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The Shift from Single-Player to Multiplayer AI Collaboration
Recent advancements have fundamentally changed how artificial intelligence is integrated into workplace operations. Notably, the era where AI served primarily as an individual productivity tool—dependent on copying, pasting, and siloed workflows—is fading. The workplace is entering an era where AI operates as an orchestrator of team-based collaboration, directly embedded in the platforms where work happens. This transition is especially vivid within communication hubs being transformed into the center of "agentic" and "headless" AI collaboration, moving away from isolated interactions toward contextual, conversational teamwork 00:16.
AI Integration in Collaboration Platforms
In the latest developments, collaborative platforms have become the connective tissue for organizations harnessing multiple AI and business systems. The conversation identified the exponential rise in deployment of intelligence tools—each promising improved productivity. However, despite massive investments, many organizations have not realized tangible returns in output, employee effectiveness, or financial metrics such as margins and revenue 04:22. The missing link: AI's presence where collaborative work occurs, not on individual desktops or isolated apps.
One concept discussed was the idea that true productivity gains happen only when AI meets human collaboration head-on. The best ideas develop through conversation, iteration, and debate in open channels—not in inboxes or isolated workflows 04:56. Embedding AI into the core of collaborative platforms bridges the gap between available intelligence and organizational output.
Slackbot and the Agentic, Context-Aware AI Assistant
A key theme that emerged was the impact of AI-powered assistants embedded in team collaboration platforms. Modern AI assistants are not generic chatbots; instead, they understand organizational context both at the individual and team level. These assistants can access all enterprise systems permitted to the user, know the user’s team, goals, and ongoing projects, and can converse conversationally to retrieve or update information across dozens of applications without additional training or onboarding 07:02.
Several points were raised, including:
The fastest adoption rate ever seen for an internal feature, driven not by generalized AI capacity, but by seamless access that "just works"—requiring no new workflow or learning curve.
Advanced contextual awareness: AI assistants recognize team structures, surface struggles or progress in specific projects, and anticipate action items based on organizational documents and historical communication—all without explicit prompts 10:13.
The ability to act (“read” and “write”) across systems of record—such as CRM, email, and other business tools—directly within the conversational interface 07:21.
Unlocking Organizational Memory and First-Party Reasoning
The discussion explored the value of unstructured data native to collaboration platforms. Years of public and private channel conversations, project threads, and shared documents represent the most valuable contextual data for AI relevance, previously inaccessible for practical daily use 09:08. Now, AI assistants can mine this organizational memory, providing instant insights (like identifying team bottlenecks, surfacing achievement against stated goals, or recommending high-priority focus areas)—all tied to real, ongoing conversational data 10:23.
This level of organizational reasoning transcends mere data connectivity. It utilizes "first-party reasoning data," making sense not just of transactions but of the nuanced patterns in how teams make decisions and execute strategies. This bridges the gap between AI potential and real-world business value, as systems can now observe and reason across the very conversations where work transpires 08:23.
Headless AI: Data Accessibility Across the Business Stack
One concept discussed was the democratization of access to critical business platforms. Traditionally, only a subset of employees accessed core systems like CRM. Now, integrated AI assistants allow anyone to retrieve or update information from across the business stack—CRM, customer records, service histories, unstructured conversation data—within a single conversational workflow 20:03.
This "headless" approach extends AI’s reach: permissions and data access remain secure, yet valuable insights and task execution are no longer reserved for platform power users. This significantly broadens the organizational value of existing business data and removes barriers to adoption for non-technical staff.
"Building in the Open" and the Rise of Organization-Wide Builders
The shift toward agentic, multiplayer AI also changes the internal cadence of how companies build, ship, and refine both product and operations. The discussion examined practical methods such as "building in the open"—working in public channels, sharing work in progress, and exposing feedback loops company-wide 13:09.
Several points were raised, including:
Collaboration platforms now serve as the operating system for how leading companies design, iterate, and learn—including native AI leaders in the market 13:27.
Everyone in the company, from marketing to engineering to HR, has the tools and visibility to become a builder. AI assistants and integrations mean that iteration and decision-making compounding happens organically, accelerating speed-to-market for new ideas 14:15.
Rethinking Employee Productivity and Orchestration
A key theme that emerged was how organizations calculate and act on productivity gains. The day-to-day friction—context switching between a dozen enterprise applications, fragmented information, and the so-called "work of work"—represents a drain equivalent to 30-60% of the entire organization’s capital outlay on human resources 26:05. Integrating AI assistants in collaboration platforms offers a pragmatic, immediate increase in actionable productivity without overwhelming employees with yet another system to learn.
True value materializes not by adding more AI, but by connecting and orchestrating existing intelligence where collaboration and decision-making are already happening. Open channels and AI orchestration create shared learning and compounding improvements, so each insight benefits the entire team, not just the individual 17:19.
The Specific Next Steps for Forward-Looking Organizations
The discussion provided concrete examples from leading organizations already moving most operational work and collaboration into these AI-empowered platforms. Some enterprises have set targets such as spending 80% of internal, non-client-facing work time within the collaboration tool, making it a hub that brings together all enterprise systems 27:39.
The most valuable takeaway: now is the time to reevaluate how organizations structure collaboration, share learning, and turn every employee into a potential builder and orchestrator of work. Organizations can achieve three- or fourfold productivity gains, create faster compounding learning, and connect the dots between intelligence and business outcomes simply by putting collaboration at the center of their AI strategy—not sprinkled around it 28:23.
Adoption of this multiplayer, context-aware, and conversational approach is rapidly coupling productivity with business intelligence. It is delivering measurable results for organizations committed to embedding AI at the heart—not at the periphery—of their workflows.
Topics Covered in This Episode:
- Shift from Single-Player to Multiplayer AI Collaboration
- Slackbot as AI Personal Assistant Overview
- Integrating AI Agents Across Enterprise Systems in Slack
- Unlocking Organizational Knowledge from Slack Conversations
- Building and Iterating in the Open with Slack
- Slackbot’s Role in Headless, Agentic Workflows
- Enhancing Productivity with Slackbot’s Contextual Actions
- Transitioning Business Strategy for Multiplayer Agentic Orchestration
Episode Transcript
Jordan Wilson [00:00:16]:
I think the pre 2026 AI story was single player, whether you were an individual, small business owner, or part of a large enterprise. I think the 2022 to 2025 strategy for AI was unfortunately a lot of copying and pasting and working in silos, but that's changed. Right? We are in 2026 where everything is agentic first and headless and also multiplayer. So that's what we're gonna be tackling on today's show. Not just that shift of AI going multiplayer, but specifically, how everyone's favorite communication tool, Slack, is actually bringing that all together. So I'm excited for today's conversation. Hope you are too. Welcome to Everyday AI.
Jordan Wilson [00:01:06]:
My name is Jordan Olson. If you're new here, we do this every day. This is your unedited, unscripted, livestream podcast, and free business, free newsletter helping everyday business leaders like you would be not just keep up with what's happening in AI because it does. It stopped. But I tell you what matters, what doesn't. You take that information to grow your company and your career. So if that's what you're trying to do, it starts here. But make sure you go to our website at youreverydayai..com.
Jordan Wilson [00:01:30]:
We're gonna be recapping the highlights from today's podcast, and it's gonna be a good one. We have a great guest and all the other AI news that you need to know to stay ahead and be the smartest person in AI in your company. Sounds like a good deal. Right? Alright. But we have a treat for everyone today. It's not just gonna be me yapping. We get to steal some of the secrets from someone building the tools we all get to use. Alright.
Jordan Wilson [00:01:55]:
So I'm excited to bring on to today's show, livestream audience. If you could, help me welcome to the show. Let's bring them on there. Ryan Gavin, the chief marketing officer at Slack. Ryan, thank you so much for joining the Everyday AI Show.
Ryan Gavin [00:02:10]:
Jordan, thanks so much for having me. It's great to be here.
Jordan Wilson [00:02:12]:
Alright. So, tell everyone a little bit what is your role at Slack. Right? Everyone knows Slack. Everyone knows CMO. But, like, what does that actually look like? Because you guys are shipping so many things, especially on the AI and agentic side.
Ryan Gavin [00:02:25]:
Yeah. I appreciate it. I like to describe myself as middle management overhead. That's really what I am. But I I I do get the privilege of looking after the Slack business and the marketing side. I have I also get to look after small, medium business here at Salesforce, as well as, like, with something we call a digital growth systems team. But, you know, at Slack, it's really about how do we take and transform, organizations and kinda get them ready for this moment. It sounds cliche, but everyone is racing as hard as they can, and many are struggling with what's going on with just the pace of change, the innovation, you know, the the AI and agent buzzword drinking game continues, and, like, everyone's trying to figure out how they navigate it.
Ryan Gavin [00:03:04]:
And and Slack's become an incredibly important tool, for many organizations to do just that. So that's where I'm spending a lot of my time in this instance.
Jordan Wilson [00:03:11]:
Yeah. Walk us through, you know, I kind of, previewed it, but it seems like, you know, so much of AI strategy, you know, especially in the earlier years of the online chatbot, was really just about how individuals can bring, you know, their best together, and then somehow you have to duct tape it altogether. You know, first of all, tell us, like, what the heck is Slackbot for those of our, you know, audience who haven't used it or maybe they haven't heard. And then what's Slackbot doing to try to turn the player from a single player game into a multiplayer agentic collaboration?
Ryan Gavin [00:03:49]:
Yeah. So so there's there's a bunch there that's important to to unpack. So I think, you know, first and foremost, I'll I'll kinda let me touch on the multiplayer piece, and then I'll kind of I'll get into Slackbot a little bit. You know, there's this interesting thing that's been happening that we've all experienced, like the this explosion of intelligence tools that are now at our fingertips. All of us have had our check to GB moments, had our cloud coworker and cloud code moments, and just, like, been blown away what these things can go do. And, you know, organizations and enterprises are sprinting, in some cases, spending unbelievably amounts of money to deploy these tools. But what's not happening is we're not seeing this throughput to employee productivity and the return of that investment in terms of the outputs of the business, you know, customer success, better revenue, you know, improve margins. Like, those those in those impacts of, like, employee productivity aren't translating through the system.
Ryan Gavin [00:04:40]:
So there's, like, this, like, dissonance right now of, like, unbelievable great intelligence, but yet it's not showing up on one of the company's most important resources, which is their people and the productivity of their people. And the reason for that is because work has always been a multiplayer sport. Like, work happens in the conversation. You know? A good idea is not nearly good enough in terms of till it gets matured and maturated and debated and and then built and built and and built in the open in the collaboration, those ideas don't come to fruition. And so work has always been in the conversation. And so what needs to happen is all this unbelievable intelligence needs to come to the humans, and it needs to come where the humans are working and collaborating, and it needs to come in a way that feels unbelievably accessible. And so what Slack is really having this incredible moment right now is, you know, it's always been for many companies this beloved collaboration tool, but it's rapidly turning into this critical component to company's AI stack. You know, we like to say it's it's the 2% of your AI spend that unlocks the value from the other 98 because it's bringing AI into your movements, and it's allowing your teams to to work and collaborate together.
Ryan Gavin [00:05:45]:
And then, you know, to do that really successfully, you're gonna have all these incredible applications inside of Slack, whether they be from Salesforce or from third parties like Box or Atlassian, OpenAI, Perplexity, Linear, the list goes on and on. It's an open platform. But, you know, how does an employee navigate all that? You know? How does an employee go through and get the value from all these enterprise systems, get the value from all that conversation, get the value from all these agents? You know? In in the fullness of time, which may be, like, six months, who knows, most companies are gonna have more agents than they're gonna have employees. But the problem is how do employees know what all those agents do? Like, how do they know what their skills? How do they know where to find them? And, like, in some cases, we're making the same problem that we've had in the past worse by just spreading all this stuff to, you know, another system, another tab, another place to go to, another agent to go learn, another skill to go develop. And there's some poor employees just sitting in the middle of this thing, like, I don't know. I've got all this intel. I don't know how to use all this stuff. So this is where Slackbot comes in.
Ryan Gavin [00:06:45]:
So Slackbot is this unbelievably powerful tool inside of Salesforce, that we built at Slack. It is the fastest growing feature in Salesforce history by far, and it's because it's an AI personal assistant for me that knows me and knows my team and knows my context. It has access to the permissions that I have inside of Slack, and it has and it's connected to all my enterprise systems. So it's trusted from day one, and I don't have to learn a thing. I just ask Slack, and Slackbot can go and query all those systems, whether it be an inbox, whether it be 15 different agents, whether it be, my CRM. And it can not only read those things. It can write to those things. And I can just have a conversation, and I can get work done across two dozen systems without ever knowing those systems exist in the back end.
Ryan Gavin [00:07:32]:
It's unbelievably transformative for how how we work. It's unbelievably transformative for employees because now all this intelligence is actually accessible because we gave this simple delightful personal assistant called Slackbot that allows you to get access
Jordan Wilson [00:07:45]:
to it.
Ryan Gavin [00:07:45]:
That was a bit of a long winded answer, but
Jordan Wilson [00:07:47]:
No. Yeah. A lot a lot to unpack there, but I think Ryan brought up, like, a really important point. Right? When you talked about, you know, not only does it bring in all of these enterprise systems, right, with your standard AI, you know, chat bots, they do that as well. But you said something important there I wanna unpack. You said it knows me and it knows my team. Right? And I think that our our long time listeners here will know I have this this weird thing when, you know, I talk about the models themselves going from, you know, these these transformer next token predictors to models that can reason and go over logic. Can I talk about this thing called first party reasoning data? Right? Because everyone can, you know, hook up your your Salesforce and your email and all these other things, but it's how your team works.
Jordan Wilson [00:08:34]:
It's how they make decisions and, you know, come to think of it, it's like, wait so much of that just literally lives and it breathes inside of Slack. So walk me through, kind of the the the reasoning or the rationale and how those Slack conversations that sometimes people think are just, you know, noise that actually might be the goal that's hiding beneath the surface.
Ryan Gavin [00:08:55]:
It's it's massively the goal. In the AI world, unstructured data is the is the context that fuels relevance for any AI system. And the most valuable unstructured data by far is the richness of years and years and years of organizational context. And one of the reasons why Slack is such a powerful tool is because it's open architecture. It allows for these public channels, these private channels where people are working and building in the open. They're not locked behind an inbox. They're not locked behind a, you know, a simple chat message. You have organizational context in the open that's living and breathing that honestly has always been valuable.
Ryan Gavin [00:09:37]:
But, you know, once it kinda happened, it's largely been inaccessible because, you know, are you really gonna go back in time to a message or a thread from three years ago? But now it is access excessive. And now it's there. And so, you know, I'll I'll just give you an example of, you know, I have hundreds and hundreds and hundreds of channels that I I'm an included in Slack. Do I read all of them? Heck no. Do I monitor all of them? Heck no. But what I can do is I can have a Slackbot skill that I have run every morning, and it says, you know, Slackbot, go through and look at all the areas that my team are working on right now. I want you to give me a prioritized list for areas they may be struggling or need my help or maybe stuck. I want you to give me an update of where you see my team making great progress on our stated goals.
Ryan Gavin [00:10:23]:
And then please help me understand what are the areas that I should probably have as my top focus areas for today and for this week based on what you're seeing. Now simple prompt, but imagine, like, what would be required to get those answers, like, pre Slackbot. I'd have to go maybe call a staff meeting. I might have to make, you know, a dozen different Slack messages or heaven forbid an email, dear lord. Hope not. You know, I might have to call a meeting and get everyone in a room and kinda, alright. What's you working on? Whatever. But the reality is Slack is looking at all these channels that I'm not looking at.
Ryan Gavin [00:10:55]:
It's looking at all these conversations today, tomorrow, and the past, etcetera. And it's able to know when I say my team, it doesn't say who's your team. It knows my team because it knows me. It knows the people I'm working with. It knows what I'm talking. When I say my goals, it doesn't say, okay. Great. Tell me your goals.
Ryan Gavin [00:11:10]:
It knows my goals because those are published in a document that I put in Slack, that it's accessible via Google Drive, and it can read those and that and ration over those. And when I say look at all the full actions, it can look into the systems of, like, my calendar. It can look into the systems of record like Salesforce, and then it can pull all that. And so I get one simple prompt. I get this unbelievably rich answer back that gives me insights of, like, hey. Your team has been over here debating this topic. They could really use your help, and you have no clue that's even going on. This thing's coming up, and you really need to spend some time on it.
Ryan Gavin [00:11:43]:
And here are the five areas that your team's made some incredible progress on your goals. And it's like, boom. In, like, two minutes, I'm, like, the best equipped manager I've ever been, all because I've got Slack bot that's working on my half across all these systems all in a conversational problem. It's crazy. And it it that's like a a very simple use case, of of how these things show up and why the the power of conversation and connecting, you know, the structured data and unstructured data becomes unbelievably powerful in this.
Jordan Wilson [00:12:13]:
Yeah. You kind of gave that example, right, of of having these hundreds of channels and even channels that you, like, once you cannot go in and monitor hundreds of channels. Right? So I think that that's a great use case. But maybe can you walk me back a little bit? You know, maybe when you were, you know, testing out Slackbot internally before it was released to the public. Did you have, like, one of those moments where you were like, wait. This is gonna change how we do multiplayer work. And if so, you know, what can our listeners learn from maybe that example of, you know, dog fooding this internally?
Ryan Gavin [00:12:51]:
Sure. Yeah. I mean, one of the one of the things we we talk about a lot, and we see it and do it inside of Slack, but it's also a pattern that plays out at all native AI companies right now. And I think very quickly, every leading company is gonna wanna follow suit, which is what I call building in the open. You know, if you look at, like, the origin stories of ChatGPT, if you look at the origin stories of computer from perplexity, Anthropic, Claude, and the the, you know, announcement from a couple weeks ago with Tag and Claude, all those in Slack bots, but all those are byproducts of building in the open. You're in Slack. You're working on this project. You're iterating with a group of people who are writing code, developing, building new pull requests.
Ryan Gavin [00:13:35]:
They're going through they're they're they're saying this is working. This isn't working. I'm trying this, etcetera. And you iterate, you iterate, you iterate, and you go through and you collectively go and build this thing at unbelievable speed. That's how we built Slackbot. You know, Slackbot started as a small team that was working on something. There's a channel. Everyone's in there.
Ryan Gavin [00:13:55]:
We're testing it out, etcetera. We have a thing called Slackbot unbaked, which is like the you know, where the team's like, hey. I just built this feature. Everyone go try it out, and we all bang on it and say, this is working. This is great. This is amazing. This totally didn't work. And it's unbelievable the collaborative power when you build in the open and the speed that happens there.
Ryan Gavin [00:14:15]:
And something super powerful is happening right now, which is it used to be that building was the domain of product and engineering, but now builders are everybody in your company. And everybody at your company now needs a platform to build in the open. If you're in marketing, you need to build in the open. If you're in finance, if you're in HR, everyone's a builder, and you have these incredibly powerful tools, not just Slackbot, but tools from Vercel, tools from Anthropic, tools from OpenAI, Linear, Chris. All these tools are deployed in Slack because that's where the humans are working. That's where the collaboration's coming together. And then you can use these tools to go and build and create incredible stuff. And so that that kind of moment for us, when I saw the pace and the power of building in the open, how quickly we could iterate by doing that, and then I you know, we're seeing that play out through all of these unbelievable, AI companies out there.
Ryan Gavin [00:15:08]:
You know, it dawned on me. It was like, this is how everyone's gonna be working in the future. We're just a little bit ahead of the curve, but everyone's a builder and everyone needs a building path.
Jordan Wilson [00:15:16]:
Yeah. Ryan, that's that's a great point. And I think it was Zapier, you know, last week, the CEO there who was talking about that exact same thing. Right? Building in public and and maybe doing less in DMs. Right? For the reason that you can share, more of that decision making with your team and make AI more, you know, multiplayer. So, you know, I'm wondering, you know, with the, advent of Slackbot and you shared, you know, some of those obvious wins, does it change how you communicate whether for the better or worse, you know, knowing that essentially what you're putting into Slack is probably gonna help you and your teammates in, you know, three months or three years? How does that change even how you use Slack or how you communicate something?
Ryan Gavin [00:16:07]:
Yeah. You know, I'll and just building on your opening point, you know, there's, I'm gonna I'm not gonna get it perfectly right, but the the Shopify CEO, Toby, he made it they built in this credible agent called River, and they deployed it. And they said it's only allowed to be deployed to channels in Slack. And the reason why and I'm not gonna get his quote exactly right, but he basically said, hey. If you're not, like, using AI and building and learning in the open, like, you're you're fundamentally in this kind of closed loop system where, like, an individual is working and getting better, maybe they're getting pro productive, but the larger team, the larger group, the larger system, that learning is not compounding. And so, like, you have to be in the open. And that's why, you know, I I think companies that still run out of the inbox are gonna be in trouble in this in this era because we do need to go to move at the speed that the market demands right now. Learning has to compound and has to compound quickly.
Ryan Gavin [00:17:00]:
And so that's why, you know, having, you know, a tool like Slack where, like, you are working in channels, and you are doing that in the open. It it's really simple things. Of course, there's always a time and a place for an individual message or something that's more private. And, like, you know, of course, we have all the affordances for that inside of Slack with private messages and private channels, etcetera. But the simple truth is when I have a question for an individual, there are nine times out of 10, there are eight other people on the team that are gonna benefit from seeing that back and forth and learning from that. And when, you know, someone gives a piece of product feedback on a a feature and there's a response vibe, The whole team being able to see and understand that benefits. So, you know, this this idea of learning and building in the open and allowing your AI to see and learn from that means the AI becomes exponentially more valuable. It becomes trusted because I know it knows me.
Ryan Gavin [00:17:55]:
And it when it talks and it's giving data, I know it's coming from, and it's I can see the sources in Slack. So, you know, that is why, you know, things like Slack bottom in like this incredibly fast adopt feature because it it creates that trust where you're not coming into this with, like, oh, what do I share? What do I not share? Like, it's this is my Slack, and it's it's in my permission base. It's in my I trust everything in there. And then I know the AI is permissioned against that. And so I can just operate as I would like a trusted teammate. And that's how it feels. It feels like I have a trusted teammate, who I, you know, trust just as much as I would any other team.
Jordan Wilson [00:18:29]:
Yeah. And, you know, we've been talking a lot so far working inside Slack, which I think is super valuable because so many teams, you know, run their day to day inside of Slack. But there's been a recent shift, which you alluded to with, you know, things like Claude Tag, right, which integrates with Slack, you know, model context protocol, you know, recent Slack MCP. And, you know, the Slack's parent company Salesforce has been a leader in one of the first big SaaS companies to say, hey. We're gonna really focus on Advilus, in the future. So can you explain kind of this shift from maybe, you know, quote, unquote, pushing people to go into Slack and use Slack versus should we be just using the data from Slack in these other platforms? How do you begin to unpack that in kind of this more recent shift toward just working head sleep?
Ryan Gavin [00:19:27]:
Yeah. So it's a great question. The you know, let's just start with Salesforce and and and, the announcement that we made last week, which was, you know, anything Salesforce can do, you can now do through Slackbot. So it's the simplest. So we Slackbot's an MCP client. It connects to our Sales Force MCP servers, and so so Slackbot cannot just read, but it can write and can take actions and go, and and work directly with your CRM, which is unbelievably powerful. And I'll we'll start with kind of a just a simple frame. If you back up and you say, wow, many companies use Salesforce, sales, service, marketing.
Ryan Gavin [00:20:03]:
But the reality is even as successful as Salesforce, I mean, only a small percentage of the employees actually ever see Salesforce. Right? And the sellers see it. The service team may see it. Maybe the managers see it. If you're on the marketing side and using marketing, they'll see it. But, like, the product engineering teams don't you know, my marketing teams don't see Sales Cloud. They they don't they don't use that system. It's, but it's unbelievably important system.
Ryan Gavin [00:20:25]:
It's like the customer record. It's the source of truth. It's it's where you're seeing what's going on with your customer service issues. Like, this is unbelievably valuable data, but it's not really accessible to most employees. So what happens when you can take a tool like Slackbot and you can safely, in a permission way, have that connected up to the Salesforce data? Well, it turns out that data becomes infinitely more valuable. That resource, that system of record becomes infinitely more usable because now and whether in marketing, you may never have seen Salesforce. You may not even know what it looks like. But now I can ask a simple question of, like, hey.
Ryan Gavin [00:20:59]:
I'm prepping for this IBM meeting. What's been going on with the IBM account? What's the latest issues? Are they having any service issues right now? Tell me about the last five meetings we've had with them. What went well? What didn't go well? And what do you think are the things that they're gonna be most, excited to hear about from? Now Slackbot can go talk to the service, you know, our agent for service, cloud. It can go talk to our agent for sales cloud. It can go look into the IBM account channel. Again, that's in my open and go and see all the discourse of how the team's been working through it and bring me back this incredibly rich answer and insights. And not only that, I can then take action based on that. I can say, oh, that opportunity record, I actually just met with them.
Ryan Gavin [00:21:38]:
The opportunity is actually 250,000. It's not 200,000. Update that opportunity. And I can just do this by talking to Slackbot. And, you know, I'll just I'll give you I was reading a stat, just last week. This kinda blew me away. There was 1,800,000 Slackbot messages that were sent, inside of sales by Salesforce employees, just last week. 750,000 of those were talking to and writing to Salesforce.
Ryan Gavin [00:22:04]:
So, like, think about that, like, in terms of and and these these Scibot will tell you, hey. It's clearing Salesforce, but these people didn't have to say go talk to Salesforce or go talk to agent for sales. They just said, what's going on with this account? Or I wanna go in this opportunity. So this headless strategy is, like, the exponential unlock for the value of your CRM data. And when you can bring it into the conversational interface of Slack, when you can bring it into where the humans are working, and when you can make it super accessible with a tool like Slackbot that, you know, to to cite a design principle that we have at Slack, so, you know, you know, we think we say all the time, like, when we build software, we don't want you to have to think. Like, don't make me think. It should just work. And when you can couple those things, it's a really, really powerful moment.
Ryan Gavin [00:22:50]:
And, of course, it extends to our entire ecosystem. So you're talking about Anthropic. You know, Slack's an open platform. So whether you're Box, Atlassian, whether you're Vercel or Linear, All these organizations are building their AI into Slack, because that open ecosystem, we know the enterprise doesn't stop at just Salesforce. It's got Microsoft. It's got Google. You've got all these other enterprise systems. You've got your own custom applications.
Ryan Gavin [00:23:14]:
All those need to be working and connected in. And the power of those systems becomes exponential when it's easy to access with this conversation.
Jordan Wilson [00:23:23]:
So, you know, obviously, as builders of the technology, you know, I I assume that many within the Slack organization have been working with an agentic first mindset for quite a while. But for the rest of our audience, you know, for our maybe nontechnical business leaders who, you know, their organizations run inside of Slack, how should they be changing their mindset right now? Right? Like, how does someone become an orchestrator of work, you know, versus just a doer of task? And, you know, how does that change with things like Slackbot or the, you know, Slack MCP?
Ryan Gavin [00:24:01]:
Yeah. I mean, there's a couple fundamental trends. Like, one, you know, we do need to kind of recognize that, this agent and agent capabilities are are kind of reaching this, like, explosion inside the enterprise. And you have to empower your teams and your individuals to be able to manage that DIN. And and I say DIN not to diminish these tools or the value of them. They're incredible. But, you know, at the at the end of the day, there's still an employee who's trying to get their job done, and we're asking them to leverage and take advantage of these tools and technologies, but it's overwhelming in some cases. In some cases, they're training.
Ryan Gavin [00:24:41]:
So the first thing you need to do is you realize you've got to have a platform that you can go through and have a deployment place for all this in technology and intelligence that your employees can use and understand and makes it accessible. So you need to have those agents connected into something like Slack. It's actually the only platform right now that allows you to do this at scale. And then allow your humans to be able to work with those agents via a simple interface like Slackbot. So to your point, we can get to the place where everyone can start to feel like a builder. So, you know, I have more agents available to me inside of Salesforce and Slack than I even know about. But when I, you know, think about getting a task done, I'm deploying probably four or five different agents in any given Slack bot query that I don't even know about. And that that allows me to just work without friction, and it allows me to to tap a lot of these capabilities, without, you know, under underlying kind of the, you know, patterns and practices of the sins of enterprise software, which has been, you know, we have a thousand enterprise applications inside of our enterprise.
Ryan Gavin [00:25:44]:
I'm switching between 10 to 12 of them every single day, and I'm wasting 40 to 50% of my day in, like, the work of work. And I think that's the the real thing. The the the piece that many people aren't talking about right now is, you know, go back to something I started with. Employee productivity, like, sounds kind of like buzzword nonsense, and sometimes it's like, oh, yeah. What what does it really mean? Like, most companies spend most of their money on their people. Like, 30 to 60% of companies spend that, you know, their capital on people. And if you can make your people, like, three to four x more productive and get the work of work off their plate, that's like a 100% revenue growth. There's not a lot of 100% revenue growth ideas just floating around the boardroom.
Ryan Gavin [00:26:24]:
And so this is a moment where everyone kinda needs to reevaluate how your how your company works. And that's why I made the comment earlier about the inbox. The inbox is death for this. Like, if you if your employees are spending a good percentage of their work time in the inbox, you're in trouble. You've got to you've got to shift that because you you will not be able to keep
Jordan Wilson [00:26:43]:
Yeah. That's that's a great, call out there. But, you know, Ryan, we've talked about a a lot on today's episode, you know, from what's new in Slackbot, headless revolution to changing your mindset and the value of those back and forth conversations. But, you know, what's the one most important thing business leaders can do today as they're grappling with maybe transitioning, you know, their AI strategy from being a collection of individual AI contributors to that true multiplayer agentic orchestration, what's the one most important move they can make?
Ryan Gavin [00:27:23]:
Well, you know, I don't know if I can always sum it down to one, but if you're a company like Box, Box is saying, hey, our sales team, out of their working time, their non selling time, they're gonna spend 80% of it all in Slack. And those the Slack is going to be the connective tissue between all the enterprise systems that they have, including Salesforce. You know, if your engine who gets, like, 800,000 customer inquiries, they're saying the way we're gonna manage the the the the the scale of our business and having one connected truth is by bringing it all into a connected system like Slack. So the the the one thing I would encourage is, like, you have to really take a a cue from how, you know, a perplexity or an OpenAI or anthropic, how they build. There's a reason why those companies say Slack is their work operating system. You know, anthropic said Slack is our work operating system. There's a reason why they say that. They run the company from this tool.
Ryan Gavin [00:28:23]:
And, you know, the one thing I would encourage everyone to do is, like, this is a moment to reevaluate how your organization works and how you build and how you enable everyone to become a builder. And it's not about one tool or one AI. It's about all the tools and all the AI and be able to unleash those in in a way that is sensible and manageable for your employees. And that's kind of why Slack and Slackbot are kind of having this incredible moment right now. It's almost a it's a renaissance in many ways because we're seeing this explosion of AI coming into Slack. We're seeing explosion of AI utilization in Slack because of Slack bots making it simple and approachable. So it's time to rethink work is the short answer.
Jordan Wilson [00:29:03]:
I love that. And what a great way to add. Rethink work, it's what we're doing every single day. And, hey, at least for today, Ryan, you helped us, give us the the the good insights on how to do that. So, thank you so much for taking time out of your day to join the show, Ryan. Appreciate it.
Ryan Gavin [00:29:19]:
Jordan, I really appreciate you, and, I hope it was helpful. Look forward to chatting again soon.
Jordan Wilson [00:29:23]:
Alright. And, hey, if you missed anything, don't worry. We're gonna be recapping all those golden nuggets Ryan just dropped in today's newsletter. So if you haven't already, please make sure you go to youreverydayai.com. Sign up for the free day free free daily newsletter. Thanks for tuning in. Hope to see you back tomorrow and everyday for more everyday AI. Thanks, y'all.