The Salesforce Admins Podcast

AI Is Transforming Marketing From Data to Personalization

Today on the Salesforce Admins Podcast, we talk to John Wall, co-host of the Marketing Over Coffee Podcast. Join us as we chat about how new generative AI tools are enabling marketers to get more personalized. You should subscribe for the full episode, but here are a few takeaways from our conversation with John Wall. Six core marketing use cases for AI Thanks to Agentforce, generative AI has moved from novelty to necessity for most organizations. It’s a key tool for strategic content creation, customer insight, and business transformation. That’s why I sat down with John Wall, co-host of the Marketing Over Coffee Podcast, with guests like Simon Sinek, Seth Godin, and Debbie Millman. John identifies six key areas where marketers can lean on AI support: Generation Summarization Extraction Rewriting Classification Question answering These tasks are helping marketers analyze massive datasets, repurpose content, and simulate customer feedback in ways that were previously unimaginable. So my question for John was: what can we, as admins, build to help them out? Better data, smarter personas Marketers use personas to help them think about the specific people in their audience that they want to reach. “Right now, that’s four people in a conference room coming up with cute nicknames like Sally Shopper or Wally the Weekend Warrior,” John says. In the future, however, AI will make it possible to decide on marketing personas based on data-driven profiling. Marketers can extract customer patterns from engagement data and train real models based on statistics, not spitballing. Even more exciting, these new persona agents are essentially customers on demand. You can ask them questions and get their feedback while you plan your next marketing campaign. Why you need a human in the loop As everyone rushes to deploy AI, John emphasizes the importance of the human in the loop. Mistakes are bound to happen, and rushed implementations can harm brand trust. You need to make sure that any solution you deploy has gone through a thorough internal vetting process before it goes live. As John says, AI advancements are probably not going to put you out of a job, but they’ll definitely make your job easier. “The big thing is you have to be curious,” he says, “go play with something and see what you can make it do and what kind of results you can get from it.”  Listen to the full episode for more from John about how AI is transforming marketing. And make sure you’re subscribed to the Salesforce Admins Podcast to catch us every Thursday. Podcast swag Salesforce Admins on the Trailhead Store Learn more John’s Podcast: Marketing Over Coffee Salesforce Admins Podcast Episode: 2025 Roadmap for Salesforce Admins: AI, Agentforce, and Emerging Trends Salesforce Admins Podcast Episode: How Agentforce Transforms Customer Interactions at Salesforce Salesforce Admins Podcast Episode: How Agentforce Is Changing the Career Landscape Admin Trailblazers Group Admin Trailblazers Community Group Social John on LinkedIn Salesforce Admins on LinkedIn Salesforce Admins on X Mike on Bluesky social Mike on Threads Mike on X Full show transcript Mike Gerholdt: This week on the Salesforce Admin’s Podcast, we’re catching up with John Wall, longtime marketer, podcaster, and co-host of Marketing Over Coffee. We’re going to dive into the rise of AI in marketing from smart summarization and rewriting tools to full-blown virtual agents. We’re going to unpack how marketers can stay ahead and why AI is not magic, even though it kind of feels that way, and what smart Salesforce admins should be watching for next. Plus, you’ll hear why having a human in the loop is still the secret sauce to marketing. So give this episode a listen and join me in welcoming John Wall to the podcast. So, John, welcome to the podcast. John Wall: Mike, it’s great to be on the mic with you again. Mike Gerholdt: I know, it’s been a while. I feel the last time we recorded was in Boston, 100 years ago. John Wall: Yeah, downtown Boston. I remember we were live on Newbury Street. That was like the heart of all the action. Mike Gerholdt: Yep. We were recording the old style podcast. We had an Edison, it was putting it on a phonograph and some wax tubes. John Wall: That’s right. Sitting there with my ear trumpet listening. Mike Gerholdt: Ear trumpet, I love it. For those people, like the two people in the world that don’t listen to Marketing Over Coffee, can you give us a brief overview of what you do and what Marketing Over Coffee is? John Wall: Yeah, sure. So, my whole career I worked in marketing and tech, and God, going on what, 16, 17 years ago when podcasting was just done with steam engine and hammers and nails. We created Marketing Over Coffee, with my co-host Christopher Penn. And we’ve had this ongoing dialogue of just every week, 25 to 30 minutes talking about what’s going on in marketing and tech. And just like CRM, this space is so insane and changing every week, there’s no shortage of stuff to talk about. But then, and it’s also grown up enough that I’ve been fortunate enough to get a lot of big marketing brains and authors on, like Simon Sinek and Debbie Millman, Seth Godin, folks like that. So yeah, it’s really kind of opened up the world because the family doesn’t want to hear what I have to say about marketing over Thanksgiving, so I have somewhere to talk about that. Mike Gerholdt: Oh, that could be another, you should rename the podcast that for the holidays, Marketing over Thanksgiving. John Wall: Yeah. Mike Gerholdt: Just see if anybody notices. John Wall: That glazed overlook when I’m talking about what I do for a living. Mike Gerholdt: So I make ads, I’m like Jon Hamm on Mad Men. No, and I remember the Boston. So much of what admins do I remember, is interface with marketing. And that’s why I love having you on because not only as a personal brand, but also as somebody that does a lot of podcasts and content creation, it just overlaps with what admins do. And marketing is such a big facet of any organization now. I mean, you can’t sit down and talk sales without, well, we should have the marketing person in here, and they always want 5,000 more requirements than what you started with, but that’s why I love having you on. So, let’s dive in. I feel like we woke up from the pandemic and AI just was everywhere now. I’d love to know on what the world of AI looks like for marketers now. John Wall: Yeah, I mean, you totally nailed that, and the world has changed yet again. We were kind of finally, things were finally stabilizing a little bit. Platforms that matured, as far as email and text messaging and advertising and things are fairly solid, and now AI has shown up to destroy everything. It’s been a little weird though, because our world didn’t change as much. We’ve been working a lot with machine learning to do data analysis for years. So my co-host on the show and partner at Trust Insights, Christopher Penn, had long been using machine learning to measure PR and advertising results. Doing statistical models to prove like, okay, what’s actually working in your branding and your advertising? These things that you can’t easily measure with clicks. And so that has been an area where we were able to kind of provide some value and insight that nobody else could get. But then really, I don’t know, about a year and a half ago when generative AI became the hottest thing going on all fronts for marketing, the amount of interest in that has just exploded. So yeah, we have a bunch of fronts that we’re applying the technology and it’s just amazing to see the range of how marketers adapt. There’s still plenty of marketers that don’t want to look at it and have their head in the sand, and all the way up to, we have clients that are like, “Hey, we want to reimagine our entire business because we think it’s going to be something completely different in the next five years.” So yeah, we spent a lot of time thinking about where this stuff is going to go, and it’s amazing how… And literally we have, Christopher works full time on monitoring this space and seeing what’s new and what’s coming next, because it’s just insane when you look at the fact that we’ve had six major models this year. There’s never been a time in tech history where you have six major products show up at once. So, yeah, everything is changing and it’s just a challenge to keep track of what’s happening this week. Mike Gerholdt: Yeah, I remember not that long ago, thinking how long in the tooth we’ve been working in tech, when I heard some statistic of, today we’ll create more content than was ever previously created in human history. So now with AI, are we exponentially creating more? Are we creating better content? Is that the converse… I always dig into like, what’s that next layer down? Are we really caring about creating better content with AI or are we just creating more content with AI? John Wall: Right. Well, of course, marketers ruin everything, right? Mike Gerholdt: Right. John Wall: This is nothing new. Yeah, there’s a whole army of people that are taking their stuff that was pretty crappy and now we have an exponential amount of pretty crappy stuff out there. So yeah, and it’s going to be really weird to see how all this goes because it’s the classic antivirus defense too. It’s, as soon as people are creating exponentially more junk, all of the search engines or AI powered search engines are adding defenses to pull all that stuff back out. So it’s just this never ending battle and yeah, the level of content, I don’t know, it’s so much so that we’re going to burn more electricity in the next year than the power of the sun. I mean, it’s just insane how this is all changing. Mike Gerholdt: But we’ll have better copy for our websites. John Wall: Right, you’ll have a better landing page. It’s going to convert for you. But then we do see, as with everything, right? There’s people that are using the technology to automate the foolishness of the past, we have electronic yellow pages being created. But at the other end, there’s people who are using these tools in totally brand new and novel ways to get some insight that they’ve never had before, or automate things that used to be just insanely difficult to automate, and yeah, go to new places and create advantage. So there are ways to win and yeah, there’s going to be a ton of things that we never even expected that will change everything for us. Mike Gerholdt: I mean, the biggest thing before AI, the wave of AI hit, the biggest thing we were dealing with was data lakes and these massive data volumes. And I think even marketers were dealing with that too, because you have people going to their website and they’re unauthenticated and we’re assigning a profile to them. How do we dig through when you’ve got millions of impressions on a page? What was that journey of that person? How did they actually get to the pair of shoes that they bought? Now with AI, are we getting smarter at doing that? Is that kind of the data that we’re digging into? John Wall: Yeah, absolutely. And so yeah, when you look back, step back and look at the landscape. Generation, we consider that one of only six different options to use AI for to help get you places. And two of them extraction and summarization, that’s just what you’re talking about. It’s like to finally be able to have all of these different data sources all over the place, load them up into a system and have it do the heavy lifting of, okay, find the commonalities between these things. And yet it’s just, we had been promising this for decades, this idea that when people in marketing talk about personas, that’s just because four people in a conference room came up with cute nicknames and an idea of who these people should be. They’re like, oh yeah, Sally Shopper and George Weekend Warrior, or whatever. But now you can get actual summarizations based on the data itself. And you actually know that, okay, we do see that 40% of the buyers look like this, and they have these things in common, and it’s all based on statistics, none of it’s based on gut. So yeah, those kinds of insights are really interesting. And we’ve actually been pushing another level. You can go ahead and create these profiles of who these people are, but then use those profiles to train the large language models. So now that you can actually treat that as a customer on demand that you can survey and ask questions to, instead of emailing everybody with every purchase of $0.35 to ask for feedback on what’s going on, you just go to the large language model and say, “Hey, here’s the next four marketing campaigns. Tell us what you think about those and does this resonate with you?” And you can get similar insight but not cause as much trouble and not have to wait. Mike Gerholdt: You mentioned six, I think you gave us one or two. What were the other four? John Wall: Yeah, so obviously generative AI, you’ve got generation, we just talked about extraction and summarization. The other three, rewriting, which is just something that can easily raise your productivity, right? If you’re somebody who’s having to, okay, I wrote this white paper for the construction industry. I want to write about the same kind of stuff for the food service industry. Rewriting is very easy and instant for generative AI to do. Classification is another use case. We see this a lot where people that have multiple products, they don’t know how they fit in together, or even if you just have large amounts of data. A good example is for a call center, you’ve got 30,000 calls a month. To have AI transcribe those and go through and find the 20 features that you should fix to make 10% of your calls go away. That kind of stuff is a huge benefit, huge lift. And then out of the six, yeah, the last is just question answering. You can really get better insight into topics than search engine results by asking AI to not only give you the answer, but explain how it got there and educate you on, what do you need to know to kind of understand the space a little bit more. Mike Gerholdt: And I think we’re seeing, I mean, from the Salesforce side, we’re showing a lot of use cases and we have a lot of customers that are standing up agents on public facing sites. Are you seeing that more and more as a trend for marketers to work with? I think one of the things, as I say this, one of the stereotypes that most marketing falls into is, how do we drive more sales? But I think a lot of marketers are also, how do we divert service cases as well and drive sales through service? Are you seeing agents on public-facing websites as something marketers are paying attention to for that? John Wall: Yeah. I mean, everybody wants that, right? And unfortunately, we’ve all seen this cycle. This happens where there’s the board meeting and the board is saying, “Hey, we got to get onto this,” and so now somebody’s like, okay, I need to get me one of these shiny object things. And unfortunately, it’s mostly disaster-ville, right? We were seeing these things of people hooking up a chatbot or whatever, and it’s starting to just spout off lies and crazy answers and it just becomes a train wreck. So yeah, that is one thing that’s going to be huge over the next couple of years. The idea of, okay, yeah, you’ve got these bots or these agents, but which ones are enterprise-ready? There’s a huge difference between something that’s been vetted and tested. For most of our clients we’re saying, no, you need to have a human in the loop. A great… The use case that you just talked about would be, yeah, have the AI generate the top 2,000 answers for problems that it sees, but then that goes through the product manager for verification to prove that they’re all real. You can’t go live with that, but yeah, there’s definitely going to be a lot of, unfortunately, we’re going to see a lot of scary news as people pull the trigger on something that goes awry. Mike Gerholdt: Well, that’s kind of like we saw like the, we’re not ready for the self-driving cars. We’ve seen that in San Francisco, but they still have somebody in the passenger seat or in the driver’s seat just in case. The human in the loop. John Wall: Right, and that’s always been, even you look back in history and it’s like, yeah, escalators and elevators. There used to be people that was their job just to make sure that nothing went wrong. Mike Gerholdt: Yeah, and of course not to be predictive, but I don’t know the last time I rode an elevator where there was a person there to press the buttons for me. John Wall: Right, exactly. And yeah, there are… Well, yeah, it’s just so much of that is the media and the way information gets presented to us as news. It’s like, yeah, okay, these three automated cars got in some kind of weird accident, but we’re not getting the story of all the ridiculous stuff humans did over the past month in cars. That’s just not news for us anymore. Mike Gerholdt: Right, contextual. You mentioned at the beginning, sort of the great spectrum of marketers with their head in the sand, all the way to, we want to revolutionize our business. Where do most marketers fall, in terms of thinking with AI, thinking about AI? And where should that be? John Wall: Yeah, that’s a great question because it’s really, in a lot of ways this is a retooling for everybody. You have to go back and look at all your processes and figure out which ones apply. And because, and you’ve talked about this in the past, the fact that it’s not about AI showing up and it’s just like the marketing department’s going to get wiped out. What’s going to happen is over time, there’s going to be three or four marketers that have added AI to a bunch of their workflows, things that they’ve hated doing, and so they’ve figured out how to automate them. And those people are going to be exponentially more productive than the folks that are avoiding AI and trying to stay away from it. So yeah, where people should be. The big thing is you have to be curious. It’s just like with every other major tech change. Go start playing around with something and see what you can make it do and what kind of results you can get out of it. Because at this stage of it, you’re going to find these really crazy things. You’re like, oh man, I never thought that I could use that to come up with an intelligent email address predictor. Every sales and marketing person has this where they’re like, oh, I have to get in touch with this person and they haven’t put their email up on the social networks that I normally follow. And so getting some suggestions to do that kind of stuff. And the other one is, yeah, so much of marketing is combing through spreadsheets and trying to prove results or manage copy and things like that. So much of that stuff can be automated and give you hours back in your day. So yeah, it’s a matter of having… Be bold, play around and kind of see what you can break. Mike Gerholdt: Yeah, I think back to, and I’ve tried to look this up, but I’ve heard the story of in the late-1800s, I forget who it was. I want to say Thomas Jefferson but that’s probably not right, writing a letter to the US patent office saying, “You can shut down because everything that’s been invented has been invented.” And correlating that to, we can’t let cars happen in the world because they’ll put wagon wheel manufacturers out of business. And the labor force of wagon wheel manufacturers, it’ll be devastating to the economy that all these wagon wheel manufacturers will go out of business. And I think back to, well, they just didn’t understand. If you’re a wagon wheel manufacturer, you’re just really good at making things with wood. And if cars come around, then make things with wood for the car, as opposed to making wagon wheels. And I feel like we’re in that age now where people are, if AI comes out, AI’s going to take my job. AI can generate an image, there’s no more graphic designers. No. Have you seen AI’s images? Graphic designers are going to be around for a while, but there will be a point where I feel we’re riding on the elevator where it’ll be pretty good, but the really good stuff will be the boutique stuff. And you think about it now, probably what, 90% of the furniture in your home probably was made by a robot. I mean, it’s slapped together really good, but the craftsmen, the people that know how to make that stuff, they’re still in high demand. There’s just a smaller labor force of them. John Wall: Yeah, right, and that’s the, we see this all the time, is the expert tools versus tools for experts, right? Mike Gerholdt: Right. John Wall: The idea that the tool is just going to do all the things for me. But yeah, no, the real neat, interesting stuff, like you said, the master woodworker who doesn’t have to deal with all of the paper instructions and measuring things. They can just work on picking the right wood and thinking about the design of the furniture itself, rather than the more mundane tasks. And yeah, that’s where things are going to… And you hit another great point of freeing resources up. I mean, yeah, okay, the big one is stock photo. Stock photo takes a huge hit if people are able to generate and just kind of get images that they want. But now it’s the thing of, okay, all these companies that really had a hard time having quality graphics and images on their website, what happens if they finally have the ability to create a better website and be able to kind of do more with less? What kind of lift can they see from that? Mike Gerholdt: Yeah. So I’ll ask a big question. Does AI make us better? John Wall: Well, it’s like any tech tool, right? That’s the problem. It can make us better and it can make us worse. It’s all about whose hands is it in and what are they trying to do with it and where are they trying to go? But it is weird in that it, again, tech, it makes everything faster and bigger and accelerating. And unfortunately, our kind of caveman brains are already having enough difficulty handling the speed and volume of everything that’s going on around us in the world. So yeah, it’s going to get a little bit wonky and weird, and the idea of me even trying to predict something is kind of silly. Mike Gerholdt: Yeah. Well, I think that’s the hardest part of it is, great tech appears as magic. Right? Isn’t that the saying? And we’re getting to the point now where we can’t tell magic from great tech. So, I guess that’s always where we’re going, but we’re always trying to out-invent ourselves. You know? John Wall: Yeah, and ultimately, it just comes down to the good news is, okay, what are people actually willing to pay for? I mean, we can do a lot of weird and crazy stuff, but what’s actually going to find something that fits? And that’s funny, that’s something that’s kind of evolved over the past 10 years too, is that we’d always thought about sales as kind of guiding people to your thing and moving the river to go in your direction. But really what we’re seeing is that business is more about, what is the existing system already there and how do we move our business so that we can get in front of whatever’s coming next and where to go? And so that idea of being able to strategically see what’s coming next and already be there waiting for the customers as they show up with the money, that’s a different approach and kind of changes everything for sales and marketing. Right? It’s not about just banging the drum, it’s more about listening ahead and figuring out where to be. Mike Gerholdt: Well, and that’s the part that I think all of this and we’ve never touched on, is the economics of AI, right? So we’re approaching all of this now because almost everything has some sort of freemium model, which means we’re the product. And it’s free because they need our data, they need our prompts, they need to be able to comb the internet. They need to be able to read our blog post and our white papers. But when they don’t need that anymore, then what is the economics of AI? Will there quickly become a have and have-nots layer? Because the have-nots can’t afford the AI, because there is a cost to it now. John Wall: Yeah, that is a gigantic question that I think is just underappreciated, is the fact that AI has taken all the oxygen out of the room as far as VC. And we normally would kind of see money being sprinkled across a whole bunch of places, but everybody is just putting all their chips on this and it’s, yeah, the- Mike Gerholdt: Well, everybody wants to have the iPod. They want to be the one that invested in the Facebook and the one that wins. John Wall: Right, yeah, yeah. Everybody is going for the top. But I can’t think of a period of time where we’re getting more powerful, free stuff than ever before. Mike Gerholdt: True. John Wall: And so, yeah, yeah, there’s huge questions as far as like, okay, when this shakes out and suddenly maybe there’s three winners or one winner or whatever, how does that change? Yeah, unfortunately, marketing again, has a horrible track record for like, yeah, it’s great and free at the beginning, but then once it starts getting tuned for ads and traffic, yeah, it gets expensive fast, and a lot of people get left behind. Mike Gerholdt: Right. I mean, that was just as you were answering that, that was something I was thinking of is, at some point, and I suppose we thought about this with social networks too, at some point they’re going to start charging. And we didn’t think that day would come, and I actually thought the model would be very different. Now, the social networks charge to verify you’re a human, which I wouldn’t have expected. We thought everything on social would go to a subscription price. We’re seeing AI be subscription price early on, but I don’t even know if in five years AILB subscription price, because there could be a completely different cost model to it because of, I don’t know, right? Could you have predicted that Facebook is going to charge you to become a verified Facebook user, as opposed to a monthly subscription, which was the traditional magazine model? John Wall: Yeah, that’s a turn that is bizarre. And I don’t know, part of me too is still hoping one day we get to that point where it’s more about verified users. Because when you get back to all these platforms, the problem is, they do violate the laws of communication. Right? Anybody can go on any platform and just say whatever they want and it can be unchallenged. Whereas for all of human history prior to that, if you were talking some crazy stuff, there was instant ramifications, whether it was somebody throwing a tomato at you or whatever, but there were repercussions for this. And so we see this as a crisis to entrust across the board in all institutions and yeah, I kind of think at some point somebody’s going to get the bright idea that by verifying who’s real and what’s fake and what’s not in anybody’s best interest, when that stuff gets filtered, how does that make it different? But I [inaudible 00:24:35], I thought that that would’ve happened a long time ago and it’s not here yet, so I don’t know. Can it even happen? Mike Gerholdt: Yeah, yeah. I mean, selfishly, I know I’ve had a friend have a YouTube video of his transcribed and turned into three online magazine articles, all without his consent. And then posted to Facebook via a bot, and the bot 100% had an AI-generated profile image. So, I’d be afraid. Yeah, verified users, that would be. John Wall: Yeah, it would be. Mike Gerholdt: It’s like when you get pulled over by the police, you have to hand them your ID. We need some sort of digital ID for that. John Wall: Yeah, that use case that you’ve described as crazy when you think about it, right? Because that’s playing under old SEO rules. Somebody’s thinking like, oh, I’m going to get in three or four more different channels and I’m going to take that traffic. And the reality is, all the search engines now, the first five things they’re throwing up are their own internally-generated AI. Organic traffic just continues to crater. Mike Gerholdt: Yeah, yeah. Well, especially when you take other people’s stuff and you duplicate it, at least they’re not rewarding that bad behavior. John Wall: Yeah, right. Mike Gerholdt: John, it was great having you on the podcast. I’m sorry it took so long, but I promise I’ve not stopped drinking coffee since then, nor will I ever, usually. John Wall: That sounds great. Yeah, no, it’s good to be back. We haven’t had a chance to hang out at Dreamforce like I used to do all the time, so it’s good to catch up. Mike Gerholdt: I know, but there is still the Dreamforce Marathon. I don’t even know what people are wearing now for wearables. You remember, it used to be Fitbits, and- John Wall: Oh, yeah. Right, yeah, yeah- Mike Gerholdt: I mean, we were all Fitbits and everybody had that, and it was the Dreamforce Marathon. I think, to be fair because I am Salesforce, we did hear that. And there has been a very long look at, how do we not necessarily keep people in the same space, but reduce the amount of- John Wall: Yeah, [inaudible 00:26:35]- Mike Gerholdt: … the 30-mile across San Francisco. Because it can be banned, there’s a few of them hills that you just look at and be like, yep, I’m just going to stay at the bottom. John Wall: Always a fan. I just get the cable car pass for the week and take care of that. Mike Gerholdt: There you go, there you go. Well, it was great having you on. I promise to have you back on sooner, because I’m sure we’re going to have more AI to talk about as it’s ever evolving so quickly. John Wall: Yeah, yeah. Hopefully it’ll still be us and not just avatars of us having to do it for us. Mike Gerholdt: Well, that’ll be fine too. We’ll see. Maybe people won’t know the difference, and then you and I can be riding a cable car in San Francisco. John Wall: Right, right, as they’re watching the video of me with my third arm wave. Mike Gerholdt: Don’t forget your sixth finger. It always gets the fingers wrong too. Huge thanks to John for joining us and bringing his insights on AI marketing trends and why curiosity is your greatest asset right now. I know I’m always curious to hear his podcast, Marketing Over Coffee. And it being summer, I like to listen to it while I’m on my yard. That’s just how I listen the podcast. How do you listen to this podcast, mowing and walking the dog? I’d love to know. Shoot me a message on social somewhere. If this episode got you thinking or questioning some AI landing pages, hey, as an admin, time to meet with your fellow marketing peer and learn more about what we can do with Agentforce and everything else. Until next time, we’ll see you in the cloud. The post AI Is Transforming Marketing From Data to Personalization appeared first on Salesforce Admins.

Breaking Into Tech With a Nontraditional Background

Today on the Salesforce Admins Podcast, we talk to Derika West, IT Application Support Analyst II at KinderCare Learning Companies. Join us as we chat about how she got started in her tech career and how she started her Salesforce journey. You should subscribe for the full episode, but here are a few takeaways from our conversation with Derika West. Getting started in a tech career Derika started her career in the U.S. Army as a Carpentry and Masonry Specialist. From there, she bounced around between service industry jobs while she tried to figure out what was next. “There’s no way I could get into tech,” she told herself, “that’s way too smart for me.” However, when Derika moved to the West Coast, her friends believed in her. She applied for a position as a QA Test Technician, and spent a lot of time figuring out how to pitch her skills in a way that would make sense for the role. And that position gave her a foothold into an entirely new career. Getting hands-on with Salesforce In her current role, Derika is the SME for her organization’s transition from Classic to Lightning. It’s an org with over 40,000 users, so change comes slowly. She found herself in more and more conversations with end users about their pain points using their Salesforce deployment, and started looking for solutions. One thing that has been very helpful for Derika is to reach out to the people at her organization who are more experienced with the Salesforce platform. Even learning the basics of what they do and how they got to where they are today was very helpful in making the decisions that would shape her career.  Why you should go to a Salesforce Admin Meetup Derika resolved to go to the next Portland Salesforce Admin Meetup, where she happened to meet Admin Evangelist superstar Kate Lessard. “I told everyone in the room that I’m new and I know nothing about what I’m doing,” Derika says, “and everyone was so welcoming and so helpful.” Kate connected Derika with Supermums, an organization that provides training and volunteer opportunities to help people get started with a career in Salesforce. She’s about to take her certification exam, and let’s all send her good vibes and good luck. Make sure to listen to the full episode for more from Derika, and don’t forget to subscribe to the Salesforce Admins Podcast so you can catch us every Thursday. Podcast swag Salesforce Admins on the Trailhead Store Supermums Admin Trailblazers Group Admin Trailblazers Community Group Social Derika on LinkedIn Salesforce Admins on LinkedIn Salesforce Admins on X Mike on Bluesky social Mike on Threads Mike on X Full show transcript Josh Birk: Hello, everybody. Welcome to The Salesforce Admins Podcast. I am your guest host, Josh Birk, and today I’m delighted to bring Derika West onto the show, to talk about her journey into Salesforce, into the world of tech. And where she is on that journey, where she’s looking for to go. Welcome to the show, Derika. All right, welcome everybody to the show. Today we are going to welcome Derika West to talk about her journey into Salesforce, where she is with it right now, and we’re her future looks. And Derika, in looking at your CV, it pretty much starts with your military experience. What was it like being in the Army? Derika West: Yeah. The Army was a wonderful thing for development for myself. I’ve always been a self-starter, I would say. And someone who thinks outside the box. And I just didn’t know where that would fit for me in terms of which direction of a career I wanted to take. I initially started in college, and then I met somebody in my math class in college who was actively in… I think it was the reserves at the time, and I think she’s full-time active duty now. But we just started talking about options of careers. And I’m always asking questions, as you’ll find out. I just asked her, what is it like being a female in the military? And she just said, “There’s so many things that you can do as a female that you aren’t really told growing up, and even high school.” For me, I never considered the military as an option for me. And then, I just learned that there’s so many different routes you can take. It’s a way to build yourself up and get some self-confidence, really, as a female. And so, I ended up speaking to a recruiter, got involved, and then I joined the Army. And did battle buddy things with her and talked to her throughout my journey. It was really great. Yeah, I had a good time in the military. Josh Birk: So two follow-up questions to that. First, was there something about the Army role that you were looking at that you were… Going back to your point, I didn’t know. I didn’t think about me being as an engineer because I haven’t seen a lot of women in tech, women in engineering, stuff like that. Was there something about the role that was like, oh, this could be something cool and new that I could learn that I hadn’t thought about before? Derika West: Yes, absolutely. That was one of the main points for me in joining the military. I really wanted self-confidence. I wanted to build myself up, and I didn’t know where to start. For me, the military seemed like a wonderful route. It had a lot of structure. I was looking for discipline, I was looking for travel, I was looking for all the things that the military had to offer. And I think anybody knows that the military is very eager to get people in. Yeah, it was pretty much, once I talked to a recruiter it was no-brainer after that. Josh Birk: Nice. I got to ask, what is traveling with the military like? I can imagine it’s wildly different from commercial. Derika West: Absolutely different. You are definitely the government’s property. Anywhere that they say you’re going, you’re going. Luckily for me, my first duty station was Hawaii, so I got very lucky. Josh Birk: There you go. Derika West: And it was just, I lucked out because nobody else got a duty station like that. And I know my brother-in-law, he’s currently active in the Army, he doesn’t really get that much flexibility on travel. But it’s definitely, it’s very safeguarded when you travel. It’s not picking the cheapest flight and going somewhere beautiful. It’s very structured in that way. Josh Birk: You roll the dice, sometimes you get a 20-unit up in Hawaii, but other times maybe not so much. That makes sense. Derika West: I got very, very lucky. Yes. Josh Birk: What was life after the military? What was that like? Derika West: Life after the military was a bit confusing for me. I was struggling with figuring out which path I wanted to take for my long-term in terms of career. Outside of having that structured day-to-day life, I was pretty much a spinning compass at that point. I decided to move back home and start from the ground and spend more time with my family. Recharge my roots back home a bit. And then for, I would say, about five to 10 years there I was just doing service industry things and just trying to find my way. And then I made another move after that out to the West Coast. And then I got more connections out here, much different than the Midwest, and found my way into tech eventually. But it did take me a while to get to this point. Josh Birk: You moved to a new coast and you started getting into tech. What was the appeal of tech to move all the way out there and try to get a job in it? Derika West: Life brought me out to Oregon. I was looking for expansion. I wanted to really grow myself physically and mentally, and I wanted to learn things that were outside of my Midwestern bubble. Josh Birk: Got it. Derika West: I felt like when I came out to the West Coast, a lot of people acted different, they thought differently. A lot of the things that I learned about in the Midwest were produced from the West Coast, so I felt like I could [inaudible 00:06:12] to people here. Josh Birk: I love that. I love that. Derika West: You feel that… I don’t know how to put this. You’re from the Midwest. Josh Birk: Yeah. Derika West: You feel a bit siloed in the Midwest. And I never really considered tech as a career option for myself when I was living there. So when I moved here and I started hearing about all these new people and different career paths, I was like, I need to expand my brain and I need to think outside the box of these potential possibilities for myself longterm. I think, really, it came down to the careers before this point that didn’t work out for me. The things that I liked about those careers and the things I didn’t like about those careers. And then just simply networking with like-minded individuals who were really interested in self-growth and just being in a space of learning more. Yeah. Josh Birk: What were some of those early touch points of here are other people in a similar situation that they’re trying to put themselves into a new skillset and something in technology? Derika West: Honestly, it started with meeting a software engineer in a friend group. And she worked for a local cannabis company here in Oregon. And she and I just started chatting, and I just asked her what she liked about tech, what got her into it. And she gave me the breakdown of her day-to-day. And just asked if I had ever considered getting into tech. And my response was, “I’ve never considered that. And also, it’s way too smart for me. There’s no way I could get into tech, I don’t understand anything about it.” That’s my first touch point in getting some exposure. Josh Birk: It’s such an important one. I feel like there’s so many people that I’ve met over the years who just needed that one friend to help demystify it a little bit. Derika West: Definitely. Josh Birk: It’d just be like I’ve done interviews where people are like, “I challenged myself to learn JavaScript by not going out socially for three months, but now I work in my dream job.” So that [inaudible 00:08:27]. What was some of your early successes? What jobs were you getting into? Derika West: My first job was a QA test technician, which I would’ve never pictured myself doing ever, but it was incredibly helpful to get me started into tech. It was everything that I didn’t know that I needed getting into this industry. It taught me how to ask hard questions. It taught me how to put myself in uncomfortable situations, and just to get into something that I know nothing about. And I honestly didn’t even think that I would get a QA job, but it really laid the foundation of my tech career. And I am very lucky and fortunate that I got that job. Because coming from a background that has zero experience in tech, I really had to talk myself up about the skillset that I had prior to that position, and that was something that I didn’t know would sell. And I just did a lot of research prior to my interview and I looked up what a QA does. I looked up where you could go with it. And I just was doing a lot of homework, I guess you could say. Just doing a ton of research. Josh Birk: Yeah. And what I love about this, and for anybody who’s listening, and if this vibes with you, I know so many people who are now product managers and senior engineers, and all of these things, and a lot of them got their start in customer support or QA. And I think part of it is you get confronted with technology that even if you didn’t build it, you have to understand its working parts. Right? Derika West: Right. Josh Birk: And then, also that QA mindset is also very similar to a programmer’s mindset, to a developer’s mindset. I’m going to get the joke wrong, but it’s like the QA engineer enters the bar. The bartender says, “What do you want?” And it’s like, “One beer, two beers, an owl, no beers, zero, null.” You have to take in all these weird use cases. Then, how did you start… Was your transition into more of the software side of things, was that Salesforce itself, or was there a transition period? Derika West: There was definitely a transition period. I went from QA to my current role, which is more software-based. My QA position was more testing hardware behind the scenes, working with our devs and working with the product owners and things like that. My current role is more end user facing, but also working with the product owners and other teams. It’s a lot of cross collaboration. In my current position, that’s where I work directly with Salesforce. And I work with their team, and I’m the person who’s the SME of our current project. And undergoing a bunch of transition from changing our old Salesforce platform to Lightning, which is a new one, for those who don’t know about it. Josh Birk: Welcome to the club. Derika West: It was quite the transition. Yeah, yeah, it was big. It’s huge. We have 40,000 users. It’s a lot. Josh Birk: Oh, wow. You have 40,000 users? Derika West: I can’t exaggerate that enough. Yes. Josh Birk: And how many of them are system administrators? Derika West: Honest, on our Salesforce team, I don’t know at the moment. But for me, it’s just me on my team. Josh Birk: Got it. Okay. It’s the old admin joke, 200 people in the company, 180 of them are system administrators. Derika West: Right. Yeah. Few and far between, that’s all I got to say there. Josh Birk: Nice. Which is the way it should be. What was it like… I’ll just come right out on that. What was it like learning Salesforce? Derika West: Learning Salesforce was something that was self-taught for myself. I knew absolutely nothing about it. I was like, “What? What do you sell? What products do you sell?” Even my family was like… My grandma was like, “Salesforce is you’re selling things?” And I was like, “No, no, no.” Josh Birk: Right. Derika West: Yeah. I had no idea what it was, so I just simply pulled out my resources. I started asking about it. I asked our Salesforce team, “Hey, what do you do? What is Salesforce?” And I had individual meetings with every single team member on that team for myself. And I just made it a point to let them know that, “Hey, this is something I’m very interested in. And on my outside working hours I’m learning this on my own.” Josh Birk: Got it. Derika West: So, yes, Trailhead was my first stop. Trailhead was very overwhelming for myself. I was like, where do I start? And also, what am I supposed to be studying? And then I found Trailmixes. And then one thing just led me to another thing, and that’s just how my tech journey has been since the beginning. I found that just played out in my own learning with Salesforce. So, that’s how I got started with that. Josh Birk: How long do you think you took from you, okay, I want to put this under my belt? Because you work with other applications as well. Or at least you have been, right? Like, oh gosh, I want to say Office 360, and that’s the worst example. Derika West: Office 365, yeah. Josh Birk: Like, who doesn’t? Derika West: Yeah. What is your question? Josh Birk: Well, no. Yeah, let me start with the question, because that was a tangent [inaudible 00:14:27]. Anyway, it worked in my brain. I swear it worked in my brain. Derika West: It’s like… Josh Birk: How long do you think it was before you’re like, oh, I really want to put this in my tool belt, I’m going to take some time that’s my own personal time and I’m going to start learning it, until you were like, I feel pretty comfortable that I could help administer our Salesforce work? What are we talking weeks, months here? Derika West: I would say about the three-month mark into our transition with our project at work is when I was like, okay, I’m fully going to dive into this and take the reins myself. Because I noticed there was a gap between our team and the Salesforce team. And I was helping these end users on a live call, and they would become extremely frustrated. It’s a big pain point in our company, and I’m the one to bring it up because I’m going to bring it up, because I want change and I want things to be smoother for people. And that’s really what I’m passionate about in this career is helping people. Josh Birk: Nice. Derika West: And I told our Salesforce team, “Hey, I do not have permissions to do X, Y and Z. Can you get them for me?” And they said no. And then, I took it upon myself to start going to more Salesforce related things so I could learn the platform better. It came down to me and wanting things to be better for myself and for other people, but no one would have bridged that gap had I not been in that gap. Josh Birk: Right. Did you eventually get those permissions? Derika West: No, I did not. Josh Birk: Okay. All right. Derika West: But I am in a place where I’m in a transition, so I understand the business needs and I understand the Salesforce side of things as well. It’s my passion hobby right now is learning Salesforce on the side. And it’s taught me a lot. Josh Birk: At least you can be that interaction between a user and what Salesforce is when the Salesforce team isn’t in the room. Yeah. Derika West: Right. Exactly. Josh Birk: Now, you recently got involved in Supermums, right? Derika West: I did, yes. Josh Birk: How did that get on the radar? And can you give us a quick elevator pitch on Supermums? Derika West: I will try my best. Josh Birk: Okay. Derika West: As I was mentioning before, I work full-time. In my application support role, I am wanting to get into our transition to the admin role. I went on Trailhead and I found one of our local Portland admin meetup groups, and I noticed that they had one coming up. I think it was back in February, it was like four months ago. And I was like, I know nothing about automation. I have no idea how it works, but I’d love to know. I’d love to learn more about this thing. So I just went as a newbie to one of these local admin group meetups. It was my first one ever. And at the end of the meeting I met a wonderful human, her name’s Kate Lessard. Shout out to you, Kate. Josh Birk: Shout out to Kate. Derika West: Hey, Kate. We just started connecting afterward. I told everyone in that room that I’m new, I know nothing about what I’m doing. And everyone was so welcoming and so helpful, and it just further enhanced my want to be in the Salesforce ecosystem. So that’s where I got started. And then Kate introduced me and gave me a bunch of resources after that meetup, and Supermums was one of those things. And Supermums is a global training program, and it helps people transition their careers and also learn Salesforce. And it can help you get into the tech industry if you aren’t already in. They offer flexible hands-on courses. They offer one-on-one mentoring sessions, and then career coaching. And then all of that bundled together at the end, you’ll get hands-on work experience with nonprofits. It’s a really cool program, and not something that I knew that I would get into. But I wanted more structure for myself, and so I just reached out, I just sent them an email. And I think there’s one slot left. Josh Birk: Nice. Derika West: And I was like, sweet, okay, I’m going to take this opportunity to learn more. And I got in there. Josh Birk: Love it. Derika West: That’s where I started, with Supermums. It’s been a game changer, for sure. Josh Birk: And I’ve talked with people who there are similar programs out there. But the thing I love about that structure twofold is the fact that I find that a lot of… Without the soft skills part of it, without the career advice part of it, like, okay, now you have a certificate, now what? But the nice thing about getting to work with nonprofits, first of all, nonprofits love people who work with Salesforce that can help them. They need this help so badly. Back when I was consulted, nonprofits and small businesses were always my favorite. Because that thing that you just fixed for them has probably been annoying the heck out of them for the last year. And suddenly you are the superhero, you’re employee of the month. But it also solves, because I’ve talked to developers, I’ve talked to admins, and they’re trying to get a new job, and it’s the classic tech chicken and egg problem. You have no experience. I want a job. Well, I won’t give you the job because you don’t have any experience. And it’s the two things. If you can work with a nonprofit and be like, “This is what I have fixed for them.” I’ve told developers, just go get a developer edition and start coding. Just have an application that works that will prove to people that this is going to work. Derika West: Right. Josh Birk: Yeah. I’m assuming the learning experience has been good. Where are you in the course history right now? Derika West: Yeah, we’re actually in exam prep, so we’re at the very end. And everyone is extremely nervous to take their exam, including myself. But I am also really excited, because I know that everything I’ve been learning over the last six months has really helped me in my full-time position, and will only further enhance my skillset moving forward. I’m really excited. Josh Birk: And I will repeat words of advice I’ve gotten from people who have taken multiple exams in our own Salesforce certifications, and stuff like that, and people who are now technical architects. It’s like, always remember, failure is an option. It doesn’t mean you fail, it just means it’s part of the learning process. They do happen, but good luck. Sorry. Derika West: Absolutely. Josh Birk: I didn’t want to be pessimistic with that, but it’s always like we have… It’s part of our ecosystem a little bit, like coders who think that they have to be perfect. No, your code’s going to break the first 15 times you’re trying to make it. That’s just the iterative process. I want to shift gears a little bit, because I get paid a nickel every time I say the word AI. And I guess this is a weird question now that I know that your current big project is moving from classic to Lightning web components, so you might be a little hindered with this, but let me ask. In general, AI has become such a focus of all of our lives. How do you think it’s been… Has it impacted your work? Not necessarily even in an agent force point of view. But when you’re learning things or you’re researching things, has AI either impacted your work or your life? Derika West: On the work aspect, we are gearing up for AI. And that was actually one of our meetings today was going over the impact that it’s going to have on our applications. We’re literally switching every application that we own over, and we’re going to start implementing AI. Our daily functions, how we support users. So it’s going to be really exciting, but we’re not there quite yet. We’re at the very beginning of that transition, and Salesforce being one of them. That’s on the work front. On a personal front, I’ve been using AI to do so many different things for myself. To help learn at my own pace, to gather different types of documentation for myself just to organize my thoughts better. It helps me brainstorm better. It helps me get all my ideas down into a simplified version. AI is something I utilize all the time, if not daily. I love AI, and I’m excited to see how it’s going to grow the ecosystem. Josh Birk: Yes, and the same. And it’s like, you’re definitely sounding… From a work point of view, I think that’s where a lot of people are right now. It feels like a lot of people are moving out of the awareness phase and more to an adoption phase. That was a lot of nickels, so thank you for that. Okay. I have one final question for you. What is your favorite non-technical hobby? Derika West: Oh, goodness. Favorite non-technical hobby is probably hiking or snowboarding. I’m going to put them together because they’re one in the same. Hiking as a summertime activity- Josh Birk: I was just going to say. Derika West: … then snow [inaudible 00:24:12]. Josh Birk: Yep. That totally tracks. And you are in a perfect part of the world in order to do both of those things. Derika West: Yes, yes. Those are definitely my hobbies. It’s summertime here in Oregon now, so I’m taking full advantage of all the beautiful hikes nearby. And then, during the winter I go up to Mount Hood and snowboard. Josh Birk: That’s awesome. Derika West: It’s been great. Josh Birk: Awesome. Derika West: I love living here for those reasons. Josh Birk: I love it. All right. Well, Derika, well, first of all, good luck on your exams. And thank you so much for the conversation, it was a lot of fun. I want to, once again, thank Derika for the wonderful conversation. And of course, I always want to thank you for listening. If you want to learn more about this show, head on over to admin.salesforce.com where you can hear old episodes, see the transcript, and also see our blogs and our videos and other aspects of being a Salesforce admin. Thanks again everybody, and I’ll talk to you soon. The post Breaking Into Tech With a Nontraditional Background appeared first on Salesforce Admins.

Cleaning Data for AI Starts With Context, Not Perfection

Today on the Salesforce Admins Podcast, we talk to Chris Emmett, Salesforce Solution Architect at Capgemini. Join us as we chat about how to clean up your data to prepare your org for Agentforce, and why data without context is useless. You should subscribe for the full episode, but here are a few takeaways from our conversation with Chris Emmett. AI requires clean data I caught up with Chris hot on the heels of his TDX London session, “Prep Like a Pro: Clean Data and Metadata for Agentforce.” He’s an experienced Salesforce consultant who has helped countless organizations of all sizes reboot their business processes. As Chris explains, unless you have a company of five people that started last week, your org probably needs some data cleanup. And if you want to get started with Agentforce, you need to do the work to make sure the agents you build can understand your data and use it to generate actionable insights. After all, if you can’t derive useful information from your data, then it’s useless. Why cleaning data can feel like boiling the ocean When I worked in sales, we used a CRM that was so complicated that only one guy at our company knew how to use it. Talk about a bottleneck! The truth is, if your business has been around for a little while, you’ve probably inherited all sorts of legacy data. Maybe it’s some random field created by that one guy in the 90s who didn’t document anything, or a legacy system like SAP or MSX that is essential to your day-to-day operations. Chris has seen it all, and it can often feel like cleaning up all that data is akin to boiling the ocean. It’s a monumental task with no end in sight, let alone getting the organizational buy-in to do it in the first place. A practical way to start cleaning your data Chris recommends focusing your data cleanup strategy on the functionality you want to build in Agentforce. For example, if you want an agent to email a customer when their opportunity is five days from the close date and still unsigned, what data do you actually need? You don’t need the 300 fields that might be on the opportunity page, or the 300 fields in that account. You might need the opportunity’s name, the stage of the opportunity, the close date, the account, and maybe the primary contact of that account. That’s five pieces of information. Suddenly, you don’t need to boil the entire ocean—you just need to boil a cup of water. So start small, focus on the functionality your data cleanup project will deliver, and get the ball rolling. Trust that the things you build with Agentforce will speak for themselves, and you’ll be able to generate momentum to clean up your data project by project. Make sure to listen to our full conversation with Chris to learn more about how to clean up your data and provide context for AI agents. And don’t forget to subscribe to the Salesforce Admins Podcast so you never miss an episode. Podcast swag Salesforce Admins on the Trailhead Store Learn more Automate with Agentforce Episode: Using AI To Maximize Sales | Automate with Agentforce Salesforce Admins Podcast Episode: How Should I Clean Metadata for Salesforce AI Agents? Admin Trailblazers Group Admin Trailblazers Community Group Social Chris on LinkedIn Salesforce Admins on LinkedIn Salesforce Admins on X Mike on Bluesky social Mike on Threads Mike on X Full show transcript Mike: This week on the Salesforce Admins Podcast, we’re joined by Chris Emmett, consultant, data enthusiast and Salesforce evangelist accidentally. Well, Chris is passionate about data, and he takes us on a journey from legacy systems and those DOS screens to databases and AI-powered actions, all while sharing practical advice on how to clean up your data without making it feel like you’re boiling the ocean. So if you ever wondered how to prepare your org for Agentforce or why data without context is basically useless, this one is for you. So listen in, share it with somebody who maybe is swimming in a sea of records. So let’s have Chris swim his life raft over and let’s get him on the podcast. So Chris, welcome to the podcast. Chris Emmett: Thanks for having me. Mike: Yeah. Well, it’s good to be here. I got a note from Jennifer Lee. She saw the session that you and Jonathan did at TDX London about cleaning data and cleaning metadata, and last week, we talked with Jonathan about cleaning metadata, so this week, of course, we’re going to clean our data because who doesn’t have clean data? But let’s start off first with a little bit about you, Chris. How did you get into Salesforce and why are you so passionate about clean data? Chris Emmett: Yeah. Before I start that, you said who doesn’t have clean data? It really should be the other way around. Mike: I know. It was a rhetorical question to get people to listen and be like, oh, but there could be that one person that tunes into the podcast, like I don’t need to listen to this. My data is sparkling. Chris Emmett: You know what? If there is a company out there with five people who just opened up last week, their data is going to be impeccable, and they do want to listen to this podcast. They can tune out. Mike: Right. Chris Emmett: I started in the ecosystem in a weird and wonderful way because a lot of … you’ve obviously got your accidental admins that find a weird and wonderful way into Salesforce. I was an accidental consultant. So I started out fresh from university as a desktop support engineer, just fixing Windows and fixing printers and fixing Office, and it was great, fun. Then I did a bit of work as a developer, cutting my teeth on Visual Basic 6.0 and .NET all the way back in 2008. But that entire team was made redundant to make way for an off-the-shelf manufacturing system. And as an SME, as an expert in how that old system worked, I was brought in, and then the project manager on that project quit, and I became a project manager, and I was a project manager for 10 years. And then about 10 years later, around 2016, I was working for a company and we were really interested in changing how we managed products. We wanted a brand new system to manage our projects, and one of the products that we looked at was Salesforce. And my word, I was blown away. Literally within one day of using Salesforce, I was creating formula fields and workflow rules as they were back then, and I just fell in love. And this is coming from a person who had spent the best part of a decade dealing with systems where if you needed to add a field, it would take two, three months to get through, and I was dealing with a system where I could start a sentence, explaining to someone what Salesforce was, and by the time I’ve finished that sentence, I could have created a field. I could have expanded that data model, and I fell in love with it. The company I was working for did not fall in love with it, and that pilot failed. It fell by the wayside, but I was hooked. I was like, man, I need to change my career. So I start looking for project management jobs within the Salesforce space. I had never project managed software before. I had project managed big old factory systems that were very waterfall in their approach. I had never done agile before, so I was applying and applying and applying, getting nowhere. I was probably applying for about eight months, and then this small company in Cambridge were like, dude, you are not great for a project manager but you seem really enthusiastic. Had you considered being a consultant? And I went, but yeah, because it’s not managing the projects that I love. It’s the system that I love. Salesforce is a platform that I love. I want to be able to empower other companies to improve themselves through Salesforce. So I got a job there as a consultant, and that was 2017, and I have just been building up and flourishing, and since then, I’ve got 600 odd badges on Trailhead and I think 23 certs now. So I’ve just gone all in and built my career up. Mike: Wow. Holy cow. That’s a lot. I feel such a kinship with you because I joined … when I started doing Salesforce stuff, I worked at a publishing company, and we had this Apple-based CRM. I can’t even remember what it was called, but there was one guy in the office that still knew how to use it, and he would create views or lenses, and that was basically the only way we got things done. All of the salespeople, I was one of them, had to go to him and be like, please, Mr. Jay, would you create a view of … because none of us knew how to use it. It was incredibly complex. And then we tried to go to this other, this was 2004, we tried to go to this other web-based CRM thing. It was called absoluteBUSY. And if you wanted a field created, you had to log a ticket, and then the person that created the CRM in Sweden would create the field. And it would be like you. It was sometimes months. I just need another phone field. How hard can that be? Chris Emmett: Yeah. Mike: And then I went to another company and they had Salesforce, and I was like, oh, click, click, boom. And I remember, I was like, this is almost too easy to create a field. This is dangerous. Chris Emmett: Dangerous is the right word. It is. I’d like to think most Salesforce professionals go through some … it’s not quite like the seven stages of grief, but it’s the seven stages of Salesforce acceptance. You can’t go in. You’re very skeptical, and then you’re like, oh, wow, this can create whatever fields I want, whatever data points I want, whatever automation I want, whatever reporting I want. And then at a certain point, you go, oh, wait a minute, I have just created a monster for myself, and then you learn to think before you build. Mike: I feel like that’s a good starting point. Is that where you find most people go off the rails, is maybe they get Salesforce and like, you know what, let’s start fresh and they create too many fields? And then because there’s too many fields and they’re in such a hurry that they get to bad data. Chris Emmett: I look at it a different way. It may be my exposure. I deal with a lot of existing companies. I’ve not really dealt with a lot of brand new companies. So a lot of existing companies, especially if they’re at least 40 or 50 years old. They’ve got a lot of older systems. They might have a bit of SAP. They might have mainframes kicking around. They might have things written in COBOL or FORTRAN. I would even deal with companies today that have things in MSX, believe it or not. So the danger isn’t, oh, let’s just create everything in Salesforce. The danger is 14 years ago, Derek created this field. We don’t know what it does. We don’t know where it’s hooked up to. It’s not documented anywhere, but we feel like we should pull it over. So the real danger is actually migrating everything. If you don’t know what that data point is, you don’t know what use it is, you can’t validate it, and you can’t use it in any meaningful way. Because if you don’t understand, then to bring it to the point of this pod, if you don’t understand what that data is, what it means, what it’s doing for your business, how can an AI agent understand that? An AI agent is not magical. It’s not telepathic. It reads the information as if it’s a human. It tries to interpret that information. So you’ve got to know what it means so your AI agent can be told what it means as well. Mike: Yeah. I think people forget that new systems or new features won’t save them if they haven’t started to save themselves. Chris Emmett: Yeah. This is genuine, by the way. I was thinking this morning as I was just leaving the gym, so I can sound like I’m healthy. Mike: Oh, wow. Fancy. My weightlifting for this morning has been coffee cups. Chris Emmett: Yeah. So I was thinking this morning like, oh, what intelligent things can I say on this pod? I was actually thinking about the meaning of information technology as a term for a department within a business. Information technology, what does that actually mean? It’s not about the data. It is, but it’s not about the data. It’s not data technology. It’s not technology that drives data to help a business. It’s information technology. And the information that you derive from that data is the most important thing because you can throw data into a data lake or just into a database and just have it stored there. But if you can’t derive useful information from it, and similarly, if an AI agent can’t derive useful information from it, it’s actually pointless. Mike: Yeah. I’ve once heard information described as data plus context. Chris Emmett: Yeah, absolutely. Mike: And so if your data is bad, then it really lacks context, or you could say it doesn’t provide context. Chris Emmett: Yeah. It is all about that context. And again, just to bring it back to the whole Agentforce thing. Agentforce needs to understand that context. It needs to be able to derive some meaning from it. So just as a random example, let’s say you’ve got an opportunity record, which is great, and you’ve got a date on that opportunity. Cool. Agentforce, can you tell me if there’s a date on this record? Agentforce might go away and it might find that date and it might go, cool, Chris, I found a date. It’s July the 24th, 2025. Now, if that’s written in a note without any context, and I say Agentforce, what does this mean? It’s going to go, well, I don’t know. A date in the future. But if it’s against the close date field, it’s immediately got context, and it immediately can derive something from that. It can say, oh, right, okay, so this is the close date. I can see that we are in a negotiation stage. We’ve got one more stage after this, which is sign contract. It’s the 24th. It’s a few weeks away, or at least from when we’re recording. I understand a bit of context. I understand that there’s another stage ahead of this, and I’ve immediately got more information other than just a record with a random date. That context is everything, especially for an LLM. Mike: But the irony is, and I’ve done other episodes on this, you could have a close date, continuing your idea, of July 24th. In the close date field, except your company doesn’t use that, that’s the date that this part of the opportunity is going to close. But then maybe there’s a follow-on implementation stage, and that’s the context in which you use that. However, if you haven’t given your AI any kind of information about that, the context at which you use the close date, ironically, because you have a date in that field, it’s bad data, even though it looks like good data. Chris Emmett: Yeah, absolutely. And the point of the TDX talk I did with Jonathan, and I’m sure Jonathan has already mentioned this in last week’s episode, the data is important, the data has to be valid, but it also has to sit within contextual metadata. Because if you have a field on your opportunity that is called installation date or delivery date or deployment date, whatever, and you have an accurate data against that, again, you’re giving meaning to that data. You’re giving meaning to Agentforce so it can interpret it and give you useful information because it is about information. It’s not about the data. It’s the information. In fact, if I had a time machine, I would go back three weeks, redo my TDX talk, and it would be called prepping your information like a pro, and I guess your meta information. Mike: Yeah. But let’s pivot into that because it’s time to get actionable and less heady. And I’ve heard this a thousand times, it can feel like boiling the ocean to clean your data. What is your approach that you would suggest people use to start cleaning their data in preparation for deploying Agentforce? Chris Emmett: Yeah, sure. So again, unless you are that three-day old company with three people in and the data is perfect, it’s probably safe to assume you are sat on a mountain of data. If you are a relatively small company, maybe it’s tens of thousands of records. If you are a medium or enterprise, you might have hundreds of thousands or millions of records. I certainly worked for a company that had 30 million accounts in the system. That is a lot of data, and you cannot possibly begin to go through that top to tail, making sure that every field is correct and accurate and has meaning. So how do you actually break that down? You’re right. You cannot boil the ocean. We start off by thinking about the actions and the intents that you want your agents to do. So if you want your agents to write an email to a customer if their opportunity is within five days of the close date and they’ve not signed yet, well, what do you need for that? You don’t need 300 fields that might be on the opportunity page or 300 fields in that account. You might need the opportunity’s name. You need the stage of the opportunity. You need the close date. You need the account, and maybe the primary contact of that account. That’s five pieces of information. And then you do not really need to think about all of the old opportunities because this is about an action where you are emailing people for opportunities that are about to expire or about to close. So immediately, you’ve gone from a million records, let’s say, you’ve got it down to a thousand records, and then you’re only looking at those five pieces of data. So you got it down to a thousand records and you got it down to five pieces of information on those thousands records. So I’m not going to do the math in my head because I’m terrible at that, but it’s- Mike: Nobody should do math live. Chris Emmett: Yeah. You’re probably looking at about less than 1% of data because you’re thinking about the intent of that action, that AI action. You’re thinking about exactly what pieces of information you need to help that agent. And you’re making sure that that specific data is accurate. My theory behind this, my thesis, is by doing that, by getting rid of 99% of the data that you don’t need to worry about today, you can get agents and agent actions out to your users quicker, which means they’re happier. They’re trying new things. You’re getting feedback on those new things. And it means that you can improve more processes because you’re getting more feedback. You’re getting more insight into what is helping people, what’s hindering people. And you’re doing that because you’re just targeting the data that matters, and everything else can wait until it’s actually needed. Mike: That is probably the most concise spot-on answer I have heard in a long time. Chris Emmett: I felt like I was talking for about 20 or 30 minutes on that. Mike: No, you weren’t. So targeting the data that matters. Chris Emmett: Yes. Mike: Those words, put that on a shirt. Somebody needs to wear that shirt at Dreamforce because … so that as you were talking through, I was realizing you’re really making it from boiling the ocean to boiling a cup of water. Everything doesn’t have to be perfect for you to start this project. Just the part that you need to worry about. And I was thinking back to last week. So in Iowa, in the US where I live, we had a really bad frost all winter. We didn’t get the snow cover that we usually do, and some of my landscaping plans didn’t make it because the roots were just burned by the frost, but not all of them. Some of them were hardy and they’re fine. And so I called my landscape company. I was like, I need to replace all these, and plus I want different ones anyway. He’s like, good, because if we go through another winter like this, we’re just going to be replacing them. And I promise you this gets somewhere. But much like your analogy, so the landscape company came out, and just in the area that they needed to replant those bushes, they scraped all the gravel, leveled the bed, put new tarp down, replanted the bushes, put the gravel back. They didn’t have to clean the entire planter bed and scoop all the gravel out and dig up all the bushes and start from scratch. They only had to do the part that mattered. And I felt like that was like, wow, that’s like a real life scenario of if we’re going to implement this and we’re going to really laser focus on this one part of it, let’s do that. But the other key thing that you said that nobody has said on a podcast about cleaning data is you improve the process while you do it. Because if you are not going to improve the process that led you to the bad data, you’re always going to be cleaning data. It’s almost like sending a janitor out to a sports stadium to pick up trash because there’s no trash cans. Well, if you’re not going to sit down and say, okay, how do we put trash cans out so that trash isn’t everywhere? All you’re doing is sending the janitor back out to clean up trash. You’re not actually fixing the problem that led to the trash being everywhere. Chris Emmett: Yeah. It’s interesting you say that because I genuinely hadn’t really thought that far ahead. Mike: Yeah, you had- Chris Emmett: Probably not. Mike: … at night in your brain while you were sleeping. Chris’ brain is like, I got this idea about this process and then it was going to sound smart, and then it surfaced while you were working out. Chris Emmett: Yeah. People are going to be so disappointed when they see a picture of me because I’m making it sound like I’m some sort of gym monkey. Gym monkey, that’s probably not the right word. Mike: Well, I could throw your picture in AI. Chris Emmett: Yeah, yeah, yeah. You should. Mike: You’re like Arnold Schwarzenegger. Chris Emmett: You should. Yeah. I’ll look exactly like Arnold Schwarzenegger. Mike: Yeah, absolutely. Chris Emmett: I look more like Captain America at the start of the film. Mike: That is the best description. I look more like Captain America, but at the start of the film. Chris Emmett: Thanks. I’m glad you agree. I’m really glad you agree. Oh my, what was the point I was trying to … yeah, yeah. Okay. Yeah, back on track. So the whole point of IT, the whole point of computer systems is to improve things. So if you genuinely are taking an existing process and you are just throwing at an agent and say, robots, do my bidding, without changing anything, you really are missing the point of IT. It’s about evolution, it’s about simplification, and it’s about making things more efficient. So why wouldn’t you try and make it more efficient in the process of moving it over? Because if you don’t, you are just lifting and shifting a process, and that is not going to help anyone. It’s not going to fix any errors. The worst case of that is that you program an agent with all of the issues and problems that a human would have, so you are just replicating those problems. You’ve got to improve. You’ve got to evolve. Mike: Do you find, because you mentioned you work with mature companies that often when they’re doing a Salesforce implementation or they’re bringing you in or they’re thinking about something, that they’re stuck thinking within the constraints of the legacy system that they have? Chris Emmett: I was going to be kind. That sounds terrible. Mike: Well, you don’t have to … I don’t want you to- Chris Emmett: I was going to be kind and say the majority of companies will try and hold onto legacy, and there’s a few that don’t. But actually, I would be as bold as to say every single customer I’ve worked with, not necessarily through any fault of their own, holds onto the past. And it is either because there’s things that they don’t know, there might be fields or tables or data points or integrations that no one knows why they exist, and they’re afraid of removing them. And in the data, they don’t know what the data means or whether it’s useful. It’s just there. So they don’t don’t know know how to cleanse it. They don’t know if it’s got any meaning. But then you’ve got companies who are just in a bind where they’ve got a 30-year-old system and they do not have the budget to replace it, but Salesforce has got to integrate with it, and the design decisions 30 years ago for that system that Salesforce has to adhere to. So sometimes, it is because the systems that you have to hook Salesforce into are just bound by old design, and then you have to introduce those bad data decisions into Salesforce. Mike: I could see that. I was also thinking back as you were saying that. About a week ago, I was standing at a rental counter and I happened to see their screen and it was still a DOS screen, like the whole … I was like, wow, you still work on that? I’m fairly certain the car you’re about to hand me keys to has a stronger computing system in it than what you’re sitting at right now. Chris Emmett: Probably. The phone in that pocket is probably more powerful. I definitely worked for a company, I can’t say their name, I’m pretty sure, but I worked for a company where they were using an MS-DOS program because the person who wrote it, he wrote it in his garage and then retired in the ’90s. And if he’s still with us, he’s probably, I’d like to think, on a yacht somewhere because the software developers in the ’70s probably earned quite a lot of money. He’s enjoying life and not thinking about it. But that company was stuck with that MS-DOS program because it did a vital thing and it can’t be removed. It can’t be replaced because they know it does a vital process, but they don’t know how it works. And then it becomes a business risk. It’s like, do you risk the operation of the business to try and rebuild this or do you just leave it? And then another thing I was thinking about this morning, I was thinking a lot of stuff at the gym. Mike: Apparently. Holy cow. But to be fair, you’re always thinking like this. This wasn’t just this morning. Chris Emmett: You are right. You are right. I’m always thinking this. My thought process flips between IMDb trivia and Salesforce. I was thinking that I have worked with a lot of companies where it’s common practice to buy old equipment from eBay. Mike: Oh, wow. Chris Emmett: If you’re a retailer and you’ve got systems that haven’t been made in 10, 15 years, but you need that equipment, your only course is to scour eBay. I’ve worked with two or three companies that have done that, and it becomes a risk. But again, not to be too mean against them, it’s more often than not a budget constraint. So bad systems and bad data with those bad systems is not necessarily because people have just made bad choices or due diligence isn’t being put into it. More often than not, it’s about legacy systems and budget, and that’s a difficult thing to overcome. Mike: Especially the budget part. Chris Emmett: Yeah. Mike: I was just thinking back. I worked retail in the ’90s. And retail in the ’90s, if you were a smaller retailer, it was common practice for smaller retailers, when the big box companies would change systems, they would have a clearing out, and smaller retailers could buy enough POS systems that worked and then enough that didn’t work for parts and literally upgrade their whole system, even though it was used systems. And that was common in retail in the ’90s. Now, it’s all changed. It’s all online. I’m sure that doesn’t happen. But I remember working for a couple retailers and like, oh, we’re getting new cash registers, and they would show up, and why are some of the keys sticky? And they’re like, well, they’re not new. THey’re new to us. Chris Emmett: Yeah. Mike: I wonder what’s creeping around inside of those old systems. You bring up a good point. I think I’ve done a lot of podcasts on cleaning data and cleaning metadata, but what’s interesting about this one, to put a point on it, is you pointed at something that none of the others have brought up, which is it’s not necessarily bad user’s fault that we have bad data. It’s sometimes a systematic failure of bad decisioning or a lack of budgeting priorities that leads to it. It’s not just Bob, the sales guy, who puts his call notes in the phone field because that’s what he does because he pays no attention. It’s sometimes working within the constraints of the budget. You’re probably doing that now, even doing a Salesforce implementation with AI. You’re like, well, we would love to do all this, one through five, but we can afford one now and maybe two later. They maybe even start on the second project, and then that’s as far as they get on their list of one through five. Chris Emmett: Yeah. You know what? If Bob wants to put his data in the wrong field, that is, in my opinion, that is probably a low impact. It’s a quick fix because either you can tell him to move it or you can, if it’s consistent, you can go in with Data Loader, export it in Excel, copy it from one column into another column, re-upload, you’re done. For me, it’s about all of this historical data that you may be pulling into Salesforce where you don’t necessarily understand its context. You don’t necessarily understand its validity. And that’s where the whole point of trying to identify what’s the actual action that you want your AI agents to carry out, and what are the data points that that action needs to interact with? Okay. And then let’s tackle those data points and turn those data points, to go way back to the start of the conversation, you turn those data points into information, because you cannot boil the ocean. And the majority of companies, at least the ones I’ve dealt with, have a sea of data that just either makes no sense or comes from old systems or comes from unnecessary decisions. And you cannot … there’s no business case that will ever be put forward to say, we need to spend 10 years improving all of this data. But there definitely would be a business case that says, we need to spend a month chipping away at this opportunity data or this account data so we can deliver this agentic functionality. Mike: Right. Spot on. Now, I want to end on a fun note. You said IMDb data trivia. Chris Emmett: I like IMDb. Mike: Is it trivia about the website IMDb or is it trivia about movies and TV shows? Chris Emmett: Oh, wow. I’m really upset that I don’t know the history of the website now. Mike: Oh, I kind of do. Chris Emmett: Oh, do tell. Mike: So the Cliff Notes version is a guy started, I don’t know when, but it was started pretty early in the … maybe even pre-internet. I want to say he either had a huge collection of VHS tapes or he ran a rental movie store, and he created this literal database of movies and actors and actresses and roles and directors, because he found it fascinating to see what, like we’ve all heard, the seven, six degrees or Six Degrees of Kevin Bacon, like connecting people to different movies. He found that fascinating. And I want to say early on, Amazon bought it and curated it into the big website that it is now. That’s the amount of history that I know about it. Chris Emmett: Well, I can add to that. Mike: But it was one person’s passion project. Chris Emmett: That’s crazy. I can add to that in a related way, in a very Salesforce related way. Mike: Oh. Chris Emmett: And if anything, that’s why we’re all here. So during COVID, we were all watching a lot of TV at home, I’m pretty sure. I was. And I wanted to track what I was watching. I wanted to be able to give it some fun ratings. And I could have done that in a notebook or on a spreadsheet or in my notes on my phone. But 23-time certified, of course, I’m going to build it on Salesforce. Mike: Yeah. You have 600 badges. You can’t not. Chris Emmett: So I built it in a developer edition, salesforce.org. I was tracking all of the movies, all of the TV programs I was watching during COVID. And to just take it a step further, I didn’t build it, I ripped it off the internet, an integration into IMDb to pull the correct title, the director, the Rotten Tomatoes rating, I think, and the synopsis. So all I needed to do is type in the title and my own personal rating. And when it saved, it pulled back the poster, all of the cast, the directors, genre, everything. And that took one weekend. If people are listening to this and they never touched Salesforce before, that’s how quick it is to build something in Salesforce. I did that in a weekend. Mike: So you’re my long-lost brother, I swear. No lie. And I can show this to you. I’ll show this to you at Dreamforce, hand to god. I was in the same scenario in December of 2013. I took a long vacation break. And for many years, up until that point, I was hooked on Top Gear, and I thought I should keep track, because you could also get all of the Top Gear episodes off of iTunes, off of that, it was called iTunes at that point. Chris Emmett: Yeah. Mike: And I was like, I should keep track of this so that I know which ones to buy, which ones I like and have a whole … And so I literally spent 30 seconds. I was like, I could do this on a spreadsheet, but wait a minute, let’s do this in a developer org in Salesforce. And I created a Top Gear app, and I branded the whole salesforce.org Top Gear with Jeremy Clarkson and all of them. I had cars and stars and lap times and episode ratings and titles. I ended up, for almost a whole weekend straight, just non-stop binging Top Gear and building this org. Chris Emmett: That is awesome. Mike: And now, it’s one of those where I have to remember every month I log into it to make sure that that org dies. I would cry if that org went away. I seriously would. But yeah, I’m not fancy and smart like you. I don’t know what I’d integrate it to. I guess I could integrate it to IMDb to pull that stuff in, but I more just wanted it of my own information. But it was so old. It was back in the day when you used to stick image files in resources. Chris Emmett: Oh, yeah. Mike: And then you would do an image. You would create a formula field that returned an image, and that’s how I did star ratings on the page. Chris Emmett: That is still a valid way to do it. I don’t care what anyone says. Mike: It just feels so old school. But I remember showing it to somebody and they’re like, how did you get stars to show up on the page? It was like, well, let me tell you. Chris Emmett: That’s what it’s about. I don’t care what anyone says. Salesforce for me is about, as a profession, you are obviously going into businesses and building out their systems to improve the way they work, but for me, the beauty of a dev or a developer org is to be able to just do my own personal random projects where I might have an idea where it’s a weekend. I want to see if it works. And nine out of 10 ideas may burn and fail, but that one idea out of 10 might be just gold. And all of a sudden, I have a movie tracker that I can use, and I’ve learned something. And you know what? I can then take some of that integration knowledge to my next customer. It’s about just trying stuff out, exploring, being bold, being crazy. Mike: I would argue even those other nine are still fun when they fail because there’s a moment when you’re like, I think this is going to work. Well, I know it’s not going to work now, and now I know what not to do. Chris Emmett: Exactly. Mike: Chris, this was a blast. Chris Emmett: It was amazing. Mike: I’m so glad … I think we talked about some clean data. Chris Emmett: Data is important. Data and information, very important. That’s the takeaway. Mike: Yeah. We got to get some shirts made for Dreamforce. Thanks so much for being on the podcast. And I’m fairly certain you and Jonathan will have long legs in presenting your clean data and metadata information to the world. Chris Emmett: Yeah, no doubt. Thanks for having me. Mike: All right. So that’s a wrap for today’s therapy session with Chris Emmett. I can’t help but say we laughed, we learned, we IMDb’d. I will say after the call, we probably went down a rabbit hole of movie fun facts from television shows from the ’80s. That was incredibly fun. But again, if you’re secretly running a DOS system or still mourning a lost developer org, just remember, not all your data deserves your attention. Boil a cup of water, not the ocean. And maybe for fun, build a movie tracker while you’re at it or a television show tracker. So if you love this episode, be sure to give us a review on iTunes. Share it with another admin who needs a nudge in the better direction of cleaning data. And until next time, we’ll see you in the cloud. The post Cleaning Data for AI Starts With Context, Not Perfection appeared first on Salesforce Admins.

How Should I Clean Metadata for Salesforce AI Agents?

Today on the Salesforce Admins Podcast, we talk to Jonathan Fox, Head of Salesforce Architecture at IntellectAI. Join us as we chat about why we should rethink how we label, structure, and maintain Salesforce metadata. You should subscribe for the full episode, but here are a few takeaways from our conversation with Jonathan Fox. How do you know if your metadata needs to be cleaned up? When we were trying to implement Agentforce on the Admin Evangelist org, we came to a sobering realization. Despite all the content we create on how to do things the right way, it turns out that we all approach metadata a little differently. That’s why I was so excited to sit down with Jonathan to talk about how to clean up your metadata for AI. Training an agent is like showing your org to someone who knows nothing about your business. Suddenly, it’s really important what the labels mean and that they’re consistent. Start small with metadata The thing about technical debt is that it’s not a problem until it becomes a problem. Your metadata is probably fine for most of your users, who have a working knowledge of your business processes. It’s only when you try to implement Agentforce that you realize you have a problem. Jonathan recommends that you start small when you’re trying to clean your metadata. Roll out Agentforce for a small use case and only clean up the metadata associated with that specific task. If you need to generate buy-in, try running Agentforce as-is and then show your stakeholders just how much difference a little bit of cleanup can make. Metadata is the foundation “Your metadata is the foundation of your Salesforce org,” Jonathan says, “you don’t want to get it wrong, you don’t want to make it worse. So it needs to be treated with that respect and that kind of importance when you’re changing it.” Documentation is the key to making sure that you’re keeping things usable for human and AI employees alike. You need to make sure that you fully understand the impacts of any changes you’re implementing, or you risk breaking all sorts of automations in your org. Jonathan had so many more great insights about how to start cleaning up your metadata for AI agents, so be sure to listen to the full episode. And don’t forget to subscribe to the Salesforce Admins Podcast to catch us every Thursday. Podcast swag Salesforce Admins on the Trailhead Store Learn more Salesforce Admins Podcast Episode: How Are 2025 Admin Predictions Holding Up So Far? Admin Trailblazers Group Admin Trailblazers Community Group Social Jonathan on LinkedIn Salesforce Admins on LinkedIn Salesforce Admins on X Mike on Bluesky social Mike on Threads Mike on X Full show transcript Mike: Welcome to the Salesforce Admin’s podcast, and hey, how did we do last week? Did you listen to that episode to see how our 2025 admin predictions were holding up? If not, add that to your play next list, because that was a fun look back. I like listening to things from the past, but let’s go ahead to the future. So in this episode this week, we’re joined by Jonathan Fox, who takes us behind the scenes on something every admin deals with, and maybe you don’t think you do, but it’s metadata. And in fact, in next week’s episode, we’re going to talk about cleaning data, so buckle up folks. It’s summer cleaning time. But the fun thing is we start off with a conversation around a barbecue that sparked Jonathan’s career and got it into amazing directions. How many people talk Salesforce over barbecue? And Jonathan also helps us rethink how we label, structure and maintain Salesforce metadata. So whether you’re prepping for Agentforce or just going through an org and wondering what some of those data labels mean, I promise you, this episode is for you, and if you love what you hear, be sure to give us a favorite or a review on iTunes. But with that, let’s get Jonathan on the episode. So Jonathan, welcome to the podcast. Jonathan Fox: Thanks for having me. I’m excited to be on. Mike: Well, I’m excited to tackle this because we’ve bounced around and I’ve done a few episodes on cleaning data and cleaning metadata and back and forth and back and forth, and I think it hit our team like a truck when we were working on implementing Agentforce in our org, and Josh, who was working on it, came to the realization that despite having three or four evangelists on the team, we’d all named fields differently and we’d all done things a little different. And he’s like, “We really have to talk to people about metadata.” And we’ll get into that and we’ll have a follow-up episode on data data, but Jonathan, let’s hear about you. How did you get started with Salesforce and what do you do? Jonathan Fox: My journey into Salesforce was, well, most people say this, a little bit unorthodox. My background is the military in the British Army, and I stumbled across Salesforce, family barbecue. My brother-in-law brought me into the Salesforce world and taught me how to be a developer basically, and I worked my way up through- Mike: At the barbecue? Jonathan Fox: At the barbecue, yeah. That was the riveting conversation we were having over beers and burgers, was Apex in fact. Not quite metadata, but at least a bit of Apex was the topic of conversation. He taught me how to get started in tech and how to be a developer, and the rest is history as they say. Mike: I feel like that was the one line that he’s telling his significant other. “No, this line’s going to pay off. I’m going to find somebody at a party or a barbecue that wants to talk about Salesforce stuff, just trust me.” Years go by, he goes to parties and nothing happens, and then he finds you and he just says something. You’re like, “Yeah, that sounds good.” “What?” Jonathan Fox: His significant other and mine at the time were just sick of hearing about what is Salesforce? It’s all we spoke. Mike: You two go off, grill a burger, talk Salesforce. Jonathan Fox: Come back later. Mike: Come back later. That’s crazy. So when we talk about data, every single feature that we roll out, it always comes back to data, but I think more so with Agentforce. Now we have to go one layer deeper with metadata, and I’m going to start off with a hard question. Jonathan Fox: Go for it. Mike: I think it’s hard. How do you know your metadata is bad metadata? Jonathan Fox: I think that’s a really good question, and I think it is a hard question. I think it’s really difficult to know whether your metadata is bad, and until you start poking around with things such as AI, you probably don’t realize it. And a really good example, and probably one that we’ve had conversations in the past about this at your org that you use and things like that where you have these field names. Field labels for example is a type of metadata, and they often have acronyms or naming conventions that only you, the users, actually know about. And until you start trying to make AI understand what they mean, you don’t realize because you’ve got all your industry knowledge, you’ve got all your organization knowledge, you’ve done your onboarding. You know how the org works because you’ve been trained and taught and you speak the lingo, but the AI doesn’t know that. So it’s only until you start getting to play around with these kinds of things, you go, oh, actually, a fresh set of eyes, somebody who has no idea about this hasn’t got a clue, and I think it’s at that point you start realizing our metadata needs to have a little bit of a revamp. Mike: Yeah, the field labels and values that you use for fields that are going to be displayed on a page is one thing. I always got quite cavalier, I’ll use the term, with fields and labels for stuff that I just needed on the object that wasn’t going to be displayed on a page. And now I’m thinking, oh God, Agentforce is going to have reference those and it’s totally not going to understand what SP_25Z_PRD means. Jonathan Fox: Exactly, but you know what it means? Mike: The whole organization knows what it means, because everybody’s into acronyms, and I just need to store the value on the object for the record but I didn’t need to display it for the user, but now I’m going to ask Agentforce for what’s the speed record number or something, and it’s going to look at me like, “I don’t know. You’re not capturing that. I’m going to go back over here and talk with this dude about some Apex and grill a burger.” Jonathan Fox: Yeah, exactly. There are ways we can get around it with Agentforce and it’s things like putting those acronyms in instructions, but is that really the best way to do it? That’s almost like hard coding references within Apex. And at that point, you start thinking, yeah, this isn’t right. This isn’t the best way to do it, and I think that probably answers your question. At that point, when you start having to do workarounds and figure things out like that, you know your metadata is not in a good state. Mike: So that feels like we’re walking down a path and we hit a fork in the road where we realize there’s a whole bunch of these weird fields. They always include underscores. Why is that? I don’t know. People like the underscore. They do that on Instagram too. Do we create this massive dictionary and feed it to Agentforce, or do we have to go back and… When we talk about clean data, you extract the data, you look at it, you fix what’s wrong and you shove it back in for the most part, or should we do that with metadata? Jonathan Fox: I think you have to take a pragmatic approach with anything that you do in the Salesforce org, and that goes for metadata, data, tidying up your flows or refactoring your Apex classes and methods. You take a look at it and go, how big is the job? You impact SS? You go, how big is the job? What’s the return on investment of me doing this now versus the cumulative over the next few years? Is it worth my time to go back and fix it all? And gold standards, what we teach and what we hope to aim for is yeah, go back, refactor it, make it perfect, but sometimes it’s not an issue until it becomes an issue. In this case, for example, your field labels, they weren’t an issue in the past, they are now, and I think it’s one of those where you have to sum up all those different variables and think, is it worth it? Now, if it’s only a couple of fields and it’s only ever going to be a couple of fields, maybe it’s quick enough just to go back and fix it, or maybe it’s not worth the effort and you write it in the instructions. But I think it’s org dependent, variable dependent, even individual skill set dependent. But it’s one of those that you have to… It’s a really non-answer, I know that, but I think there are so many variables. You can’t just blanket rule. Obviously, we want to aim for gold standard. Mike: Well, the fallacy is we hear metadata and data and you think, “Well, I’m just cleaning data.” But the cleansing of it is actually very different, so what are the implications? I’m sure Chris and I will talk about this, but if you go through your org and you’re like, well, everybody has to have a proper name, and so you fix all the nicknames or shortened names. And so you come across the John Fox record. You’re like, nope, it’s got to be Jonathan. I can confidently say for the most part that changing John to Jonathan isn’t going to fire anything, isn’t going to break anything, but my question to you is if I go in and I change a field label or I change some metadata on a field, what could I break? Jonathan Fox: Oh yeah, you are risking breaking things. You’re potentially risking breaking your flows, your Apex, your validation rules. Sometimes, hopefully you referenced them through API names and we might not be changing them here. We’re probably changing field labels, not API names, but you may want to change those as well, and then at that point, you are potentially impacting all of your automation in the org, your validation rules, your assignment rules, et cetera, et cetera. So you have a big knock-on effect by changing metadata, and that’s because metadata in Salesforce is the replacement for you writing code on the back end. That’s the whole point of it. That’s why it’s a SaaS and a PaaS to some degree. Salesforce themselves by producing the platform is saving you having to write how fields appear on the UI. You are just putting placeholders there and that’s what metadata is on the Salesforce platform, and you change that, you’re impacting everything else that references it potentially. So there are big consequences and it isn’t just a case of going to object manager and going switch some characters around to make it look neat for Agentforce. Mike: So I think oftentimes, people hear cleaning data and I’m sure cleaning metadata, which feels like next level cleaning. It’s like having your carpet shampooed. It’s like, cleaning your house is just vacuuming. Nope, we’re calling in Stanley Steamer. They’re going to do the rugs now. They’re going to get all of the dirt out. It can feel like, oh, we have to do all of it. We have to clean everything. And I don’t know, maybe you have a tiny house and you can spend half a day and clean your whole house. I can’t clean my whole house, but people for some reason look at, “I have to clean all of my data.” Given the implications of updating information and metadata, how should people approach cleaning or getting their metadata right for Agentforce? Jonathan Fox: There’s probably a couple of ways to approach it. I have a small house, I can probably clear most of mine within a day so I’m lucky. That doesn’t mean I enjoy it though, so there are definitely- Mike: No. Well, there’s that. I don’t know, using the big leaf blower, I could probably clean my whole house and I wouldn’t enjoy it, but it’d be clean. Jonathan Fox: Well, that’s true, and it’d be good fun in the process. I suppose if you think you’re going to have guests over to your house, you’re going to host a dinner party or just have some friends, you don’t go cleaning all the bedrooms necessarily, and you clean the places that they’re going to see. You clean your living room or your kitchen and the bathroom that they’re going to use. In a similar way, what is Agentforce going to be using within your org? You might be rolling out Agentforce for a small use case first to prove the ROI to your org. Fantastic. So you might have a small use case and it’s only referencing fields on the contact object. Start with the contact object then. Start with those fields that Agentforce is going to be using, and you’ve proven out that return on investment, your organization loves it, and now they want to expand it to using data from opportunities or orders or whatever else. Then you start moving out to where your guests, your agent, is going to look next. So that’s how I would personally approach it, is start with what it’s going to be looking at first, because otherwise you’re going to be overwhelmed with such a huge task and that’s not going to be as productive. Be iterative, work on it in chunks, break it down. Mike: No, I like that. Clean where the guests are going to be, close the doors to the rest of the house. There’s nothing there. Jonathan Fox: Exactly. Mike: It’s a doorway to a big black hole. Don’t open that. Jonathan Fox: You don’t need to look in there. You don’t need to see the piles of boxes. Mike: Here be dragons. So one thing, and I’m going to have to ask Chris this when we record his podcast, because I’ve done data cleansing exercises before where you look at things and consultants, you’re brought into jobs and stuff, and you look at the data and you’re like, well, this is close date and there’s July 27th, 2025. That’s a valid close date. Why is that bad data? And it’s bad data because the process is, well, but after the opportunity closes, we also have an implementation stage and blah, blah, blah, and so if we ask Agentforce, what’s the close date? It should say August 24th because it’s always a month after the close date of the opportunity. How do you know when you’re looking at metadata in the same way that you’re like, oh wait, this is something that Agentforce can’t use, although it completely looks like usable metadata. Jonathan Fox: I guess you have to almost treat the agent as it is your employee. It’s your agent employee within your org, but it’s one that hasn’t gone through on board and it doesn’t work day to day in your org doing all the different processes that your service agents or sales reps might be doing. So you’ve got to look at it and treat it as if it is a brand new fresh employee that hasn’t been through any of that training, hasn’t gone through any of that. Straight out of college or something, never been in the industry either, and walk through the life of what you’re asking that agent to do, and if it can’t do it, then that’s where you need to be looking at changing that metadata, change that label. And you’ve also got to think as well, you don’t necessarily want to change it if it’s going to impact all your human employees either, so where do you draw the line and strike the balance between making your metadata perfect for agents, AI agents, and making it really confusing and changing it all after many, many years for your human employees? And I think there’s a balance that needs to be struck there. Mike: So that to me sounds like the importance of perhaps a data dictionary or just org documentation, right? Jonathan Fox: Absolutely. Mike: We can upload those as resources. I think that’s getting better. I haven’t done it. Have you done that? Jonathan Fox: I’ve played around with it a little bit and I think it’ll only get more powerful, and I think it only really highlights the absolute need to have strong documentation within your Salesforce org. Again, documentation is one of those really good topics that we can speak for hours about because documentation is only as good at the point in time when it’s written because your org is ever evolving. As soon as you bring out a new field, you’re having to update that documentation, so keeping on top of it is really important, and trying to have that living document, you upload it to Salesforce for Agentforce to use, it comes out of date immediately. So again, that’s a whole topic of its own, but I think it does really highlight to Salesforce customers and people working in Salesforce orgs that tracking all these kind of things is really key if you haven’t already done it, and that is a big task, but it will pay dividends. Mike: Yeah, I think sometimes people, and myself included, you get caught up in the speed and the immediacy at which you can do things and you forget, oh, I need to, best practice, write down what I created, why I created it. So I want to pivot off that because if you have bad metadata, it could be the result of you have a bad deployment process or a bad, I don’t know, requirements or discovery process. Can both be true? Jonathan Fox: Yeah, absolutely. If you think all the way back to the beginning of their future and you’ve got your BAs looking into what the product owner wants and they’re trying to gain this information from them and then perhaps translate it into Salesforce terms, and maybe there’s a gap there or maybe the Salesforce consultant hasn’t poked enough holes in the requirements and tried to transform them a bit more. You may have missed that gap all way at the beginning. Or it may be it’s absolutely fine for what you’ve been requested to do and you’ve built it exactly to spec, but it gets to UAT, and at that point, it was missed that your users had no idea or your agentic employees had no idea what it was doing and it got deployed. And absolutely, that whole lifecycle of development there, there are different quality control gates that absolutely could have missed this or just never had to think about it in the past, and now we do have to think about it. And I heard you laugh a little bit then about the agentic employees and the UAT. Is that something that we maybe need to start thinking about? Testing in UAT, but with agentic employees rather than just running scripts to test things, and taking it outside of the box a little bit. If we’re going to treat them as employees then perhaps that’s the right stage for them to get involved in a different way. Mike: Until you said that, I never thought about UAT for agentic employees, but it completely makes sense. And it completely makes sense you can do it with user testing because you don’t want to get all the way to production and then suddenly it falls on its face so you’re like, wait a minute, how come that didn’t work? No, it’s fascinating concept. I think one of the things you mentioned that I want to bring up, so when we have Chris on next week and we talk about data cleansing, I’m going to ask him about changing data. Because data, for everybody, they see it, it’s very visual. If you change the date format, let’s say, of a field and you go from European style to American style, your user is going to be, “Whoa.” They’re going to immediately see that. I don’t know that they would immediately see, or they probably shouldn’t unless they’re pulling in weird fields and reports, metadata fixes. But with that, I think what is important to get in terms of sign-off or process or executives to go through this process? Because at some point, you’re going to have to talk, well, we got to fix this data, we got to do this, we got to do that, and we need to make sure that we’re fixing the process. I think data is a public thing, your users see it, but metadata is almost the behind the scenes. How do we make the backstage cleaner, and then how do we make sure that all the stagehands know to keep the backstage cleaner? So that’s a really long question of in addition to knowing we need to fix it, if I’m sitting here saying, “Cool, I’ve listened to this podcast and Jonathan’s hammered it into my head, I need to fix it,” who should I start talking to? What are the sign-offs I should get? Jonathan Fox: Yeah, I think you are obviously going to need sign-off. You’re going to need the buy-in of the people who hold the budget within the organization, and that could be all sorts of different roles within your organization to all sorts of different levels. I don’t know who that will be in your given organization, but it’s whoever owns the platform ultimately and whoever has the budget to deploy the team who’s going to do, one, the analysis, but two, the actual development, we’ll call it the implementation and the testing and deployment afterwards. And I think the best approach for that is to even perhaps try using Agentforce today without changing your metadata, in a sandbox or something, and then show even the smallest of change and how it impacts the agent. Because listening to the podcast today and hearing that you need to transform your metadata isn’t going to get the sign-off and the approval of these people within the organization. They’re going to want to see how it changes, why, the metrics behind it, and I think that’s the best way to do it because every org is so different. Your metadata is going to be so different from the org next to yours, there is no one rule fits all, and I think other than just showing and visually demonstrating how much Agentforce can enhance your org without it versus with the change and show how much it can speed up your users and all the automations it can do, I think that’s the best way to approach it, and it is with that person who ultimately holds the budget. Because it’s not a one-person job. There is going to have to be some analysis there. You’re going to have to do some changes, you’re going to have to test them and deploy them. It’s almost a project in itself, and I think it should be treated as such because it is such an important step. And your metadata is the foundations of your Salesforce org. You don’t want to get it wrong, you don’t want to make it worse, so it needs to be treated with that respect and that importance when you’re changing it. Mike: Well, if you think of it, I’ve always answered the question, if you ask a company what’s its most valuable asset, it shouldn’t be the product it puts out. It’s the data that it has, and its second most valuable is its metadata because that’s the way that you find out what data you have. Jonathan Fox: Yeah, exactly. Mike: And you query it. Jonathan Fox: Yeah. If you don’t have a strong metadata structure within your Salesforce org, well, then you don’t really have a Salesforce org because your data’s not going to fit. So yeah, it’s second because obviously the data is what you’re using day-to day. That’s the valuable part. Mike: One thing we haven’t touched on is we’ve lived in this perfect world of we’re just fixing metadata in Salesforce. I don’t want to say the wrong term, but when I think about it, integrations, I call it the data you inherit, the data that comes from other systems. How should we approach metadata fixes for that? Jonathan Fox: It’s difficult, especially if you’re forced into a particular route because of an integration or another system, but the Salesforce platform is really flexible. There’s not really any reason why the metadata that Agentforce uses today can’t be specific and clean in accordance with your Salesforce org. There is no other external system out there that necessarily will force you down a rabbit hole and make you have to do it in a certain way. There are always ways that within the org, you can transform your data from where it’s held on that metadata and make it work for those external systems. I think it goes back down to again though, making sure your documentation’s clean, because if you are forced down a particular route through inherited metadata or third party systems and all the things that you can’t control perhaps, then that’s where the documentation becomes vital again as we mentioned earlier. Mike: Yeah, especially if you’re… Anytime you bring something in or Salesforce pushes data out, there has to be some documentation on that. That was always the fear that I had as an admin of did I leave enough behind so that somebody knows if things go thermonuclear, what buttons to push? And the end result is if you feel like you have enough, you’re probably halfway there because you could always write more. Jonathan Fox: Yeah, absolutely, and even look at the things that you can’t control. You have some really cool app exchange apps in your org. You can’t control their metadata. That’s the whole point of those vendors, and perhaps they’re not top of mind for AI at the moment or they’re getting round to doing it, but you want to adopt it before they’ve had chance. That’s where documentation is going to become key, because you can’t control what they’ve produced for your org, and it works amazingly because it’s the product you’ve been using for years. But you need it to work today for Agentforce and perhaps they’re not ready or it doesn’t work the way that you want it to but it works for them and all their other customers. Documentation is going to be a key there. Mike: Right, absolutely. Well, this is fun. We dove into the scenes behind the scenes. It’s like best practices on writing cue cards for comedians. Jonathan Fox: Absolutely. Mike: It’s the person that stands behind the camera that tells the camera and the comedian what to do is often underappreciated. There’s a whole world of people, just to go off on a tangent, that do write cue cards, and there’s a script to learn how to write it so that it’s very readable. It was a fascinating- Jonathan Fox: I did not know that was a thing. Mike: A fascinating little rabbit hole I went down one day on YouTube and the internet, because you can learn everything from the internet these days. Jonathan Fox: Oh, it’s so true. Mike: Yeah, isn’t it? But you’d think by now we’d be printing it, but nope, it’s humans writing it. So Jonathan, this was a blast. I’m glad we came on, we got to talk about metadata. I think it’s probably the thing that most people aren’t looking at. They’re probably like, “Oh, I got to fix my data. I got to do this,” and they’re just tidying up the entryway and they’re forgetting there’s a whole lot more to do behind the scenes in addition to just the data that Agentforce consumes, and it pays dividends outside of that too. Better reporting, better everything. I know that I’m guilty of users running reports and including fields and them saying, “I don’t know what it is, but I just included it because it had numbers in it.” I’m like, cool. Jonathan Fox: Because it makes the report look fancy. Mike: I need to fix that field and make it a little bit better. But no, this was great. Thanks for coming on the podcast. Jonathan Fox: Yeah, thank you for having me. I’ve really enjoyed it. Mike: Big thanks to Jonathan Fox for joining us and breaking down the realities and opportunities of cleaning up metadata, and as Agentforce becomes part of the how we work, taking a closer look at what’s under the hood of our orgs is more important than ever. Now, before I say that and you’re this far, get ready for next week’s episode because in addition to cleaning metadata, I’m going to talk with Chris Emmett about cleaning data, and this is a super fun episode. We do go off the rails a little bit about movies, but that’s okay. So I hope you enjoyed this episode. I hope you take the time, listen to what Jonathan has to say, talk to your executives, your stakeholders about field labels, documentation habits. And if you loved what you hear, share it with a fellow Salesforce admin, tweet it out on social, and until next time, we’ll see you in the cloud. The post How Should I Clean Metadata for Salesforce AI Agents? appeared first on Salesforce Admins.

How Are 2025 Admin Predictions Holding Up So Far?

Today on the Salesforce Admins Podcast, we talk to Jennifer Lee, Joshua Birk, and Kate Lessard from the Admin Evangelist team at Salesforce. Join us as we revisit the team’s predictions from the beginning of the year for how Agentforce will change the game for admins in 2025.  You should subscribe for the full episode, but here are a few takeaways from our conversation. Agentforce content highlights from 2024 I started by asking the team which content from 2024 still holds up. Between “Automate This!” and “How I Solved It”, Jen puts a lot of great stuff out there. However, she pointed to her modular flows walkthrough on the blog. By breaking complicated processes down into smaller chunks, you make it easier to reuse bits and pieces of them in future solutions. Kate was more focused on the big picture. In her blog, “Introduction to Agentforce for Salesforce Admins,” she explains why admins are the perfect candidates to become the go-to AI expert in their organizations. Unsurprisingly, Josh got a little more technical with his answer, highlighting the growing importance of Retrieval Augmented Generation (RAG) and simple prompt engineering. He points to his interview with Nochum Klein about how he uses Agentforce to organize and search information security documentation at Salesforce. How Agentforce will help admins in 2025 The team also looked ahead to 2025, and I think it’s fun to look back on how things are shaping up now that it’s July. Kate was focused on how Agentforce will affect admins’ core responsibilities. The agents you build make life easier for both you and your users. However, she pointed out that security and AI governance will be critical as it becomes easier for more people to interact with your data. Jen was excited to launch two new video series in 2025. If you haven’t yet checked out “Automate with Agentforce”, it’s been incredibly helpful in showing all the cool new solutions you can build with AI. She also is contributing to a series called “Agentforce Decoded” where she walks you through various new things she’s learning about Agentforce, which is a great place to get started. Finally, Josh was excited about building AI agents that interact with documentation and metadata, enabling faster support, onboarding, and troubleshooting experiences. When combined with Slack integration, you can save your users so much time. What we’ll be saying at the end of 2025 To finish out the episode, I asked the team to make predictions for what we’ll be saying at the end of 2025. Josh: “It’s the end of 2025, and I can’t believe Salesforce Admins found Agentforce so easy to work with.” Kate: “It’s the end of 2025 and I can’t believe Salesforce Admins are creating dynamic experiences this advanced!” Jen: “It’s the end of 2025 and I can’t believe Salesforce Admins can now do things like troubleshoot user management issues faster than ever before!” It’s halfway through the year now, so how did we do? And how is your 2025 going? Are you working with Agentforce? Navigating new AI tools? Hit us up in the Trailblazer Community and share your admin wins and lessons. Podcast swag Salesforce Admins on the Trailhead Store Learn more Jen’s 2024 blog post: Embrace Modular Flows to Build Smarter Automation for Agentforce Kate’s 2024 blog post: Introduction to Agentforce for Salesforce Admins Kate’s other 2024 blog post: Advance Your Admin Career With Dev Fundamentals Josh’s 2024 Salesforce Admins Podcast Episode: How Agentforce Transforms Customer Interactions at Salesforce Blog: 6 Tips To Help You Troubleshoot Agentforce With Confidence Blog: How Admins Drive Innovation With Core Responsibilities in the Agentforce Era Video Series: Automate with Agentforce Video Series: Agentforce Decoded  Video series: Automate This! Video series: How I Solved It Admin Trailblazers Group Admin Trailblazers Community Group Social Jen on LinkedIn Josh on LinkedIn Kate on LinkedIn Salesforce Admins on LinkedIn Salesforce Admins on X Mike on Bluesky social Mike on Threads Mike on X Full show transcript Mike Gerholdt: Hey, Salesforce Admins! It’s July, and we’re officially halfway through 2025—which makes it the perfect time to hit pause and reflect. Back on January 1, we gathered the Admin Evangelist Team—Jen Lee, Kate Lassard, and Josh Burke—for a special kickoff episode full of predictions, priorities, and plans for the year ahead. So today, we’re rebroadcasting that conversation as a mid-year check-in. Were we right? Were we way off? You decide. Give it a listen, and then let us know how your year as a Salesforce Admin is shaping up. Stay tuned—and see how far we’ve come. Welcome, everybody, to the podcast. There’s a lot of people to introduce, so I’m going to go in reverse order. Jen, let’s start off with you. Can you give us a brief introduction and some of the cool content you’ve created last year at Salesforce? Jennifer Lee: Sure, absolutely. I am Jen Lee, Lead Admin Evangelist, and you all probably know me as the host of Automate This or How I Solved It on our Salesforce Admins YouTube channel or for reading my mega blog for each release. Some of the things I’m really excited that I created last year was, again, I love Automate This. I love the How I Solved It, bringing in trailblazers who showcase their skills and what they’ve built in their orgs, and I really enjoyed writing the blog on building modular flows and thinking about really chunking out and building out smaller flows to get ready for your company in moving over to Agentforce. Mike Gerholdt: Nice and got Agentforce in the first minute of the show. Kate, you’re our newest member. Let’s go with you next. Kate Lassard: Hi, everyone. Kate Lassard, also a Lead Admin Evangelist here at Salesforce, and I have been here since August, so still diving in. This past year, I’ve been really focused on Agentforce and have put together some content including an intro to Agentforce blog post, talking about why admins make great AI specialists, and then also talking about advancing your admin career with dev fundamentals. So you might’ve seen me on the road at one of the Agentforce tours talking about core responsibilities, and in the new year, keep your eyes open for some new content about how emerging AI technologies fit into those admin core responsibilities. Mike Gerholdt: New stuff in the new year. I like it. And of course, Josh Burke. Josh Birk: Hi, everybody. I think actually I’m technically the oldest member of the team, but that’s only by chronological age. I’ve been on the admin team for, gosh, I think it’s a little over a year now, but I’ve been at Salesforce for coming on 15 years in 2025. All of them in evangelism in one form or another. And a lot of the things I’ve been trying to write about and post about and blog and video and some of our podcasts is really trying to explain through some of the more technical side of artificial intelligence. We have all of these terms. We’ve got things like LLMs, we’ve got RAGs, we’ve got vector databases, and honestly, frequently the concepts are far more simple than the tech terms actually seem to suggest. I’m on record for saying I don’t like the term prompt engineering, for instance, because it sounds like you need some kind of union guy to come over and rewire your computer in order to, but is basically just talking to a conversational UI in the first place. So definitely see more of that in the near future, especially as our Agentforce features keep expanding into things like RAG and being able to pull in your knowledge libraries and your documentations and actually have a conversation with them. Mike Gerholdt: Awesome. Well, and of course anytime somebody goes to Trailhead, Josh, they’re using something you invented. Josh Birk: I get a penny every time. Mike Gerholdt: Oh, a penny. Josh Birk: A whole penny. Mike Gerholdt: A whole penny. That’s before taxes. Okay. Well even in 2025. So speaking of which, we would be like, if you’re listening to this the day it comes out, you’re in the second day of paying for a gym membership that you think you’re going to use for the rest of the month, bet you’re probably not going to make it to the 15th, most of us anyway. Or eating vegetables. That’s usually the two things. At least those were my horribly tried out New Year’s resolutions. But I’m going to start off with Jen. So Jen, it’s 2025. We’ve got 363 days ahead of us as Salesforce admins. What are you, as of now, going to start focusing on? Jennifer Lee: Well, of course, Agentforce. Who isn’t? I am very excited for two video series that I’m working on and hoping to put out soon, and this will focus around one will focus around automation and thinking ahead about how that factors into Agentforce and the strategy that you should think about and work through in bringing that along with your company. So that’s going to be, I think about 10 to 12 episodes. We’re looking to do monthly and then we’ll be going through, and just like you all are learning Agentforce, I’m learning Agentforce, so I’m going to take you on my journey of how I’m working through various pieces. So really excited to put that type of video content out. Mike Gerholdt: Yeah, we’re excited to see it. Kate, similar question, but a little bit different. You were most recently in the seat as an admin. What are some things you should be thinking of as a Salesforce admin in January that would help set you up for success for the rest of the year? Kate Lassard: That is a great question. With all the advancements in AI and with, as I said, admins being the ideal candidates at their organizations to become their internal AI specialists due to their unique understanding of business and user needs combined with their declarative Salesforce skillset, I’m going to be paying attention to new ways of managing admin responsibilities we already have in place. So one that is top of mind for me is security. New technology like Agentforce brings advanced value to admins, but it also brings new security concerns and the need for AI governance, so I have my eyes on the innovative ways that our admin community will continue to evolve in their roles while they’re addressing these emerging technologies. Mike Gerholdt: Yeah, that’s good. Josh, you probably work on some of the most advanced stuff, and half of the words that you said in your previous answer I didn’t understand. Are there things that you’re looking ahead at 2025 to understand that you weren’t on your roadmap for 2024? Josh Birk: Yeah. Well, not to repeat myself too much, but it’s been an interesting journey with our friend RAG, which is a Retrieval Augmented Generation, which is a very fancy way of saying that the AI models can absorb information that was not part of their original training, their original model. And typically this is going to be in the form of things like PDFs and documents and things like that. And the reason why I think it’s an interesting journey is when we first started talking about RAG here internally at Salesforce, it was actually more about how our models were going to start getting trained on enterprise data. So we have all of this wonderful custom metadata, and it tells the models of what your custom objects look like, what your custom fields look like, and so they can consume that using RAG in a very nice and flexible way, and you don’t have to rebuild an entire LLM for it. We didn’t talk about it much back then because that was behind the scenes, under the covers. This is how the engine is running kind of thing. Now it’s actually turning into a very common use case where people are putting in 500 page documents. Think about that mega blog that Jen was talking about. Think about having release notes available to you through a conversational UI kind of thing, so it’s something that’s fastly growing. And when it comes to those like, oh, what’s that killer use case that we could get in to have Agentforce really do good things for our company, RAG is turning in one of those big solutions. Mike Gerholdt: And it’s another acronym for us to learn. Josh Birk: Right. Mike Gerholdt: Let’s pivot. We do a lot of things as events at Salesforce, and I know our admins, I always try to make it to a lot of events, but you can’t make it to them all, right? FOMO is a thing. As you’re planning your year, and Kate, I’ll start off with you just to mix up the questions a little bit. How would you, as a Salesforce admin for 2025, look at events and what you could or could not go to? And Katie, bar the door. There’s no restrictions. Kate Lassard: Oh my goodness. Well, I would love to go to all of them. FOMO is real, but not a possibility. I think it’s really about prioritizing what you want to learn. So at the beginning of every year, I always try to think about what are my learning goals? What do I want to come out of this year? And whether it’s a specific certification or something like learning more about Agentforce and AI governance and security, to go back to my last answer. And then finding the events that are in alignment with that. So obviously things like TDX and Dreamforce are going to be great options because there’s going to be a huge amount of content, but the community conferences are also fantastic, and figuring out which ones thematically match your learning goals is really the way that I like to approach events and always maybe trying to fit in a fun new destination like Irish Dreaming this year. So if you’ve never been to Ireland, maybe that’s a good one to add to your event bucket list. Mike Gerholdt: Wow, budget. Budget. Katie, bar. Kate Lassard: I didn’t say my event bucket list. Mike Gerholdt: Yeah. No, that’s cool. I mean, I love all of those Dreaming events. And Jen, to pivot to you, you speak at a lot of the Dreaming events. What are some of the things that, as an admin, you looked for and got out of going to some of these community-run conferences? Jennifer Lee: It’s a different vibe from attending Salesforce events like TDX and Dreamforce, it’s more low-key, but you’re actually learning from the practitioner. So it’s beyond the things that Salesforce is focusing on, but getting those really best practices and things like that from the people on the ground who are doing the thing that you’re doing. And that’s what really excites me about going to community events because you’re able to learn from your peers and talk to them and ask questions. There might be something that you’re working on that you ran into roadblock, but then you attend a session and then that opened your eyes and gave you ideas and inspired you to go back and try different things, so that’s why I love going to community events and just seeing all the people in the community. Mike Gerholdt: And the time in between sessions is usually the most fun because it’s when you connect with everybody. Jennifer Lee: Exactly. Mike Gerholdt: I love that. Josh, I’m not going to ask you to pick between your two favorite children of TDX and Salesforce, but I know you’ve been a part of both and building activations for both. I think very real in the minds of Salesforce admins is how do I justify going to one or both? What are some of the considerations that you would give admins as advice for planning their travel to one or both of those this year? Josh Birk: Yeah. Well, I think it’s important to point out that we’ve kind of acknowledged TDX’s role as more of a builder-centric conference, something that’s really about enablement, and it’s about knowledge, and it’s about learning, and it’s really about upscaling your career and your skill set. And so I think that’s one justification if you’re trying to convince your boss that you really need to go to both is that one’s a really good learning experience, and the other one is a really good networking experience. Not that you’re not going to learn from Dreamforce, not that you’re not going to get the good sessions and the good breakouts and all of that, but it is definitely, we are kind of trying to make TDX a little bit more of its own thing on the map as opposed to just kind of a companion event to Dreamforce itself. And the advice I always give people is prepare, prepare, prepare. It’s just like go to agenda builder, make sure you know which sessions ahead of time that you’re really going to get the most bang for your buck out of. And always that constant reminder, if breakouts don’t have repeats, you might want to show up early because if that’s the session that you convinced your boss to send you on the plane for, make sure that you get a seat. So yeah, no, very much looking forward to them this year. Also looking forward to the community events. I’ll echo what Jen said. So I used to joke, I’m not really a developer, I just play one on TV. I guess I’m not really a developer, but I just play one on TV. But it’s like we need to hear from you. You’re the people on the front lines. You’re the people who are actually putting these use cases together. You’re going to be the people finding the weird little niche things about these features that maybe when we kick the tires of them, we didn’t consider it. So it’s a great way to get that wonderful feedback loop kind of closed in. Mike Gerholdt: Yeah, no, I hear you. Plus going to TDX means sometimes you can eat at the restaurants around Moscone Center, right? There’s some really good ones there. Always food. This podcast always has food, food and time travel, which is what we’re going to do. So last question, and this is for everybody, and now everybody’s sweating like, “Oh God, don’t call on me first.” Okay, Mike takes an hour and a half to ask a question. You have plenty of time. You can read War and Peace in the time it takes for me to ask a question, but we often time travel on the podcast. So we’re going to fast-forward. It’s now the end of December 2025. You go back and listen to this podcast, and Josh, I’m going to start with you because I didn’t start with you on any of the questions. You have to complete this sentence. It’s the end of 2025, and I can’t believe Salesforce admins blank. Josh Birk: Can’t believe Salesforce admins found Agentforce so easy to work with. And I can kind of say that safely because it’s something I’ve seen on the road a lot, and it’s part of our job is to make it like when you say, “I’m going to go develop an artificial intelligence custom agent.” It sounds like something that you better put on your scholarly hat and really dig in deep. What we’re finding is it’s just really not that hard. So what I’m hoping is that as we do these enablement workshops and as we get the Trailhead Playgrounds, and people can go in and kick the tires, and they just want to give that a shout-out that that’s here in the present, not just in the future, that you can go get a free version of this, and you can go to Trailhead, and you can start learning these things now. And I remember back when Lightning One components hit, and everybody’s like, “Oh, what do we do?” It’s like, “What do we do about LWC?” It’s like, well, don’t panic, but now is the time to learn it. Now is the time. And one of the things I’ve said many times in my keynotes is like, now is the time to determine your relationship with AI. It’s your time to figure out what’s going to make you more efficient, what’s going to make you more productive, what’s going to make your job happier. Mike Gerholdt: Okay, well, that was a great answer. Kate, you have to follow Frank Sinatra. Kate Lassard: Oh my gosh. Mike Gerholdt: So it’s the end of 2025, and I can’t believe Salesforce admins. Kate Lassard: Are creating dynamic user experiences this advanced. I think that a few years ago when Salesforce announced dynamic forms, that was such a game changer for admins allowing us to create more customized dynamic user experiences right on those record pages for our users. And with Agentforce and Prompt Builder, that adds completely new functionality that admins can leverage to really create those dynamic experiences for their users, for their customers. And I think we’re going to see not only a resurgence of creating those dynamic user experiences, but now we have even more capability to do so, so I can’t wait to see how advanced and how exciting those experiences are. Mike Gerholdt: Yeah, a hackathon at the end of 2025 is probably going to look a lot different than the hackathon we did in New York back in November. Kate Lassard: Exactly. Mike Gerholdt: Yeah. Jen, you get the final word. It’s the end of 2025, and I can’t believe Salesforce admins. Jennifer Lee: Right. So not to copy what Josh or Kate said. Mike Gerholdt: Oh, it’s the hardest when you’re the third person on a panel. Ditto. That’s what you should say. Ditto. And the first guy just went ahead and went right to AI. Josh Birk: I know. Jennifer Lee: I would say, I can’t believe Salesforce admins can now do things like troubleshoot user management issues faster than ever before. Just knowing what Cheryl’s team is doing behind the scenes and the things that they’re working on, your mind’s going to be blown. We’re going to have agents that help you troubleshoot those things so that you are not spending all the time trying to figure out why Josh has this permission, but Kate doesn’t. Kate Lassard: Great answer. Way to close with a bang. Mike Gerholdt: You know what’s going to be fun is I’m going to save this, and we’re going to do this again at the end of 2025 and see how close we were. Oh, because why not? And then hopefully we’ll say, “Yeah, so we could do that by June.” Maybe not. Who knows? Thanks all for coming on the podcast and helping admins get ready for the new year. I know we have a lot of content lined up, so I appreciate it, and I appreciate your perspective on bringing things. Josh Birk: Thanks for having us. You bet. Jennifer Lee: Happy New Year. 2025 here we come. Mike Gerholdt: What a ride, right? It’s always fascinating to look back and see what held true—and what surprised us. Huge thanks again to Jen, Kate, and Josh for setting the tone back in January. And now, we want to hear from you: how’s your 2025 going? Are you working with Agentforce? Navigating new AI tools? Hit us up in the Trailblazer Community and share your admin wins and lessons. Until next time, we’ll see you in the cloud. The post How Are 2025 Admin Predictions Holding Up So Far? appeared first on Salesforce Admins.