One Engine, Every Experience | Revenue Keynote, Dreamforce 2026

Please welcome EVP and GM Revenue Cloud, Salesforce, Meredith Schmidt. Woo! Wow, this is pretty incredible. Welcome and good afternoon. So many familiar faces in the audience, and how awesome to see so many new ones as well. And if you were here last year, what do you think about this room? We got quite the upgrade. Because honestly, we've had a phenomenal year, and it's because of all of you, our customers and our partners. Thank you, thank you, thank you. And what happened since the last 12 months? We have increased the number of customers that we have on Revenue Cloud by over 300%. That's not all. Look at the incredible scale we're getting with all of you. In the last 12 months alone, you have created over 80 million quotes going through our system. Also pretty incredible. One of the things we are absolutely the most proud of that happened in the last 12 months was being named a leader in the Magic Quadrant by Gartner for our very first evaluation ever. We've been listening to you. We've been listening to all of our customers and all of our partners.

There we go.

Now, don't look at these small little words. They're really too hard to see. What's important here is the top left. In the last 12 months, we've delivered over 150 features requested by you, our customers and our partners. Keep bringing us those insights. Keep bringing us that feedback. We're listening and we wanna hear it, so keep going. While we've been doing all this and building all this stuff, the world has continued to get more complex all around us, and it's multiplying. Last year, we were talking about delivering a single catalog through every channel, direct, partner, self-service. Now we have models to deliver And all of these flexible business models, and by the way, just so you know, you all define consumption a little bit differently. So thank you for the challenge on having to build it for all of you. And now you're talking about outcomes, and how are we going to sell outcome-based pricing? And you guys are moving faster than ever. I can't tell you how many of you as customers are A/B testing new pricing models. Launching new promos. It is pretty exciting. And I think you're going to guess what's coming next, because what's the biggest change we saw in the last 12 months? Of course, AI redefining everything that is possible at work, how we build and implement our products, how we work and where we work. And I would absolutely argue that the number one process that is ready for an agentic transformation is the revenue process. You all in finance, IT, you have spent years building processes, building policies, controls, and guess what? We do a lot of high-volume repeatable processes, and you know what that does? It creates a ton of data, and guess what AI needs? AI needs data, right? It needs data with trusted context to reason with. But guess what AI also needs? It needs guardrails. It needs revenue rules. It needs product rules, pricing rules, approval rules, right? Because the revenue process itself is deterministic and compliant by design, right? And for this, what do you need? You need an infrastructure, right? You cannot have probably right revenue. I think every one of you would agree to this, right?

Yeah.

And models alone, LLMs and models, they cannot run revenue, right? They can reason and they can tell you what is probably right. That's not good enough for revenue.

Right?

You need deterministic systems. You need to know what's true and what's accurate and what can be guaranteed. And for this, you need a trusted foundation. And this is what Revenue Cloud is to you. Revenue Cloud is your revenue infrastructure for the agentic enterprise. It is a single platform standardizing everything from product to cash, right? It's a single source of truth for all of your revenue data.

How do you—

to help you grow your revenue, reduce your costs, and scale your business. And Revenue Cloud was actually built headless first. And headless doesn't mean there's no interface, right? There's no experience. Headless just means we're unlocking the revenue processes so you can meet your customers where they are, whether they're in Claude, Slackbot, Agentforce, Coworker, right? That headless means you can have the exact same experience no matter where you are. And here's the most important part of why Revenue Cloud being built headless matters the most, right? We gave you APIs. The APIs that make us headless contain the business logic to run revenue. And a lot of, a lot of what we see sometimes is you've put the business logic in the UI. The models don't know how to read the logic that you've put into a workflow on the UI. They need the APIs, and we have delivered to you the APIs to make sure that Every action that's taken is accurate, no matter where you are, and no matter what service you're working in. And this is what's really exciting. I am so excited for what you're going to see today. We've got a great show for you. You're going to see demos, demos of things that I only wished and dreamed that I could do when I was running revenue operations for Salesforce. And we're going to have 3 chapters today. The foundation, the workflows, and the surfaces, and how AI is changing everything around how we implement and set up Revenue Cloud. But before we start, I am so excited to talk about why Workday chose Salesforce as their revenue infrastructure. And for that, I'm so excited to welcome my friend Ronnie Johnson to the stage, CIO, Workday.

Woo!

Thank you so much, Thank you so much, Ronni.

So for those of you who don't know, we have been partners, our companies, for years. We are both customers of each other and just have a great working relationship. The minute I met Ronni, I think the first time when she told me she was going to do this and do it in a speed that I never thought was possible, I was like, okay, let's go. And she's going to talk a little bit about that today. But let's start at the beginning of this journey. You know, Workday was seeing explosive growth, and with that came the complexity. What was the point at which you said, I need to look at a revenue infrastructure, and you look at how— what am I going to do here?

You called it. Because of our growth, we had just outpaced our architecture. Y'all, our Salesforce environment was the original environment that our founders, Dave Duffield and Aneel Bishri, stood up 20 years ago. We actually could see the code that they'd committed. And unfortunately, we did what we now tell our customers not to do. We'd over-customized that environment. That customization was actually yielding some pretty unfortunate results. The customizations had started to fossilize that environment into some pretty significant technical debt. Now, my team briefed me on the numbers, so hopefully I make y'all proud. We had 36 million characters of custom Apex code. We had run out of available fields for standard objects.

Mm-hmm.

We had more profiles than we had employees.

That's my favorite one.

We'd essentially designed our system to really support exceptions and not standard quoting practices. And we looked up and made the realization you cannot run an AI-first business on some Y2K-era processes. And so we needed to change our infrastructure. And so we of the commitments that we made, we drew a line in the sand. We said we have to modernize our CPQ practices, and we decided to go Salesforce native. We built from the ground up. So, this is a full reimplementation of Salesforce with RevCloud, and we call it Agentic CPQ. And we're really excited. It was an important, important unlock for us.

Thank you, and thank you for trusting and choosing us. One of my favorite parts of your journey, and I think we've heard a lot about this throughout the last 1.5 days, is how AI is changing how we implement product. Just hearing your journey, I think you were ahead of the curve on this one. Maybe tell us a little bit how you used AI actually in the implementation journey for Revenue Cloud.

So first, I have to get a shout out to my friends at Accenture. They were a huge, huge partner and a component of our success. So our transformation was really, really fast, as you mentioned. We did this work in 7 months. Generally, a transformation like this takes something on the order of a year to 18 months. And so this is a reimplementation of Salesforce with RevCloud and Agentforce. And one of the 2 key unlocks for us— first, my team's going to laugh at me— we went AI AF throughout the SDLC. And for those of y'all with dirty minds, that's AI as a first principle throughout our software development lifecycle. And so that was really important through every stage from even our resource planning to our designs. We were even using transcripts to, to take customer or, or customer business customer meetings and turn them into requirements. We took those requirements and turned them into test cases. We took those test cases and automated them and then autonomized that in our CI/CD lifecycle. No AI was left behind. We took every single opportunity Wow. to deploy AI in our, in our CI/CD. SDLC. The other thing that I think was the really big unlock for us too was the selection or the choice of RevCloud. The fact that we weren't bolting on third parties and having to do the integrations and worrying about performance. We had a single platform, Salesforce native, that allowed us to truly streamline and simplify our architecture. And it really made it where we could deliver capabilities much faster and deliver value faster back to our business stakeholders.

Also incredible. We should, like, I think we could do a whole podcast just on this. But maybe—

AI AF.

AI AF, yeah, AI AF.

I love it.

Maybe I'll get one last question in if I can. So the business outcomes, you're live, you've been live for a few months. Tell us about the business outcomes that you've seen and the ROI that's come from going onto the revenue platform.

So 3 stand out for me. So our seller experience, the very first thing is our sellers now can quote. They were going through a deal desk to do that quoting before. And so sellers now can quote, and those quotes are agent-guided. The second thing is our sellers now can actually build those quotes and actually manage the product catalog in a single view. Before, it was a lot of dropdowns. So that for us has manifested in 40%, um, faster quote creation. I'm getting that right, right? Okay. 40% faster quote creation and 60% fewer clicks. And we did a sentiment survey, and our sellers, basically, the number one thing they've said is, they said it in 2 words, night and day in the experience. The other big thing was our deal desk. Our deal desk was a huge bottleneck before. Our deal desk is made up of our finance, our legal, and our RevOps teams. Every one of our deals was going through that deal desk. And now going forward, only approvals, all of our approvals are automated, and the deal desk is only engaged when you actually need human intervention and human judgment to make those calls. And the third thing, and what I'm probably the most proud of, is the work we're getting in operational efficiency. Because our data is clean, our reporting is accurate. Frankly, our close is faster. And more importantly for me, we have standard— our standard systems have made it where we have better compliance. And so we're really excited about that. And now our maintenance has turned into true engineering. We'll be able to reuse those developers to actually deliver value. So thank you for the opportunity. This has been amazing.

Thank you so much, Ronnie. So for our first chapter, Welcome to the stage, Sam Chung, Chief Customer Officer for RevenueCloud.

Thank you, Meredith. Ronnie, what a great story. Thank you for being such an incredible customer, and thank you for sharing your incredible story with all of us. You know, Meredith talked about the explosion in complexity in go-to-market operations, but the reality is, is that most of our companies are still using a patchwork of disconnected systems, fragile integrations, and data that is too difficult to use. And we call this the messy middle between CRM and ERP. And when companies use a messy middle strategy for their revenue and cash flow processes, really bad things happen. Your data lineage breaks, which increases the risk of compliance and errors. Your IT organization has to create unnecessary points of integration, and your business functions have to create an increasing number of internal controls and manage those internal controls, as part of their SOX environment. This is a terrible outcome, and now AI is about to expose all the cracks in your processes that your people have been quietly filling. If you want to scale AI, you have to fix the underlying foundation first, and that is what Revenue Cloud does. Revenue Cloud standardizes your revenue and cash flow processes onto a single unified platform that unlocks growth today and sets the foundation for AI tomorrow. One set of data, one data model, one work— set of workflows, one system of control, all with shared business context. That is pretty amazing. And it gives your AI the grounding it needs to understand your business and the guardrails it needs to be able to act reliably. This is what you need to run your organization. This is not an extension of CRM. This isn't an add-on or managed package to CRM. This is core to CRM. It is the foundation of your revenue and cash flow strategy. And companies that are already using this strategy are seeing amazing results. They're lowering their IT costs, they're increasing seller productivity, and they're getting to revenue faster because they're being able to introduce products faster than they ever could before. And as Meredith said, We're really excited about our innovation journey. With our winter release, which is coming out in October, we're excited to really be able to support evenly increasing amounts of pricing schemas with promotions now being generally available. We're supporting even more complex deal structures with enhancements to our deal ramp deal structure. And I'm really excited about our investments in performance and scale. We are going to be able to support quote lines with quotes with up to 15,000 quote lines and tens of thousands of attributes on those quote lines. So, you are all going to take advantage of all this amazing innovation. We're really excited about this. But enough talking about the product, let's see it in action. And to do that, let me bring to the stage Vance and Emily, my brother and sister from another mother, to walk through a couple of demos for all of you. And so we're going to start here in Product Catalog. This is what you sell and how you sell it. Now, product launches typically start like this. They start in Slack, because Slack is where your teams collaborate on all of the requirements to define and configure your products. Your titles, your descriptions, your pricing, your configuration rules. That's what happens. I'm going to show you with agent technology and Slackbot a brand-new way to launch products in Salesforce. Now, normally, we would take this PDF document, we would then convert it into a project plan or to a spreadsheet, and then someone in product operations would have to manually go into Salesforce. They'd click through product setup, and this would take a long time. But what if we could simply ask Slackbot to take this document, And convert it automatically into products in Salesforce. And so Vance is going to show us how to do that in a second. And if we switch over to Lightning, you could see these products have now been set up. This saves your product operations teams weeks, if not months of time, and gets your products into the hands of your customers and your sellers faster than ever before. So that's pretty cool, right? But the number one thing that all of you have talked to me about is you are really focused on increasing seller productivity and effectiveness. So let's switch personas to be a seller. Now, we all know the most complicated transactions are actually renewals because a renewal transaction requires your AE to really deeply understand the full history of your company's relationship with that customer in order to secure that renewal. Now, if I was a seller back before the age of AI, what I would do is I would go into Salesforce, I'd maybe look at a list view of opportunities and begin starting to work. But now AI is part of how I work. And so instead, I'm going to go to Coworker, and I'm going to ask a simple prompt. And the prompt is going to be, tell me about the renewal transactions that matter the most to me. And what Coworker is doing is it's combing the entire database of CRM, and it's exposing insights to me that I probably wouldn't have been able to have gotten on my own. And look here, it's already identified a number of renewals for me to focus on. And if I go to the top one, the top one is actually Blackstone. And the reason why coworkers signaled this as the number one priority for me is because in a recent call with a customer and a CSM, Momentum flagged that there is a risk. Looks like the customer is actually evaluating a competitive product to a product they're using from us. So again, normally I would not have gotten this. I would not have seen this. But because of the power of AI, these signals are now brought to me. And so now I can take action. So now let's go into our renewals dashboard. And this is the one place where I'm going to manage this renewal transaction from beginning to end. And as we scroll down, you can see I already have a renewal quote set up. Now, this renewal quote is essentially an extension of what the customer already has and just extending the term. But there's also an AI-generated renewal quote. So let's dig into what is different about this renewal quote. So if we scroll up to the top and you go to Einstein Insights, oh, there's 3 things here that the renewal quote has that is very interesting. First, because Revenue Cloud is tied to my usage management database, I actually know that the customer's usage of our API product is running ahead of schedule. So what Coworker did is it added another tier of commitment automatically onto my quote, and it also recommended another tier of discounting to really address the concern that I have that my customer is going to evaluate a competitive product. Secondly, because Revenue Cloud is part of CRM, it knows that this customer also has logged a fair amount of cases with our customer support team. And so it recommended a premier support offering called Signature Success and also added that to my quote. And oh, by the way, that product is on promotion, and that promotion was automatically applied to my renewal quote. And lastly, because this is a unified revenue platform, the agent also looked at the MSA that we have with our customer, And the customer had negotiated a price protection clause in their MSA that limits their price uplift at 5%, even though the company's standard policy is 8%, and automatically adjusted my price uplift accordingly. Now, if I didn't have the power of AI with me, this would've taken me as a seller days, if not weeks of time, maybe a frantic phone call to someone in operations. and hoped and prayed that I actually had a valid quote ready to go to a customer. But with this technology, I can be very confident that this is a valid quote, that it complies with all of the commitments I've made to my customer, and that it puts the customer at the center of everything I'm doing and hopefully secures this renewal. So I'm really excited about this AI-generated quote. I'm going to send this off to my customer. And what do you know? Customer signed. So I'm really happy. I get to go to club this year. Good for me. You know, all my work is done, right? Not so fast. The work isn't done when the quote is created or even when the customer signs. This is where dynamic revenue orchestration comes into play. It provides all the coordination you need to ensure all of your backend processes happen— your provisioning, your service entitlements, and your invoicing. It is essentially the full audit trail You need to make sure that your customers get what they paid for, that you get to recognize revenue accurately, and that you get to get paid for this deal when it comes down to invoicing. And of course, it's all about that cash. So with robust billing functionality embedded natively into Revenue Cloud, you can ensure that not only are your AEs going to be paid for this transaction, but your company will as well to manage your cash flow and your operations. So, really incredible work. But invoicing has never been more complicated than it is right now. So, if we can go back to the slides. This is why we're so incredibly excited about our recent acquisition of Meter, because event consumption and usage models are becoming increasingly more important for all of you. So, to talk a little bit more about that, I'm excited to bring to the Dreamforce stage my friend Griffin Perry, co-founder and CEO of Meter, to talk more about this. Riven, to you.

Thank you very much, Sam. For decades, software companies have sold principally based on access. They package up capabilities and sell access to those via subscriptions, and the unit of value is typically a seat. But the world of software is changing, and there's a move towards selling based on consumption. Now, in this world, the price you pay isn't known in advance. Instead, it needs to be worked out afterwards depending on what you've used, or what outcomes you've derived. It's the natural model for AI and also for API businesses and infrastructure businesses, but we're seeing its reach extend far beyond those, not least because customers really like the tighter connection between price and value. Now, designing this pricing isn't easy, which this slide speaks to. Firstly, you need to choose your pricing metric, the new unit of value. And you've got a broad range of choice with the right answer generally being quite specific to your company or your product. And then you face some complicated choices about wrapping pricing constructs around those to make adoption easy, reward higher levels of consumption, getting the right balance between flexibility and predictability. So things like pay-as-you-go, tiers, credits, et cetera. All this is difficult, and that's why it's a good time to be a pricing strategist. But it's not the only thing that's difficult. Pricing is 50% design, but the other 50% is operations, and the operations side of the house is complicated too. Now, why is that? Because the invoice is no longer a lookup where you check what the customer has already committed to pay. Instead, it becomes a calculation where, in the simplest terms, you need to count things, apply pricing to them, and that determines the accurate charge. And that changes the way your revenue infrastructure needs to work. You need to track usage variables, you need to bring them together with pricing, you need to perform a calculation, and you need to deliver that to downstream systems. Now today, many companies stitch this process together. They use data warehouses, custom code, SQL, and spreadsheets, and sometimes it's enough. It's enough if your pricing is simple, if it's simple P times simple Q performed once a month at invoice time. But in the wild, it's rarely that simple. Firstly, the pricing is more complex, and that makes the calculation more complex. You need to take into account things like a mix of fixed and variable elements, if this then that dependencies. You need to think about minimum spend commitments, and billing hierarchies, so the calculation is more complex. You also have higher event volumes. You need to track not thousands of things per month, but often millions or billions or sometimes much more. And thirdly, the frequency of bill calculation is much higher. It's rarely good to— good enough to calculate bills just once per month at invoice time. You need to calculate them every day or every hour or even every minute or every second. And why is that? Because in a consumption world, your customer and multiple roles in your company need up-to-date running total of bills at any time. All this is why the impact of Meta on Revenue Cloud will be so significant. We're extending our revenue structure to offer native support for the most complex consumption pricing models, and that'll allow you our customers to monetize complex consumption at scale. How are we doing that? Well, firstly, it's by introducing something new. So that— and that is complex usage metering, mediation, and aggregation, something that you currently have to build yourself or source from elsewhere. And it's also about extending and enhancing existing capabilities about supporting the complex pricing and billing logic associated with consumption models. Overall, the impact is going to be bulletproof revenue infrastructure, for the era of consumption. Deeply composable, deeply integrated with the existing product suite. We're hard at work, and we're looking forward to shipping in the first half of next year. And with that, let's transition to the next chapter about revenue workflows on any surface. Take it away, David Beebe.

Sounds good. Sounds good. Griffin, thank you for that. Excited for you to be part of Salesforce and looking forward to our future. Citizens of the Revenue Cloud Nation, here we are. Look at this room. This is unbelievable. So, a couple— earlier this year, our co-founder Parker Harris said something very provocative. Why would you ever log into Salesforce again? And then just yesterday, our other co-founder, more commonly known as CEO Marc Benioff, said we are in the middle of an interface revolution, and I agree completely. You see, folks, your sales reps have already left the chat. They're already utilizing other UIs. They're utilizing Claude, they're utilizing Slack, ChatGPT, Gemini, and of course, the beloved spreadsheets. And the issue that this creates is those spreadsheets remove them, make things invisible. It makes things invisible like what pricing they're working on, It makes things invisible like the teams that need to support them, and it circumvents every guardrail that you have created for your business. The problem this creates: phantom pricing, inaccurate orders, and inaccurate invoices, one by one, one spreadsheet at a time. And we're not just talking about customer satisfaction issues here, we are talking about true compliance risk And revenue leakage. Now, standalone AI, it makes it worse because standalone AI is confident and it will give you answers, and those confident answers are wrong. Why? Because all your standalone AI understands is what the sales rep has told it. And I don't know about you, do you know a lot of sales reps that say, hey, build me a quote. By the way, here are my guardrails, and please use them as you build my quote. I haven't met— well, the folks here at Salesforce do. I haven't met them otherwise, though, right? So what happens when you're using standalone AI? It doesn't understand your commercial context. It doesn't understand that last week, the customer you're speaking with renewed, they upgraded their products, and we need to treat them different than we treat a new customer. And what happens when you need to take action? You need to use your revenue process. You need to enforce your policies and your guardrails. How do we take the conversation that we're having with our customer and move it into enterprise-grade action?

Simple.

We'll just put it on the surfaces where your sales reps are already working or where they want to work. What we've done is we have decomposed Revenue Cloud to make it the headless revenue interface, the headless revenue infrastructure powering the surfaces like Claude, Slack, and my favorite coworker, Coworker is sweet, by the way. You should be using it to help them build their deals, to model their pricing, to make sure that all of the guardrails are adopted, that they are utilized. Your sales reps get the experience they want, and your business gets the rules that you have to have through your business context. Now, I am excited to announce that in October, we will be bringing Revenue Cloud Tools and Skills Library to the Salesforce MCP. Secure instant connectivity to Revenue Cloud. Now, your MCP tools are your actions, right? It's what your sales rep is doing— creating quotes, putting together pricing, initiating renewals. And your skills library, that is what's grounded in your data, your metadata, and your user permissions. It's what ensures that as your sales user is going through and typing out exactly what they want, The skills are those context-based workflows to ensure that they are tying to the rules and the structures and the governance that you have put forward. Team, January will be 10 years for me at Salesforce, and I have never been more excited about the innovation that we've been rolling out as I am about this. So, one of the things that's interesting about clickers is that sometimes they work, So one of the things you heard Meredith say earlier, you can't have probably right revenue. It's gotta be accurate every single time. Well, frontier AI models are amazing at probabilistic reasoning. They understand intent, they infer, they imply. The issue with that is it needs to be tied to an execution layer. That's what your headless revenue infrastructure through Revenue Cloud provides. It provides the deterministic execution layer. And when you pair those 2 together, probabilistic reasoning with deterministic execution, that's when it all comes together. Let me give you an example, an illustration. I'm a sales rep, and I want to offer a 30% discount to my customer. So I type in, give me a 30% discount. The deterministic execution is going to come back and say, Hey, buddy, your max is 10%. You cannot do that, but I'll give you 3 options. This is the probabilistic reasoning. I'll give you 3 options: cap it at 10, update the quantities to get a volume discount, or I'll route you through approvals. What do you think? Probabilistic reasoning, deterministic execution through your headless revenue infrastructure. At the end of the day, your AI suggests and your revenue infrastructure decides. But enough of that. Who actually wants to see this in action? So in order to show it, I invite my friend, good friend, to the stage, Rahi Tharam, Senior Director of Product Management.

Thank you, David. Today, I'm going to be playing the role of a sales rep. I recently had a call with Bob at ACME, just finished a Zoom call, and he said he was ready to purchase. But, you know, I did not capture all the call details. Who did? Momentum did that. Momentum has the ability to convert customer conversations into call notes that can be easily referenced and addressed by an agent. So here I am in Claude, and I simply prompt, create quotes based on my Momentum call notes with Bob at Acme. That's it. Notice I did not provide any product details, pricing details, discount details, or even the agreements that I have in place with Acme. All I mentioned was simply refer the call notes. Behind the scenes, Claude is grounded in the trusted context that resides in Revenue Cloud. It goes ahead, understands the call transcripts, knows the products that were discussed in the call, has an understanding of the pricing, and above all, it has the commercial understanding of the agreements that I have in place with Acme. With that, my permissions, Claude comes back with 2 quotes that match my customer's needs. One is a 3-year RAM deal quote, and the other is a 4-year RAM deal quote, both with different pricing options and different user counts as requested by the customer. Claude is simply not just taking orders. It's in fact acting like my partner. In this case, it's acting like a deal strategist. It's giving me various recommendations based on the pricing and the uses as asked by the customer. Additionally, what Claude also does here is that it's grounded in the knowledge that it has behind the scenes. So it makes sure that every deal that it makes is compliant, it's accurate, and more importantly, it's well within the guardrails that's put up by my customer, ensuring that there is no violation of any agreements. Additionally, I also have a visualizer here. This visualizer enables the buyer and the seller to understand the quotes and the various proposals that we have in place so the buyer and seller can understand trade-offs between the two. Now let's push this a little further. I'm gonna go ahead and ask Claude to bump the discount percent from 15% to 20%. This is where Claude goes ahead and takes this request from the user of updating my discount from 15 to 20 for a particular year, in this case, the year 4 or in quote number 2. Claude has the full context of what I can or cannot do in this case. It needs to make sure that anything that I do is very well within the reasons or the permissions that I have as a user. There is no boundaries that Claude can overtake or go over with. So it needs to ensure that if I am a sales rep, There is a certain boundary behind which I can go ahead and exceed the discounts or not. As you can see, Claude does not blindly take orders. Why? Because Revenue Cloud's rules engine steps in. 20% exceeds my delegated authority, so I cannot apply on that. Claude reasons, gives me what the next best action is, and best yet, it also has some recommendations that I can take. How cool is that? What we just saw here is sales rep can easily and comfortably quote in Claude, but have all the rules and guardrails defined in Salesforce, therefore making sure that every deal is compliant and accurate. Now, as a sales rep, I really like working in Claude, but we all know work happens in Slack. So let's get into Slack and look at another deal that I've been working on. Deals are not simply won by a single conversation that you have with your customer. Deals are won when multiple players are working together. There is the My Business Manager, the Deal Desk team, all the various solution engineers, all of us put together for a deal to be successful. Now, with Slackbot in channels, it's again not acting like a personal AI assistant. It's actually acting like a deal teammate. So here I am in the Infinitech channel, And I've been recently conversing with my SE. Couple of days ago, we did a demo to a customer. Once again, I wasn't paying attention, so I really don't know what went through the deal. So who comes to rescue? Slackbot comes to rescue. I simply asked Slackbot to go ahead and look at the context of the conversation and create certain proposals for me. In addition to that, I also asked Slackbot to give me a deal point of view. This is where, again, Slack's not simply just doing admin work. It has the context of the entire conversation. It makes sure that every deal that I create is actually compliant, and it's meeting my customer's need. I want to partner more with Slack, so I'm going to go ahead and tell me, ask it to go ahead and give me a little more insight with what the way I have structured my deal, and what's the point of view. Slackbot, knowing what's going behind the scenes, is able to analyze the deal, understand how the request has come in from the customer, and is able to come back with a deal strategy with respect to how this deal is structured. Watch what happened. The way I have my deal structured is not optimal. It actually comes back and tells me that I'm not meeting my company's goals. In addition to that, it also gives me recommendation of how better I can do. Guys, this is powerful. This is simply not just optimizing for deal velocity. This is optimizing for revenue. And with that, I like the way Slackbot comes back with this. So now I want to go ahead and create pricing proposals and send it out to my customers so they can go ahead and start making decisions. Gone are the days where I had to copy and paste and take all of these pricing proposals, put it into a spreadsheet, and send it across. Now, with Slackbot Slack Surfaces feature here, I can now create a fully branded suggestion or a fully branded presentation that I would like to go ahead and give it to the customer so they can start seeing it. With respect to this fully branded proposal that we put up together, customer now has insights as to how they can make decisions with respect to the proposals they have in hand. This enables them to view them, make meaningful judgments, and further go ahead and carry out decision-making. How awesome and amazing was that to see an entire deal being transferred, proposals being created, and send it over? With that, what we just saw here was sales rep and the entire AI acceleration for the sales processes. Next, to see how AI can accelerate the whole admin and setup, I'd like to call upon Annie Wright, Annie, take it away.

Thank you, Aitha. So when I first started on the Revenue Cloud team about 10 years ago, one of the first people I met was one of our best SEs. His name was Bundles. Well, I come to find out about 6 months later, the Bundles name actually wasn't Bundles. It was the nickname that his team gave him because he was really good at building out product bundles and for demos super fast. And at the time, it pretty much made him a legend because everyone knew just how long and, and really how many clicks it took to set up the product. But now today with AI and agents, those days are over. We are really in a whole new world. And with our new Revenue Cloud Skills Library, we are making every agent a revenue expert. A Revenue Cloud expert who knows how to set up the product, So think of these skills as prepackaged instructions. They're playbooks that give the agents the step-by-step guide that they need to do the work.

And they—

to do the work. And so I'm going to show you what this looks like in action. And I'm going to start with something that all of you are probably very familiar with, a spreadsheet full of SKUs. And typically with a spreadsheet full of SKUs, to get it into products that your team can sell, you need to configure those product bundles one by one. But now I'm going to have an agent do that for me. I'm going to start here in Cursor with my agent, drop that spreadsheet in, and give it the simple prompt to use this file to build out a new— the new product SKUs. And of course, I'm going to ask to sign off before I put it into production. Now, the agent's going to ask me a few clarifying questions and then get to work. Now, behind the scenes, the agent is going to be referencing those skills. It's going to be using all of the expertise, the workflow, and the logic provided by the skills so that it can get the job done. And all the complexity around things like bundle structures or selling models, I don't need to worry about that. The agent is taking care of that for me. So we're gonna fast forward about 20 minutes and we'll see that our spreadsheet full of SKUs are now products in the product catalog. And these aren't just simple products. These are products that are configured with product attributes. so that you no longer need to create a unique product record for every single version of the same product that you sell. This becomes easier for your admins to administer and easier for your sales team to navigate. Now, we know we've always been strong with our customers meeting the complexity in what they sell and how they need to sell it. But admittedly, it's required too many clicks for our admins to make new rules, to update rules, to make changes to the product. But now we truly are in a whole new world with agents and AI. And the skills library isn't just limited to setting up the product catalog. This is a comprehensive skills library for the entire Revenue Cloud product. You can access it today. We have the QR code right there on the screen. So anyone want to pick your phone up and grab a— Grab a shot of that. And we're so excited because we're not just launching the Skills Library. In October, we are also delivering our Revenue Cloud Accelerators. And these are our most popular and proven workflows from thousands of customers that we've packaged up as ready-to-go automations available to you all through Salesforce Go. And finally, the last thing I'm so excited I get to be the one to share it today. I know many of you have been waiting for it. We, in December, we are launching our new Migration Assistant. I was hoping for a clap with that one. This is to help all of you move from the Salesforce CPQ managed package to the new Revenue Cloud, and not just migrate your data, this is migrating your full configuration. So, we're super excited to be delivering this to all of our customers and also to our partners, many of them who have been pushing the boundaries with AI for for years now. And we've got one of those partners here today. We've got JM Tremblay from The Cloud Update. Join us here on stage. So you might recognize JM from his YouTube channel, where he has done everything from some of the first Revenue Cloud and Agentforce videos to fantastic release videos that you do, that you do every release. JM, thank you so much for being here today.

Thanks, Annie.

I'd love for you to share with everyone what inspires your YouTube channel and essentially for you to— become a content creator for RevenueCloud?

Absolutely. I'd been meaning to start creating content for the old Manage Package CPQ for a long time, and when RevenueCloud, or Revenue Lifecycle Management back then, was announced, it felt like a great opportunity to take the space that was available to give more content and more opportunities to the people that wanted to learn how to get on board with Revenue Lifecycle Management. It was also a great way for me to learn the tool as I was going in there and just doing deep dives to learn and be able to share that knowledge.

Amazing. Well, and we— I mean, I said it a second ago, you really created some of the first Agentforce and Revenue Cloud videos. That is how we met. I literally cold-called you after seeing your videos on LinkedIn, and I'm like, I need to talk to this guy. What inspired you to go down and do that early experimentation with Agentforce and Revenue Cloud?

I mean, for— and David, you know, made a reference to our sales rep work earlier, and we know that sales reps, getting them in there, getting them in Salesforce, doing their quotes and not just working outside is hard. So Agentforce felt like a great opportunity to give them a better UI, a better UX, to actually get their work done, make their lives easier, right? There's a lot of repetitive tasks, and that allowed us to meet them where they were, right? And we're extending that today, right, as we're seeing. And also everything and how the product is built, how Revenue Cloud is built, being headless and API-first, just opened a lot of doors that weren't available before.

Amazing. Well, before I let you go, I've got one last question. Last question. What would you say is a common myth or misconception about Revenue Cloud that you can kind of be a mythbuster here today for everyone?

Yeah, a lot of people I hear and a lot of customers or, you know, people on the internet like to say that quote-to-cash projects are hard, long, and that's the main myth that I'm trying to remove out there. We're working across projects faster than ever before. We're adding new tooling now today, right? And we've built our own tooling. We've migrated customers from CPQ to RC in 8 weeks. We're working with another customer that's going to be implementing Revenue Cloud in 4 weeks only. So it doesn't have to be hard. It can be easy. The tooling allows us to go faster than ever before.

That's amazing. Well, thank you so much for being here, and let's give a round of applause for JM.

One—

actually, one more thing before you go. We've got Meredith up here to present you.

Guess what? You are officially the first ever Revenue Cloud Golden Hoodie winner. Congratulations. Thank you so much. Thank you.

Yes.

Thank you. Thank you, both of you. We're taking a picture here. We're just a celebration. We had a great idea to play Golden from K-pop Demon Hunters. They wouldn't let us. There's copyright errors. But thank you, and it was so exciting. So you can learn more. This is the same QR code. This will be available. It's really cool. I've already passed it out to a lot of people. Get hands-on with Revenue Cloud. There's lots of opportunity the rest of this week. We have more sessions to come. And just to close it off, this has just been incredible. Thank you all for joining, and have a great— best rest of Dreamforce. Thank you.