Zoe Beard: Hello, welcome to DevOps Quick Bites. This is the podcast for Salesforce leaders navigating a rapidly changing ecosystem. I am Zoe and in the time that it takes you to finish your morning coffee, you'll have some insights from leaders across the Salesforce ecosystem. And with us today is Christopher Ramp from Capgemini Germany. So welcome to the podcast.
Christopher Ramm: Thank you for having me. Thanks for the invitation.
Zoe Beard: ⁓ yeah, so excited to have you on the podcast. we'll of diving into everything related to TDX quite soon. Cause I know you're attending ⁓ and have a few talks, ⁓ at the event. but for those of, ⁓ you know, those listing who aren't, ⁓ you know, maybe super familiar with you and, ⁓ your kind of your role, would you be able to give us a bit of a background in terms of, ⁓ yeah, your role at Capgemini Germany and kind of how you got into the industry.
Christopher Ramm: Oh, wow. Okay, that's now a long story. let's start with my current duty. So I'm the sales for CTO for Capgemini Germany. They are responsible basically what we are delivering in terms of all the kind of technical stuff around sales for. So all the kind of projects typically within our setup, we serving enterprise customers. Maybe that's no real surprise for a German based subsidiary of a company is like, we're doing a lot of automotive and manufacturing stuff. This is our major footprint within the Salesforce market. We're doing that now since the last almost 10 years where we've successfully, which I'm really proud of, to answering the first part of the question, how I came into that. I almost stumbled into Salesforce like everybody. It started with the kind of accidental admin career. So back in those days, I was a working student at Groupon and Salesforce was one of the systems they've used. And it was like the first touch points I had. then I ⁓ basically got addicted to it, starting getting my Mercurius admin and as a kind of ⁓ product manager. then later on I moved over to the consultancy job.
Zoe Beard: And probably one thing I would also like to point out is that you are a gear set DevOps leader as well. you can also, you're also hopefully adding that to your CV career milestones.
Christopher Ramm: ⁓ That's an aspect to be very honest, I'm super proud of. ⁓ So obviously DevOps is one of those very, very big challenges within ⁓ Salesforce. And ⁓ we as a team, put so much thought process around that, how to basically...
Zoe Beard: Thank
Christopher Ramm: enable our customers to provide them with the right setup and we put so much effort into also from a cultural perspective to structure everything. Getting recognized by a company like Geosat and they spending so much effort on that means a lot for me.
Zoe Beard: Yeah, I mean, obviously we're super happy to have you on board the program. And, um, I know I touched on it just in the intro, but, uh, one of the things we're going to talk about quite in depth in this podcast is TDX and give everyone a bit of a preview about what, you know, we may expect some of the biggest trends and topics to be at TDX. and I think one thing is that TDX is known to be the builders event and show the industry, how to build things and, you know, with key things that they can take away and start building their desk the following week. From your perspective, what do you expect some of the key trends will be, uh, you know, in San Francisco in just a few weeks time.
Christopher Ramm: Well, I strongly believe that we will see the connectivity from Salesforce, the core platform, but also potentially data cloud, how it will be ⁓ integrated and potentially even with Slack. This is maybe the third tool I have in mind. ⁓ How it's getting closely connected to all that kind of GNI capabilities which are around there. Obviously right now, ⁓ all kinds of SaaS companies are under pressure with their model. But we shouldn't forget about that Salesforce still owns most of the data. They have access to it. They have all the metadata information available. they can basically, and they have the business processes. We shouldn't forget that as well. our daily business where we spend tons of effort, blood, sweat, and tears into establishing those within our customers, they have all that valuable information.
Zoe Beard: Mm-hmm.
Christopher Ramm: and how to potentially make them available for ⁓ tools like Chat GPT, OpenAI, ⁓ or whatever we want to use. I guess this will be one important pillar, potentially in conjunction then always leave with like agent force as a tool and how everything ⁓ comes together in a really kind of end-to-end journey. So over the last 18 months from my perspective, what we saw was like kind of glimpse processing steps or like Here's like, ⁓ for example, how Agentforce is forces embedded into your process. But if you're taking the broader look from an enterprise perspective or like kind of a company perspective, you potentially want to enable so many different kind of ⁓ team ⁓ partners, customers with those AI capabilities that ⁓ you need to open up the platform. And I guess this is something where we will see then the next steps and the next iterations. ⁓ ⁓ in the next six weeks or phrase it differently during Tdx.
Zoe Beard: Mm-hmm. And that's actually, think, one of your talks at TDX, isn't it? Like how we shift around the kind of like how we're shifting from deploying code, managing the data, the data health of them that these agents can use that can, you know, enables them to function in real time.
Christopher Ramm: Yeah, exactly. ⁓ last year, was basically the first time I had a talk during the TDX and what we did together with my private grime, Sebastian was like, we presented something around UTAM, which is like a dedicated kind of testing framework for UI driven tests, which is kind of still great that it's around there because Salesforce is like a highly, or you can modify the UI super easily. ⁓ and it's a high changeable. Obviously, this is a nightmare for each testing teams. If you're changing the positioning, for example, within the page layout or the tab structure, whatever you have in mind, UTEM helps you to basically standardize that, that you don't rewrite the tests all the time. But what we didn't have in mind when we did the session one year ago was how even AI can accelerate that. One year ago, back at the stage, we said, you need to test your critical business process. And critical was like the understoked twice, like just the critical stuff, because it's still so much effort to basically produce such a kind of a test. And now we played around with all that kind of fancy tools around that and realized, yes, you can basically give the instruction to an agent and the agent is basically
Zoe Beard: and
Christopher Ramm: creating the test with you with the aid of the U-Tone specific language, producing then the respective tests. And obviously, you can now think about like broadening up your test case and test suites, is pretty great. And even empowers like business users when you're creating user stories to write those tests or providing the entry points. And just like in your natural language, this is awesome. And I couldn't believe that one year ago.
Zoe Beard: Mm-hmm. And do you think, just thinking about those two specific talks you have, the one around, you know, kind of managing data health, help agents function better in real time. And also, you talk around UTAM and page objects. Do you think those talks, the similarities are really about helping teams make, especially on the testing use case, make things easier for maybe like the non-technical team members to be able to kind of like use Salesforce more easily. And especially like the business users, as you just mentioned.
Christopher Ramm: Yeah. Good question. I ⁓ strongly believe everything around DevOps, yeah, and ⁓ you can basically combine the two talks I will have around those topics. like there's one kind of key aspect for me is all the time, like how are we enabling our teams potentially also from our Gemini perspective, also our customers, how are we enabling them? to make DevOps work. This is for me always like a kind of a cultural question as well in terms of like what kind of skills I have available. ⁓ What is also like the, how is it embedded into like the overall cultural approach as well as like the overall setup. And a key aspect for me and that kind of senses then how you enabling all those kind of team members to use what you've defined. So. Is it like UI driven to a like you said? Then obviously even then you need to come up with like dedicated training steps, processes, how you make it work. And then you can establish very easily ⁓ very, very good results. And this is very important. And of course, there's the other side is like, hey, we have like a lot of experience in like ⁓ CLI driven deployment. We have like a very complex structure and we want to say it was just embed into that. And there you potentially need to have answers as well. with multiple different ways, but this is something where I'm more focusing on what is the current situation and how does everybody feel comfortable with it, including business units, users, and then rather than coming and trying to squeeze in tooling and approach, which just doesn't fit.
Zoe Beard: Exactly. So kind of make sure that it's kind of taking people on the, on the, you know, bring everyone along for that journey. Um, and one thing actually I'm quite interested, cause obviously we've touched around agent force and AI more generally. Um, how do you think, because we know that AI is going to help, um, you know, kind of ultimately a lot of manual tasks and things like that for teams. Um, what do you think, how do you imagine that might change how people approach their day to day work?
Christopher Ramm: I guess our mid... It's changing so much, it's crazy. ⁓ So really based on the kind of different roles, I strongly believe that we will see totally new processes will establish. So we will definitely see that English or taking English may as a kind of a synonym here, language in general, will be the kind of new coding language. So rather than coming up with like... ⁓ dedicated knowledge around that we will see kind of a democratization of like ⁓ everybody could use it in that kind of sense producing the respective problems and the AI is then doing the job for you ⁓ meaning we are so much faster in terms of potentially producing certain artifacts but on the other hand of course we need to think about how we establish those then in entry and processes starting from like gathering ideas exploring around and what what adds business value, where's the purpose of the product we are delivering? And then of course, the whole production process, ensuring that from an architecture perspective, also something which was very important, like the security things fits in there. And last but not least, how are you potentially migrating that into like kind of a productive environment? And you also need to ensure, again, to enable your users, your customers to basically use it. And I guess this is something where I totally will change the way how we're doing that. Even then, if you're thinking for an additional AI layer as a kind of an engagement layer where you're just interacting maybe more like with something in a kind of a chatbotch sense or AI sense, that will also change the experience around that how we could potentially consume it. So this is also something where we totally need to rethink. ⁓ how we basically producing our artifacts, which is an interesting journey, definitely. But we, guess, all have to learn a lot.
Zoe Beard: Yeah. And I think what I was having a conversation with someone recently about, especially for people that maybe are still kind of getting into groups of AI is just being able to experiment a little bit with it and just try things out. I think especially before deploying it in a business environment, kind of like doing it in a more low stakes environment where you kind of experiment and understand like its capabilities. I know you mentioned actually that you built like an, as an iOS prototype and just four hours without writing a line of code. I'm just interested in what that project taught you about AI and ⁓ how that's maybe influenced how you approach it in work as well.
Christopher Ramm: Yeah, so basically it was just like kind of an accidental hobby project more or less and the root cause was like ⁓ I was kind of isolated sitting here in my office with the flu ⁓ and actually I couldn't do anything barely so I thought okay yeah you now have ⁓ that kind of Claude license paid so let's play a little bit around with that. How about ⁓ creating an iOS app. And then I just write a few prompts, basically. And as you mentioned, after roughly three, four hours, I had already like a kind of a prototype, which I was like able to see and play around with on my phone. And then it took me potentially another two, three days actually to get like to a 90, 95 % status and then maybe half day bug fixing. And then after a week, I had an app in an app store. which I couldn't really believe that the whole process, as Apple has dedicated guidelines, it took basically longer than basically producing the app to get through that episode. But jokes aside, that was a totally new experience and in a sense, where you actually came from. We already use that within our daily work. especially when it comes to prototyping stuff, where we're seeing like, what I meant earlier, we are trying to discover new business processes or processes together with our customers, that then obviously we are way more capable to provide unique experiences because we can produce code way more faster. So the idea what we had before in terms of like, everything needs to be saved for standard and ⁓ we can't handle too much code and complexity is potentially shifting a little bit with AI. We can build way more stuff. We can tailor things way more than we could imagine before. So giving maybe an example like ⁓ providing on the core or like end users or users with a component to see all the data from Data 360 and reaching it with maybe multiple tabs for a K that are product recommendations, that is your consensus data and so on and so on. ⁓ You can easily produce such a component within almost an hour, which is crazy. Previously, you had to think about way more deep how to actually achieve that. Taking that as rapid prototyping, exploring new things gives you ⁓ way more room to be creative ⁓ and to be way more on the spot. because otherwise you have potentially, yeah, I still need to see to say, senders and use such flows, screen flows, all those kind of things. But you never reach a point potentially where you create such kind of a unique experience. So this is something I definitely see as a of a great step forward to tailor the results for our customers. But obviously also then The other part is where I'm very still exploring, what is then the downside or the things you need to change and adjust in terms of the governance to ensure that what you produce is basically not so production-ready.
Zoe Beard: Yeah, mean, that's all that's genuinely so fascinating and hearing about people's own experiences, like a kind of experiment of AI, just the possibility that it is opening up to teams. And I think importantly, it's about how do we reallocate our time? We can use AI to kind of do these prototypes or to kind of do these kind of more manual tasks and what kind of gives us that extra brain capacity and cognitive space to kind of like, okay, like. bring new creativity into our work, which I think is really exciting. Yeah. Perfect. mean, thanks. I mean, this is all like a really, for me, like I love listening to people's talks kind of like around new topics, especially AI's it's kind of evolving so quickly and the use cases are rolling out are generally quite exciting. Obviously you'll be at TDX next, next month. ⁓ Do you have any tips for people attending TDX?
Christopher Ramm: for sure ⁓ yeah, so enjoy your time. And that's of course the most important part. But during TDX, you have so much chances basically to ⁓ exploring things, getting in touch with like product owners, developers, Salesforce folks, peers, ⁓ and of course partners where you basically can dive really deep into like the technical discussions. And I can encourage you to take those because this is like...
Zoe Beard: you
Christopher Ramm: Maybe also the biggest deviation, if you compare TDX with Dreamforce, Dreamforce is always way more business driven. And during TDX, you have the chance to go really deep and a really good understanding how the products are basically working. And this is like, yeah, it's a gift to spend those two days together during the TDX to exploring the new stuff in the Salesforce ecosystem.
Zoe Beard: And for people attending TDX, you give us maybe just a quick short summary of your talks at the events so people can catch you when they're there.
Christopher Ramm: Yeah, so basically if you're checking the session catalog and searching for my name, you basically will find three sessions. The first one is around Agent Forest and the respective data strategies around there. Then I do a really long session or two with Sebastiano to be more precise. The first one is ⁓ DevOps in a multi-hoc setup. So there we're bringing our stories from our... customers, how we basically established DevOps in multi-org environments and also where potentially things like data cloud come into the picture as well. And I mean, I gave you already the answer for the UTEM session in the short nutshell. The third one is like how you basically can leverage UTEM with the aid of AI to establish like a really strong and solid testing framework for yourself.
Zoe Beard: Awesome. Yeah, I mean, I definitely recommend anyone listening or attending TDX to obviously check out your sessions. I they are going to be quite fascinating. But thank you so much for joining us on the podcast. It's been great and we hope you have an amazing time at TDX and looking forward to kind of hearing your insights as well post event just around like what you learned and some of the biggest trends. So yeah, have a great time.
Christopher Ramm: Thank you. And thank you for having me.
Christopher Ramm: Thank you for having me. Thanks for the invitation.
Zoe Beard: ⁓ yeah, so excited to have you on the podcast. we'll of diving into everything related to TDX quite soon. Cause I know you're attending ⁓ and have a few talks, ⁓ at the event. but for those of, ⁓ you know, those listing who aren't, ⁓ you know, maybe super familiar with you and, ⁓ your kind of your role, would you be able to give us a bit of a background in terms of, ⁓ yeah, your role at Capgemini Germany and kind of how you got into the industry.
Christopher Ramm: Oh, wow. Okay, that's now a long story. let's start with my current duty. So I'm the sales for CTO for Capgemini Germany. They are responsible basically what we are delivering in terms of all the kind of technical stuff around sales for. So all the kind of projects typically within our setup, we serving enterprise customers. Maybe that's no real surprise for a German based subsidiary of a company is like, we're doing a lot of automotive and manufacturing stuff. This is our major footprint within the Salesforce market. We're doing that now since the last almost 10 years where we've successfully, which I'm really proud of, to answering the first part of the question, how I came into that. I almost stumbled into Salesforce like everybody. It started with the kind of accidental admin career. So back in those days, I was a working student at Groupon and Salesforce was one of the systems they've used. And it was like the first touch points I had. then I ⁓ basically got addicted to it, starting getting my Mercurius admin and as a kind of ⁓ product manager. then later on I moved over to the consultancy job.
Zoe Beard: And probably one thing I would also like to point out is that you are a gear set DevOps leader as well. you can also, you're also hopefully adding that to your CV career milestones.
Christopher Ramm: ⁓ That's an aspect to be very honest, I'm super proud of. ⁓ So obviously DevOps is one of those very, very big challenges within ⁓ Salesforce. And ⁓ we as a team, put so much thought process around that, how to basically...
Zoe Beard: Thank
Christopher Ramm: enable our customers to provide them with the right setup and we put so much effort into also from a cultural perspective to structure everything. Getting recognized by a company like Geosat and they spending so much effort on that means a lot for me.
Zoe Beard: Yeah, I mean, obviously we're super happy to have you on board the program. And, um, I know I touched on it just in the intro, but, uh, one of the things we're going to talk about quite in depth in this podcast is TDX and give everyone a bit of a preview about what, you know, we may expect some of the biggest trends and topics to be at TDX. and I think one thing is that TDX is known to be the builders event and show the industry, how to build things and, you know, with key things that they can take away and start building their desk the following week. From your perspective, what do you expect some of the key trends will be, uh, you know, in San Francisco in just a few weeks time.
Christopher Ramm: Well, I strongly believe that we will see the connectivity from Salesforce, the core platform, but also potentially data cloud, how it will be ⁓ integrated and potentially even with Slack. This is maybe the third tool I have in mind. ⁓ How it's getting closely connected to all that kind of GNI capabilities which are around there. Obviously right now, ⁓ all kinds of SaaS companies are under pressure with their model. But we shouldn't forget about that Salesforce still owns most of the data. They have access to it. They have all the metadata information available. they can basically, and they have the business processes. We shouldn't forget that as well. our daily business where we spend tons of effort, blood, sweat, and tears into establishing those within our customers, they have all that valuable information.
Zoe Beard: Mm-hmm.
Christopher Ramm: and how to potentially make them available for ⁓ tools like Chat GPT, OpenAI, ⁓ or whatever we want to use. I guess this will be one important pillar, potentially in conjunction then always leave with like agent force as a tool and how everything ⁓ comes together in a really kind of end-to-end journey. So over the last 18 months from my perspective, what we saw was like kind of glimpse processing steps or like Here's like, ⁓ for example, how Agentforce is forces embedded into your process. But if you're taking the broader look from an enterprise perspective or like kind of a company perspective, you potentially want to enable so many different kind of ⁓ team ⁓ partners, customers with those AI capabilities that ⁓ you need to open up the platform. And I guess this is something where we will see then the next steps and the next iterations. ⁓ ⁓ in the next six weeks or phrase it differently during Tdx.
Zoe Beard: Mm-hmm. And that's actually, think, one of your talks at TDX, isn't it? Like how we shift around the kind of like how we're shifting from deploying code, managing the data, the data health of them that these agents can use that can, you know, enables them to function in real time.
Christopher Ramm: Yeah, exactly. ⁓ last year, was basically the first time I had a talk during the TDX and what we did together with my private grime, Sebastian was like, we presented something around UTAM, which is like a dedicated kind of testing framework for UI driven tests, which is kind of still great that it's around there because Salesforce is like a highly, or you can modify the UI super easily. ⁓ and it's a high changeable. Obviously, this is a nightmare for each testing teams. If you're changing the positioning, for example, within the page layout or the tab structure, whatever you have in mind, UTEM helps you to basically standardize that, that you don't rewrite the tests all the time. But what we didn't have in mind when we did the session one year ago was how even AI can accelerate that. One year ago, back at the stage, we said, you need to test your critical business process. And critical was like the understoked twice, like just the critical stuff, because it's still so much effort to basically produce such a kind of a test. And now we played around with all that kind of fancy tools around that and realized, yes, you can basically give the instruction to an agent and the agent is basically
Zoe Beard: and
Christopher Ramm: creating the test with you with the aid of the U-Tone specific language, producing then the respective tests. And obviously, you can now think about like broadening up your test case and test suites, is pretty great. And even empowers like business users when you're creating user stories to write those tests or providing the entry points. And just like in your natural language, this is awesome. And I couldn't believe that one year ago.
Zoe Beard: Mm-hmm. And do you think, just thinking about those two specific talks you have, the one around, you know, kind of managing data health, help agents function better in real time. And also, you talk around UTAM and page objects. Do you think those talks, the similarities are really about helping teams make, especially on the testing use case, make things easier for maybe like the non-technical team members to be able to kind of like use Salesforce more easily. And especially like the business users, as you just mentioned.
Christopher Ramm: Yeah. Good question. I ⁓ strongly believe everything around DevOps, yeah, and ⁓ you can basically combine the two talks I will have around those topics. like there's one kind of key aspect for me is all the time, like how are we enabling our teams potentially also from our Gemini perspective, also our customers, how are we enabling them? to make DevOps work. This is for me always like a kind of a cultural question as well in terms of like what kind of skills I have available. ⁓ What is also like the, how is it embedded into like the overall cultural approach as well as like the overall setup. And a key aspect for me and that kind of senses then how you enabling all those kind of team members to use what you've defined. So. Is it like UI driven to a like you said? Then obviously even then you need to come up with like dedicated training steps, processes, how you make it work. And then you can establish very easily ⁓ very, very good results. And this is very important. And of course, there's the other side is like, hey, we have like a lot of experience in like ⁓ CLI driven deployment. We have like a very complex structure and we want to say it was just embed into that. And there you potentially need to have answers as well. with multiple different ways, but this is something where I'm more focusing on what is the current situation and how does everybody feel comfortable with it, including business units, users, and then rather than coming and trying to squeeze in tooling and approach, which just doesn't fit.
Zoe Beard: Exactly. So kind of make sure that it's kind of taking people on the, on the, you know, bring everyone along for that journey. Um, and one thing actually I'm quite interested, cause obviously we've touched around agent force and AI more generally. Um, how do you think, because we know that AI is going to help, um, you know, kind of ultimately a lot of manual tasks and things like that for teams. Um, what do you think, how do you imagine that might change how people approach their day to day work?
Christopher Ramm: I guess our mid... It's changing so much, it's crazy. ⁓ So really based on the kind of different roles, I strongly believe that we will see totally new processes will establish. So we will definitely see that English or taking English may as a kind of a synonym here, language in general, will be the kind of new coding language. So rather than coming up with like... ⁓ dedicated knowledge around that we will see kind of a democratization of like ⁓ everybody could use it in that kind of sense producing the respective problems and the AI is then doing the job for you ⁓ meaning we are so much faster in terms of potentially producing certain artifacts but on the other hand of course we need to think about how we establish those then in entry and processes starting from like gathering ideas exploring around and what what adds business value, where's the purpose of the product we are delivering? And then of course, the whole production process, ensuring that from an architecture perspective, also something which was very important, like the security things fits in there. And last but not least, how are you potentially migrating that into like kind of a productive environment? And you also need to ensure, again, to enable your users, your customers to basically use it. And I guess this is something where I totally will change the way how we're doing that. Even then, if you're thinking for an additional AI layer as a kind of an engagement layer where you're just interacting maybe more like with something in a kind of a chatbotch sense or AI sense, that will also change the experience around that how we could potentially consume it. So this is also something where we totally need to rethink. ⁓ how we basically producing our artifacts, which is an interesting journey, definitely. But we, guess, all have to learn a lot.
Zoe Beard: Yeah. And I think what I was having a conversation with someone recently about, especially for people that maybe are still kind of getting into groups of AI is just being able to experiment a little bit with it and just try things out. I think especially before deploying it in a business environment, kind of like doing it in a more low stakes environment where you kind of experiment and understand like its capabilities. I know you mentioned actually that you built like an, as an iOS prototype and just four hours without writing a line of code. I'm just interested in what that project taught you about AI and ⁓ how that's maybe influenced how you approach it in work as well.
Christopher Ramm: Yeah, so basically it was just like kind of an accidental hobby project more or less and the root cause was like ⁓ I was kind of isolated sitting here in my office with the flu ⁓ and actually I couldn't do anything barely so I thought okay yeah you now have ⁓ that kind of Claude license paid so let's play a little bit around with that. How about ⁓ creating an iOS app. And then I just write a few prompts, basically. And as you mentioned, after roughly three, four hours, I had already like a kind of a prototype, which I was like able to see and play around with on my phone. And then it took me potentially another two, three days actually to get like to a 90, 95 % status and then maybe half day bug fixing. And then after a week, I had an app in an app store. which I couldn't really believe that the whole process, as Apple has dedicated guidelines, it took basically longer than basically producing the app to get through that episode. But jokes aside, that was a totally new experience and in a sense, where you actually came from. We already use that within our daily work. especially when it comes to prototyping stuff, where we're seeing like, what I meant earlier, we are trying to discover new business processes or processes together with our customers, that then obviously we are way more capable to provide unique experiences because we can produce code way more faster. So the idea what we had before in terms of like, everything needs to be saved for standard and ⁓ we can't handle too much code and complexity is potentially shifting a little bit with AI. We can build way more stuff. We can tailor things way more than we could imagine before. So giving maybe an example like ⁓ providing on the core or like end users or users with a component to see all the data from Data 360 and reaching it with maybe multiple tabs for a K that are product recommendations, that is your consensus data and so on and so on. ⁓ You can easily produce such a component within almost an hour, which is crazy. Previously, you had to think about way more deep how to actually achieve that. Taking that as rapid prototyping, exploring new things gives you ⁓ way more room to be creative ⁓ and to be way more on the spot. because otherwise you have potentially, yeah, I still need to see to say, senders and use such flows, screen flows, all those kind of things. But you never reach a point potentially where you create such kind of a unique experience. So this is something I definitely see as a of a great step forward to tailor the results for our customers. But obviously also then The other part is where I'm very still exploring, what is then the downside or the things you need to change and adjust in terms of the governance to ensure that what you produce is basically not so production-ready.
Zoe Beard: Yeah, mean, that's all that's genuinely so fascinating and hearing about people's own experiences, like a kind of experiment of AI, just the possibility that it is opening up to teams. And I think importantly, it's about how do we reallocate our time? We can use AI to kind of do these prototypes or to kind of do these kind of more manual tasks and what kind of gives us that extra brain capacity and cognitive space to kind of like, okay, like. bring new creativity into our work, which I think is really exciting. Yeah. Perfect. mean, thanks. I mean, this is all like a really, for me, like I love listening to people's talks kind of like around new topics, especially AI's it's kind of evolving so quickly and the use cases are rolling out are generally quite exciting. Obviously you'll be at TDX next, next month. ⁓ Do you have any tips for people attending TDX?
Christopher Ramm: for sure ⁓ yeah, so enjoy your time. And that's of course the most important part. But during TDX, you have so much chances basically to ⁓ exploring things, getting in touch with like product owners, developers, Salesforce folks, peers, ⁓ and of course partners where you basically can dive really deep into like the technical discussions. And I can encourage you to take those because this is like...
Zoe Beard: you
Christopher Ramm: Maybe also the biggest deviation, if you compare TDX with Dreamforce, Dreamforce is always way more business driven. And during TDX, you have the chance to go really deep and a really good understanding how the products are basically working. And this is like, yeah, it's a gift to spend those two days together during the TDX to exploring the new stuff in the Salesforce ecosystem.
Zoe Beard: And for people attending TDX, you give us maybe just a quick short summary of your talks at the events so people can catch you when they're there.
Christopher Ramm: Yeah, so basically if you're checking the session catalog and searching for my name, you basically will find three sessions. The first one is around Agent Forest and the respective data strategies around there. Then I do a really long session or two with Sebastiano to be more precise. The first one is ⁓ DevOps in a multi-hoc setup. So there we're bringing our stories from our... customers, how we basically established DevOps in multi-org environments and also where potentially things like data cloud come into the picture as well. And I mean, I gave you already the answer for the UTEM session in the short nutshell. The third one is like how you basically can leverage UTEM with the aid of AI to establish like a really strong and solid testing framework for yourself.
Zoe Beard: Awesome. Yeah, I mean, I definitely recommend anyone listening or attending TDX to obviously check out your sessions. I they are going to be quite fascinating. But thank you so much for joining us on the podcast. It's been great and we hope you have an amazing time at TDX and looking forward to kind of hearing your insights as well post event just around like what you learned and some of the biggest trends. So yeah, have a great time.
Christopher Ramm: Thank you. And thank you for having me.
