone listening why AI can improve the operations of any kind of business yeah so I think first of all something that might surprise a lot of people is that I actually see AI not only being helpful for the stuff that I'm not good at but I see it even more so as a tool to scale what I am good at or like what my team is really good at like our core competencies and so I think like a lot of times you know people are like using trash TBT to kind of fill gaps of like maybe like they're not um the best like they don't do a lot of like marketing copy and so they're using it for that but like if you flip that on its head and you think about what are the systems and processes in your business that you are really good at that are your proven methods like you can actually use AI train AI to scale that um and so like operations uh is admittedly a pretty like big term like it can mean a lot of different things a lot of different types of businesses but um like one analog I'll give you in the agency context is like um especially when agencies get a lot larger they have kind of like an Ops person whose job is a lot of times to like set up the Monday boards do all of the process automation think about client onboarding think about the experience think about um efficiency the whole like client um engagement like that's a lot of the same type of stuff you can actually pull AI in to help with and scale again like uh building off of what you're already good at um so it's not just about like you know things like content creation like we actually uh I think in any business there's use cases along like the whole spectrum of everything you're doing and agencies you know especially like we talked about a lot um there's you know things in the client Outreach process there's things in the client onboarding process there's things in shaping the strategy auditing what clients are doing there's stuff in the reporting and Analysis like like again any proven method that you have in your business you can actually think about how could you set up AI to scale the operations like of that method or process I love that um and you know you're talking about agencies and like you know if you're an agency obviously you've got you got research you're doing on you know who you want as your customers you've got proposals you've got reporting and Analysis you know all the things that an agency would do and everyone who's listening who's not an agency there are things that we do as marketers right like if you're in the business of creating content you know there's a million things you have to do like what am I going to create my next piece of content about how well is that piece of content performing should I create more content about that topic um did I do a good job creating that content right is are the attention graphs on these things good or am I getting them on of views I mean there's a million little things right and I love what you're saying because so many of my guests are utilizing AI to um supplement their gifts and skills meaning to use to use it in a way where they're not strong I really like the idea of using it in a way you are strong because in my mind that means you can train it well right that means you you understand where it's weak and where it's strong and all of a sudden now you can become effectively way more efficient are you finding that um when people businesses entrepreneurs are using AI to streamline their operations that has a massive upside for them and if so what are kind of some of those advantages people are are receiving so I'll give you like one of my favorite Concepts on this exact point which is the idea um started calling it like the unlimited time offer which is exactly what you're saying what are the things that if you even could step back and think I have unlimited time to do solve some problem or do something for this client or this project or this campaign like if I again have unlimited time to go do something what would I do given like my expertise and you know what data I wish I could pull what stuff I think I wish I could analyze what things I wish I could research all that stuff and then can you pull pull that together um and basically with AI package it up so that you could actually do the thing that you know you don't have a limited time for but now with AI you can kick stuff off and it can go do stuff for you like I'll give you an example um we see this a lot with uh people thinking about um auditing existing strategies so you know if you're uh like looking at a new um a new client or like a new uh brand and you're looking other their social media you know you might have time to scroll through 10 20 posts maybe like it just takes a lot of time to go through and analyze that stuff what if you could go through and use AI to analyze the last thousand stuff that they posted right and then pull in some scorecard method that you've developed to say like hey here was like the high ranking topics here's the stuff that's resoning with your audience here's like the stuff that we should dig more into here's the stuff that was off brand here's the you know you can start to like think about how you could um shape this unlimited time offer and what we find you know you're asking about like the impact the impact of AI on every business I'll just say like it's different right it really depends on the mechanics of your business and what the bottlenecks really are like you shouldn't just sprinkle AI in for the sake of it like you should figure out like what are really the limiting factors of your business and figure out like how can AI um like uh either change or you know fix that uh bottleneck change the equation um but something like being able to yeah like package up these unlimited time offers and then use those either in the sales process or as a initial onboarding thing or even some people are choosing to put it in the Outreach process to new clients as a way to like prove kind of what their method looks like like there's just so many possibilities and um honestly that's a huge part that's exciting about my work is we just to like sit down with really really smart marketers and really smart people and help them kind of uncover like you know what expertise do they have that they could be training AI to go and do for them and then you know our skill set is pulling all that all together and like making it happen so it's very fun I love this question that you said which is if you had unlimited time meaning if Time Was No Object what would you do right because all of us have things we really want to do but for what whatever reason we don't have time to do it and if you imagine the answer to that question and then you apply AI to it which we're going to talk about here um it actually might make it possible and that's like a massive unlock for a lot of people right so okay when it's comes to using AI to improve our marketing operations or operations in general um where do we start uh let's just start with like what do we need to be thinking about first what are the things we need to be like processing if you will in our own Brain before we start using AI yeah so um as I said I really like to think about every business's Journey with AI is different and you need to figure out like what's going to make sense for you there's not a like blanket here the like three use cases right so what I would you know rather like give people and what we work on with people is like giving them a tool of How to Think Through like how your business operates today and then also as things change how you can like continue looking for opportunities um so one of the things that uh like we start with first is figuring out do you actually have quick wins in your business for AI that you're spending enough time on on a repeated basis that it's worth spending the effort to train AI to do something as a simple heuristic for everybody if you're not doing something like four hours a month and really I would say like four hours a week if you're just getting started like look for the stuff that you're spending four hours a week on then it's probably not a very like quick win it might just be um something in a second bucket the second bucket that we talk about um with folks is the stuff that again like because you don't have unlimited time you're not doing as much as you could but if you uh trained AI to help you scale that okay then that could actually be a really big win a really big growth driver for your business help you get new clients help you um um you know close customers convert customers all that stuff um but we first like yeah again like really look at the workload um that is associated to whatever the use case you're talking about is so real quick just to clarify first thing is to ask yourself what am I spending a fair amount of time on ideally on a weekly basis like four hours a week for example um or maybe 10 to 15 hours a month or something along those lines those are the that are highly rep repetitive process that would be an obvious candidate to apply AI to the second bucket I think I heard you say something along the lines of will it impact Revenue can you elaborate on that a little bit yeah so that's that we we call them kind of the big wins so there's like the quick wins which is the stuff that sometimes you just need to free up bandwidth and then there's like the big wins which is if you had a way to do that type of work at a scale or economics or um a lot of times in marketing ends up being a level of personalization to the End customer in a way that like you can't do today would that have a really big impact on your business where either you could again close more clients charge more um upsell current clients like you just have to think through what that actual bottom line is um but those two categories are I mean there's so many again so many use cases and we really try to like look for those um inside businesses so once we've identified these use cases like how do we even know if they're ready to for AI I know we talked about this a little bit right about how there's some things that kind of are easier for AI to tackle yeah so the way that we found to um kind of be the simplest heris on this is actually thinking about if you um like think about training AI like you're training a person to do it and so if you think about anything in your business just in general scaling that thing is going to require that you probably document or have some sort of guides or we use this term we call playbooks a lot which happy to go more into um but you you have to have some level of documentation or you have to be confident you could build that like pretty quickly um and uh if you're not if you don't feel like something could be documented then that's usually like a sign to double click into it and figure out why and it could not be a good use case um for AI I would love you to talk about the Playbook thing a little bit since you just hinted and teased at it of course I'm going to ask yes so um yeah so we've really found that the best way again the best way to think about training AI is like you're training somebody um I know a lot of people love the uh think of AI like your really smart intern I am like 100% on board with that and I think that you can take that one step further and think about if you had to build documentation to train an intern to do again something that you're good at that you're trying to scale then that's what you need to do and the way that we've found that worked really well for that is what we call um building these playbooks which I actually got the inspiration from some of the best marketers I've ever worked with they had these like amazing playbooks that um I thought really struck a really good balance between giving the high level context and vision and Framing and mindset for how to do certain type of work while also having the level of details that maybe if some people are familiar with like Sops standard operating procedures or kind of like stepbystep documents that some businesses have if you can build um a guide or Playbook that mirrors those two where you have again the context and the steps then that is like the perfect asset to structure a process to then where you can turn around and start go thinking about how to use AI for those different pieces so have you done this oh yes this is like all we do okay do you have an example of one that do you have an example of one you've done maybe for yourself or for a client that you can talk about um we have so many uh unfortunately a lot of the really really fun ones are under NDA so I can't talk about those but um I will share we we did one that was um a little more experimental uh recently which was kind of an idea I had from I know how much time you spent on LinkedIn a lot yeah a lot okay you know like the LinkedIn like really noxious AI comments like they drive they drive me nuts yeah yeah so um we were thinking could we build a Playbook to write like not icky comments um and in fact like you know I post a lot of content on LinkedIn I have some pretty clear goals around like you know ideally in my comment section I'm like providing more value I'm really appreciating when people are contributing their thoughts to whatever I'm talking about um you know asking follow-up questions like I have all these like goals of like what I want to happen in my comments and so um we built a Playbook uh like literally to mirror exactly like Rachel's thought process to responding to comments um and it was it was really fun it was really good it was like scarily good um some of the numbers out of it at the end and and something to mention too like when you start getting to the place where you're really like teaching AI to do stuff like people would be surprised how much you can control and how good it can get to where you don't even have to think about editing the output anymore like it's just it really is like mirroring you've taught it just like hopefully if you teach an intern to do something eventually you're not editing their work anymore so for this experiment we got it down to um somewhere around like 70 to 75% of the time like I was not editing anything in the comment and the rest of the time um kind of it was missing some context that we could have pulled in if we were going to continue with the project we decided to not actually like go to use that so if you're in my comment section on LinkedIn um it's still me but um it was just a really interesting experiment to see like can you Playbook something that feels so personal like responding to comments like Rachel would um and yeah it's fascinating and if and if I mean if you built it right and there was a review process before you you you submitted or whatever that's even more interesting right because I can imagine the AI looking at their personal profile understanding what their business is all about and then looking at the context of their comment on your post I mean like it's fascinating it's scary and it's exciting that you decide to run it as an experiment which I think is also cool because you decided to not proceed with this and that's another take-home lesson for everybody who's listening is you could go ahead and try some things and maybe you feel like it's not really relevant for your brand to be able to do some of these things but at least you learn something from the process right totally yeah um it's a yeah and like just to share too I think for you know everybody especially like a lot of the marketers who are listening like like when you just think about your like dream day of building like writing the book on your process or like um where you're you know uh trying to build that that slide deck that you're it's going to explain to people like this method that you figured out like take the those thoughts and that energy and like that is exactly like what it what you need to do to get to the place where you're articulating stuff so that you can train AI to do it um and then yeah to get like practical about it once you have these playbooks um the way to to think about it is usually like at the top you have like context and mindset and a lot of this stuff which gets maybe reused across a lot of different prompts that you might be using when you actually apply AI um to running the Playbook uh or if you're automating you can pull it in as context in different ways um but then the next step that uh we work with a lot of people through is actually starting to like write prompts on those specific sections in the Playbook um to where they can see how AI can start doing it um and then we kind of help them get to a proof of concept uh before like a lot of times like we kind of um work out some more in-depth techniques uh to get stuff to really really work and uh and be great but yeah let's talk about your prompting uh process a little bit because I think that'd be really helpful for people yeah um so so the first thing I would say about prompting is there's a difference between prompting and prompt engineering and I think that there's a lot of um public discourse that prompt engineering is not worth learning because AI is just going to like do it and all that stuff and I would say for 99% of people you should not learn prompt engineering because it's it is engineering like it's just very like scientific testing like all that stuff and yeah AI is like pretty good at a lot of that but on the other side there's like prompting which I would just say is like literally can you communicate or prompt AI to do what you want and that I think is an essential skill that is a skill that um it's like like fundamental communication at work like you you have to be able to think about how to articulate what you want done um considering the the strengths and weaknesses of the thing you're communicating to you know um in this case Ai and so we um we teach a a prompt like fundamentals course uh where we try to just give you like the crash course so that you like most importantly understand like what you're communicating with and you can have tools in your tool belt so that you actually feel like you're able to get your point across delegate whatever you're trying to do communicate with it effectively um and yeah uh that's where a lot of our work is um task hierarchy is something we talked about that we were going to kind of dig a little deep on uh specifically with prompting so go ahead and explain what the task hierarchy concept is and then let's talk about that a little bit Yeah so um when you're thinking about uh again like communicating with AI or like delegating um you if you're imagining The Playbook like it's like delegating like specific sections or specific tasks in that Playbook to AI like getting it to do the scoring method of the Instagram post or something like something very specific um we always try to bring the lens of like what are we actually asking AI to do in this instance because it helps us uh be more like grounded in how um we like write a prompt or have like expectations of what AI is going to do and the best uh framework that we found and we've been using for over a year now it's it's been great is what we call the task hierarchy which um is basically three levels where at the bottom um of the we usually showed as a pyramid the bottom of the pyramid uh is objective tasks and these are the easiest to get AI to do where basically you know that it either has a either gave you a right or a wrong answer based on what you're asking it to do and the way to get AI to do these types of things is usually by just giving it a bunch of examples and being really really clear in your rules or your instructions um then the second tier is uh what probably all the marketers listening are going to like absolutely cringe at what I call it but I just haven't found a better branding term so like open invite if you have a better term for me I call them good enough tasks um because it's truly like it's the stuff that you want AI to do where you just need it to be done good enough and more specifically when we think about good enough tasks we think about what are the what's the criteria or like the list of expectations we have that like as long as it meets those expectations we would consider it good enough um and for that really it's again using examples but adding in and defining those criteria like if you can Define what does good enough look like AI is pretty good at meeting your expectations um and so that's like what it takes to delegate like those types of tasks real quick can you kind of delineate the difference between objective and good enough just so people understand like maybe give an example of a task that's a good enough task and one that's an objective task so um really good examp of good enough tasks are things like writing emails um or sometimes even uh more creative stuff like outlining uh a blog post um or even in other cases like drafting the post writing the hook that kind of stuff got it as long as you can again like Define the criteria of what does good enough look like um the uh difference between good enough and objectiv objective is really like you know you could write out the rules and you could give it to someone else um of like yeah they it was done correctly or not um it has the right answer or not yeah yeah so a good enough task would be like um summarizing a transcript or something like that yeah and then some of the criteria might be like don't make stuff up yeah right yeah yeah yeah so um yeah and uh there's like people are usually surprised with how much of their work could actually fall into the good enough um task like bucket because um the third bucket is what we call Expert tasks and this is where you know you're really you feel like you're leaning on your own context experience background creativity like a lot more like fuzzy stuff and you feel like it's like harder to articulate what like how you got that output or like how you did that work um and one of the best things about this hierarchy is that when you find that you're have a bunch of expert tasks that's a really good signal to try to see like okay well could you break it down into some more good enough tasks like could you get more specific could you separate out stuff um and as people do that exercise again they find that they could actually like delegate a lot more than they thought they could um to AI yeah so on the expert tasks can you give us an example cuz I think what I heard you say is hey if you take an expert task and you break it down into it elements you could have a bunch of good enough tasks but what I wasn't clear about is whether AI can actually do the expert tasks so it can do it really depends it can do the expert tasks like sometimes in our experience um but usually uh there's like a a spectrum of stuff so like um the expert tests that we get actually working are usually have like we're talking hundreds of thousands of words of context and it's kind of like um it feels a little bit less controlled that it actually like does that task like we are much more a fan of trying to see like can we break expert tasks down into a mix of good enough and objective tasks because then um you just have a lot more control over the output and you're actually teaching it instead of relying on like shoving a bunch of stuff in it and like hoping that it got all that and you know did its best a really good example of this is actually that comment responder because like just on its face value to get a um AI to respond like like me using like a you know strategic mindset and like the quality that I would want like that's definitely an expert task but this Playbook that we built broke it down into tons of subcomponents like well let's first analyze the comment in the context of the post from the person like you mentioned and let's see like what are they actually saying like let's slow down and actually understand like what the context is okay cool now that's a good enough task then let's think about like all the different techniques that we might want to use to respond to these comments and like pick our favorite one okay cool that's another good enough task we just want to pick a technique that like makes sense for the context then drafting then you know editing then like all the stuff as you can see you can just like break it down more so that similar to if you were again like training an intern writing that like amazing you know uh Playbook what would that look like it's breaking it down into smaller and smaller stuff so you have control you can delegate it to AI um you have this method called the master method which is for prompting I would love if you could kind of skim through it real quick so people could kind of understand your prompting methodology yeah so um within uh again like once you've kind of defined the type of tasks then uh honestly I find one of the most fun Parts writing the prompt um we developed the master method really just as a like a kind of a way to teach some of the fundamental concepts of like what works really well in these um llms like both tra BT Claude Google Gemini all that stuff um it's less of a like you need to follow an exact format but it teaches like really important Concepts and so to go through it really quickly um and by the way this is like a whole like hour and a half like thing on its own with examples and everything but M uh stands for markdown and if you're not familiar with markdown basically it's a way to add structure to text that uh computers and these language models are familiar with so if you ever see a document with like hashtag like two hashtags and then text and then if you like see it you know in Google uh doc something and like it's a header two like that's markdown um and that's something that's been around for a while you can totally Google it and learn it highly recommend um using markdown to structure your prompt because you're just giving it you know it's it's just a little bit more organization um uh in the prompt itself then a stands for act as a so we do really uh prefer to kind of prime the AI model to think about the problem that we're giving it from a certain context um because like act as a expert marketer for example right yeah or act as a really busy mom and look at this ad copy that I have and stands out to you right I love that yeah um any you know you can use it for anything but um the reason that's so powerful is because at the end of the day all these models are doing is predicting the next most likely word given the prompt you gave it and it really is that simple and so if you are uh priming it to uh think about or have the context from a certain um like piece of its model like it is going to understand and be able to follow the concepts and you have more control so that's um act as a and then s stands for be specific so um we have a whole bunch of techniques in this but really it's just like the more specific you are the better um one of the biggest ones is adding that criteria I talked about then um T stands for Threads um and this is really about understanding what's actually being considered when you write that prompt and so in chat gbt origin Ally um you might have noticed like it didn't actually like remember stuff from each chat thread so really important actually as a user to kind of like know that so that you're not expecting it to do something that it can't and you're kind of adjusting accordingly you know now chat gbt has a little bit more of like memory that it can pull from um that you can access in your account but again still just being aware of what you actually have in the thread and what the AI is considering yeah and just so we're clear for everybody who it might be confusing this with like threads on social media it's kind of like a thread is like the chat it's like the chat window is really what we're talking about y like the chat conversation okay cool keep going yeah that's great um and then e stands for uh sharing examples um it really is one of the best ways like show don't don't just rely on telling and then R is um actually like considering regenerating the output if you don't like it so another thing that a lot of people don't know like fundamentally about um these AI models is that when you're using chat GPT the app like you're going to like chat jbt.com they actually um add a level of Randomness to that predicting the next most likely word piece and so um if you don't like the output you can actually just click regenerate and it adds Randomness into it and like tries again yeah and for those that don't know what it looks like it's just a little like uh two arrows in a square right isn't that kind of what it is or am I thinking about something I or is it isn't that it looks like kind of like the recycling like yeah yeah yeah yeah yeah the square thing is copy never mind yeah there's a little symbol so do you recommend editing your original prompt or you just recommend regenerating because I'm curious what your thoughts are so um it depends we recommend both uh the reason to regenerate is if you just want some like just like a a fresh take but you don't want to give it any new instructions um if you want to like refine it more something that a lot of people um uh do which is totally okay but is they'll just like ask it another question or give it feedback like in the chat conversation um again that's okay but the problem with that is that you're not building something that's like reusable in the future so if instead of refining it via sending another message you actually back into the original chat and if you hover over in chat GPT there's like a little edit button and if you add in there like let's say you had a list of criteria of what like good looked like and you're like okay actually like don't include emojis like you like put that into to the prompt and you rerun it then and if you like that output boom like you just made a prompt that works well for your use case versus if you if you go through and you're just kind of like always having that chat conversation you're just missing out on the opportunity build like one little prompt that like works well um yeah and then our favorite thing is when you have these prompts that work well put them in the Playbook because you can store them there for later so that either then like next time you're doing that task or next time someone on your team wants to like go like run your playbook and do your thing then they can immediately have access to the proven prompts that you have already kind of figured out for how to do that type of work I love that because I've heard stories of people for whatever reason losing their original prompts they couldn't find their original prompts that created whatever they were looking for I like the idea of storing it like in a Google doc or something along those lines back to the Playbook I know we've spent a lot of time on the Playbook is there any other parts of the creation of the Playbook that we need to be thinking about because it sounds like it's a pretty massive document does it need to be a massive document at first it doesn't need to be massive at first and this is kind of more where it's like um part of the art and the like creativity that I think people get to bring into like how they want to use AI um so a couple things you know we personally build our playbooks like kind of small and we'll like have playbooks really specific stuff and we have a lot of them um another thing you can do is how small is small just so people understand what you mean by that um couple Pages what was that couple Pages or what are we talking about when we say small okay well when it's in a Google doc it's it's still probably like 10 pages um oh wow that's small okay yeah sounds B but you're putting you're putting all of like here's the thing when you picture A playbook like I want you to picture like it's a book like you could hand it to an intern and they could really understand like oh how do we write our product marketing releases ah so the examples take up a big chunk of that right yeah examples um listing out again kind of the criteria or like what does good look like um do you write in first person second person you know like it's just it's all that uh stuff um because again that's like the level of detail that if you have it that's exactly what you need to put in you know AI prompts and stuff so this is the key take-home that I think everybody needs to pay attention to is that if you're just using chat GPT Claude Gemini whatever and you're just going in there and creatively spontaneously creating stuff randomly out of your brain um it might be pretty good but we're talking about creating operation operational efficiency right which is getting out of your brain and getting it into a place where someone else could leverage a procedure and process and and take it up when you're out sick or you're on vacation or you don't want to do it anymore right and this is just good business right to do something like this and and the benefit of having this document I would imagine is other people can discover ways to make it better as well well is that true totally yeah and you're really like you're elevating yourself out of needing to execute everything to where like you know a lot of times when we're working with people we start to see their mindset shift they're like wow maybe my day-to-day isn't as much executing the campaigns doing the deliverables all that stuff maybe it's more kind of like R&D like let me think about how I can improve the process let me think about new techniques we could do let me think about like new new campaigns new ideas new ways we could research stuff new ways we could Elevate what we're doing and I think that um for me at least like in everything that I do that's a really exciting place to be and think about how I can work alongside in my career and I for like all the clients that we work with that's a really exciting thing for them as well okay there is another part of your process which we haven't addressed yet so go ahead and talk to us about this next part yeah so um the last piece is is uh more of addressing a misconception which is that like AI is something that you like adopt and you're like done you know um that's just not how it works like AI is something that not only is it changing and evolving as models get better their capabilities get better they can you know do new things but also you know um when's the last time you had something in business I mean especially in more of the like marketing and creative side that like stayed the exact same for a really really long time right like your processes your expectations um how you do work is also changing and so uh a really important part of this process is always that level of like feedback if you're using um chat GPT as your main tool for doing this kind of like play booking and dedicating those pieces to AI then the best way to give AI feedback is doing we talked about earlier where you're going in clicking edit and fixing that prompt um where you're really like looking at what did it get wrong and you're trying to give it better and better instructions um depending on the tools that you're uh using there are some tools like some of the tools that we use um kind of internally uh you know that are actually kind of learning from and uh kind of um basically drawing conclusions on like what you did give it feedback on um but that's a really really important part is recognizing that not only like the technology is going to change your expectations are going to change and you need to be actively working on how to improve the clarity of what you're asking AI to do so that you get the best results just to help people understand how to give AI feedback it's one thing to edit the prompt which in some people's mind isn't giving it feedback as much as is trying to guess how the AI can better output something um like help everybody understand like what kind of feedback is helpful feedback I mean can we just sometimes say hey look I didn't like that I don't know I mean like what kind of feedback is acceptable feedback to the AI yeah so um it really depends on the tool you're using on what kind of techniques you can use to give AI feedback one is just in the chat conversation thread and chat GPT telling it to like do better you know that actually works um another thing is to be a little bit more structured in your approach where you ask it to critique itself maybe you create a scorecard and you ask it to fill out the scorecard on how well it did on that uh you know response or output and then you um ask it to fix those responses those are some of the techniques you can also use if you are like automating or using um kind of more of a um uh yeah an automatic like AI tool um but then yeah at the end of the day like the most important thing is that um I think if you are really serious about scaling your work with AI then you need to take like an active role and an active mind set to it's not good enough let me figure out how to give it better information be more specific like you would with an intern um because that that's where people are really figuring out how to get stuff to the place where again like you know doesn't need any editing because they've gotten broken it down and gotten it spef gotten it specific enough Rachel uh Woods this has been really really amazing if people want to connect with you do you have a preferred social platform and if they want to check out uh your business or businesses where do you want to send them yeah I H if you are on Tik Tok I would definitely welcome you to come join me on Tik Tok it's where all the uh the cool business people who uh are making videos and talking about stuff there's a lot of really great how do how do we find you there is there is there more than one Rachel Woods on there or no um if you search Rachel Woods AI I should come up um or hopefully not some of the impostor accounts um cool but uh the other thing is I'll you a link that we can put um in you know show notes or wherever that has access to all of the social accounts you know we try to post a lot of content about everything about AI operations and how you can actually put this stuff to work um and then I'll also have links to learn more about the AI exchange if you want to learn about AI operations and how you can apply that in your work or divy up if you're a marketing agency and you want to talk you want to figure out how you can scale some of the amazing expertise that you have um because that's really uh our butt and butter is there a particular URL you want to just mention by name if they wanted to to to go to your uh divvyup is it divy up. something uh and what about the AI exchange so divvyup is divvyup agency.com okay and then the AI exchange is the AI exchange.com perfect easy enough Rachel thank you so much for coming on the show and sharing your insights with us thank you for having me this has been really really fun