Simplify troubleshooting and support case management with Product Support Agent

Transcript

Don’t touch that dial, product support agent bout to rock your file From the call to the case to the troubleshoot show When the system goes down that’s the pro you know I said P-S-A in effect, when your stack goes wild better show respect You got logs, timeouts, bugs on the screen But PSA jumps in keeping systems clean Hit the chat like yo I need support Agent rolls in like the tech escort No panic no stress just a step by step Got the runbook ready and the knowledge prepped PM nodes to a funky old cue PSA breaks it down like here’s what we do Check one, check two, configuration tight In a minute flat everything’s alright PSA in the house today Solving big time issues in an old school way From the bug to the fix, from the log to the patch PSA is the champ that you just can’t match PSA turn the trouble to smooth When the beat breaks down we improve your groove If your app goes whack don’t sweat don’t fret Call product support agent that’s your best bet Some folks freeze when the screen goes black But PSA attacks with a knowledge stack Trace backs, errors 500 codes Agent navigating all the tricky roads Got root cause gaming mitigation too Work around now now long term in view You say my deploy just failed again PSA replies let the session begin Check pipeline logs see the step that stuck Says inch jammed up but we’ll push your luck Re-check and the lights turn green Your whole release flow looking crisp and clean Who you call when the bug’s insane? PSA remember the name Who you ping when the logs go wild? Product support agent that problem child This ain’t luck this is skill on demand PSA got playbooks right in hand Conflicts, networks, queues That one weird issue with the misset fuse No band-aid hacks or mystery spin Just real tight answers that you trust to win Turn a messy outage to a clean case foul Now you and PSA backing up time style PSA, yo, keep the system alive Old school rhythm with a modern drive From sunrise shift to the late night crew Product support agent gets you through When your stack goes down and you feel that fear Just say PSA, the fix is here Turn the volume up, don’t touch that dial Product support agent bout to rock your foul From the call to the case to the troubleshoot show When the system goes down that’s the pro you know I said P-S-A-N effect When your stack goes wild better show respect You got logs, timeouts, bugs on the screen But PSA jumps in keeping systems clean Hit the chat like yo, I need support Agent rolls in like the tech escort No panic, no stress, just a step by step Got the runbook ready and the knowledge prepped From AEM nodes to a funky old queue PSA breaks it down like here’s what we do Check one, check two, configuration tight In a minute flat everything’s alright PSA, in the house today Solving big time issues in an old school way From the bug to the fix From the log to the patch PSA’s the champ that you just can’t match PSA, turn the trouble to smooth When the beat breaks down we improve your groove If your app goes whack don’t sweat, don’t fret Call product support agent that’s your best bet Some folks freeze when the screen goes black But PSA attacks with a knowledge stack Trace backs, errors 500 codes Agent navigating all the tricky roads Got root cause gaming mitigation too Work around now now long term in view You say my deploy just failed again PSA replies, let the session begin Check pipeline logs, see the step that stuck Says inch jammed up but we’ll push your luck Re-check and the lights turn green Your whole release flow looking crisp and clean Who you call when the bug’s insane? PSA, remember the name Who you ping when the logs go wild? Product support agent, that problem child This ain’t luck, this is skill on demand PSA got playbooks right in hand Conflicts, networks, cues That one weird issue with the misset fuse No band-aid hacks or mystery spin Just real tight answers that you trust to win Turn a messy outage to a clean case foul Now you and PSA backing up time style PSA, yo, keep the system alive Old school rhythm with a modern drive From sunrise shift to the late night crew Product support agent gets you through When your stack goes down and you feel that fear Just say PSA, the fix is here Product support agent is in effect When your stack goes wild, better show respect I’m Daniel Wright, Technical Marketing Engineer for Experience Platform Welcome to our episode, Simplified Troubleshooting in Support Case Management with Product Support This session is part of a series spotlighting experience platform agent orchestrator and purpose-built agents, each episode offering a deep dive into how Agentic is transforming marketing workflows, streamlining operations and delivering smarter customer experiences. And of course, each episode now ships with its own theme song. So let’s talk about what marketing and customer experience teams are facing today. They’re under huge pressure to deliver highly personalized multi-channel campaigns, faster and with fewer resources. But here’s the challenge. Instead of focusing on strategic high impact work, a lot of their time gets eaten up by operational tasks like troubleshooting and managing support issues. That’s where Experience Platform agent orchestrator comes in. With a product support agent, these teams get an interactive way to troubleshoot, diagnose and escalate issues right inside of their experience platform applications. The result? Faster resolutions, less operational drag and more time to focus on creating amazing customer experiences. Speaking of amazing customer experiences, let’s get moving with our episode and welcome our guests. So first to step onto the stage is Product Marketing Manager for Adobe Experience Platform. Please welcome Hung Vu.

Hi Daniel. Hey Hung. Good to see you again.

So your fun facts, you are a self-proclaimed foodie and always willing and ready to travel far and long in pursuit of good food. So what’s the farthest and the longest you’ve traveled for food? And did it meet your expectations? Yeah, of course. Yeah. I’m just going to do a quick introduction as well. This is my third time on the show. I’m so very excited and happy to be back. Hi everyone. My name is Product Marketing Manager on Adobe Experience Platform team. So as Daniel has mentioned, I am a self-proclaimed foodie, so I am always willing and ready to travel really far and wide for food. I can’t remember the farthest I have gone for food, but I can say for sure that I am a pretty annoying travel buddy. If you’re not into food, if you’re the type who eat to live and not live to eat like myself, then it’s pretty annoying to travel with me because even after a very long day of traveling and being on your feet, I will still force you to travel, to walk for up to an hour and then wait in line for another hour to make the meal worth it. You can ask my mom. She’s been subject to this torture for many, many trips and she’s a guy who can just settle for whatever. And she has been forced to wait for two hours with me to eat at a pretty highly rated restaurant and she was not having it.

Do you have any food goals for 2026? Any places you want to go to or new experiences? Yeah, I would love to go back to Japan to have, I think one of the kind of oatmarker places at fish market itself. So basically they get fresh from the fishermen and then kind of ship that straight to the restaurants at the fish market and you have it like as fresh as it can be at, I believe 7am in the morning. I’ve never had sushi at 7am in the morning, but apparently you start queuing at 3am. So now my partner will take on that torture. So we don’t know how he feels about that yet, but it’s already signed him up without him knowing. So unfortunately. You might like it so much that you started setting your alarm clock for 3am so you can wake up at home and eat some sushi. I hope it’s worth it because 3am, yeah, that’s going to be the most I’ve done for food, but we’ll see. Yeah. My recommendation for you, since you live in California, I had a really amazing food experience. There’s a little tiny town called Harmony, California. The population is like 15 people and they have historically it was a dairy. So the whole town used to be a dairy and they have an ice cream shop called the Harmony. I think it’s just called the Harmony Dairy and it is the best ice cream I’ve ever had. And I’m a big ice cream connoisseur. So it’s very between Cambria and Big Sur, but totally worth it if you like ice cream. We are big ice cream fans here, so I’m adding that to the list.

So let’s welcome our next guest. Next up, we have Senior Product Manager Shreya Anantha Raman.

So Shreya, you shared that for this year you had a 15 book reading goal, which you did not keep up with and you’ve been panic reading for the last six weeks to meet your goals. So tell us about some of those last 11 books and how you crank through so many in such a short period of time. I mean, I always read a lot more towards the end of the year than I do the start of the year. So I always knew it was going to be a bit heavy on the later half of the year. But come October, I had only read like four books and I really did not want to mark my goal as incomplete on Goodreads. I really wanted like the confetti that tells me that I was a publicist. And so I was reading at like a non-productive pace because I wasn’t doing anything else outside of like work and reading. Nothing else was getting done by me. So I don’t know that my husband really appreciated that, but it is what it is. And then I did 11 books in the last six weeks, including this incomplete series, which I’m currently really obsessed with. And I’m deep in the throes of Reddit and Instagram research on like, what is happening? What’s going to happen next? When’s the next book coming out? And things like that. So it’s just a fun place for me to be in. What’s your favorite genre that you like to read? Yeah, I usually read like thrillers or semi-realistic dramas, like set in real context with virtualized stories. But this year I’ve gotten into fantasy quite a bit.

That’s the incomplete series I read was fantasy and it’s got me hooked right now. Cool. Good. Well, hopefully you have lots of time in the last couple weeks. How many more books do you have left? I finished it. I was finished. And so I’m setting myself up for 18 books next year. Let’s see how long it takes. Oh, 18. Nice. I’m going to find your Goodreads account and cheer you on.

All right. So let’s get moving with this episode. So we’re going to go through, we’re going to have an overview of Product Support Agent. There’s going to be a demo and then there’s going to be some talk of innovations on the horizon. And just a reminder, those of you watching the episode, please ask questions. We’re here. I’ll be monitoring the chat throughout. And if you’re not already, please drop in questions as they pop in your head and we will do our best to address all of them. So first up is Huan. Would you like to get us started? Yeah, of course. Let me just bring this into full screen. Daniel, I’m sure you are looking all right on your end. It is. Okay. Perfect. All right. So yes, feel free to stop me anytime, ask any questions that you have. We do have a couple of slides so that I can set the scene for our main hero of the day, Product Support Agent. And then we’ll go straight into Shreya for you to see Product Support Agent in action. But to start this conversation, again, as I have mentioned, I have joined this show a few times before and you might have seen this slide before in my previous episode that focused on Agent Orchestrator. But for those of you who haven’t seen this slide before, this is such a great way to start any conversation related to Adobe Customers Experience Orchestration Vision, Adobe Experience Platform Agent Orchestrator, as well as our 12 Purpose View Experience Platform Agents that Daniel has mentioned. But basically, it does a great job of outlining Adobe Customers Experience Orchestration Vision here by bringing together the content piece, the data piece, the journey piece to help brands like yourself deliver personalized experiences itself. And we believe Agenic AI, specifically Adobe Experience Platform Agent Orchestrator, as well as our 12 Purpose View Adobe Experience Platform Agents, you can see on that layer over there, is the ultimate key to unlocking this very ambitious vision. But as I mentioned before, today the spotlight will be on Product Support Agents. So I just want to begin by walking you through the major customer problem that we’re solving. So our key persona for Product Support Agents is the Marketing Operations Specialists. Maybe you know them, maybe you are a Marketing Operations Specialist, but they are someone who work very closely with the broader marketing team to really streamline the processes to analyze performance, to drive strategic planning, to improve efficiency and effectiveness. So a couple of their roles involve managing, optimizing marketing workflows in Adobe applications, as well as handling support cases when things go wrong. So very often, this Marketing Operations Specialist is the primary liaison with the Adobe support team. So this Marketing Operations Specialist, let’s call her Ashley. So she’s very sharp, she’s resourceful, she’s always solving. But despite her skills, she’s constantly stuck chasing answers. So she’s managing very complex systems, resolving issues across teams, keeping campaign moving. But the support work, if you’ve done it before, if you have seen your colleague do it before, it’s very relentless, manual, very fragmented and very frustrating. So here are a couple of challenges that Ashley might face day in and day out, which are more than just technical issues, right? She’s navigating a very tangled net of very manual support cases that slow her down at every step. So first, troubleshooting is really anything but simple. A documentation can be very technical and kind of scattered, which make it easy to locate them and then to interpret the steps that are involved in that troubleshooting process. And when the issues span multiple teams, you know, just coordinating who does what can lead to a lot of delays and breakdown. And then comes the case creation process. So historically, it has been pretty slow, very manual, very prone to errors. So Marketing Operations Specialists like Ashley can spend a lot of valuable time just pulling together the right information. And even then there’s a lot of back and forth with multiple teams to fill in the gaps that are needed to build that support case. And then even after the support case have been created, even tracking that case is a challenge in itself. So updates can come in through multiple channels, it can come in through email, it come in through portal updates. But the problem is that you do have to manually keep track of it. So the challenges are very difficult to manage. So you have to manually filter through cases, really slow things down further. And all of these challenges add up not just to frustration to Ashley, but also real delays for the business. So to help you better understand the challenge that Ashley faces, let’s take a quick look at her most recent challenge. So she works for Weekends, it’s a retail company. So Weekends onboarding campaign is due to go live soon. And this is just in time for the Super Bowl, which is undoubtedly one of the most important marketing moments of the year. So Ashley team aim to convert that 5 million trial users into paid subscriber. But soon they realize that they hit a very serious roadblocks, which is the fact that there are no new profiles entering the campaigns, which is a serious issue, considering how quickly Super Bowl is approaching. So how does Ashley typically go about removing roadblocks? So first, Ashley might go through a lot of fragmented troubleshooting documentation. She might try a couple of different methods to troubleshoot, like checking journey, checking recent changes to audience definition, but nothing seems to be a problem. Then she speak to other team, they can’t see a problem either. So she’s stuck, she’s frustrated. And that’s when she decides to fill out the support cases. Again, this is a manual process. So key details like logs are pretty hard to find because they are stored across multiple system. And after all of the manual efforts, you know, the case might still like some of the key details that it needs. So it lacks a position that it needs for the support team to be able to step in and solve that. So she’s going to be in constant back and forth trying to make sure that she has all of those information that’s critical.

After the support case has been created, she then, you know, find the root cause, and which in this case might be the fact that the streaming segmentation is turned out. But by the time you manage to solve the problem, this has been weeks from when she discovered the problem. And you know what that means the Super Bowl is already over and they miss that very critical marketing moments. So actually challenges do not just slow her down alone, they mean miss opportunity for the business. So manual troubleshooting navigation really reduce this operational efficiency is disrupt marketing workflows. error prone case creation will lead to allow back and forth with support team and just general frustrations across the entire business business units. And then last but not least, the fact that case monitoring is very manual means that Ashley will risk delaying visibility and missing critical updates, and very timely escalations. So there has to be a better way you know, we all need a smarter way to work Ashley needs a smarter way to work she needs a more intelligent system that can keep up with her pace, one that can adapt and can move as fast as possible with her. And which is when we enter product support agent enters the picture. So it’s designed to really reduce the friction in support workflows and making it a lot faster and easier for the specialists to be able to identify to report and to track issues. So freeing them up to do what they do best. And product support can provide a very guided, very interactive and effective way to troubleshoot, diagnose and escalate issues. And all of these will lead to faster time to resolution, greater operational efficiency and just overall enhance, you know, satisfaction for our users. So as you can see on the screen, the first set of skills available to all users include quick troubleshooting. So the fact that you can ask questions and then you can get back quick responses to common support questions. And all the answers are sourced from expert curated documentation. So you know, you can trust them, you’ll be able to also click on the the very verifiability to find where the sources are coming from. And you know that you can trust these, these answers. We also have support case creation. So for those of you who have already had access to AI system, you’ll be able to use product support agent and initiate support cases directly from the AI system interface, automatically capture more contextual insights. All of those key details are really hard to find manually to be able to really accelerate that case creation and hence case resolution. And then last but not least support case tracking once again from the AI system interface, users will be able to seamlessly track the status of their support issues through the same interface. So product support agent is now available to all Adobe experience platform and application customers. So Adobe journey optimizer, Adobe real time CDP, Adobe customer journey analytics, as well as Adobe experience manager. There are some nuances to some of the skills availability. But we will cover that in just a little bit. And then before we go straight into the demo, and you can see product support agent in action, I just want to quickly go through how Ashley’s workflow will look with product support agent in the picture. So you can see instead of having to jump between system between different documentation trying and chasing down the answers to her problem, she can start with a question she can start this question inside AI system, you know, interface, he can ask for troubleshooting guidance, and AI system can come back with multiple recommended steps that she can do, she can check the sources, she can stay in control of what to do next. She can get very immediate and contextual guidance on what to do. So she can try a couple of them. And for anything very advanced, like filtering, for example, she can still go on to to to submit that support case for Adobe’s help. When she’s ready to escalate you again, you don’t have to fill out that support case manually anymore. Product support agent can step in to help pre populate some of these important details in that support case for you making it a lot faster, a lot easier to build out that support case that you can then go on and and submit. And once Ashley has submitted the case, again, once inside that AI system interface, Ashley can prompt product support agent to provide her with the the status updates that she needs. So all of these time and efficiency gains using product support agent ensure that there are no disruptions to the marketing workflows. And the result is great. They can go ahead and reach their goal of five million conversions and still plenty of time until the Super Bowl. So needless to say, they have won big at Super Bowl. So, yeah, that is my quick spiel for product support agent. I don’t know. I think, Daniel, if we have any questions so far, anything I can help to clarify before we move on? No questions at this point, but just a reminder, if you do have questions, just type them in the chat and we will answer them. Yeah, let’s see it in action. Slides are one thing, but let’s see the actual product. Show us Shreya. Yes, I’m just going to run through a really simple scenario. This is our brand new AI assistant interface. I’m going to first just query to see what data sets I have in my sandbox. And so what the assistant is going to do is query the operational data and provide a list of data sets that are available to me in my sandbox. And this is also my first time doing something like this live, so just thank you for having me. Good. So here is a list of all of the data sets that I have. It’s about six rows here. I can always look to see more data sets and a list of all of my data sets here in the response. Say I notice some data set that I don’t recognize or I want to no longer and I’m trying to delete it, but find that I’m getting errors while deleting it. So I can just ask product support agent, why can’t I delete my data set? And so what product support agent does is query through a lot of expert curated documentation, most of which is rooted on real troubleshooting patterns and give us a response based off of that, right? So based off of things that have worked in the past or rationale that have worked in the past. And so you see that here, you see that it gives you a set of common reasons why a data set cannot be deleted. It also includes multimodal content in the responses where applicable. So in this case, for example, there is an applicable video and there’s an image that’s included in the response to better the understanding of this as well. One of the reasons that it gives me in this response is that I might have a system configured data set and that’s why I’m not able to delete it. There’s related suggestions here. So let’s just say I’m trying to find out how to check whether the data set that I’m trying to delete is a system created one and that’s why it cannot be deleted. Again, it goes through a lot of documentation and gives me a response that hopefully answers my question and again is rooted in previous successful examples. Say this still isn’t what I’m looking for and the data set that I want to delete is not a system created data set, but I’m still getting errors. A product support agent like Hong mentioned can help me raise support cases for Adobe support by simply saying create a support ticket. We can ask the agent to summarize the conversation details from my sandbox, from my org history, and then generate a draft ticket that me as a user can review. So here you see that there is a sample, a draft ticket generated, all of which is editable. I can always add details, take out details. For example, I haven’t specified a data set ID. I can add that into the description and make sure that it really reflects the issue that I’m seeing. You can add any attachments, set the business impact, set the priority, and once satisfied, submit this ticket again through the chat interface directly into the Adobe support queue. And then once the ticket is submitted, product support agent will give you a short card linking you to the ticket and then telling you simple details about it, like its status, when it was created and who it was created by. And then the last thing you can also do with the agent just to close the loop is ask about the status of your cases. So here again, I’m just going to ask the status of the case that I just created. And again, you get back the same card showing you whatever the latest status on that ticket is, if there’s been any progress and things like that. So this is product support agent in action in the product that we have. If you want to just quickly go back to the deck, like Hong mentioned, there’s some nuances as far as availability of these skills go. Yeah, sure. Can I pause you for a second and ask some questions? So are those the magic words, create a support ticket after conversing in the AI assistant? Yes, you can use those words or something like it and then it knows. Yeah, so you can say here a support ticket, can you create a support ticket, create a support case, anything like that. And you don’t even have to have had a conversation beforehand. You can start off a session by saying create a support ticket. What product support agent is going to do is prompt you for more information about the issue that you’re facing. So you can then say, I’m having issues with data set X, Y, and Z, and I’m unable to delete it. And it will summarize that and generate that same draft ticket for you to submit, review and submit as well. So yeah, something like that. So if you do interact and ask some questions before opening the support ticket, then it’s able to add additional context to the technical support team about where the issue is. And then I guess you don’t have to write all of that stuff up yourself. It’s just grabbing it from your conversation in the assistant. Precisely. And like you said, Daniel, the higher the volume of the conversation I have, the more detail the agent has to summarize and the more effective the ticket gets. But that’s exactly the idea is reduce the burden of creating tickets of the user and summarize and contextualize as much information as we can and simply have the user review, edit, and then submit it rather than through all of the details. Could you go back and show the account context details that were included in the ticket? Because that seems like it’s an annoying thing that I wouldn’t want to do as a customer. Okay, it’s this org and this is the account ID. How many bits and pieces of that are there that are useful to have in the support ticket? It’s like the org, the sandbox, the data set ID, all of that kind of stuff. Yes, exactly. So we capture page information. So if you’re looking at something else on the page, and then you’re trying to create a ticket, we capture that. We capture your org ID, your user ID, your sandbox information automatically. If you are talking about specific objects in the chat beforehand, we capture those details as well. There is the AI assistant chat ID included. So if somebody wanted to review the conversation that led up to the creation of the ticket, and they have the access to do so, they have that available as well. And this ticket again, you can review it in the tools that you would typically use to review tickets. So I’m just trying to load this page up here on admin console, which would give you a summary of the tickets submitted. Usually just takes a minute. But those are, yeah, there we go. So those are the kind of details that we are capturing. You can see here we have active sandbox, the product, which data here I didn’t mention a specific data set. But if I did, that would have been captured here as well. It captures key points, and then the page observations, as well as the assistant chat ID. So this would be the ticket that you would need.

I can see how just automatically including that kind of information could save several days of back and forth over email. What is the account name, and what was the data set ID that you’re having trouble with? All of that. I used to be an Adobe customer before I joined Adobe. And I remember how some of those conversations that you’d have over email just to make sure that they had all of the info that was required. You’re not always thinking about it as the customer that I need to provide all of these low level details. But of course, that’s what’s needed. And to not have to copy and paste all that info in. I can really see how that’s going to save time and frustration of monitoring your email inbox to see what else is needed to move things along. So that’s great. Absolutely. And thank you for bringing that up, because this is something that we’ve heard from customers that have tried this out already. They’ve obviously seen value in us aggregating across all of the documentation that we have and providing them pertinent answers. But more importantly, they are finding value in the fact that exactly like you said, they don’t have to hunt through different things to find information. And we are able to capture all of that automatically. They feel like they don’t have to repeat themselves when the ticket goes through different stages in the support lifecycle as well. And so that’s our goal, is just trying to make this process as seamless and as easy as possible. And now can any customer with a product, one of those four or five products that were shown, can any of those people with access create a support ticket or do they need some elevated privileges to get that extra prompt to open the ticket? So to create a ticket specifically, a user needs to have something called the support administrator role. This is a role that the user should have even outside of AI-assisted and product support agent to create tickets. If you already have permissions to create and manage tickets on your own, you are able to do so using product support agent as well. So that’s the one like permission that I would call out. The other thing is right now, product support agent on this brand new UI, we are in a closed explorer beta. And so this is available to customers that are part of that beta. For other customers that are using the old UI of AI-assisted, they should have product support agent available as well. And then I think there’s also a licensing element to this, Hong, if you want to talk about that. Yeah, I can talk about Shreya before that, if you don’t mind going back to the previous demo screen real quick. And if you can switch back to the conversation, I just want to quickly kind of last one to the fact that we have moved on to more immersive UI. So for those of you who have tried product support agent before in the ride-rail experience, you know that it’s been great and we’re able to do everything that you are doing right now. But it is a little bit more limited in size. But now that we have moved on to a more immersive interface, you can see a lot richer details that are more in that full screen. And you’ll be able to, when Shreya created the tickets before, you can see that it kind of split into a split view. So you have your conversation on one side, you have the tickets on the other side that you can review without having to leave the screen that you’re on. So I find that is such a much better user experience that we have. So I just mentioned that the agent on the ride-rail interface is still available to customers without the agent orchestrator skill that you need. However, if you want to access product support agent in this new interface, you do have to reach out to your Adobe account team to license the ride skill to be able to access it in this format. So that is the one caveat that we have.

Kushal left a couple of comments in the chat around the topic I asked about earlier for the users who don’t have permission to create the support ticket. Are you able to show what that looks like, how far they can get? Because I would imagine that some of the things you showed, they would be able to do like asking the AI assistant questions about why can’t I delete my data set? What would happen for those users if they then put in a prompt, create a support ticket? Yeah. I should be able to, and this is really important. So I’m on an org where I don’t have stuck in processing. So the first part of product support agent, which is the quick troubleshooting piece, that’s available to anybody, everybody. You don’t need any specific support related permissions to be able to do that. So once I ask a troubleshooting question, we query what we call product knowledge. So this is any customer facing public information that we have in Experience League. And we are able to provide an answer again, if we have that expert curated documentation available, that’s included as well. And so that’s what you would see a response based off of. Same thing, if we had multimodal content that was relevant to the question, that would show up in this response as well, no new permissions needed. Now, if I do try to create a support ticket, right now, what happens is that I would see a message saying I don’t have the required permissions. I think I don’t, yeah, I don’t have the options in this org. So I would see a message saying I don’t have the right permissions, and I need to talk to my administrator. If I wanted to a ticket. And so that’s, this is one piece of the experience that I’ll just touch upon in a little bit. We are trying to address as part of our roadmap as well as to have a sort of seamless handoff where if I as a user who doesn’t have permission to create support tickets, go through some level of troubleshooting, I can then hand off that context to my admin, and they can then use it to create a ticket. So that’s part of our roadmap, but it just doesn’t exist today. So this is what you would see if you weren’t a support admin on the org, and you don’t have permission. Yeah, that sounds like a great feature to be able to, because sometimes it’s like the user with like deep knowledge of the specific product and then they need to hand off to somebody else to open the ticket. So that would be cool if that handoff could be managed so they don’t have to, you know, it’s like having a separate ticket. First, I need to report to this other person and then they report to Adobe and it’s like that old game of telephone where, you know, you say something and then they pass it to the next person and sometimes information gets lost and it changes. And so that sounds like a great enhancement to this.

Absolutely. Yeah. Any other questions we can answer before we jump back into the presentation and I can cover availability and what’s coming next with that collaboration. Yeah, yeah, I see some roadmap questions. So when you’re ready to get into the roadmap, I can bring those up. Let’s do it. Let’s switch back to the other screen real quick. Let me bring this back.

Awesome. Thank you. So like I said, the quick troubleshooting scale is available to everybody across CDP, AJO, Customer Journey Analytics, Adobe Experience Manager, and then we’re working to bring parity across all of the Adobe products that you would be using as well. Support case creation and case tracking is limited to support administrators and is currently available on CDP, AJO, and AEM. With the other apps, we are working on bringing that to those apps as well. Pretty quickly, I see a question about Workfront that it’s not available today, but hopefully soon we will have the product support agent available on Workfront as well. Right now, the case creation and case tracking elements are available in CDP, AJO, and AEM. That’s what we have. And then if we move to the next slide, very quickly about the roadmap. What is available today is, again, quick troubleshooting. So getting responses based on documentation that’s rooted in troubleshooting patterns from the past. We have support case creation and support case tracking like you saw. And then we also have multimodal content. So that’s where you start seeing videos or images when applicable in your responses. What’s cool is those videos are also queued to the right place, which is relevant to your response. So if you hit play on it, you can go exactly to the point that that pertains to your response. So this is all available today. What’s coming next? The first piece is context sharing and collaboration. This is not available today, but this is what I spoke about where a practitioner can share context from their debugging and their troubleshooting to a support administrator from within the chat interface. So that’s something that we are really excited to bring to life and hopefully soon can talk about in more detail. But this is something that’s on our roadmap. We also have interactive diagnostics, which is going beyond the documentation that we have today to be able to provide responses and troubleshooting plans based off of runbooks that we have internally. And so the idea is that we are able to do guided multi-step troubleshooting for more complex issues that go beyond what is provided in the documentation already. So that’s interactive diagnostics. We also have special events calendar where we hope to provide a workflow where you can set up specific automations or optimizations for your sandbox for peak events or special events such that everything runs smoothly when you need it to. And then finally, we are also going to be introducing proactive monitoring and alerting where we monitor your scheduled jobs or the workflows in your sandbox automatically and alert you when things appear like they could go wrong. So before an issue occurs, we want to be able to identify any indicators that say that there is a guardrail violation, any anomaly or an error has been detected or a job is taking too long to run, things like that we would want to alert our users to. So that’s also something that we are working on bringing to life. So these items are part of our roadmap and then we just went over what is available today as well. So I’ll pause really quickly here to see if there’s any questions on the roadmap or anything that I haven’t answered already.

Shreya, when will we be able to get our new product support agent theme song to play in the interface when people are interacting? Because I think that will cheer them up so much as they open their tickets that they will look forward to creating tickets.

I’m adding a Jira right now to the team so that every time they interact with the opposite product agent, it’s like a theme song that plays in the background. Yeah, then everybody will want to be the admin user in their org. Well, Kusha commented about wanting to pass the info to the admin, which is that contact sharing and collaboration item on the roadmap. So Kusha is happy and also is wanting license usage alerts. Is that part of the proactive monitoring and alerting? Yes, it’s a whole system of alerting that we are looking into.

Hopefully we have more concrete timeline soon. We don’t have that right now, but that is absolutely something that we are looking into. You cannot set up license usage alerts using the agent today, but once we have that alerting, my hope is that you will be able to. Great.

Awesome. So those are all of the questions. Is there anything else that you wanted to share? Yes, Hong, I think you had something more to share.

Or was that it? No, I think that’s it. Yeah, the roadmap is where we’re hoping to close off, but I think we really appreciate all the questions coming in to share a little bit more on what’s available, but more importantly, where we’re taking products that are agent next, to different applications or with better and more useful feature to everyone involved.

Great. OK, well, I guess that brings us to the end of our show. But one of the things that we like to do before we wrap up is to have a little unrelated cool tip.

And this episode’s unrelated cool tip is brought to us by Shreya. Please enlighten us.

I think most people know this already, but in case you didn’t, whenever you’re cutting into lemons or lime, make sure you roll them a little bit on your countertop before you do so. That always gives you more juice, whether you’re trying to make lemonade or whether you’re trying to add salad. Just roll it on the countertop a little bit. You look professional, gives you more juice to lemonade.

And over your your skills of it. All right. Well, thank you so much, Hong and Shreya. And thanks to all of our audience members who joined us for this episode.

Take care. And let’s hear that theme music again.

Turn the volume up. Don’t touch that dial. Product support agent bout to rock your file. From the call to the case to the troubleshoot show. When the system goes down, that’s the pro. You know, I said P S A in effect. When your stack goes wild, better show respect. You got logs, timeouts, bugs on the screen. But PSA jumps in keeping systems clean. Hit the chat like, yo, I need support. Agent rolls in like the tech is caught. No panic, no stress. Just a step by step. Got the run book ready and the knowledge print from a M nodes to a funky old cue. PSA breaks it down like here’s what we do. Check one, check two, configuration type in a minute. Flab. Everything’s all right. PSA in the house today. Solving big time issues in an old school way from the bug to the fix from the log to the patch.