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Today on the Salesforce Admins Podcast, we talk to Parth Shah, Director of Product Marketing, and Rikke Hovgaard, Director of Product Management for the Agentforce Coworker team at Salesforce.
Join us as we chat about Agentforce Coworker and what it means for the way admins help teams get work done.
You should subscribe for the full episode, but here are a few takeaways from our conversation with Parth Shah and Rikke Hovgaard.
Agentforce Coworker brings AI into everyday business workAI has been a game changer for coding, but integrating it into normal business processes has proved more challenging. That's where Agentforce Coworker comes in. It's an autonomous AI teammate, grounded in your enterprise data from day one.
For this episode, I sat down with with Rikke Hovgaard, Director of Product Management, and Parth Shah, Director of Product Marketing, to find out what Agentforce Coworker is and how it can help admins bring new tools to their team.
Salesforce permissions remain central to trust and accessTrust is central to any conversation about AI. New tools are exciting, but you need to be sure that they won't give people access to data they shouldn't be able to see. Luckily, Agentforce Coworker works around the permissions you've already configured in Salesforce. It's simple for admins, and keeps those guardrails in place.
As far as configuration goes, Rikke and Parth are all about keeping it simple and transparent. While Agentforce Coworker automatically inherits the security and governance settings that are already in your org, you also have special configuration options just for the agent.
Admins can connect more data through Data Cloud and SlackFor Rikke, Agentforce Coworker is especially useful for summarizing her team's Slack conversations. She can quickly understand which team member is working on which issue, and where she might need to lend a helping hand.
At the end of the day, Agentforce Coworker gives you a conversational interface to do more with your Salesforce data. "Coworker does the work in the background so that your team can actually focus on what matters," Parth says.
Listen to the full episode for more from Parth and Rikke about Agentforce Coworker. And don't forget to subscribe to the Salesforce Admins Podcast to catch us every Thursday.
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Salesforce Admins Podcast Episode: How Headless 360 Helps Admins Bring Salesforce Anywhere
Mike: This week on the Salesforce Admins podcast, we're talking with Parth Shah and Rikke Hovgaard about Agentforce Coworker and what it means for the way admins help teams get work done. Now, this isn't just about turning on another AI feature. It's about bringing trusted business context, permissions, data, and automation together so users can ask better questions and take action faster. Parth and Rikke are going to walk us through how Coworker connects to Salesforce data, how it respects existing permissions, and how it gives admins a simpler path to roll out and governance. So, be sure to listen in, press that subscribe button if you haven't already. And I would always appreciate it if you could share this episode with a fellow Salesforce admin. And with that, let's get Parth and Rikke on the podcast. So, Parth and Rikke, welcome to the podcast.
Rikke Hovgaard: Thank you for having us.
Parth Shah: Thank you.
Mike: Well, I'm glad we could get you both on. This is the first time I've had a product manager and a product marketing major on a podcast. Usually, one of them has something too important to do that they bail out, but I'm bringing people together. It's going to be great. So, we're going to talk about Agentforce Coworker, but first I want to learn a little bit about each of you. Parth, I'm just going to start with you because you were the first one to bug me in my Slack DMs about Agentforce Coworker. So, I'd love to learn just a little bit about how you came to Salesforce and what you currently are working on.
Parth Shah: Yeah, absolutely. Slack makes it really easy to bug my Coworkers, especially my favorite ones. I sent a lot of emojis. So, sorry, Mike.
Mike: Oh, I'm your favorite.
Parth Shah: Yeah. So, a bit about me. I grew up in Ohio, was a chemical engineer in undergrad, which really I love to build things and I love to, I guess, solve complex problems. And then when I graduated, I didn't want to go work in a plant, in a chemical plant. And so, I ended up going into sales within oil and gas. Did that for about three years, really understood how to actually talk to customers and what their pain points are. And then switched over to a really early stage startup in education technology, really passionate about education. Did that for about three years, which is where I learned a lot about product marketing. Then got my MBA and then joined Salesforce. So, been at Salesforce as a product marketer for about coming up to seven years. And what's been kind of interesting is I started off on the MuleSoft side of Salesforce, so all about integrations. I really learned what it means to connect data between different systems and how developers and admins go about doing that. And that's when I switched over. MuleSoft wanted to launch a new product called MuleSoft Composer at that time, which is now Flow. So, the next level of after connecting data is like, how do you actually use that data to automate processes and make it super simple for admins like our viewers out there? So, help launch that and then moved over to our Data 360, previously data cloud business. And here, I focus on everything that is around unstructured data. So, again, the through line here, if you look at data is, now we can start tapping into the unstructured data that's all out there because of AI. But the more important thing is now that AI is coming in, how do we actually bring that data, which is full of richness in audio, video, meeting notes, et cetera? How do we bring it into AI so that AI is really grounded? And so, that's been kind of my journey. Obviously, looking back at it, everything kind of connected. I didn't know at that time, but the through line I think is my curiosity of what's next within tech has kind of propelled me to go and find out and work on the cool next product that's coming up, which is also how I land on a Coworker.
Mike: Wow. I would've had no idea that you started in oil and gas. Also, what's sales like in oil and gas? Hi, do you want any? Yes.
Parth Shah: Cool. Yeah. It's very old. It's a very people oriented business.
Mike: Yeah. All right. Well, I had to get that joke in. Rikke, I know you're letting me say your name that way, but in all fairness, being German, there's names that we just can't pronounce. So, I'd love to hear how you got started at Salesforce and obviously you're working on Coworker now.
Rikke Hovgaard: Yeah. So, originally I'm from Denmark, which is why my name is a little hard to pronounce. Believe it or not, that's actually a pretty common name in Denmark. So, Rikke is fine here, but I started out after university working for a consultation partner. So, I started implementing Salesforce randomly, started out with Sales Cloud, Service Cloud, moved over to Pardot and Marketing Cloud when that was acquired by Salesforce and ended up also doing a little bit of data and analytics there. And then I decided it was time to move on to other things. So, I joined another partner in London and I moved to London and did that for a bit. I was working a lot on analytics at that point and also marketing. And so, it was mostly focused on what we know now as CRM Analytics and I started a blog on it as well. And so, a few years into it, I joined Salesforce in the CIM Analytics product team, helping customers get the most out of CIM analytics, deescalate some of their issues, best practices, all this kind of stuff. And I think that's where I also got a lot more involved with the community. And then I joined later in Data Cloud, moved over there and about two years ago I started the team with the search team in Data Cloud and we had this idea of Coworker and I ended up working on the admin side. And today I own the Coworker setup experience as well as search manager.
Mike: Oh, wow. I mean, all roads lead through Data 360, literally and figuratively. So, Parth, let's talk about that. I mean, for anybody that hasn't heard, what is Agentforce Coworker and what is it there to help with?
Parth Shah: Yeah. So, Agentforce Coworker, it is your autonomous AI teammate and it's available in Salesforce and it's also going to be available in a lot of different services like Microsoft Teams, desktop, mobile, ChatGPT, Claude, and a lot more. Fundamentally, what it is is it's an AI assistant that knows your business from day one. It's already connected to all of your enterprise data, whether it's structured, unstructured, your opportunities, your cases, your accounts, all of that context that you have within Salesforce and then what's connected to Salesforce. And of course, it respects all the permissions when you do connect those systems. So, it's grounded in your context from the first prompt that you ask. Number two is it can also orchestrate a lot of your agents. It can also execute a lot of complex tasks so that way, it moves your work forward. In other ways, it takes action on your behalf and you can actually update your CRM using Coworker. And then lastly, we built that headless. So, what's really cool about this is yes, it's available in Salesforce, but now you'll be able to take that Salesforce experience and that data and the context that you've spent so many years building into wherever you work. Now a question that we usually get is like, why do we build it? What was kind of the reason behind it? What's the pain point that is really trying to solve? And I think if you look at the industry trends, what's been interesting and what's kind of been going on is you've seen AI obviously augment software engineering, right? It's writing code and it's improving their productivity, but when we think about how business users actually do their work, it's quite different than software engineers, right? Of course, AI can help write emails, it can create the docs. We're going into customer service, but it gets a bit more complex because in our day-to-day work, we're switching a lot between different applications. We're copy pasting a lot of different data from one application to the next, for example, from Slack to Google Docs and so on and so forth. And it's not adding as much value as it does for software engineering. And so, we said, "Okay, how do we bring all of that context that you have wherever you work into a product that brings in AI and actually helps you do the work so you can focus on a lot of the other things that are more important, like building your relationship?" And Salesforce being Salesforce, we said, "Let's bring in that context and we have that AI and let's put it into Agentforce Coworker, which is where also Salesforce, our users work." And the second thing that we also did on top is if you think through where most of your work actually starts, which is again, very different than how we think about agents in general, it starts from work. Anytime you have a question about a task, you go to search. And so, we said, "Why don't we turn that search into something agentic where search gets you answers and then answers can help you take those actions?" And so, fundamentally what we've done is we brought in that context and made it really easy for our users to use Salesforce and fundamentally get a lot more value out of Salesforce and all the things that it can do with the data that you have.
Mike: Yeah. I think what's cool is Coworker's not just for admins. I mean, we'll talk about that, but it's for all of your users. So, one question based on everything that you said, just to make sure that I kind of wrap my head around it as an admin, if I'm setting it up, I can permission what it can and cannot have access to in terms of data. So, if I have, let's say payroll data in Salesforce, I don't want to give it access to that so that Bob and sales can go down and be like, "Hey, I wonder what Sally makes," and then ask Coworker and get a response, right?
Rikke Hovgaard: Well, we're actually using the same permissions that you've already as an admin set up in Salesforce.
Mike: Oh, great.
Rikke Hovgaard: So, there's nothing extra to set up. We tried to make the setup experience super simple and one of that is also, of course, knowing what you've already set up in terms of permissioning. So, if you have in your object given access to something, then the user that is locking in will be able to see that. And if they don't have access to it, they won't be able to see that data either.
Mike: Gotcha. Wow, that's huge. So, it automatically just respects the user's permissions as opposed to me the admin having to go and set something up for it.
Rikke Hovgaard: Correct. Yeah.
Mike: Wow, that's really ... I mean, what's funny is every time I see or work through some of these new products, I'm like, "Oh, well that totally makes sense." Except I think that was probably really hard to do. So, it's always really cool when it happens. It's like intermittent wipers, I suppose.
Rikke Hovgaard: Yeah. Well, we have some amazing engineers that figure out all the architecture and build this stuff. So, I can't take credit for that, but I guess from my point of view at least, as an admin, there are so many things that you have to learn with all these new features. And so, our vision was really to try and make the whole setup simple. We also wanted to be transparent around the permissioning and the governance around it. So, we've also tried to balance that, but it's also how much information do you give upfront? How much is in the documentation? So, it's a fine balance to try and make it all simple enough.
Mike: Yeah. Now can we talk a little bit about the design of it too because I've seen, thankfully I've had an org and I got to play around with it and it couldn't be more intuitive. I'm sure it could be, but can you talk about what went into how you thought about what that user experience is looking like?
Rikke Hovgaard: So, I think it's really down to the jobs to be done. What are you trying to achieve? And that's why the ask mode is very much focused on just asking the question and having that conversation. We wanted to make that a very clear, crisp understanding of what is it that you're supposed to do on this screen. I don't know if you had a chance to also play with the other part, which is we also introduced a new search experience and here that's more of a balance where we're trying to figure out, well, all the things that people love from the original search and how do we bring that in as well as also how do we make it a little bit more new and look a little bit more or nicer, so to speak. I think that has been a little bit of a challenge when we're thinking of all of the data that you can bring in Coworker compared to what we have in Global Search. And now I know we're going a little bit more into the admin side of things, but in order to display things correctly, we need to make sure we also have the information of the data in order to show it correctly. So, that has been an interesting challenge to look at, but yeah, really trying to make it super easy for users to know what they actually have to do, prompt them to get the most out of the tool.
Mike: Yeah. I mean, it almost feels like at times there's a balance between making it super simple and having people trust it and making it a little bit more difficult just so that people trust it because you've gone through it. And if it's almost too easy, then it's like, "Hmm, but did it really do? Is it really..." I can always feel that anxiety in a user or an executive when you demo something the first time and they're like, "Yeah, but does it really do that?"
Rikke Hovgaard: Especially also when we think about AI, we're putting a lot of trust into it and allowing us to get the answers that we're looking for. And so, I think that's why the whole thinking steps that we have implemented is super important for the agentic response. So, we built a level of trust or transparency in what is it that we're actually looking and giving that information to the end user so they can see how we got to the result.
Mike: Yeah, absolutely. Now trust and governance is top of mind. It's literally the first thing everybody talks about with AI. Can we talk a little bit about how that works with Agentforce Coworker and maybe some of what you're seeing in the beta version? I feel like I was on that Agentforce Coworker page and there was an admin on that page that's awfully familiar to a lot of the community that had some great quotes.
Rikke Hovgaard: Mike, let's maybe start with how do you actually set up Coworker. I think that will lead into how do we control the permissions and-
Mike: Yeah, let's start there.
Rikke Hovgaard: Okay. So, the vision we had with the setup page, because if we're being honest, we are using features from other parts of Salesforce. So, we're using Agentforce, we are also using Data Cloud, we're also using global search. So, the thought that we had in the beginning was that's a lot of steps and hoops for an admin to go to in order to set up a Coworker. And so, our vision was really, how can we simplify this? How can we get an admin up and running super-fast? That doesn't mean that they don't have more things they can do, but from the first click turn on to they have access to Coworker, we wanted that to be super simple. So, we have defined a bunch of steps that has to be done in order for you to use Coworker. One, for instance, we have to create the search agent. So, when you click turn on, you actually go ahead and we've automated a bunch of steps for you that goes ahead and creates the things that we need to get Coworker up and running. And in that we've created the agent, we created the permission set group that you need to give access to users and we also have enabled your Salesforce data out of the box. So, any Salesforce data, any custom object, any default or standard object that you have is automatically searchable just by hitting turn on. Now, since we are in a beta, we still need you to opt into the beta. So, there is a little step that some people might miss, which is just go ahead and opt in so you have the new search experience in the front end with the global search bar and the ask button. And then the final step in order to get a user to access and use Coworker is to assign them this permission set group. Essentially, if you're an admin, you're probably familiar with different permission sets are giving you access to different things. So, you need to have a permission set for your agent, you need to have a permission set to use some basic features of Coworker and there's some other things, but essentially we're bundling all of this together in the permission set group. And so, all you have to do is directly from the page, the setup page. You can assign your users directly from that, or you can use the permission sets or permission set group from the user setup page as well. So, that's to say that we tried our best to make everything as simple as possible and then you can lay additional features on top of that with external data, et cetera. So, this is how we are controlling whether or not you have access to it, just permission sets and permission set groups.
Mike: That's very easy. So, if an admin turns it on, it's not just available to everybody.
Rikke Hovgaard: No.
Mike: You can choose whether or not maybe you want a small set of users to try it out first.
Rikke Hovgaard: Exactly.
Mike: Perfect.
Rikke Hovgaard: This is all permission based.
Mike: I like it.
Parth Shah: Now Mike, following on that, I think if we look at trust, trust goes I think even beyond permissions. And I think one of the beautiful things about Coworkers is built on Salesforce, the Salesforce platform that we all know. And so, it automatically inherits a lot of the security and governance, the data residency controls, the access based policies, audit logging, all of that, that Salesforce has that automatically inherits that. So, to kind of give you a couple examples, when it orchestrates across agents, the agents that you've built, they all have observability and monitoring because they're built on the Agentforce platform. So, you have access to that. So, you have an understanding of what it's trying to do and then also the actions that it's taking and how it's doing it. That's number one. And then if you also look at the data itself, if we look at some of the data built into Data 360, that already has a lot of policies built into it. It also has masking built into it, right? And so, it automatically inherits those. And so, when Coworker actually gives out that response, it's not just looking at the permission sets for the user themselves, but it's also looking at the data and the agent side of governance, security and the trust that comes with the Salesforce platform.
Mike: Oh, wow. I mean, that's really, really beneficial there. I was thinking, Parth, you mentioned Data 360. Ironically, both of you have worked in Data 360. Outside of Agentforce just being able to answer questions around the data that we have in Salesforce, we can also give it the ability to get information elsewhere. Can you explain a little bit more about that and kind of what an admin would be configuring and possibly doing there?
Parth Shah: Yes. I can give ... Oh, sorry, Rikke, go ahead.
Rikke Hovgaard: Oh, no, you can answer.
Parth Shah: No, no, no, go for it. Go for it. Go for it. Well, I'll give a high level overview. You can bring in connectors to connect to external sources and then you can also ground a Coworker on the Data 360 data that you have. So, then Rikke, go on.
Rikke Hovgaard: Yeah. So, we knew that we wanted to allow Admins to go ahead and take all of this rich data that they have ingested into Data Cloud and use that as well. So, when you are on the setup screen, we have a little data table as we call it that shows that you've set up your Salesforce data by default. And when you click, there's a little button there that says add more data and in here you can go ahead and add any of the data that you have already ingested into Data Cloud. So, if you have unstructured and structured data in Data Cloud that you want to go ahead and make searchable, you go ahead and go through that flow. And what we've done is very simple model where you select the DMOs that you're interested in. You then have for each one of these DMOs select some search metadata because what I said earlier, it gets a little bit tricky sometimes. With Salesforce, we already know what is the name field. We know what is a supporting field. We know how the layout is, we know the ID, et cetera. For DMOs, we don't know always know that. So, we allow you to go ahead and make those selections, finish that process and at the end we go ahead and create a search index for you that we can use both for the keyword search that appears, but also for the agentic responses that we have.
Mike: Wow.
Rikke Hovgaard: So, that's how you can add that data. But I actually remembered that we haven't actually talked about getting Slack data in as well.
Mike: Oh yeah. Let's talk about that.
Rikke Hovgaard: Yeah. I know that you mentioned Teams, but we also hopefully have some admins out there that have Slack and we've also made that super simple. So, if you've already authenticated Slack within your Salesforce environment, you can go to that same ad data model and you just select the Slack, you click next and you click save and then you also now have Slack data just within your Coworker experience. And this is again, this is actually federated. So, we're looking at the user and you're only getting access to the data that you have access through that user connection. So, that's another really interesting thing that I would definitely use in my Coworker experience.
Mike: Yeah. And it just pairs really well. That way, you know there's conversations happening in Slack that would need to be brought in.
Rikke Hovgaard: Yeah. So, we use Salesforce obviously in Salesforce ourselves. We have our own engineering product engineering environment and in there we've enabled Coworker as well. And so, one thing that I ask a lot is for specific work stream that we're working on, I want to get an update that includes both the work items that I have in Salesforce, but it also includes all the Slack conversations that we're having on the side. And I get an update just by asking Coworker about what's happening. I know which engineer is working what work item and what risk or whatever else we might have that we have to, that might need my attention.
Mike: How stressful were you when they turned Coworker on in that org? Because all the other product managers are just eyeballing, right? Is this going to work? I wouldn't sleep that night. You kidding me?
Rikke Hovgaard: I actually felt pretty confident in it. I can't turn it on myself. I'm not an [inaudible 00:25:12].
Mike: Oh, well, that's good.
Rikke Hovgaard: But I did have very great collaboration with our admins, both on the GUS and TheOrg62 environment. And I leveraged my partner experience or my implementation experience. I wrote a really detailed walkthrough. I had amazing help from my engineers and it went pretty smoothly, and we had some check-ins every day. We watched the numbers grow and it was pretty cool to see.
Mike: Yeah, I could imagine. Parth, I know we've had some customers in the product as well because it's in beta. What have they had to say? What were some of the things they've shared back?
Parth Shah: I think this is one of my favorite products to work on in my career.
Mike: Oh, you say that about all the products.
Parth Shah: No, no, no. I say this seriously. I say this seriously because every time I've talked to a customer, they're so excited about it. I'll give you an example. Andrew Russo, he is currently a VP of business systems at, I'm saying it correctly, BACA Systems. And when he first heard about the product, I think Mark Benioff had tweeted about it, he heard about it. He was so excited to quote and kind of paraphrase a bit, he's like, "I felt like Santa Claus on Christmas bringing it to my team." And the use cases that he started seeing was like, start something super simple with a sales and business development team. One of the use cases he mentioned was, let's just get all of the context that we haven't reached out to. And I think he had mentioned something along the lines of like, it was a holiday coming up and this would've taken up so much of their team's time to actually find the contacts and reach out to them. Coworker did it really quickly and their teams were able to quickly reach out to the customers they haven't been able to reach out to and they were able to engage them. And so, this just kind of shows you the power of Coworker doing the work in the background so that your sales teams can actually focus on what matters, which is building out the relationships. I think overall, when I think about the use cases and how customers have been using it, what I repeatedly hear is the use cases are endless. There isn't just one use case that kind of shines. That's really the power of AI. But what it allows you to do is it allows a person to be as creative as possible. And I think as admins or the folks that are kind of introducing it, what I've seen work really well is nurture it. Give people one or two small use cases to start with so they start to see the power of it and then the natural curiosity of that team just kind of takes over. They're like, "Huh, what if we just get more complex?" It's almost like, can you thump Coworker? And the queries and the prompts that you put in just get more and more and more complex. I mean, even internally, we were recently working on a product of like we introduced a new feature, so how do we email the customers? And part of that is we want to make sure that they have the right license. Historically, that would've taken a long time, but we're like, "Huh, I wonder if Coworker can do it." Coworker kind of became a part of natural language, I guess, that you talk about every day and you naturally go to it because you start seeing the power of it and you're like, "Let Coworker do it." So, I think that's what I've seen is seed it and then just watch it grow. And then once you watch it grow within one team, take that idea, take those wins and take the people that have used it and they will talk about it to the other teams.
Mike: Well, I feel like Thursday night bowling league's going to get awkward when six of you are standing around and going, "I feel like we're missing somebody. Didn't anybody invite Agentforce Coworker?" Oh. They couldn't make it. They're stuck at the office. That's it. That's the one joke for the podcast. It never really lands and people always give it a bad review, but that you got to try every now and then. To kind of wrap things up, I always like to see what other people do. I feel having talked with a lot of people in technology, we often have very tactile hobbies or things that we like to do on the side. I'm usually pretty obsessed with my lawn. I can tell you soil levels and pH and all kinds of stuff that's not fun unless you're into lawn care. But Rikke, I'd love to know outside of making Agentforce Coworker awesome, is there a fun hobby that you have that you use to get away from Coworker every now and then?
Rikke Hovgaard: I don't know if I would say hobby per se, but for me, I really like going out by the water. I actually bike quite a lot out to the beach and then I have a puppy that I just let run around and that gives me a lot of common peace. I mean, hobbies, I don't think I have anything that I'm super nerdy about except for sometimes I get a little detail with some of my own data, but I feel like that's a little bit too close to work to mention as a good hobby.
Mike: Yeah. I'll take the biking thing. Boy, of all the dogs I've had, that was the best way to get them to run. Especially when you've been inside in meetings all day and they're like, "Mom, can we go for a run?" And you're like, "Yes, we can." That was about the only way I could keep up with my dogs was a good mountain bike.
Rikke Hovgaard: And I trained him early enough to actually jump in, or not jump, but I put him in a basket and we go.
Mike: Oh, mine were always too big for that. They're either making or they're not. One time though, he was running and I used to live in an area that was under construction. They had a manhole cover off and he was running along just beside me and one of his feet hit that manhole and it popped out of joint and that's when I learned how heavy a 30-pound dog is to carry over your shoulder and mountain bike back to the house and call the vet.
Parth Shah: Oh, no.
Mike: That was the only time I carried him. No basket for me though.
Rikke Hovgaard: Yeah. I'm happy I have a small dog now.
Mike: Right.
Rikke Hovgaard: Yeah.
Mike: Note to self. Buy a small dog that's easy to carry. Parth, I mean, you've been doing a lot of things. Plus you were in the Buckeye State, so I don't know, football.
Parth Shah: I watch football. I'm in New York, so go Knicks, Knicks in 5. Also, I love this question. Rikke, I had no idea that you bike. I would love to bike with you someday and obviously bring your dog.
Rikke Hovgaard: I mean, it's not like a race kind of thing, but yeah, I like biking around. I don't have a car. So, that's the only way I get around.
Parth Shah: Yeah. So, I live in New York and there's a lot of things that I absolutely love to do. What I've been really focusing on is one, I love going to museums. I absolutely love going to museums so much that I've pretty much checked out every single museum in New York and I'll go to them again. Part of that is just like it invokes this creativity in me, which is why I'm a marketer, just to see how other people are thinking through life and kind of portraying it. Second thing that I've been trying to get it more into is I've been trying to do a lot more of comedy. I know it's not coming through right now, but that's something that I want to work on. And then the last is yoga. Yoga because no AI is there in yoga. It's just me and myself.
Mike: Not yet.
Parth Shah: Not yet.
Mike: Somebody will invent an AI mat. Parth, your downward dog is not doing so well.
Rikke Hovgaard: There's those mirrors where you can get workout commentary on your-
Mike: Oh, that kind of weirds me out.
Parth Shah: Oh, me too.
Rikke Hovgaard: Yeah.
Parth Shah: I can't do that.
Rikke Hovgaard: I prefer my workouts to be just me and whatever I'm doing. I don't need any instructions to do.
Mike: You're biking your dog.
Rikke Hovgaard: Yeah. I mean, I do other things too, but I would say I don't like anybody commentary on what I'm doing.
Mike: Nope. Nope. Parth, that's so cool. I love the museum part. The presentation nerd in me loves going to museums and paying for the guided tour just to see the person and how they kind of direct people through because there's often a lot. There's a lot of people to pay attention to. There's a lot of information. I don't know. I like walking through museums all by myself. Don't get me wrong, but if I can do a guided tour, I always find that kind of fun too.
Parth Shah: One tip someone told me is look at the artwork and then also look at the people looking at the artwork. That itself is art as well. And I was like, "Whoa."
Mike: Yes. Yes, absolutely.
Rikke Hovgaard: I also find that a lot of museums are starting to have free tours with a specific theme. So, they take you on a path. I've noticed, at least when I was in Europe last time, there was a couple of museums doing that. So, something worth looking at the website all the time, because I definitely like having somebody cover a theme and take me through a journey in the museum.
Mike: Yep. I've been through a few where they have an app on the phone and you can just listen to and it walks you through. And that was always kind of fun because I feel there's a lot to take in and I'll read the plaque or the information by it, but it's like they can't put everything there. I know I did a few where I think they had the artist kind of comment in addition to what the information was and just kind of standing there and hearing in the artist's own words and seeing their work, it was very powerful. So, very cool. Well, see, it's not all about AI on the podcast. Every now and then we talk about some things that are fun. I want to thank you both for coming on. I think we covered a ton of stuff and I'm excited to see the future versions of Agentforce Coworker. I'm not going to ask you what they are because it's in beta and there's a big roadmap to come, but I think it's going to be very exciting for admins.
Rikke Hovgaard: I think we have some very exciting stuff coming up. We have a lot of good ideas from customers and from what we're thinking about ourselves. So, I think you have something.
Mike: Oh, I could only imagine. And I bet we're going to see some of them at Dreamforce, right?
Rikke Hovgaard: I am sure we will.
Mike: Knock on wood. Great. Well, Parth, Rikke, thanks for coming on the podcast.
Rikke Hovgaard: Thank you for having us.
Parth Shah: Thank you for having us.
Mike: Big thanks to Parth and Rikke for helping us unpack Agentforce Coworker from search to Slack to that magical moment when users ask, "Wait, it can do that." Oh yes, that's the best. Admins, this is your lane, connecting the data, guiding the rollout, and making sure AI helps the business without wandering off with the keys to the org. Now, if you haven't already, press that subscribe button, share this episode with your favorite Salesforce admin or your favorite Coworker. Maybe they're one and the same, or invite a Coworker to a bowling league. Just say it. It'd be fun, wouldn't it? I'd like to go bowling. Just don't expect them to rent the shoes. Maybe you rent the shoes. I would buy the shoes. Other people have worn those shoes a lot. You never know what could be in those shoes. Anyway, until next time, we'll see you in the cloud.
