Today on the Salesforce Admins Podcast, we talk to Skye Tyler, Principal Solution Consultant at Beyond the Horizon Technology.
Join us as we chat about why clean metadata is crucial for getting the most out of AI.
You should subscribe for the full episode, but here are a few takeaways from our conversation with Skye Tyler.
You’ve done it, I’ve done it. Sales wants a name changed on a report, so you just change the field label rather than create something new and mess with the integrations. Or maybe you have four different dates, but your marketing team knows which one they’re actually looking for. What’s the big deal?
The problem is that while humans can get by on institutional knowledge, AI agents need a bit more help from your metadata. As my guest this week, Skye Tyler, explains, you should think of AI like an overenthusiastic intern with short-term memory problems. It really wants to answer your question, so if it sees four different dates, it’s going to take a guess.
Think of metadata like an onboarding manual for AI. With clear field descriptions and help texts, you can point your agents in the right direction and prevent hallucinations.
Obviously, cleaning up your org’s metadata is easier said than done. However, Skye has some great tips for how to get started.
If your business has busy periods and slow periods, you might be able to schedule time specifically to work on your metadata. But for the rest of us, Skye recommends a clean-as-you-go approach. Any time you update an object, set aside some time to review all of the related metadata and update the description.
Similarly, any time your organization is building a new business process that includes AI, you need to clean up any metadata an agent could interact with. As Skye points out, while you don’t necessarily have time to deep clean your house every week, a little spot cleaning can go a long way.
We also took some time to talk about Skye’s career path from nonprofit arts and what advice she has for folks who are new to the Salesforce ecosystem. AI is changing things fast, and that means there are more opportunities. “With all of these newer technologies and tools, anybody who’s looking to come into the space today is learning the same things that I’m learning, having been in the space for a decade,” she says.
The Salesforce community is incredibly supportive, and Skye recommends putting yourself out there. You never know who you’ll meet at an event, and where those connections could take you. “No matter where you are in your journey, you know something that other people don’t,” she says, “put yourself out there, and I guarantee you someone’s going to appreciate it.”
Listen to my full conversation with Skye for more on how to clean up your metadata and stop AI hallucinations. And make sure you’re subscribed to the Salesforce Admins Podcast so you never miss an episode.
Mike:
This week on the Salesforce Admins Podcast, I’m talking with Skye Tyler about the part of AI readiness that, well, it’s easy to overlook. That’s your metadata. We all know that clean data matters, but agents also need clear field descriptions, documentation, permissions, and context to understand what your business actually means. Skye explains why metadata acts like onboarding for an enthusiastic new employee and why a confident answer isn’t always a correct one.
We’ll also talk about practical ways admins can improve metadata without trying to clean the entire org overnight. So give this episode a listen, subscribe wherever you get your podcasts, and of course share it with an admin who maybe has prepared their platform for Agentforce. And with that, let’s get Skye on the podcast.
So Skye, welcome to the podcast.
Skye Tyler:
Hi, thanks for having me back.
Mike:
I’m excited. Going through everything that we’re doing to prepare for Dreamforce and admins are preparing for the agentic future, which is coming faster than eve, I stumbled across your session. And I thought, hey, before we get into Dreamforce, maybe we can dive into all of the stuff that you might not be able to cover in your 40-minute breakout session. So we’ll talk about that because it’s data related and data related is agent related. But before we get started, can you just refresh everybody on how you got started with Salesforce and what you do in the ecosystem?
Skye Tyler:
Oh, I’d love to. So I’ve been fortunate enough to be working in the Salesforce space with the nonprofit industry for a little over a decade now, and started off doing implementation work with nonprofit arts organizations, doing ticketing and donation. And then I’ve moved in and through the consulting space. Again, focusing primarily on nonprofits with a little bit of dipping into education along the way. And over the course of that decade, I’ve been fortunate enough to meet some amazing folks, yourself included, that has given me an opportunity to have the chance to share not just my journey, but my experiences, my struggles, successes, failures. And some of those avenues have included things like coaching and mentoring with super moms and the Salesforce military program, and then also just being really honored to be able to speak at community dream and events and events like Dreamforce and Trailblazer DX.
Mike:
I mean, that’s a great answer. You know what’s funny is so many people ask me, “How do I get started in the community,” or, “What should I do?” And I feel like now I’m just going to point back to your answer because what you said was just perfect. Well, don’t be afraid to share what you’ve learned, or what you’re learning, or how you’ve learned it, or things you’re working on because that’s what people love to see. They love to see how you’re doing it so that they can get an idea for how to do it. So thanks for answering a question I didn’t have.
Skye Tyler:
Yeah, absolutely. I also just want to throw in, and I say this at many of my live sessions, that no matter where you are in your journey, you know something that other people don’t. And everybody learns more when folks show up, and are vulnerable, and are willing to share those things. So definitely just give it a try. Put yourself out there and I guarantee you someone’s going to appreciate it.
Mike:
Yeah, absolutely. Plus the thing I add to that is there’s probably somebody out there like you that really needs to see somebody like you on stage.
Skye Tyler:
Yes, absolutely.
Mike:
So we talk a lot about data with agents and cleaning data, making sure your data’s up-to-date, making sure your data’s fresh, which every time I use the word fresh, I always think of how that plastic comes off an iPhone. I don’t know why, but that’s where my brain goes, because agents and AI and LLMs do a really good job of consuming a vast amount of information and giving it back to you in what you asked for. I think one of the things that we talk less about and that I want to talk to you about is your metadata, because I’ll be honest, I pay attention to my metadata for five seconds when I’m creating the field.
Skye Tyler:
I’d say that’s four seconds more than most people.
Mike:
Right, because all you got to do is click outside the box and it fills in the developer name, so I’m good. And description, ah, fill it in later.
Skye Tyler:
Yeah. And for the longest time, that’s been really standard. And again, working across several consultancies and with lots of different works, people assume, well, we know what this field means. You give it a field name, the team knows what this means. I don’t need to fill in description. I don’t need to fill in help text. It’s fine.
And again, for the longest time, that institutional knowledge was enough of a stopgap that it was fine. Nothing was going to break or go horribly wrong if you left the description field empty. But all of that changes when you start introducing agents. And an example I may reference a couple times on this podcast is, I don’t know if you’ve ever heard this, but the idea of thinking about your agent as a really enthusiastic intern with short-term memory problems.
Mike:
Like memory of a goldfish.
Skye Tyler:
Yes, exactly. So if you’ve got a new intern and they don’t have deep industry experience, or they don’t have longer term institutional memory within your organization, and they come on site, they’re excited to be there, they’re energized, they’re probably young and enthusiastic, and they’re going to sound really confident. You’re going to ask them a question. They’re like, “Yeah, absolutely. I can absolutely do that.”
But there’s a difference between sounding confident and actually knowing the answer. And where AI gets really tricky is not only does it sound confident, it usually has a certain level of fluency to it with the amazing jumps in natural language processing over the past few years, it sounds both confident and right because it’s just a well-structured sentence. And there’s a huge gap between the structure of the sentence and the actual understanding of the data behind it.
Mike:
Right. It reads to us as so confident in its own answer that we would be silly to think it’s wrong.
Skye Tyler:
Oh, absolutely. It would be a waste of time to go back and check it because look at how confident it is.
Mike:
Yeah. And look at all the part that I always think of is look at all the information it gave me. I asked it two sentences and it gave me four paragraphs of an answer. It must be right.
Skye Tyler:
Yes. And of course, don’t forget that at the beginning, it also flattered you and said, “Oh, Mike, that’s a great question. Let’s dig into that.”
Mike:
Yeah. You sound just like my AI.
Skye Tyler:
Exactly.
Mike:
“Of course it’s a great idea, Mike. You should totally do that. Everything’s a great idea.” So when we think about that though, why is it making those mistakes? Because if we’re paying attention, and I mean, I was even working on some content today that’s like, got to keep your stuff fresh. If you’re going to do call notes or have a summary agent, then make sure your salespeople are doing call notes and keeping it up to date or keeping the data up to date. Then why is it so confidently giving us, I don’t want to say the wrong answer, but confidently providing us with information that it thinks is correct, but isn’t?
Skye Tyler:
Yeah. So a big part of this comes down to the difference between how humans think and form answers and how the large language models do it. And one of the real risks around this false fluency framework is that you pose a question, you ask a question, and first there’s the basic understanding that the agent, whichever model or system you’re using, their goal is to accomplish the thing that you asked.
So the first thing is getting really careful about how you ask your questions so that you’re not sort of setting it up to just affirm the thing that you have asked. But then beyond that, the way that these LLMs, these large language models work, is it’s basically a really complex pattern completing process. And so you mentioned peeling that plastic off of your new iPhone. How many times are you typing a text message on your iPhone and it has that auto recommend that comes up right above your keyboard?
Mike:
Yeah.
Skye Tyler:
So that’s a good example of a simple version of this. So depending on how often you type in “Oh my,” and then it’s going to recommend a couple of different things that often come after “Oh my” in the training data. When we’re thinking about this in the context of asking an agent something in Salesforce, the way that it identifies what to propose for an answer is not looking at just the data in the field, it first has to go look and see what information is available and that’s when it dips into the metadata. So if you’ve got four different fields that have very similar field names, but have no metadata to tell the agent field one means this, field two means that, field three means this, and field four means this completely other thing, it’s just going to guess.
Mike:
So if you had four dates on a record that were, I don’t know, draft dates because it ties to a contract or something, and it’s draft one, draft two, draft three, draft four, and you know as the user, those are the dates that you completed those drafts, but your metadata just shows four draft dates and there’s no explanation for the agent. So the agent’s like, “Here’s when all the drafts were completed.”
Skye Tyler:
Right, it’s going to guess. And because it’s non-deterministic, it might guess right the first time you ask it a question. It might guess right the second, third, fourth, fifth, 20th time, and then the 21st time, it guesses wrong.
Mike:
But confidently.
Skye Tyler:
But confidently wrong.
Mike:
Confidently. Right.
Skye Tyler:
Right. And so when we’re thinking about how to support our agents, if we go back to that analogy of the over-enthusiastic summer intern, the metadata is effectively the onboarding process for that new intern or a new employee. It’s the manual about what your data means, and it’s the context that the agent can use to give you more consistently reliable, correct answers.
Mike:
Love it. So I remember, I think it was TDX two years ago, we were talking kind of on this subject. And whenever we roll out a new feature, it’s here’s the things you need to do to prepare. And I remember getting up and talking with a lot of people of like, “Hey, it’s more than just the data that’s got to be cleaned because there’s a lot of data cleaning services and hopefully you have a lot of validation rules and stuff in place, but also your metadata needs to be cleaned as well.”
And I looked over in the audience, I felt this guy just shrug his shoulders and just kind of turn a lighter shade of pale, I’ll say. And I walked up to him afterward and I asked him, I was like, “Are you okay?” And he’s like, “Yeah, your words just hit me really hard. I was thinking of all the metadata I have to clean up.” So obviously it would be awesome if every day people woke up and you cleaned your whole house. But let’s be honest, you don’t have to wake up every day just to live in your house to clean your whole house. What is the approach that an admin should think of in terms of getting their metadata to that next level and to prepare for an agent force implementation?
Skye Tyler:
Yeah, I love the analogy of cleaning your house every day because I’ll tell you, I do not wipe my baseboards every day.
Mike:
oh, man. I would pay somebody to come once a week to do my baseboards. It would be awesome.
Skye Tyler:
Yeah. So there’s a couple of ways that you can look at this. The first one is figuring out within your workflows, your day-to-day and annual workflows, where you can build metadata maintenance into your process. And so what this might look like for admins is the next time someone on your team asks for an update on an object, whether it’s a page layout, or some new fields or what have you, taking and building some extra time into however long you budget or allocate for that task to include reviewing related metadata. Every time you need to update a flow because the business process has changed and you say save as new version, as soon as you click save as new version, update the description of the flow.
That’s the first thing that agents are looking at to be able to figure out what automations do I call, what automations are related to a process, et cetera. So building it into the workflow of what you already do is one avenue to consider. If you have an amazing organization that lets you do proactive maintenance, working that into your project plan and saying, “Hey, this is a usually kind of quiet time of the year for new admin requests. Let’s go ahead and block two weeks or three weeks and do a more thorough or a deeper dive into updating the metadata.” If you work at one of those organizations, let me know, because I’ve heard they exist. I haven’t encountered one in the wild.
But then lastly, when you have any new agent related process, it should be considered mandatory as part of that project to do a metadata review of every aspect of metadata that that agentic process is going to interact with. Because one of the big challenges that organizations have been seeing is they’re putting a lot of time and resources and money into creating agentic solutions, but the research and the data is just not showing the level of return on investment or the level of success that people are expecting. And one of several underlying factors is you’re not setting your agents up for success.
You’ve got this new employee, this new agent employee, but you didn’t onboard them. You didn’t provide them with adequate institutional knowledge and training. You gave them some direction. But if you think about it, Mike, when you’ve got a new employee that comes on and they go to that podcast or that blog record for the first time and they see your four review dates and they don’t know, they stop and ask someone. They ping you on Slack and be like, “Mike, can you explain these four review dates to me?” Your agent can’t do that. So set them up for success with that onboarding through the metadata updates.
Mike:
And I think that also, I mean, I really like how you approach that. I think that’s also a funnel or a pathway that you could flip. So you don’t have to think of, I have to tackle everything and clean all my metadata first, as opposed to, well, if we’re going to roll out an agent and it’s going to touch these three objects and these 15 fields, then that’s where you start.
Skye Tyler:
Absolutely.
Mike:
Because then that will help you set up a plan for here’s how we’re going to tackle this part of it. And then as the agent responsibilities or you build additional sub-agents expands, then you can tackle two or three more objects that maybe that sub-agent has to talk to as opposed to, okay, we’re going to wake up at 3:00 AM, clean the whole house just to live in it, which is a good idea. I think sometimes readiness to the extreme can feel overwhelming.
Skye Tyler:
Right. And if it’s overwhelming to the point where you don’t make any progress on it, then it’s not useful either. So definitely thinking about what’s within scope. Where I would challenge that a little bit though is unless you have put very firm guardrails on your agent, there’s always the possibility that it’s going to get creative. So you might intend for that agent to only look at these four fields, or these 15 fields, or these two objects, but if you don’t actually instantiate that guardrail or that limit into how you build the agent, it could start to be like, huh, I wonder if this related record might impact me being able to answer Mike’s question better. Let me just go take a look at that.
And that’s where we could get into some of the more deeper technical things, but the idea that authentication is not the same as permission. And so making sure that each of your agents has very clearly defined, and that ties in with the metadata too, because all of those settings in Agentforce and Agentforce builder are set up, the sub-agent descriptions, the scope, all of those things are metadata around your agents.
Mike:
And I think there’s downstream effects to this that are also positive too. I’m thinking of all of the reports that you’re dealing with that will suddenly get better because I know you’re always building reports, sometimes not off of the report label. So help me through this. You’ve got an implementation and you have an integration with another system and you change metadata descriptions or field names. How do you need to approach that? Because obviously you need to identify that early in your discovery.
Skye Tyler:
Yeah. This is a little bit of a catch-22. Let’s just say that we’ve got five fields on, I’m going to just call it the case object, that are updated through some form of integration. Maybe it’s a form submission, maybe it’s an external data source, whatever. But there’s five fields that are tracked and interact outside of Salesforce, and you’re going to set up an agent that does something that impacts those five fields. When you set up the previous integration, if you didn’t put in the description somewhere on those five fields that this field is part of X integration or this field is populated via X external data source, one, past you did future you no favors by not putting that in there.
Mike:
Man, when the DeLorean gets out of the shop, I’m going to go back and really tell myself.
Skye Tyler:
Exactly. So again, going back to that idea of you’ve got a new project, you’ve got a new request, you’ve got a new thing that you’re building. Taking the time to do that slew thing and to really investigate what are all of the things that touch this piece of data or this particular metadata. The simplest sort of way to address that is whatever else you’re changing, don’t change the API name.
Mike:
Smart.
Skye Tyler:
Now where that kind of gets, I’ve seen more orgs than I can count where the field label is something completely different from the API name because it had some kind of external connection or integration, and if you try to change it would break it. So they just changed what referenced to the human. That’s going to be a problem for your agent. If you are expecting interaction around review date one and the API name is something completely unrelated and there’s no description to give the agent more context, they may not even look at that field. They might not even recognize it.
Mike:
Oh man, I am so guilty as charged.
Skye Tyler:
We’ve all done it. We’ve all done it.
Mike:
I mean, businesses change process and I was like, I can just change the field label. If it says this on the screen, are you happy with that? Mostly because I didn’t want to … It always happened where I didn’t want to have to create a new field, move the data over just because they wanted a different name.
Skye Tyler:
Yeah. Yeah. Well, and if you are an admin that does not do Apex, which most admins don’t, right?
Mike:
Not me. Nope.
Skye Tyler:
They’re differentiated roles for a reason, and you have Apex that’s running against those custom fields, you can’t just go in and change the API name. You are going to break things. And so this is where that cascading effect can come into play and you say, okay, well maybe this one quick fix that the marketing team was asking for isn’t actually a quick fix because we do want to get the org as ready as possible for future agentic improvements.
Mike:
I love how you set me up for my next question there because I was just going to ask you. So I could see somebody’s listening to this and hopefully they got this far and they’re like, “That was a fun podcast, but we’re not really getting ready to deploy Agentforce, so why should I care about my metadata?”
Skye Tyler:
Yeah, this is one of those things, and I’ll admit early in my consulting career, this wasn’t as emphasized. It was all about the user’s experience. Does the page layout make sense? Can the user click through and do the things they need to do? And the stuff that’s behind the scenes, the admins can cope with that or the consultants can deal with that, and it just wasn’t as important. But even things like as flow gets more complex and now, I mean, we’re talking about moving to this whole headless experience, the system itself has just matured to a point where if your top or only priority is the UI, the user experience and the user interface, you are limiting the capacity of what your organization can do on Salesforce.
Mike:
Very true. Very true. I feel like as an admin that did focus very much on the UI, would bounce back and forth on trying to make Salesforce the one-stop shop for everybody. I remember way back in the day, do you remember when we used to be able to build web tabs?
Skye Tyler:
Oh, yes. Oh, those days.
Mike:
And so I remember we had a travel system, and I put it in a web tab because I need my users not only to sign in, but sign in and update their opportunities and update the accounts and stuff. And so I asked the salespeople back then, “What is the number one thing you check almost every day?” And they’re like, “Our travel thing,” because they’re traveling and they need to book things and stuff like that. And I said, “Cool. I can do that.” And so I put it in as a tab, but it was like a simple I-frame. It’s just there.
And I had one user, when I showed it to them, they were like, “Oh, this is amazing, but I booked my travel and it didn’t sync with my calendar.” And I was like, right, because it’s literally a pane of glass that I’m giving you into another system. But your whole conversation about this made me think back to when I would try to bring all of my users together in Salesforce, and then when I would try to make it so that they didn’t have to pay attention to the UI in Salesforce. And I feel like I tried to make both, because you brought up headless. And headless in theory is you use a tool and then you just at Salesforce or something, you can bring all of that knowledge in.
Skye Tyler:
Well, I mean, you and I have both been in the space long enough that we remember the days when the mantra was, if it’s not in Salesforce, it doesn’t exist.
Mike:
Oh, yeah. I mean, I still say that.
Skye Tyler:
Right. But the reality of the world now is there’s a lot of data and there are a lot of processes that don’t exist in Salesforce. They can be surfaced there or they can be represented there, but they live somewhere else. And that’s where, going back to my previous comment that the platform, the system itself has just matured beyond that. You have to log into Salesforce, you have to create a record or update a field in Salesforce for it to count. And that’s not the case anymore. And even things like using experience cloud sites to be able to allow external partners or site guest users to be able to get information into Salesforce, all of those connections, all of those disparate data points are potentially accessible by agents, and then if you move into a headless environment from a headless perspective.
And so taking whatever time and resources you have at this moment and making whatever improvements or whatever cleanups you can make is just going to help future you, future admins who manage the system, be more successful in doing that. And I know right now in the nonprofit space, there’s lots of conversations for folks who are considering moving from the nonprofit success pack to Agentforce Nonprofit. And when I talk to folks who are considering the move, one of the things, even before Agentforce Nonprofit, moving from a different data system into Salesforce, really doing an audit.
And we were talking about cleaning houses. I have this great story from one of the times we moved when I was a kid and my mom was real stressed out, she ended up packing the trash can full of trash. And by the time we got around to unpacking that box, you can imagine how pleasant that was. So when you’re packing up your house, when you’re packing up your data house or your data system and you’re planning to move, don’t pack your trash. Go through and do a data audit. Go through and update your metadata. Make sure that you’re moving into your clean new house with just the things that you want, and they’re going to be easier to access and more effective. And then your over-enthusiastic summer intern of an agent is going to be much more likely to give you a coherent, fluent, and accurate response, not just a confidently wrong one.
Mike:
I like that. Packed your trash. It is odd when you move because there’s stuff that lives in the world that when you move, you have to figure out what to do with it.
Skye Tyler:
See, I can’t relate. Having been associated with the military for a decade, I can now fit my entire house in a U-Haul. Every time I move, it’s a purging process.
Mike:
Sure. Yeah, I can understand that. I’d love to end on that, but I have one other thought, which is, this doesn’t just apply for Salesforce. When we’re working with our IT colleagues or people in the organization that own other platforms, a lot of the power comes not only from Agentforce being able to bring in Salesforce information, but to be able to consume other information. And I have to believe that we have to sit down and do the same kind of audit when we’re looking to integrate with another platform.
Skye Tyler:
Oh, absolutely. And this is where, I mean, the kind of highest level way to think about this is it’s the context. You have to have some mechanism in Salesforce, it’s primarily metadata, but you have to have some mechanism for the agent to understand and to have the context of what you’re actually asking them to do. So these large language models have been trained on the entirety of human knowledge that has been encoded into the internet. Well, that’s not helpful for your specific question or your specific query.
So having systems in place, whether it’s knowledge articles, whether it’s Jira tickets, whether it’s Confluence folder structures, having mechanisms that give the agents the proper level of context for them to be able to support you in solving the problem, designing the solution, answering the question, whatever your purpose is, this is transferable across any touchpoint of agentic work.
Mike:
Yeah, totally makes sense. I always push the speakers that I work with for Dreamforce, or TDX, or any event to think about what happens when the person stands up after your presentation is over. And so I’ll ask you the same thing. So what happens when somebody presses stop on the podcast and goes about their day? What’s the one thing they should do after they listen to this?
Skye Tyler:
Well, obviously keep listening to the other podcast episodes.
Mike:
Right. Just continue on to the next episode.
Skye Tyler:
I think the takeaway that’s sort of bigger than just data or metadata or even agentic work, is keep learning. All of these systems and all of these tools are evolving so quickly. And while that can be a challenge and can be maybe intimidating, it’s also potentially very democratizing. And when we think about your comment earlier about people trying to get into the ecosystem, for a while it got very hard. There was the age of the accidental admin when Salesforce was young enough that just if you were good at fixing the printer, you became a Salesforce admin.
And then we moved into a period of time where it had matured enough that organizations wanted people with deep experience. With all of these newer technologies and tools, anybody who’s looking to come into the space today is learning the same things that I’m learning having been in the space for a decade. So my call to action for anyone listening to this podcast would be find other avenues of learning. And then if it’s in your wheelhouse or your interest, offer what you’ve learned to other people and share that experience.
Mike:
I think that’s great. I mean, that ties right in with the podcast I did with Gene Velonis, which was open up a Trailhead org and just start playing around and-
Skye Tyler:
Just try it out.
Mike:
… don’t be afraid to break things. I think there was a point in time when I would work with a lot of community members and they were always afraid, “But what if it doesn’t work?” And I’m like, “Cool.” And then we know we have to go back and get to tinker with something.
Skye Tyler:
Yeah.
Mike:
That to me is half the fun.
Skye Tyler:
If it works the first time, then it means you weren’t trying something hard enough.
Mike:
I know. Yeah. Yeah. That or I’m worried when it’s going to stop working, because if it worked the first time, then I didn’t get to troubleshoot stuff.
Skye Tyler:
This is true. This is true.
Mike:
Skye, it’s always a pleasure to have you on the podcast. And in the ever-changing world of AI, and metadata, and data, and everything else, it’s good to have you kind of keeping us honest and keeping us on our toes.
Skye Tyler:
Well, I don’t know if I want to bear that responsibility, but I’m happy to try.
Mike:
You’re one of many people.
Skye Tyler:
Great. Thank you so much, Mike.
Mike:
Big thanks to Skye for joining us and making metadata feel practical, useful, and well, a lot less overwhelming. My key takeaway was for admins, it’s really simple. Agents can only act reliably when Salesforce clearly reflects what the business means. So build metadata review into the work you’re already doing. Maybe pick one active process and document the fields and the automation it depends on, and give the future you and the future agents the context they need.
Now, of course, you should subscribe to the Salesforce Admins podcast wherever you listen to podcasts, and be sure to keep learning and trying something new in your org. Until next time, we’ll see you in the cloud.
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