The AI Memory Hack Every Marketer Needs to Know

When AI gives a wrong answer, it is tempting to blame the tool. Sometimes the problem is how we are using it. AI has something like short-term and long-term memory, and the quality of the result changes depending on which one we ask it to rely on.

Give the model useful context

Long-term memory is everything a model absorbed during training: books, articles, transcripts, and other material. It is broad and powerful, but it is also fuzzy. Information can conflict, details can be missing, and the model can produce a confident answer that is not correct.

Short-term memory is the context window available for the current task. Prompts, uploaded documents, web research, examples, and instructions all load information into that working space. The more relevant context you provide, the less the model has to guess from general training.

That changes how I approach marketing work. If I want a useful article, I do not simply ask for an article on a topic and hope the model remembers the right facts. I give it the title, research, outline, audience, examples, and the constraints that matter. A chain of prompts can build context step by step. A CustomGPT can also keep a set of instructions and documents ready for a recurring workflow.

Use memory for real work

I use this approach for newsletters and educational projects. A transcript or source document can provide the facts, while a prompt provides the structure and voice. In a homeschooling example, I could give AI the assignment and the grading criteria rather than asking it to invent what the student was supposed to learn.

The same principle applies to marketing analysis. Feed the model the customer research, the offer, the audience, and the decision you are trying to make. Ask it to identify what is supported by the material and where it needs more information. Context does not guarantee a perfect answer, but it makes the answer more grounded and easier to check.

Accuracy is a workflow decision

As context windows become larger, AI will be able to hold more of the material needed for complex tasks. That does not remove the need for judgment. It makes it more important to decide what belongs in the working context, what needs verification, and which sources deserve trust.

The practical hack is simple: stop asking AI to remember everything. Load the information you want it to use, give it a clear job, and check the result against the source. Many apparent AI errors are really context errors, and better context gives marketers a much more reliable starting point.

hi welcome back to the AI driven marketer my name's Dan Sanchez my friends commi danz and I am getting sick and tired of people knocking AI for things that are actually their fault now you might have heard it said that AI hallucinates it gets things wrong it can't remember dates it counts incorrectly all those things are true it can get things wrong just like all tools can be misapplied the problem is is not AI it's your understanding of how AI works so if you want AI to be more accurate if you want AI to perform better for you listen to this episode because chances are if you're not getting what you want at AI it's probably a user error not an AI error the funny thing is like AI become so easy to talk to and it seems so smart that when it makes mistakes and doesn't fact check itself it just seems like oh it's it's wrong it's an error but there's a few different things to keep in mind so follow along with this episode I'm going to try to explain something that's somewhat abstract I don't have any visuals for you so all your audio listeners I'm not going to throw any slides or anything into it but there's two different ways of working with AI and it has to do with the ai's what I'm calling memory and I've heard a few other people use this now so I'm not the only one using this language but I find that it's a a helpful metaphor into how it works by comparing it to how a human brain works so the way we work as humans is that we have short-term memory and long-term memory it's a well-studied psychological phenomenon that we have things that have happened recently to US versus things that have happened a long time ago if you ever watched the movie Inside Out they try to they had a fun time P Disney Pixar had a fun time visualizing short-term versus long-term memory right uh AI has the same thing it has short-term and long-term memory and where people go off the rails is when they take a prompt and ask it to do something relying completely on long-term memory the problem is long-term memory is faulty what is long-term memory and AI though you got to remember these AIS are trained on all the information that's out there on the Internet or at least a lot of it right all the podcast transcripts and YouTube transcripts and blog articles and books and books and books uh and libraries of news articles from the last hundred years right it's read all these things it knows a lot of dates and facts and figures and all kinds of things that have happened and it's somewhat reliable like just like if we had humans that remember their whole lives and the things that have happened it remembers a lot of things relatively well the problem is there's always holes in those in those memories especially since it's reading sometimes conflicting information it gets things wrong but that's long-term memory for you it's great at remembering patterns and leading up to what we can do to make decisions today but it can be faulty AI has it and that's the reason why it hallucinates a lot is that long-term memory so if I'm talking about long-term memory then naturally you expect to talk me to talk about short-term memory and that's where a lot of the real action happens with AI is if you can fe uh feed it short-term memory um some people call it a context window and you've probably heard this in AI related to tokens right what's a token a token is a piece of information uh it often represents like three quarters of a word so 125,000 tokens is related to about 100,000 isword um that's uh ai's ability to have a short-term memory right the larger the context window or the amount of tokens it can handle at a time is the amount of short-term memory it can handle at a time which right now open AI is about 125,000 tokens at a time Google's pushing a million or two two million tokens which is really helpful but I generally just stick to open AI because it's still kind of on the edge it kind of goes back and forth with other models but I'm I'm using that for now um as AI gets better at short-term window will get bigger and better and we'll be able to take more into account which means it'll have to depend Less on uh the long-term memory and just focus on short-term here's why it matters though the more you load load into the short-term memory the more accurate it becomes if I ask it to write a blog post about a topic and maybe give it a title maybe even an out rough outline it'll be able to fill it in with long-term memory but chances are it's still going to be generic it's not going to be that good but if I give it a really good podcast transcript and outline the blog post based on what was said in that podcast transcript and I'm Lo taking that podcast transcript and I'm loading it into short-term memory and then asking it to go off that that blog post becomes way more accurate it becomes way more susten of and it has to pull less from long-term memory to fill in the little tiny gaps it's it's only f filling in small gaps versus large gaps when it comes to writing out the content which is why it works so much better and is way more accurate the more information you can load into the short-term memory the better AI becomes and as somebody who's engineering now ai processes I'm always trying to figure out ways I can load and absolutely maximize the a uh the short-term memory so that it can produce more accurate more concise and uh just more dependable results even especially as I'm automating it and can't even check all the things that it's doing I want to have good results so there's a bunch of different ways to load information into the short term and I'll just kind of list them all off and then I'll give some practical examples of how I'm overcoming the long-term memory limits and maximizing what it can do in the short-term memory limits so the first one is just your prompt right like what you give to it the more context you give to it the better the outputs it's going to give to you so don't write short prompts tell me a story like give it a long prompt tell me a a story about a man who met a woman and then they broke up and I don't know like just get paint a picture for it like you don't have to tell it the story but give it more parameters in order to give it give to you what you are actually looking for um just the other day I was working with the client and trying to write an email sequence and I had it I loaded it up with information on the client and of course it wrote a better sequence but there's other ways to do it and I'll use that example to kind of like talk about different ways you can load up the short-term memory another popular way that I love doing it with with chat GPT is putting in a document yes if I have a PDF of something that has some really relevant information it helps to not only put a prompt in the prompt engine but to actually upload a document a PDF with maybe some research or some findings or information about the topic that I'm talking about um I recently again that client I uploaded a a kind of like a shorten version of a book that client had written in order to educate the model on the methodology the client uses with its with their clients and it was really helpful because I had to write a whole summary of the document and then it was going off The Document Plus its summary in order to inform the outputs that I was asking for later you can also do it with uh um csvs or Excel sheets or different uh Google Sheets now I'm using more and more often since it can now correct connect directly to Google Drive but there's a number of different document types that it can read and I use them more and more I'm just dragging documents in including them with the prompt for context and information information for it to pull from again loading it into that shortterm memory the next one is web search I talked about this in the last episode you know they're talking about launching search search GPT but you can search already in chat GPT just tell it to do a search on Bing and it can go and find some context for you and go and search the web for it if you kind of know what's already searching uh ranking on a website then you can use that those search results in chat GPT to better freshen up its short-term memory especially if you're doing some uh something on that's happened recently like these models are only trained up to a certain date so if you want more accurate information or something that's happened recently in your industry or regarding a person or whatever have it Go and Do a search and scrape what's currently going on with that person right tell it what search parameters to use or what search query to use in order to find something accurate and it can come do a summary dump it into a short-term memory and now it has fresh information to actually work from the next one is using a custom GPT now I've talked extensively about custom GPT so I won't go into all the use cases and what they do here but it's essentially a slightly customized version of chat GPT and the other models like anthropic have their versions of this thing too um and you can use the instructions area to load it with information to give it more context so that you don't have to reload it over and over and over again if you find you're uploading a document to chat GPT the same one over and over again you should probably just build a custom GPT and and put that in the instructions or in this next one like you can do it custom GPT via the instructions area or via its documents area and you can just have the document there permanently and just reference it every time you do a GPT instead of having to upload it every time and lastly with a custom GPT you can also do some sophisticated things by tapping into an API it's a little bit more Technical and honestly I haven't even used it yet I I don't know a lot of people that use it but I know it's there for those who know how to deal with apis like manually that's available to you but for the most part we're using those we're using prompts we're using documents we're using web searches we're us uh and custom gpts to pre-load the instructions and upload documents those are the main five ways that I'm doing it all the time in order to load the short-term memory so that I get back accurate results that I'm pretty pleased with consistently so here's three projects that I've done recently that I've documented here on the show and how I'm using it to load short-term memory the first one is this newsletter Builder I've made now I'm using a program called high level um that has kind of like a marketing automation Journey Builder and since it's not a custom GPT and I can't load documents into it I essentially have to build this super long Mega prompt and inject information into a a prompt that goes to the the open ai's API to bring back the response um but I'm doing a ton of different things like when I'm building this newsletter I'm putting the trans essentially just fill out a form real quick with the title of the podcast and the transcript and I don't do anything else it goes and takes a pre belt prompt injects the transcript into it injects some information about the show and then injects the title into it it comes back with the newsletter content then and it does that a couple of times to get different sections of the newsletter out um but I'm depending on it short-term memory by giving it the whole podcast by giving it the title and giving it a very very long beefy prompt in order to give it very clear step-by-step instructions of how to put it together now it's not doing it multi- prompt it's just doing it all on one prompt often um but I'm get up I'm loading its short-term memory up as much as possible so that it doesn't have to depend on its long-term memory to pull data in order to format the newsletter the next one I going to talk about is my showrunner uh which is something you can find at myow runner.com it's a custom GPT that I've built and you can go find it in the GPT store but if you go to myor runner.com And subscribe to my newsletter I built this with Susan Diaz um it'll actually take you to a landing page afterwards that gives you the full instructions and documents that runs the GPT um so if you ever want to figure out how a GPT a custom GPT works that's the best place to start especially if you have a podcast because it's a it's a podcast a pre-production assistant is what it does it helps you build out your episodes with interview guests I use it every time I I have an interview on the show now and that whole GPT is designed to load the short-term memory and what it does is it proactively asks you questions as the Show creator to give it the things that need it needs in order to actually give you great results so it's like hey who are we interviewing today you give it a name great you want to paste in that person's LinkedIn profile again we're using a prompt taking the LinkedIn profile data to educate the GPT put it in it short-term memory it then goes and does a web search again bringing accurate fresh information about the person you're you're interviewing and brings it into short-term memory so it's like you got the name you got the LinkedIn profile you copy and paste into my showrunner and then it does a web search to go and refresh and get it grab anything new that's happened with that person to then educate itself on the guest that you're interviewing it then goes and asks you like hey what angle do you want to take now because this GPT is loaded with information about your show and it now understands the guest it can actually ask you the question cool what are we talking about and it'll you give it an an uh a general description of what you want to talk to them about it feeds you back five different angles and those angles are based on what it knows about everything that's going on in its short-term memory right and it's using its long-term me memory to fill in the gaps and then it goes and write creates titles and then creates a show outline based on everything it's nodes the reason why this particular custom GPT is so popular I keep getting feedback people saying they love it they love working with this one is because it takes the thinking out of loading the short-term memory that's why this custom GPT works so freaking well is because it it makes it it doesn't make it doesn't require you to think about what it needs to know it proactively asks you what it needs to know in order to deliver results but if you can learn how to do it yourself you won't have to have ai proactively prompt you you could just give it everything it needs on the first pass so and the last one is a really fun one that I'm working on now I'm I'm a homeschool dad I I teach my kids history uh science and Bible and they have to write journal entries in their note about what we learn about each day about the history and the science and it grading is a pain so like I often sometimes misg grading sometimes I just enter it sometimes I grade it sometimes I don't um but what I've done recently is I used AI to come up with a rubric for their read their writing assignments and what I do now is I take a picture with my open AI app and or a chat GPT app in my phone it amazingly can read their writing we're talking about elementary school middle school their writing's H it's okay I teach also teach them how to type because that's become a bigger bigger piece of I don't know adult life is typing more than writing but um it reads their writing and actually analyzes it against the rubric um in order to grade it and it it is it's remarkable how accurate it is so what am I doing to load it into the short-term memory one there's instructions that I've given on what it's supposed to be do what it's supposed to expect it's expecting a picture of me from either my son or my daughter's uh Daily Journal i' actually don't give it context on what we learn but based on the image that I give it it understands the context this is where that long-term memory comes in hand handy because if they're my son's writing about mellin like circumnavigating the globe it can go to long-term memory and have a rough idea of pretty good idea of like what that topic is and what we're what he was learning about and then it can go ahead and analyze the image um and then give me back a grade so I'm using a custom GPT that's loaded with instructions as far as the context of what this image is for and what I wanted to do with it it has the grading rubric already pre-loaded in there that I co-created with the AI and then it gets the image from me that has the writing for my son um so that it has the context of what generally what was learned about and his take on it um so because I'm loading all that stuff into the short-term memory its ability to grade it and context contextualize the grading uh is very smooth and delivers wonderful results that speeds up my homeschooling dramatically and of course I read the grade and under under I I read the summary from Ai and hand that over to my son or my daughter to be able to make Corrections um but I'm reading it as I'm passing it along to make sure the AI is not screwing up somewhere and I can tell you it's it's very accurate and is very good at delivering that output so hopefully this lesson has kind of educated you on how to approach AI the difference between it short-term memory and its long-term memory the one last thing I'll leave you with is that as it short-term memory the context window gets larger that's going to open up so many more use cases for us marketers I mean right now window is a 125,000 is uh tokens it can take in and that's roughly 100,000 words it's one long book right a normal business book is 60,000 words so it's a it's a longer it's like a it's a pretty long book it's not the whole Harry Potter series you have to get to like two million context a context meno 2 million tokens for that but imagine when we get to the day where it's like 10 million 20 million 50 million 100 million what's then possible well right now you can't just feed AI your whole CRM especially if you've been in business for 10 years and there's thousands of Records in there you can't feed it because of the short context window your whole slack account and it expect it to understand the context of every conversation ever said because its long-term memory is it's a little fuzzy like our long-term memory but it short-term memory is very sharp so as that context window uh opens up think about the possibilities of us feeding it the whole database once a day or our whole organization's slack window like slack conversations once a day uh all all the social media that's taking place and everybody that's interacted with us on social um over the last couple of years well now all of a sudden AI is going to be much more accurate in its analysis of what's going on be able to highlight things that we're not paying attention to be able to find Opportunities find threats so we can strengthen our organization so we can manage better that's the kind of future we're looking I'm looking forward to as as the context window grows we're going to be able to feed it vast sums of data and actually expect it to be able to do a pretty good analysis based on what we want to know so right now the context window is short but that's going to grow over time in the meantime figure out how to maximize the short-term memory uh even while it's short it's pretty good at being able to accomplish most texts and projects if you were able to feed it with the right information to give it the context it need [Music]