Podcasts about HubSpot

It was a wild week in artificial intelligence. Joe and Robert break down a surprising stumble from OpenAI and the aggressive counter-moves coming from Anthropic. The hosts unpack what these developments signal for the broader AI landscape and why the growing concentration of power among a small number of platforms should concern marketers and creators alike. If a handful of companies ultimately control how AI works and how it distributes information, that likely tells us exactly where marketing is headed as well. Along the way, Joe and Robert offer a few friendly suggestions to Sam Altman on how he might rethink his public communication strategy during moments of controversy and rapid change. Next, the show shifts to a supposed social media "problem" involving the CEO of McDonald's on Instagram. Except… it wasn't really a problem at all. Joe and Robert argue the episode was actually a major brand win. The bigger lesson? Companies should stop hiding their quirky, weird, and interesting employees. Celebrating authentic personalities inside organizations may be one of the most underused marketing advantages available today. The conversation then moves into the exploding trend of 90-second serialized dramas dominating short-form video platforms. What started as a niche format is quickly becoming a global phenomenon, reshaping storytelling and opening the door to entirely new forms of brand entertainment. Winners and Losers Joe highlights the creative marketing moves coming from Staples and why the brand may be onto something smart in a crowded retail environment. Robert, meanwhile, calls out what he believes was a strategic misstep from global advertising giant WPP. Rants and Raves Joe raves about a growing opportunity inspired by a recent article in The Wall Street Journal on the rise of subscription mail products and why creators should pay close attention to physical experiences in a digital world. And in a rare twist, Robert offers praise for the research and insights coming from Gartner… something listeners may not have expected. As always, Joe and Robert break down what it all means for marketers trying to build sustainable media brands in a world increasingly shaped by platforms, AI, and shifting audience behavior. Subscribe and Follow: Follow Joe Pulizzi and Robert Rose on LinkedIn for insights, hot takes, and weekly updates from the world of content and marketing.  ------- This week's sponsor: Did you know that most businesses only use 20% of their data? That's like reading a book with most of the pages torn out. Point is, you miss a lot. Unless you use HubSpot. Their customer platform gives you access to the data you need to grow your business. The insights trapped in emails, call logs, and transcripts.  All that unstructured data that makes all the difference. Because when you know more, you grow more. Visit https://www.hubspot.com/ to hear how HubSpot can help you grow better. ------- Get all the show notes: https://www.thisoldmarketing.com/ Get Joe's new book, Burn the Playbook, at http://www.joepulizzi.com/books/burn-the-playbook/ Subscribe to Joe's Newsletter at https://www.joepulizzi.com/signup/. Get Robert Rose's new book, Valuable Friction, at https://robertrose.net/valuable-friction/  Subscribe to Robert's Newsletter at https://seventhbearlens.substack.com/ ------- This Old Marketing is part of the HubSpot Podcast Network: https://www.hubspot.com/podcastnetwork

B2B demand generation struggles with vanity metrics over pipeline results. Nick Zeckets, Chief Fire Starter at Smoke Signals AI, brings serial MarTech founder experience and AI-first HubSpot agency expertise to signal-based marketing. He explains how to redesign demand generation systems using AI agents and HubSpot workflows to capture buying signals that convert to measurable revenue. The discussion covers bootstrapping versus venture capital strategies for sustainable MarTech business growth.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Melissa Theiss, Head of People Ops at Kit, joined us on The Modern People Leader to break down how HR leaders can build real business acumen using practical frameworks like Track-Racehorse-Jockey, her PeopleOps maturity diagnostic, and a 90-in-90 listening tour. We also walked through how to turn employee feedback into an actionable backlog and use it to shape a people strategy that supports the business first while staying people-centric.----  Downloadable PDF with top takeaways: https://modernpeopleleader.kit.com/episode285Sponsor Links:

In this episode of Startup Hustle, Matt Watson interviews Mark Roberge, a former HubSpot executive and current venture capitalist, about his journey from engineering to sales and the importance of scaling startups. Mark discusses the genesis of HubSpot, the significance of sales in startups, and the concept of product-market fit. He emphasizes the need for customer research, avoiding false positives in feedback, and identifying the ideal customer profile. Mark also shares insights on scaling strategies, key metrics for success, and the science behind scaling businesses effectively.⏱️ Episode Breakdown00:00 The Genesis of HubSpot02:56 Transitioning from Engineering to Sales06:06 The Science of Scaling08:53 The Importance of Selling Early12:12 Understanding Customer Needs14:58 Avoiding False Positives in Feedback15:39 Design Partner Dilemma18:21 Target Audience Insights19:56 Ideal Customer Profile Framework23:00 The Science of Scaling25:05 Understanding Growth Investment30:55 Navigating Growth Challenges35:25 Final Thoughts on Scaling SuccessTAKEAWAYSSales is crucial for startup success.Understanding product-market fit is essential before scaling.Customer research should start at the ideation stage.Avoid false positives by validating customer interest.Identify your ideal customer profile to focus efforts.Scaling should be approached methodically and strategically.Establish leading indicators of customer retention.Sales methodologies must evolve as the company grows.Demand generation must align with growth aspirations.The science of scaling involves data-driven decision making.Links & ResourcesConnect with Mark Roberge on LinkedInWhat Smart CTOs Are Doing Differently With Offshore Teams in 2025Subscribe to the Global Talent SprintFull Scale – Build your dev team quickly and affordablyIf you're trying to get your team out of the basement and into real product ownership, this episode is your playbook. Stop being a ticket factory. Build teams that think, create, and lead.Follow the show, rate it, and send this to someone who's still trying to do “real Scrum.” They need it more than you do.

Signal-based demand generation requires tracking the right data points. Nick Zeckets, Chief Fire Starter at Smoke Signals AI, brings expertise from two MarTech exits and building AI-first HubSpot programs. He identifies SEC filings as the most valuable signal for enterprise sales, revealing executive discussions about business risks, projections, and budget allocations. Executive hiring patterns at VP-level and above indicate strategic shifts and fresh budget priorities, while M&A activity creates 18-36 months of organizational change and new problem sets.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

The reception to our recent post on Code Reviews has been strong. Catch up!Amid a maelstrom of discussion on whether or not AI is killing SaaS, one of the top publicly listed SaaS companies in the world has just reported record revenues, clearing well over $1.1B in ARR for the first time with a 28% margin. As we comment on the pod, Aaron Levie is the rare public company CEO equally at home in both worlds of Silicon Valley and Wall Street/Main Street, by day helping 70% of the Fortune 500 with their Enterprise Advanced Suite, and yet by night is often found in the basements of early startups and tweeting viral insights about the future of agents.Now that both Cursor, Cloudflare, Perplexity, Anthropic and more have made Filesystems and Sandboxes and various forms of “Just Give the Agent a Box” cool (not just cool; it is now one of the single hottest areas in AI infrastructure growing 100% MoM), we find it a delightfully appropriate time to do the episode with the OG CEO who has been giving humans and computers Boxes since he was a college dropout pitching VCs at a Michael Arrington house party.Enjoy our special pod, with fan favorite returning guest/guest cohost Jeff Huber!Note: We didn't directly discuss the AI vs SaaS debate - Aaron has done many, many, many other podcasts on that, and you should read his definitive essay on it. Most commentators do not understand SaaS businesses because they have never scaled one themselves, and deeply reflected on what the true value proposition of SaaS is.We also discuss Your Company is a Filesystem:We also shoutout CTO Ben Kus' and the AI team, who talked about the technical architecture and will return for AIE WF 2026.Full Video EpisodeTimestamps* 00:00 Adapting Work for Agents* 01:29 Why Every Agent Needs a Box* 04:38 Agent Governance and Identity* 11:28 Why Coding Agents Took Off First* 21:42 Context Engineering and Search Limits* 31:29 Inside Agent Evals* 33:23 Industries and Datasets* 35:22 Building the Agent Team* 38:50 Read Write Agent Workflows* 41:54 Docs Graphs and Founder Mode* 55:38 Token FOMO Culture* 56:31 Production Function Secrets* 01:01:08 Film Roots to Box* 01:03:38 AI Future of Movies* 01:06:47 Media DevRel and EngineeringTranscriptAdapting Work for AgentsAaron Levie: Like you don't write code, you talk to an agent and it goes and does it for you, and you may be at best review it. That's even probably like, like largely not even what you're doing. What's happening is we are changing our work to make the agents effective. In that model, the agent didn't really adapt to how we work.We basically adapted to how the agent works. All of the economy has to go through that exact same evolution. Right now, it's a huge asset and an advantage for the teams that do it early and that are kinda wired into doing this ‘cause you'll see compounding returns. But that's just gonna take a while for most companies to actually go and get this deployed.swyx: Welcome to the Lane Space Pod. We're back in the chroma studio with uh, chroma, CEO, Jeff Hoover. Welcome returning guest now guest host.Aaron Levie: It's a pleasure. Wow. How'd you get upgraded to, uh, to that?swyx: Because he's like the perfect guy to be guest those for you.Aaron Levie: That makes sense actually, for We love context. We, we both really love context le we really do.We really do.swyx: Uh, and we're here with, uh, Aaron Levy. Welcome.Aaron Levie: Thank you. Good to, uh, good to be [00:01:00] here.swyx: Uh, yeah. So we've all met offline and like chatted a little bit, but like, it's always nice to get these things in person and conversation. Yeah. You just started off with so much energy. You're, you're super excited about agents.I loveAaron Levie: agents.swyx: Yeah. Open claw. Just got by, got bought by OpenAI. No, not bought, but you know, you know what I mean?Aaron Levie: Some, some, you know, acquihire. Executiveswyx: hire.Aaron Levie: Executive hire. Okay. Executive hire. Say,swyx: hey, that's my term. Okay. Um, what are you pounding the table on on agents? You have so many insightful tweets.Why Every Agent Needs a BoxAaron Levie: Well, the thing that, that we get super excited by that I think is probably, you know, should be relatively obvious is we've, we've built a platform to help enterprises manage their files and their, their corporate files and the permissions of who has access to those files and the sharing collaboration of those files.All of those files contain really, really important information for the enterprise. It might have your contracts, it might have your research materials, it might have marketing information, it might have your memos. All that data obviously has, you know, predominantly been used by humans. [00:02:00] But there's been one really interesting problem, which is that, you know, humans only really work with their files during an active engagement with them, and they kind of go away and you don't really see them for a long time.And all of a sudden, uh, with the power of AI and AI agents, all of that data becomes extremely relevant as this ongoing source of, of answers to new questions of data that will transform into, into something else that, that produces value in your organization. It, it contains the answer to the new employee that's onboarding, that needs to ramp up on a project.Um, it contains the answer to the right thing to sell a customer when you're having a conversation to them, with them contains the roadmap information that's gonna produce the next feature. So all that data. That previously we've been just sort of storing and, and you know, occasionally forgetting about, ‘cause we're only working on the new active stuff.All of that information becomes valuable to the enterprise and it's gonna become extremely valuable to end users because now they can have agents go find what they're looking for and produce new, new [00:03:00] value and new data on that information. And it's gonna become incredibly valuable to agents because agents can roam around and do a bunch of work and they're gonna need access to that data as well.And um, and you know, sometimes that will be an agent that is sort of working on behalf of, of, of you and, and effectively as you as and, and they are kind of accessing all of the same information that you have access to and, and operating as you in the system. And then sometimes there's gonna be agents that are just.Effectively autonomous and kind of run on their own and, and you're gonna collaborate and work with them kind of like you did another person. Open Claw being the most recent and maybe first real sort of, you know, kind of, you know, up updating everybody's, you know, views of this landscape version of, of what that could look like, which is, okay, I have an agent.It's on its own system, it's on its own computer, it has access to its own tools. I probably don't give it access to my entire life. I probably communicate with it like I would an assistant or a colleague and then it, it sort of has this sandbox environment. So all of that has massive implications for a platform that manage that [00:04:00] enterprise data.We think it's gonna just transform how we work with all of the enterprise content that we work with, and we just have to make sure we're building the right platform to support that.swyx: The sort of shorthand I put it is as people build agents, everybody's just realizing that every agent needs a box. Yes.And it's nice to be called box and just give everyone a box.Aaron Levie: Hey, I if I, you know, if we can make that go viral, uh, like I, I think that that terminology, I, that's theswyx: tagline. Every agentAaron Levie: needs a box. Every agent needs a box. If we can make that the headline of this, I'm fine with this. And that's the billboard I wanna like Yeah, exactly.Every agent needs a box. Um, I like it. Can we ship this? Like,swyx: okay, let's do it. Yeah.Aaron Levie: Uh, my work here is done and I got the value I needed outta this podcast Drinks.swyx: Yeah.Agent Governance and IdentityAaron Levie: But, but, um, but, but, you know, so the thing that we, we kind of think about is, um, is, you know, whether you think the number 10 x or a hundred x or whatever the number is, we're gonna have some order of magnitude more agents than people.That's inevitable. It has to happen. So then the question is, what is the infrastructure that's needed to make all those agents effective in the enterprise? Make sure that they are well governed. Make sure they're only doing [00:05:00] safe things on your information. Make sure that they're not getting exposed. The data that they shouldn't have access to.There's gonna be just incredibly spectacularly crazy security incidents that will happen with agents because you'll prompt, inject an agent and sort of find your way through the CRM system and pull out data that you shouldn't have access to. Oh, weJeff Huber: have God,Aaron Levie: right? I mean, that's just gonna happen all over the place, right?So, so then the thing is, is how do you make sure you have the right security, the permissions, the access controls, the data governance. Um, we actually don't yet exactly know in many cases how we're gonna regulate some of these agents, right? If you think about an agent in financial services, does it have the exact same financial sort of, uh, requirements that a human did?Or is it, is the risk fully on the human that was interacting or created the agent? All open questions, but no matter what, there's gonna need to be a layer that manages the, the data they have access to, the workflows that they're involved in, pulling up data from multiple systems. This is the new infrastructure opportunity in the era of agents.swyx: You have a piece on agent identities, [00:06:00] which I think was today, um, which I think a lot of breaking news, the security, security people are talking about, right? Like you basically, I, I always think of this as like, well you need the human you and then there you need the agent. YouAaron Levie: Yes.swyx: And uh, well, I don't know if it's that simple, but is box going to have an opinion on that or you're just gonna be like, well we're just the sort of the, the source layer.Yeah. Let's Okta of zero handle that.Aaron Levie: I think we're gonna have an opinion and we will work with generally wherever the contours of the market end up. Um, and the reason that we're gonna have an opinion more than other topics probably is because one of the biggest use cases for why your agent might need it, an identity is for file system access.So thus we have to kind of think about this pretty deeply. And I think, uh, unless you're like in our world thinking about this particular problem all day long, it might be, you know, like, why is this such a big deal? And the reason why it's a really big deal is because sometimes sort of say, well just give the agent an, an account on the system and it just treats, treat it like every other type of user on the system.The [00:07:00] problem is, is that I as Aaron don't really have any responsibility over anybody else's box account in our organization. I can't see the box account of any other employee that I work with. I am not liable for anything that they do. And they have, I have, I have, you know, strict privacy requirements on everything that they're able to, you know, that, that, that they work on.Agents don't have that, you know, don't have those properties. The person who creates the agent probably is gonna, for the foreseeable future, take on a lot of the liability of what that agent does. That agent doesn't deserve any privacy because, because it's, you know, it can't fully be autonomously operated and it doesn't have any legal, you know, kind of, you know, responsibility.So thus you can't just be like, oh, well I'll just create a bunch of accounts and then I'll, I'll kind of work with that agent and I'll talk to it occasionally. Like you need oversight of that. And so then the question is, how do you have a world where the agent, sometimes you have oversight of, but what if that agent goes and works with other people?That person over there is collaborating with the agent on something you shouldn't have [00:08:00] access to what they're doing. So we have all of these new boundaries that we're gonna have to figure out of, of, you know, it's really, really easy. So far we've been in, in easy mode. We've hit the easy button with ai, which is the agent just is you.And when you're in quad code and you're in cursor, and you're in Codex, you're just, the agent is you. You're offing into your services. It can do everything you can do. That's the easy mode. The hard mode is agents are kind of running on their own. People check in with them occasionally, they're doing things autonomously.How do you give them access to resources in the enterprise and not dramatically increased the security risk and the risk that you might expose the wrong thing to somebody. These are all the new problems that we have to get solved. I like the identity layer and, and identity vendors as being a solution to that, but we'll, we'll need some opinions as well because so many of the use cases are these collaborative file system use cases, which is how do I give it an agent, a subset of my data?Give it its own workspace as well. ‘cause it's gonna need to store off its own information that would be relevant for it. And how do I have the right oversight into that? [00:09:00]Jeff Huber: One thing, which, um, I think is kind interesting, think about is that you know, how humans work, right? Like I may not also just like give you access to the whole file.I might like sit next to you and like scroll to this like one part of the file and just show you that like one part and like, you know,swyx: partial file access.Jeff Huber: I'm just saying I think like our, like RA does seem to be dead, right? Like you wanna say something is dead uhhuh probably RA is dead. And uh, like the auth story to me seems like incredibly unsolved and unaddressed by like the existing state of like AI vendors.ButAaron Levie: yeah, I think, um, we're, I mean you're taking obviously really to level limit that we probably need to solve for. Yeah. And we built an access control system that was, was kind of like, you know, its own little world for, for a long time. And um, and the idea was this, it's a many to many collaboration system where I can give you any part of the file system.And it's a waterfall model. So if I give you higher up in the, in the, in the system, you get everything below. And that, that kind of created immense flexibility because I can kind of point you to any layer in the, in the tree, but then you're gonna get access to everything kind of below it. And that [00:10:00] mostly is, is working in this, in this world.But you do have to manage this issue, which is how do I create an agent that has access to some of my stuff and somebody else's stuff as well. Mm-hmm. And which parts do I get to look at as the creator of the agent? And, and these are just brand new problems? Yeah. Crazy. And humans, when there was a human there that was really easy to do.Like, like if the three of us were all sharing, there'd be a Venn diagram where we'd have an overlapping set of things we've shared, but then we'd have our own ways that we shared with each other. In an agent world, somebody needs to take responsibility for what that agent has access to and what they're working on.These are like the, some of the most probably, you know, boring problems for 98% of people on, on the internet, but they will be the problems that are the difference between can you actually have autonomous agents in an enterprise contextswyx: Yeah.Aaron Levie: That are not leaking your data constantly.swyx: No. Like, I mean, you know, I run a very, very small company for my conference and like we already have data sensitivity issues.Yes. And some of my team members cannot see Yes. Uh, the others and like, I can't imagine what it's like to run a Fortune 500 and like, you have to [00:11:00] worry about this. I'm just kinda curious, like you, you talked to a lot like, like 70, 80% of your cus uh, of the Fortune 500, your customers.Aaron Levie: Yep. 67%. Just so we're being verySEswyx: precise.So Yeah. I'm notAaron Levie: Okay. Okay.swyx: Something I'm rounding up. Yes. Round up. I'm projecting to, forAaron Levie: the government.swyx: I'm projecting to the end of the year.Aaron Levie: Okay.swyx: There you go.Aaron Levie: You do make it sound like, like we, we, well we've gotta be on this. Like we're, we're taking way too long to get to 80%. Well,swyx: no, I mean, so like. How are they approaching it?Right? Because you're, you don't have a, you don't have a final answer yet.Why Coding Agents Took Off FirstAaron Levie: Well, okay, so, so this is actually, this is the stark reality that like, unfortunately is the kinda like pouring the water on the party a little bit.swyx: Yes.Aaron Levie: We all in Silicon Valley are like, have the absolute best conditions possible for AI ever.And I think we all saw the dke, you know, kind of Dario podcast and this idea of AI coding. Why is that taken off? And, and we're not yet fully seeing it everywhere else. Well, look, if you just like enumerated the list of properties that AI coding has and then compared it to other [00:12:00] knowledge work, let's just, let's just go through a few of them.Generally speaking, you bring on a new engineer, they have access to a large swath of the code base. Like, there's like very, like you, just, like new engineer comes on, they can just go and find the, the, the stuff that they, they need to work with. It's a fully text in text out. Medium. It's only, it's just gonna be text at the end of the day.So it's like really great from a, from just a, uh, you know, kinda what the agent can work with. Obviously the models are super trained on that dataset. The labs themselves have a really strong, kind of self-reinforcing positive flywheel of why they need to do, you know, agent coding deeply. So then you get just better tooling, better services.The actual developers of the AI are daily users of the, of the thing that they're we're working on versus like the, you know, probably there's only like seven Claude Cowork legal plugin users at Anthropic any given day, but there's like a couple thousand Claude code and you know, users every single day.So just like, think about which one are they getting more feedback on. All day long. So you just go through this list. You have a, you know, everybody who's a [00:13:00] developer by definition is technical so they can go install the latest thing. We're all generally online, or at least, you know, kinda the weird ones are, and we're all talking to each other, sharing best practices, like that's like already eight differences.Versus the rest of the economy. Every other part of the economy has like, like six to seven headwinds relative to that list. You go into a company, you're a banker in financial services, you have access to like a, a tiny little subset of the total data that's gonna be relevant to do your job. And you're have to start to go and talk to a bunch of people to get the right data to do your job because Sally didn't add you to that deal room, you know, folder.And that that, you know, the information is actually in a completely different organization that you now have to go in and, and sort of run into. And it's like you have this endless list of access controls and security. As, as you talked about, you have a medium, which is not, it's not just text, right? You have, you have a zoom call that, that you're getting all of the requirements from the customer.You have a lot of in-person conversations and you're doing in-person sales and like how do you ever [00:14:00] digitize all of that information? Um, you know, I think a lot of people got upset with this idea that the code base has all the context, um, that I don't know if you follow, you know, did you follow some of that conversation that that went viral?Is like, you know, it's not that simple that, that the code base doesn't have all the knowledge, but like it's a lot, you're a lot better off than you are with other areas of knowledge work. Like you, we like, we like have documentation practices, you write specifications. Those things don't exist for like 80% of work that happens in the enterprise.That's the divide that we have, which is, which is AI coding has, has just fully, you know, where we've reached escape velocity of how powerful this stuff is, and then we're gonna have to find a way to bring that same energy and momentum, but to all these other areas of knowledge work. Where the tools aren't there, the data's not set up to be there.The access controls don't make it that easy. The context engineering is an incredibly hard problem because again, you have access control challenges, you have different data formats. You have end users that are gonna need to kind of be kind of trained through this as opposed to their adopting [00:15:00] these tools in their free time.That's where the Fortune 500 is. And so we, I think, you know, have to be prepared as an industry where we are gonna be on a multi-year march to, to be able to bring agents to the enterprise for these workflows. And I think probably the, the thing that we've learned most in coding that, that the rest of the world is not yet, I think ready for, I mean, we're, they'll, they'll have to be ready for it because it's just gonna inevitably happen is I think in coding.What, what's interesting is if you think about the practice of coding today versus two years ago. It's probably the most changed workflow in maybe the history of time from the amount of time it's changed, right? Yeah. Like, like has any, has any workflow in the entire economy changed that quickly in terms of the amount of change?I just, you know, at least in any knowledge worker workflow, there's like very rarely been an event where one piece of technology and work practice has so fundamentally, you know, changed, changed what you do. Like you don't write code, you talk to an agent and it goes and [00:16:00] does it for you, and you may be at best review it.And even that's even probably like, like largely not even what you're doing. What's happening is we are changing our work to make the agents effective. In that model, the agent didn't really adapt to how we work. We basically adapted to how the agent works. Mm-hmm. All of the economy has to go through that exact same evolution.The rest of the economy is gonna have to update its workflows to make agents effective. And to give agents the context that they need and to actually figure out what kind of prompting works and to figure out how do you ensure that the agent has the right access to information to be able to execute on its work.I, you know, this is not the panacea that people were hoping for, of the agent drops in, just automates your life. Like you have to basically re-engineer your workflow to get the most out of agents and, uh, and that, that's just gonna take, you know, multiple years across the economy. Right now it's a huge asset and an advantage for the teams that do it early and that are kinda wired into doing this.‘cause [00:17:00] you'll see compounding returns, but that's just gonna take a while for most companies to actually go and get this deployed.swyx: I love, I love pushing back. I think that. That is what a lot of technology consultants love to hear this sort of thing, right? Yeah, yeah, yeah. First to, to embrace the ai. Yes. To get to the promised land, you must pay me so much money to a hundred percent to adopt the prescribed way of, uh, conforming to the agents.Yes. And I worry that you will be eclipsed by someone else who says, no, come as you are.Aaron Levie: Yeah.swyx: And we'll meet you where you are.Aaron Levie: And, and, and and what was the thing that went viral a week ago? OpenAI probably, uh, is hiring F Dees. Yeah. Uh, to go into the enterprise. Yeah. Yeah. And then philanthropic is embedded at Goldman Sachs.Yeah. So if the labs are having to do this, if, if the labs have decided that they need to hire FDE and professional services, then I think that's a pretty clear indication that this, there's no easy mode of workflow transformation. Yeah. Yeah. So, so to your point, I think actually this is a market opportunity for, you know, new professional services and consulting [00:18:00] firms that are like Agent Build and they, and they kind of, you know, go into organizations and they figure out how to re-engineer your workflows to make them more agent ready and get your data into the right format and, you know, reconstruct your business process.So you're, you're not doing most of the work. You're telling agents how to do the work and then you're reviewing it. But I haven't seen the thing that can just drop in and, and kinda let you not go through those changes.swyx: I don't know how that kind of sales pitch goes over. Yeah. You know, you're, you're saying things like, well, in my sort of nice beautiful walled garden, here's, there's, uh, because here's this, here's this beautiful box account that has everything.Yes. And I'm like, well, most, most real life is extremely messy. Sure. And like, poorly named and there duplicate this outdated s**tAaron Levie: a hundred percent. And so No, no, a hundred percent. And so this is actually No. So, so this is, I mean, we agree that, that getting to the beautiful garden is gonna be tough.swyx: Yeah.Aaron Levie: There's also the other end of the spectrum where I, I just like, it's a technical impossibility to solve. The agent is, is truly cannot get enough context to make the right decision in, in the, in the incredibly messy land. Like there's [00:19:00] no a GI that will solve that. So, so we're gonna have to kind of land in somewhere in between, which is like we all collectively get better at.Documentation practices and, and having authoritative relatively up-to-date information and putting it in the right place like agents will, will certainly cause us to be much better organized around how we work with our information, simply because the severity of the agent pulling the wrong data will be too high and the productivity gain of that you'll miss out on by not doing this will be too high as well, that you, that your competition will just do it and they'll just have higher velocity.So, uh, and, and we, we see this a lot firsthand. So we, we build a series of agents internally that they can kind of have access to your full box account and go off and you give it a task and it can go find whatever information you're looking for and work with. And, you know, thank God for the model progress, but like, if, if you gave that task to an agent.Nine months ago, you're just gonna get lots of bogus answers because it's gonna, it's gonna say, Hey, here's, here are fi [00:20:00] five, you know, documents that all kind of smell like the right thing. And I'm gonna, but I, but you're, you're putting me on the clock. ‘cause my assistant prompt says like, you know, be pretty smart, but also try and respond to the user and it's gonna respond.And it's like, ah, it got the wrong document. And then you do that once or twice as a knowledge worker and you're just neverswyx: again,Aaron Levie: never again. You're just like done with the system.swyx: Yeah. It doesn't work.Aaron Levie: It doesn't work. And so, you know, Opus four six and Gemini three one Pro and you know, whatever the latest five 3G BT will be, like, those things are getting better and better and it's using better judgment.And this sort of like the, all of these updates to the agentic tool and search systems are, are, we're seeing, we're seeing very real progress where the agent. Kind of can, can almost smell some things a little bit fishy when it's getting, you know, we, we have this process where we, we have it go fan out, do a bunch of searches, pull up a bunch of data, and then it has to sort of do its own ranking of, you know, what are the right documents that, that it should be working with.And again, like, you know, the intelligence level of a model six months ago, [00:21:00] it'd be just throwing a dart at like, I'm just, I'm gonna grab these seven files and I, I pray, I hope that that's the right answer. And something like an opus first four five, and now four six is like, oh, it's like, no, that one doesn't seem right relative to this question because I'm seeing some signal that is making that, you know, that's contradicting the document where it would normally be in the tree and who should have access.Like it's doing all of that kind of work for you. But like, it still doesn't work if you just have a total wasteland of data. Like, it's just not, it's just not possible. Partly ‘cause a human wouldn't even be able to do it. So basically if a, if a really, really smart human. Could not do that task in five or 10 minutes for a search retrieval type task.Look, you know, your agent's not gonna be able to do it any better. You see this all day long. SoContext Engineering and Search Limitsswyx: this touches on a thing that just passionate about it was just context engineering. I, I'm just gonna let you ramble or riff on, on context engineering. If, if, if there's anything like he, he did really good work on context fraud, which has really taken over as like the term that people use and the referenceAaron Levie: a hundred percent.We, we all we think about is, is the context rob problem. [00:22:00]Jeff Huber: Yeah, there's certainly a lot of like ranking considerations. Gentech surgery think is incredibly promising. Um, yeah, I was trying to generate a question though. I think I have a question right now. Swyx.Aaron Levie: Yeah, no, but like, like I think there was this moment, um, you know, like, I don't know, two years ago before, before we knew like where the, the gotchas were gonna be in ai and I think someone was like, was like, well, infinite context windows will just solve all of these problems and ‘cause you'll just, you'll just give the context window like all the data and.It's just like, okay, I mean, maybe in 2035, like this is a viable solution. First of all, it, it would just, it would just simply cost too much. Like we just can't give the model like the 5,000 documents that might be relevant and it's gonna read them all. And I've seen enough to, to start believing in crazy stuff.So like, I'm willing to just say, sure. Like in, in 10 years from now,swyx: never say, never, never.Aaron Levie: In, in 10 years from now, we'll have infinite context windows at, at a thousandth of the price of today. Like, let's just like believe that that's possible, but Right. We're in reality today. So today we have a context engineering [00:23:00] problem, which is, I got, I got, you know, 200,000 tokens that I can work with, or prob, I don't even know what the latest graph is before, like massive degradation.16. Okay. I have 60,000 tokens that I get to work with where I'm gonna get accurate information. That's not a lot of tokens for a corpus of 10 million documents that a knowledge worker might have across all of the teams and all the projects and all the people they work with. I have, I have 10 million documents.Which, you know, maybe is times five pages per document or something like that. I'm at 50 million pages of information and I have 60,000 tokens. Like, holy s**t. Yeah. This is like, how do I bridge the 50 million pages of information with, you know, the couple hundred that I get to work with in that, in that token window.Yeah. This is like, this is like such an interesting problem and that's why actually so much work is actually like, just like search systems and the databases and that layer has to just get so locked in, but models getting better and importantly [00:24:00] knowing when they've done a search, they found the wrong thing, they go back, they check their work, they, they find a way to balance sort of appeasing the user versus double checking.We have this one, we have this one test case where we ask the agent to go find. 10 pieces of information.swyx: Is this the complex work eval?Aaron Levie: Uh, this is actually not in the eval. This is, this is sort of just like we have a bunch of different, we have a bunch of internal benchmark kind of scenarios. Every time we, we update our agent, we have one, which is, I ask it to find all of our office addresses, and I give it the list of 10 offices that we have.And there's not one document that has this, maybe there should be, that would be a great example of the kind of thing that like maybe over time companies start to, you know, have these sort of like, what are the canonical, you know, kind of key areas of knowledge that we need to have. We don't seem to have this one document that says, here are all of our offices.We have a bunch of documents that have like, here's the New York office and whatever. So you task this agent and you, you get, you say, I need the addresses for these 10 offices. Okay. And by the way, if you do this on any, you know, [00:25:00] public chat model, the same outcome is gonna happen. But for a different kind of query, you give it, you say, I need these 10 addresses.How many times should the agent go and do its search before it decides whether or not, there's just no answer to this question. Often, and especially the, the, let's say lower tier models, it'll come back and it'll give you six of the 10 addresses. And it'll, and I'll just say I couldn't find the otherswyx: four.It, it doesn't know what It doesn't know. ItAaron Levie: doesn't know what It doesn't know. Yeah. So the model is just like, like when should it stop? When should it stop doing? Like should it, should it do that task for literally an hour and just keep cranking through? Maybe I actually made up an office location and it doesn't know that I made it up and I didn't even know that I made it up.Like, should it just keep, re should it read every single file in your entire box account until it, until it should exhaust every single piece of information.swyx: Expensive.Aaron Levie: These are the new problems that we have. So, you know, something like, let's say a new opus model is sort of like, okay, I'm gonna try these types of queries.I didn't get exactly what I wanted. I'm gonna try again. I'm gonna, at [00:26:00] some point I'm gonna stop searching. ‘cause I've determined that that no amount of searching is gonna solve this problem. I'm just not able to do it. And that judgment is like a really new thing that the model needs to be able to have.It's like, when should it give up on a task? ‘cause, ‘cause you just don't, it's a can't find the thing. That's the real world of knowledge, work problems. And this is the stuff that the coding agents don't have to deal with. Because they, it just doesn't like, like you're not usually asking it about, you're, you're always creating net new information coming right outta the model for the most part.Obviously it has to know about your code base and your specs and your documentation, but, but when you deploy an agent on all of your data that now you have all of these new problems that you're dealing withJeff Huber: our, uh, follow follow-up research to context ride is actually on a genetic search. Ah. Um, and we've like right, sort of stress tested like frontier models and their ability to search.Um, and they're not actually that good at searching. Right. Uh, so you're sort of highlighting this like explore, exploit.swyx: You're just say, Debbie, Donna say everything doesn't work. Like,Aaron Levie: well,Jeff Huber: somebody has to be,Aaron Levie: um, can I just throw out one more thing? Yeah. That is different from coding and, and the rest [00:27:00] of the knowledge work that I, I failed to mention.So one other kind of key point is, is that, you know, at the end of the day. Whether you believe we're in a slop apocalypse or, or whatever. At the end of the day, if you, if you build a working product at the end of, if you, if you've built a working solution that is ultimately what the customer is paying for, like whether I have a lot of slop, a little slop or whatever, I'm sure there's lots of code bases we could go into in enterprise software companies where it's like just crazy slop that humans did over a 20 year period, but the end customer just gets this little interface.They can, they can type into it, it does its thing. Knowledge work, uh, doesn't have that property. If I have an AI model, go generate a contract and I generate a contract 20 times and, you know, all 20 times it's just 3% different and like that I, that, that kind of lop introduces all new kinds of risk for my organization that the code version of that LOP didn't, didn't introduce.These are, and so like, so how do you constrain these models to just the part that you want [00:28:00] them to work on and just do the thing that you want them to do? And, and, you know, in engineering, we don't, you can't be disbarred as an engineer, but you could be disbarred as a lawyer. Like you can do the wrong medical thing In healthcare, you, there's no, there's no equivalent to that of engineering.Like, doswyx: you want there to be, because I've considered softwareJeff Huber: engineer. What's that? Civil engineering there is, right? NotAaron Levie: software civil engineer. Sure. Oh yeah, for sure. But like in any of our companies, you like, you know, you'll be forgiven if you took down the site and, and we, we will do a rollback and you'll, you'll be in a meeting, but you have not been disbarred as an engineer.We don't, we don't change your, you know, your computer science, uh, blameJeff Huber: degree, this postmortem.Aaron Levie: Yeah, exactly. Exactly. So, so, uh, now maybe we collectively as an industry need to figure out like, what are you liable for? Not legally, but like in a, in a management sense, uh, of these agents. All sorts of interesting problems that, that, that, uh, that have to come out.But in knowledge work, that's the real hostile environments that we're operating in. Hmm.swyx: I do think like, uh, a lot of the last year's, 2025 story was the rise of coding agents and I think [00:29:00] 2026 story is definitely knowledge work agents. Yes. A hundredAaron Levie: percent.swyx: Right. Like that would, and I think open claw core work are just the beginning.Yes. Like it's, the next one's gonna just gonna be absolute craziness.Aaron Levie: It it is. And, and, uh, and it's gonna be, I mean, again, like this is gonna be this, this wave where we, we are gonna try and bring as many of the practices from coding because that, that will clearly be the forefront, which is tell an agent to go do something and has an access to a set of resources.You need to be responsible for reviewing it at the end of the process. That to me is the, is the kind of template that I just think goes across knowledge, work and odd. Cowork is a great example. Open Closet's a great example. You can kind of, sort of see what Codex could become over time. These are some, some really interesting kind of platforms that are emerging.swyx: Okay. Um, I wanted to, we touched on evals a little bit. You had, you had the report that you're gonna go bring up and then I was gonna go into like, uh, boxes, evals, but uh, go ahead. Talk about your genetic search thing.Jeff Huber: Yeah. Mostly I think kinda a few of the insights. It's like number one frontier model is not good at search.Humans have this [00:30:00] natural explore, exploit trade off where we kinda understand like when to stop doing something. Also, humans are pretty good at like forgetting actually, and like pruning their own context, whereas agents are not, and actually an agent in their kind of context history, if they knew something was bad and they even, you could see in the trace the reason you trace, Hey, that probably wasn't a good idea.If it's still in the trace, still in the context, they'll still do it again. Uhhuh. Uh, and so like, I think pruning is also gonna be like, really, it's already becoming a thing, right? But like, letting self prune the con windowsswyx: be a big deal. Yeah. So, so don't leave the mistake. Don't leave the mistake in there.Cut out the mistake but tell it that you made a mistake in the past and so it doesn't repeat it.Jeff Huber: Yeah. But like cut it out so it doesn't get like distracted by it again. ‘cause really, you know, what is so, so it will repeat its mistake just because it's been, it's inswyx: theJeff Huber: context. It'sAaron Levie: in the context so much.That's a few shot example. Even if it, yeah.Jeff Huber: It's like oh thisAaron Levie: is a great thing to go try even ifJeff Huber: it didn't work.Aaron Levie: Yeah,Jeff Huber: exactly.Aaron Levie: SoJeff Huber: there's like a bunch of stuff there. JustAaron Levie: Groundhogs Day inside these models. Yeah. I'm gonna go keep doing the same wrongJeff Huber: thing. Covering sense. I feel like, you know, some creator analogy you're trying like fit a manifold in latent space, which kind is doing break program synthesis, which is kinda one we think about we're doing right.Like, you know, certain [00:31:00] facts might be like sort of overly pitting it. There are certain, you know, sec sectors of latent space and so like plug clean space. Yeah. And, uh, andswyx: so we have a bell, our editor as a bell every time you say that. SoJeff Huber: you have, you have to like remove those, likeswyx: you shoulda a gong like TPN or something.IfJeff Huber: we gong, you either remove those links to like kinda give it the freedom, kind of do what you need to do. So, but yeah. We'll, we'll release more soon. That'sAaron Levie: awesome.Jeff Huber: That'll, that'll be cool.swyx: We're a cerebral podcast that people listen to us and, and sort of think really deep. So yeah, we try to keep it subtle.Okay. We try to keep it.Aaron Levie: Okay, fine.Inside Agent Evalsswyx: Um, you, you guys do, you guys do have EVs, you talked about your, your office thing, but, uh, you've been also promoting APEX agents and complex work. Uh, yeah, whatever you, wherever you wanna take this just Yeah. How youAaron Levie: Apex is, is obviously me, core's, uh, uh, kind of, um, agent eval.We, we supported that by sort of. Opening up some data for them around how we kind of see these, um, data workspaces in, in the, you know, kind of regular economy. So how do lawyers have a workspace? How do investment bankers have a workspace? What kind of data goes into those? And so we, [00:32:00] we partner with them on their, their apex eval.Our own, um, eval is, it's actually relatively straightforward. We have a, a set of, of documents in a, in a range of industries. We give the agent previously did this as a one shot test of just purely the model. And then we just realized we, we need to, based on where everything's going, it's just gotta be more agentic.So now it's a bit more of a test of both our harness and the model. And we have a rubric of a set of things that has to get right and we score it. Um, and you're just seeing, you know, these incredible jumps in almost every single model in its own family of, you know, opus four, um, you know, sonnet four six versus sonnet four five.swyx: Yeah. We have this up on screen.Aaron Levie: Okay, cool. So some, you're seeing it somewhere like. I, I forget the to, it was like 15 point jump, I think on the main, on the overall,swyx: yes.Aaron Levie: And it's just like, you know, these incredible leaps that, that are starting to happen. Um,swyx: and OP doesn't know any, like any, it's completely held out from op.Aaron Levie: This is not in any, there's no public data which has, you know, Ben benefits and this is just a private eval that we [00:33:00] do, and then we just happen to show it to, to the world. Hmm. So you can't, you can't train against it. And I think it's just as representative of. It's obviously reasoning capabilities, what it's doing at, at, you know, kind of test time, compute capabilities, thinking levels, all like the context rot issues.So many interesting, you know, kind of, uh, uh, capabilities that are, that are now improvingswyx: one sector that you have. That's interesting.Industries and Datasetsswyx: Uh, people are roughly familiar with healthcare and legal, but you have public sector in there.Aaron Levie: Yeah.swyx: Uh, what's that? Like, what, what, what is that?Aaron Levie: Yeah, and, and we actually test against, I dunno, maybe 10 industries.We, we end up usually just cutting a few that we think have interesting gains. All extras, won a lot of like government type documents. Um,swyx: what is that? What is it? Government type documents?Aaron Levie: Government filings. Like a taxswyx: return, likeAaron Levie: a probably not tax returns. It would be more of what would go the government be using, uh, as data.So, okay. Um, so think about research that, that type of, of, of data sets. And then we have financial services for things like data rooms and what would be in an investment prospectus. Uhhuh,swyx: that one you can dog food.Aaron Levie: Yeah, exactly. Exactly. Yes. Yes. [00:34:00] So, uh, so we, we run the models, um, in now, you know, more of an agent mode, but, but still with, with kinda limited capacity and just try and see like on a, like, for like basis, what are the improvements?And, and again, we just continue to be blown away by. How, how good these models are getting.swyx: Yeah, I mean, I think every serious AI company needs something like that where like, well, this is the work we do. Here's our company eval. Yeah. And if you don't have it, well, you're not a serious AI company.Aaron Levie: There's two dimensions, right?So there's, there's like, how are the models improving? And so which models should you either recommend a customer use, which one should you adopt? But then every single day, we're making changes to our agents. And you need to knowswyx: if you regressed,Aaron Levie: if you know. Yeah. You know, I've been fully convinced that the whole agent observability and eval space is gonna be a massive space.Um, super excited for what Braintrust is doing, excited for, you know, Lang Smith, all the things. And I think what you're going to, I mean, this is like every enter like literally every enterprise right now. It's like the AI companies are the customers of these tools. Every enterprise will have this. Yeah, you'll just [00:35:00] have to have an eval.Of all of your work and like, we'll, you'll have an eval of your RFP generation, you'll have an eval of your sales material creation. You'll have an eval of your, uh, invoice processing. And, and as you, you know, buy or use new agentic systems, you are gonna need to know like, what's the quality of your, of your pipeline.swyx: Yeah.Aaron Levie: Um, so huge, huge market with agent evals.swyx: Yeah.Building the Agent Teamswyx: And, and you know, I'm gonna shout out your, your team a bit, uh, your CTO, Ben, uh, did a great talk with us last year. Awesome. And he's gonna come back again. Oh, cool. For World's Fair.Aaron Levie: Yep.swyx: Just talk about your team, like brag a little bit. I think I, I think people take these eval numbers in pretty charts for granted, but No, there, I mean, there's, there's lots of really smart people at work during all this.Aaron Levie: Biggest shout out, uh, is we have a, we have a couple folks at Dya, uh, Sidarth, uh, that, that kind of run this. They're like a, you know, kind of tag tag team duo on our evals, Ben, our CTO, heavily involved Yasha, head of ai, uh, you know, a bunch of folks. And, um, evals is one part of the story. And then just like the full, you know, kind of AI.An agent team [00:36:00] is, uh, is a, is a pretty, you know, is core to this whole effort. So there's probably, I don't know, like maybe a few dozen people that are like the epicenter. And then you just have like layers and layers of, of kind of concentric circles of okay, then there's a search team that supports them and an infrastructure team that supports them.And it's starting to ripple through the entire company. But there's that kind of core agent team, um, that's a pretty, pretty close, uh, close knit group.swyx: The search team is separate from the infra team.Aaron Levie: I mean, we have like every, every layer of the stack we have to kind of do, except for just pure public cloud.Um, but um, you know, we, we store, I don't even know what our public numbers are in, you know, but like, you can just think about it as like a lot of data is, is stored in box. And so we have, and you have every layer of the, of the stack of, you know, how do you manage the data, the file system, the metadata system, the search system, just all of those components.And then they all are having to understand that now you've got this new customer. Which is the agent, and they've been building for two types of customers in the past. They've been building for users and they've been building for like applications. [00:37:00] And now you've got this new agent user, and it comes in with a difference of it, of property sometimes, like, hey, maybe sometimes we should do embeddings, an embedding based, you know, kind of search versus, you know, your, your typical semantic search.Like, it's just like you have to build the, the capabilities to support all of this. And we're testing stuff, throwing things away, something doesn't work and, and not relevant. It's like just, you know, total chaos. But all of those teams are supporting the agent team that is kind of coming up with its requirements of what, what do we need?swyx: Yeah. No, uh, we just came from, uh, fireside chat where you did, and you, you talked about how you're doing this. It's, it's kind of like an internal startup. Yeah. Within the broader company. The broader company's like 3000 people. Yeah. But you know, there's, there's a, this is a core team of like, well, here's the innovation center.Aaron Levie: Yeah.swyx: And like that every company kind of is run this way.Aaron Levie: Yeah. I wanna be sensitive. I don't call it the innovation center. Yeah. Only because I think everybody has to do innovation. Um, there, there's a part of the, the, the company that is, is sort of do or die for the agent wave.swyx: Yeah.Aaron Levie: And it only happens to be more of my focus simply because it's existential that [00:38:00] we get it right.swyx: Yeah.Aaron Levie: All of the supporting systems are necessary. All of the surrounding adjacent capabilities are necessary. Like the only reason we get to be a platform where you'd run an agent is because we have a security feature or a compliance feature, or a governance feature that, that some team is working on.But that's not gonna be the make or break of, of whether we get agents right. Like that already exists and we need to keep innovating there. I don't know what the right, exact precise number is, but it's not a thousand people and it's not 10 people. There's a number of people that are like the, the kind of like, you know, startup within the company that are the make or break on everything related to AI agents, you know, leveraging our platform and letting you work with your data.And that's where I spend a lot of my time, and Ben and Yosh and Diego and Teri, you know, these are just, you know, people that, that, you know, kind of across the team. Are working.swyx: Yeah. Amazing.Read Write Agent WorkflowsJeff Huber: How do you, how do you think about, I mean, you talked a lot about like kinda read workflows over your box data. Yep.Right. You know, gen search questions, queries, et cetera. But like, what about like, write or like authoring workflows?Aaron Levie: Yes. I've [00:39:00] already probably revealed too much actually now that I think about it. So, um, I've talked about whatever,Jeff Huber: whatever you can.Aaron Levie: Okay. It's just us. It's just us. Yeah. Okay. Of course, of course.So I, I guess I would just, uh, I'll make it a little bit conceptual, uh, because again, I've already, I've already said things that are not even ga but, but we've, we've kinda like danced around it publicly, so I, yeah, yeah. Okay. Just like, hopefully nobody watches this, um, episode. No.swyx: It's tidbits for the Heidi engaged to go figure out like what exactly, um, you know, is, is your sort of line of thinking.Sure. They can connect the dots.Aaron Levie: Yeah. So, so I would say that, that, uh, we, you know, as a, as a place where you have your enterprise content, there's a use case where I want to, you know, have an agent read that data and answer questions for me. And then there's a use case where I want the agent to create something.And use the file system to create something or store off data that it's working on, or be able to have, you know, various files that it's writing to about the work it's doing. So we do see it as a total read write. The harder problem has so far been the read only because, because again, you have that kind of like 10 [00:40:00] million to one ratio problem, whereas rights are a lot of, that's just gonna come from the model and, and we just like, we'll just put it in the file system and kinda use it.So it's a little bit of a technically easier problem, but the only part that's like, not necessarily technically hard, it is just like it's not yet perfected in the state of the ecosystem is, you know, building a beautiful PowerPoint presentation. It's still a hard problem for these models. Like, like we still, you know, like, like these formats are just, we're not built for.They'reswyx: working on it.Aaron Levie: They're, they're working on it. Everybody's working on it.swyx: Every launch is like, well, we do PowerPoint now.Aaron Levie: We're getting, yeah, getting a lot, getting a lot of better each time. But then you'll do this thing where you'll ask the update one slide and all of a sudden, like the fonts will be just like a little bit different, you know, on two of the slides, or it moved, you know, some shape over to the left a little bit.And again, these are the kind of things that, like in code, obviously you could really care about if you really care about, you know, how beautiful is the code, but at the end, user doesn't notice all those problems and file creation, the end user instantly sees it. You're [00:41:00] like, ah, like paragraph three, like, you literally just changed the font on me.Like it's a totally different font and like midway through the document. Mm-hmm. Those are the kind of things that you run into a lot of in the, in the content creation side. So, mm-hmm. We are gonna have native agents. That do all of those things, they'll be powered by the leading kind of models and labs.But the thing that I think is, is probably gonna be a much bigger idea over time is any agent on any system, again, using Box as a file system for its work, and in that kind of scenario, we don't necessarily care what it's putting in the file system. It could put its memory files, it could put its, you know, specification, you know, documents.It could put, you know, whatever its markdown files are, or it could, you know, generate PDFs. It's just like, it's a workspace that is, is sort of sandboxed off for its work. People can collaborate into it, it can share with other people. And, and so we, we were thinking a lot about what's the right, you know, kind of way to, to deliver that at scale.Docs Graphs and Founder Modeswyx: I wanted to come into sort of the sort of AI transformation or AI sort of, uh, operations things. [00:42:00] Um, one of the tweets that you, that you wanted to talk about, this is just me going through your tweets, by the way. Oh, okay. I mean, like, this is, you readAaron Levie: one by one,swyx: you're the, you're the easiest guest to prep for because you, you already have like, this is the, this is what I'm interested in.I'm like, okay, well, areAaron Levie: we gonna get to like, like February, January or something? Where are we in the, in the timelines? How far back are we going?swyx: Can you, can you describe boxes? A set of skills? Right? Like that, that's like, that's like one of the extremes of like, well if you, you just turn everything into a markdown file.Yeah. Then your agent can run your company. Uh, like you just have to write, find the right sequence of words toAaron Levie: Yes.swyx: To do it.Aaron Levie: Sorry, isthatswyx: the question? So I think the question is like, what if we documented everything? Yes. The way that you exactly said like,Aaron Levie: yes.swyx: Um, let's get all the Fortune five hundreds, uh, prepared for agents.Yes. And like, you know, everything's in golden and, and nicely filed away and everything. Yes. What's missing? Like, what's left, right? LikeAaron Levie: Yeah.swyx: You've, you've run your company for a decade. LikeAaron Levie: Yeah. I think the challenge is that, that that information changes a week later. And because something happened in the market for that [00:43:00] customer, or us as a company that now has to go get updated, and so these systems are living and breathing and they have to experience reality and updates to reality, which right now is probably gonna be humans, you know, kinda giving those, giving them the updates.And, you know, there is this piece about context graphs as as, uh, that kinda went very viral. Yeah. And I, I, I was like a, i, I, I thought it was super provocative. I agreed with many parts of it. I disagree with a few parts around. You know, it's not gonna be as easy as as just if we just had the agent traces, then we can finally do that work because there's just like, there's so much more other stuff that that's happening that, that we haven't been able to capture and digitize.And I think they actually represented that in the piece to be clear. But like there's just a lot of work, you know, that that has to, you just can't have only skills files, you know, for your company because it's just gonna be like, there's gonna be a lot of other stuff that happens. Yeah. Change over time.Yeah. Most companies are practically apprenticeships.swyx: Most companies are practically apprenticeships. LikeJeff Huber: every new employee who joins the team, [00:44:00] like you span one to three months. Like ramping them up.Aaron Levie: Yes. AllJeff Huber: that tat knowledgeAaron Levie: isJeff Huber: not written down.Aaron Levie: Yes.Jeff Huber: But like, it would have to be if you wanted to like give it to an Asian.Right. And so like that seems to me like to beAaron Levie: one is I think you're gonna see again a premium on companies that can document this. Mm-hmm. Much. There'll be a huge premium on that because, because you know, can you shorten that three month ramp cycle to a two week ramp cycle? That's an instant productivity gain.Can you re dramatically reduce rework in the organization because you've documented where all the stuff is and where the answers are. Can you make your average employee as good as your 90th percentile employee because you've captured the knowledge that's sort of in the heads of, of those top employees and make that available.So like you can see some very clear productivity benefits. Mm-hmm. If you had a company culture of making sure you know your information was captured, digitized, put in a format that was agent ready and then made available to agents to work with, and then you just, again, have this reality of like add a 10,000 person [00:45:00] company.Mapping that to the, you know, access structure of the company is just a hard problem. Is like, is like, yeah, well, you just, not every piece of information that's digitized can be shared to everybody. And so now you have to organize that in a way that actually works. There was a pretty good piece, um, this, this, uh, this piece called your company as a file is a file system.I, did you see that one?swyx: Nope.Aaron Levie: Uh, yes. You saw it. Yeah. And, and, uh, I actually be curious your thoughts on it. Um, like, like an interesting kind of like, we, we agree with it because, because that's how we see the world and, uh,swyx: okay. We, we have it up on screen. Oh,Aaron Levie: okay. Yeah. But, but it's all about basically like, you know, we've already, we, we, we already organized in this kind of like, you know, permission structure way.Uh, and, and these are the kind of, you know, natural ways that, that agents can now work with data. So it's kind of like this, this, you know, kind of interesting metaphor, but I do think companies will have to start to think about how they start to digitize more, more of that data. What was your take?Jeff Huber: Yeah, I mean, like the company's probably like an acid compliant file system.Aaron Levie: Uh,Jeff Huber: yeah. Which I'm guessing boxes, right? So, yeah. Yes.swyx: Yeah. [00:46:00]Jeff Huber: Which you have a great piece on, but,swyx: uh, yeah. Well, uh, I, I, my, my, my direction is a little bit like, I wanna rewind a little bit to the graph word you said that there, that's a magic trigger word for us. I always ask what's your take on knowledge graphs?Yeah. Uh, ‘cause every, especially at every data database person, I just wanna see what they think. There's been knowledge graphs, hype cycles, and you've seen it all. So.Aaron Levie: Hmm. I actually am not the expert in knowledge graphs, so, so that you might need toswyx: research, you don't need to be an expert. Yeah. I think it's just like, well, how, how seriously do people take it?Yeah. Like, is is, is there a lot of potential in the, in the HOVI?Aaron Levie: Uh, well, can I, can I, uh, understand first if it's, um, is this a loaded question in the sense of are you super pro, super con, super anti medium? Iswyx: see pro, I see pros and cons. Okay. Uh, but I, I think your opinion should be independent of mine.Aaron Levie: Yeah. No, no, totally. Yeah. I just want to see what I'm stepping into.swyx: No, I know. It's a, and it's a huge trigger word for a lot of people out Yeah. In our audience. And they're, they're trying to figure out why is that? Because whyAaron Levie: is this such aswyx: hot item for them? Because a lot of people get graph religion.And they're like, everything's a graph. Of course you have to represent it as a graph. Well, [00:47:00] how do you solve your knowledge? Um, changing over time? Well, it's a graph.Aaron Levie: Yeah.swyx: And, and I think there, there's that line of work and then there's, there's a lot of people who are like, well, you don't need it. And both are right.Aaron Levie: Yeah. And what do the people who say you don't need it, what are theyswyx: arguing for Mark down files. Oh, sure, sure. Simplicity.Aaron Levie: Yeah.swyx: Versus it's, it's structure versus less structure. Right. That's, that's all what it is. I do.Aaron Levie: I think the tricky thing is, um, is, is again, when this gets met with real humans, they're just going to their computer.They're just working with some people on Slack or teams. They're just sharing some data through a collaborative file system and Google Docs or Box or whatever. I certainly like the vision of most, most knowledge graph, you know, kind of futuristic kind of ways of thinking about it. Uh, it's just like, you know, it's 2026.We haven't seen it yet. Kind of play out as as, I mean, I remember. Do you remember the, um, in like, actually I don't, I don't even know how old you guys are, but I'll for, for to show my age. I remember 17 years ago, everybody thought enterprises would just run on [00:48:00] Wikis. Yeah. And, uh, confluence and, and not even, I mean, confluence actually took off for engineering for sure.Like unquestionably. But like, this was like everything would be in the w. And I think based on our, uh, our, uh, general style of, of, of what we were building, like we were just like, I don't know, people just like wanna workspace. They're gonna collaborate with other people.swyx: Exactly. Yeah. So you were, you were anti-knowledge graph.Aaron Levie: Not anti, not anti. Soswyx: not nonAaron Levie: I'm not, I'm not anti. ‘cause I think, I think your search system, I just think these are two systems that probably, but like, I'm, I'm not in any religious war. I don't want to be in anybody's YouTube comments on this. There's not a fight for me.swyx: We, we love YouTube comments. We're, we're, we're get into comments.Aaron Levie: Okay. Uh, but like, but I, I, it's mostly just a virtue of what we built. Yeah. And we just continued down that path. Yeah.swyx: Yeah.Aaron Levie: And, um, and that, that was what we pursued. But I'm not, this is not a, you know, kind of, this is not a, uh, it'sswyx: not existential for you. Great.Aaron Levie: We're happy to plug into somebody else's graph.We're happy to feed data into it. We're happy for [00:49:00] agents to, to talk to multiple systems. Not, not our fight.swyx: Yeah.Aaron Levie: But I need your answer. Yeah. Graphs or nerd Snipes is very effective nerd.swyx: See this is, this is one, one opinion and then I've,Jeff Huber: and I think that the actual graph structure is emergent in the mind of the agent.Ah, in the same way it is in the mind of the human. And that's a more powerful graph ‘cause it actually involved over time.swyx: So don't tell me how to graph. I'll, I'll figure it out myself. Exactly. Okay. All right. AndJeff Huber: what's yours?swyx: I like the, the Wiki approach. Uh, my, I'm actually

You can build the best product in the market and still lose to a mediocre competitor. This isn't reverse psychology—it's how markets actually work. In this episode, Sophia Matveeva breaks down why superior products lose to inferior ones, and what you can do about it. You'll learn: Why ecosystem lock-in makes incumbents nearly impossible to beat The "good enough" trap (and why being 20% better isn't enough) How VHS beat Betamax and Salesforce beat better CRMs Why distribution matters more than product quality The unfair advantage question you must answer before you build Whether enterprise sales is even the right game for you to play If you're building a tech product and wondering why traction is harder than you expected, this episode explains what's actually standing in your way—and how to navigate it. Essential listening for non-technical founders targeting enterprise customers. For more career & tech lessons, subscribe to Tech for Non-Techies on: Apple Spotify YouTube Amazon Podcasts Stitcher Pandora TIMESTAMPS 00:00 - Introduction: Why better products lose to mediocre competitors 02:14 - Ecosystem lock-in: The Salesforce and BMW example 04:30 - Why 20% better isn't enough: The switching cost barrier 06:46 - Catalyzing events: When incumbents are vulnerable (Zoom and Slack examples) 08:08 - Strategy 1: Understanding investor perspective on enterprise sales 09:10 - Strategies 2–4: Sales, unfair advantage, and choosing your market 11:28 - Strategy 5: Enterprise timelines and runway reality 12:16 - Create a new category instead of competing directly (HubSpot example) 13:39 - Action steps and closing   FULL TRANSCRIPT: https://www.techfornontechies.co/blog/why-the-best-products-dont-always-win

Signal-based demand generation replaces traditional lead scoring with real buying intent data. Nick Zeckets, Chief Fire Starter at Smoke Signals AI, brings expertise from two MarTech exits and building AI-first HubSpot solutions. He advocates bootstrapping over venture capital to maintain customer focus and control. The discussion covers transitioning from vanity metrics to pipeline measurement and redesigning demand generation systems for AI-driven buyer behavior tracking.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Signal-based demand generation replaces traditional lead scoring with real buying intent data. Nick Zeckets, Chief Fire Starter at Smoke Signals AI, brings expertise from two MarTech exits and building AI-first HubSpot solutions. He advocates bootstrapping over venture capital to maintain customer focus and control. The discussion covers transitioning from vanity metrics to pipeline measurement and redesigning demand generation systems for AI-driven buyer behavior tracking.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Sales is a rollercoaster: one month you're flying, the next you hit a wall because a client changes their mind, a supply chain hiccup wipes out the order, or someone inside your own organisation drops the ball. What we can control, completely, is our time, our talent, and our treasure—and that's where the real leverage sits. In a post-pandemic market (and especially as of 2025), buyers are time-poor, inboxes are brutal, and competitors are one click away. So the question is simple: are we making the most of the three things that are actually ours?   Why is a salesperson's time the most expensive asset? Time is the one asset you can't replenish, and it dictates your pipeline, your reputation, and your commission. If you spend your week "busy" but not building relationships, you're basically renting stress. As a buyer, I see it constantly: poor follow-up. And it's bizarre, because we all know acquiring a new customer costs far more than expanding an existing customer's purchase profile (land-and-expand is not a buzzword—it's survival). Yet many salespeople stop after three rejections in cold calling, then wonder why the quarter looks like a horror movie. Compare that with high-performing teams in the US and Japan who run disciplined cadence systems using Salesforce, HubSpot, or Microsoft Dynamics—touchpoints are planned, tracked, and measured like a production line at Toyota. Do now: Block recurring weekly follow-up time and treat it like a client meeting—non-negotiable. How do you stay "top of mind" without spamming people? You stay top of mind by being useful, personal, and consistent—not by blasting a weekly email and hoping for miracles. Most "newsletters" end up in junk, clutter, or the "unsubscribe and forget forever" bin. Staying top of mind takes effort, but the upside is massive—especially if your competitor is lazy. Think in terms of buyer psychology: people choose the option that costs them the least mental energy. If they already know you, trust you, and can predict your quality, you become the easy decision. This is why professional services firms—translation agencies, consultancies, training providers—win on relationship continuity. In Japan, where trust and reliability are weighted heavily in B2B decisions, sustained contact beats flashy pitch decks. Do now: Replace "email blast" with a simple cadence: 1 helpful note + 1 relevant insight + 1 human check-in each month. What does "good follow-up" look like in the real world? Good follow-up is a system, not a mood—and it works even when you're busy. The best example is when a supplier meets you once, then keeps in touch thoughtfully for years, so when you need them, they're already in pole position.  That's not luck. That's process. It's logging touchpoints, setting reminders, and sending value that matches the buyer's context: a short video, a case study, a relevant event invite, a quick "saw this and thought of you." Compare startups versus multinationals: startups often have hustle but no system; large firms have tools but suffer from internal handoffs. Your job is to combine both—human warmth plus operational discipline. Mini checklist One CRM record per decision-maker Next step dated and owned 3 channels: email + LinkedIn + one "real" touch (call/voice) Do now: Set CRM tasks immediately after every interaction—no "I'll do it later." How do you future-proof your sales talent as the market changes? Talent is time-bound—if your skills don't evolve, your results won't either. Being a Modern selling is a blend: consultative discovery, social credibility, and content that proves you can solve problems. Are you comfortable using LinkedIn, YouTube, short-form video, webinars, and a breadcrumb trail of useful insights? In 2025, buyers often "pre-qualify" you before they reply—your digital footprint becomes your silent salesperson. This is where markets differ: US sellers may lean harder into personal brand and outbound automation; Japan often rewards consistency, humility, and proof over hype. Either way, the basics still matter: questioning, listening, objection handling, and clear next steps—Dale Carnegie fundamentals don't expire. Do now: Pick one skill to upgrade this month (video, discovery, negotiation) and practise it weekly. Is investing in sales training still worth it when so much is free? Yes—free information is everywhere, but disciplined learning and application are rare. You can binge podcasts, hoard books, and still stay average if you never implement.  Back in 1939, Dale Carnegie made world-class training accessible through public classes. The logic still holds: if your company doesn't train you well, invest a microscopic part of your treasure and go get the best. Today, you've got Coursera, LinkedIn Learning, Dale Carnegie programs, specialist coaching, and industry conferences across Asia-Pacific, Europe, and North America. The difference between top performers and everyone else isn't access—it's commitment and execution. Top sellers learn, apply, customise, refine… then repeat. Do now: Spend treasure where it changes behaviour: coaching, role-plays, and frameworks you'll actually use in live deals. What separates top salespeople from everyone else over the long run? Top salespeople don't stop learning—and they don't just "consume," they apply. They stay current through market shocks, tech shifts, and buyer behaviour changes, then tailor what they learn to their patch.  They also protect their time like a dragon guarding gold. They're intentional about: prospecting blocks, client follow-up, pipeline hygiene, and skill practice. They understand cause-and-effect: no follow-up → no trust → no deal. No talent upgrades → commoditisation → price pressure. No treasure invested → stalled growth. This is true whether you sell SaaS in Singapore, industrial equipment in Osaka, or professional services in Sydney. And as work norms shift—think hybrid work and tighter labour conditions in parts of Asia, including Japan's evolving workplace reforms in recent years—buyers want clarity, speed, and reliability. Be that person. Do now: Audit your week: cut 2 low-value activities, add 2 relationship touches, and schedule 1 learning/practice session. Final wrap Sales will always throw curveballs—clients change, supply chains wobble, internal delivery misses happen. But time, talent, and treasure are your controllables, and they compound when you manage them like a pro. Build a follow-up system, evolve your skills for modern selling, and invest in learning that translates into behaviour. Then you'll stop riding the rollercoaster with your eyes closed—and start driving. Optional FAQs Is cold calling dead in 2025? Cold calling still works when paired with a cadence (LinkedIn + email + calls) and a clear value hook, not random dialling. How often should I follow up with a prospect? Monthly is a strong default for warm prospects, with tighter weekly touchpoints during active deal stages. What's the best CRM for follow-up? The best CRM is the one you actually use daily—Salesforce, HubSpot, and Dynamics all work if your cadence is disciplined. Next steps for leaders and salespeople Build a minimum follow-up cadence and measure it weekly Run monthly role-plays on discovery, objections, and closing Set learning KPIs (hours practised, not hours watched) Coach on personal brand: one useful post per week Review pipeline hygiene every Friday Author bio Dr. Greg Story, Ph.D. in Japanese Decision-Making, is President of Dale Carnegie Tokyo Training and Adjunct Professor at Griffith University. He is a two-time winner of the Dale Carnegie "One Carnegie Award" (2018, 2021) and recipient of the Griffith University Business School Outstanding Alumnus Award (2012). As a Dale Carnegie Master Trainer, Greg is certified to deliver globally across all leadership, communication, sales, and Greg has written several books, including three best-sellers — Japan Business Mastery, Japan Sales Mastery, and Japan Presentations Mastery — along with Japan Leadership Mastery and How to Stop Wasting Money on Training. His works have been translated into Japanese, including Za Eigyō (ザ営業), Purezen no Tatsujin (プレゼンの達人), Torēningu de Okane o Muda ni Suru no wa Yamemashō (トレーニングでお金を無駄にするのはやめましょう), and Gendaiban "Hito o Ugokasu" Rīdā (現代版「人を動かす」リーダー).  Greg also publishes daily business insights on LinkedIn, Facebook, and Twitter, and hosts six weekly podcasts. On YouTube, he produces The Cutting Edge Japan Business Show, Japan Business Mastery, and Japan's Top Business Interviews, followed by executives seeking success strategies in Japan. 

In this episode of The LinkedIn Marketer podcast I chat to Charlotte Lloyd. As a dedicated leader in the ICT industry with a focus on creating impactful customer experiences, Charlotte's journey has been driven by a passion for connecting businesses with the right technological solutions. I met Charlotte through my involvement with Women on Boards. She is a fabulous connector and understands the power of LinkedIn to elevate your LinkedIn presence. In this episode Charlotte offers lots of helpful tips for making the most of LinkedIn.More about Charlotte:Embracing diversity and inclusivity, Charlotte chairs the DEI Committee, advocating for a workplace where everyone's voice is heard and valued. This expertise is complemented by her active involvement in DEI initiatives such as being a Judge for Tech Diversity Australia, a Mentor for RMIT's Career Mentoring Program and am a certified Woman Rising Leader & Coach.Charlotte is a Graduate and member of the Australian Institute of Company Directors (AICD), and a member and moderator with Women on Boards.Connect with Charlotte on LinkedIn at https://www.linkedin.com/in/charlotte-lloyd-gaicd-0aa86b33/Resources:Sign up to my newsletter (sent via Hubspot) and get your free LinkedIn Profile Checklist https://thinkbespoke.com.au/linkedin-profile-checklist-3/Follow me on LinkedIn https://www.linkedin.com/in/karenhollenbach/Think Bespoke's Knowledge Basehttps://thinkbespoke.com.au/insights-blog-2/Elevate with KPH (Substack) https://thelinkedinmarketer.substack.com/

In episode #64 of PodSpot, Jon Pittham is joined by Hank Lander, Group Product Manager at HubSpot, to discuss sensitive data management and AI governance in regulated industries. The episode explores how HubSpot defines and categorises sensitive data, how firms can configure controls within the platform, and what enhanced auditing and visibility look like in practice. The discussion also covers integration considerations for organisations connecting HubSpot with core systems. A key focus is AI. Hank explains HubSpot's approach to zero data retention, the handling of sensitive properties within AI workflows, and how customers can align platform controls with their own risk appetite. The episode also touches on emerging capabilities designed to help firms identify and manage sensitive information more proactively. This is a practical conversation for financial services and professional services leaders who want to balance innovation with strong governance, without compromising trust.   Key discussion points: 04:10 – What Is Sensitive Data? 10:05 – Standard vs Highly Sensitive Properties 16:05 – Audit Controls & Integrations 21:05 – Zero Data Retention and AI Model Transparency 29:10 – Roadmap Direction and Future Investment in Data Controls   Want to learn more about HubSpot? Visit our website: https://www.karman.digital/ Follow us on LinkedIn Listen on Spotify Listen on Apple Podcasts

Traditional intent data fails to predict actual buying behavior. Nick Zeckets, Chief Fire Starter at Smoke Signals AI, explains how signal-based demand generation replaces outdated intent tracking methods. He outlines strategies for capturing alpha signals through AI-powered content engagement, building custom HubSpot workflows that activate on meaningful buyer interactions, and measuring pipeline generation instead of vanity metrics.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Traditional intent data fails to predict actual buying behavior. Nick Zeckets, Chief Fire Starter at Smoke Signals AI, explains how signal-based demand generation replaces outdated intent tracking methods. He outlines strategies for capturing alpha signals through AI-powered content engagement, building custom HubSpot workflows that activate on meaningful buyer interactions, and measuring pipeline generation instead of vanity metrics.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

#334 | Dave is joined by Jessica Serrano, CMO at Bagel Brands (Einstein Brothers, Noah's, Bruegger's, Manhattan Bagel), for a conversation about what B2B marketers can learn from consumer restaurant marketing. They discuss why consumer and B2B marketing are way more similar than people think, how she's using AI across her marketing and sales process, and her philosophy that her job is to ‘build brand over time and drive sales overnight.' Jessica shares how COVID forced Dig Inn to rebuild itself as an e-commerce business, how she built a B2B catering sales motion from scratch using HubSpot and buyer personas, and how filtering work emails out of a consumer list became a real customer acquisition tactic. Listen to this episode to learn tactics that work whether you're selling bagels or software.Timestamps(00:00) - Why a consumer CMO listens to B2B marketers (and vice versa) (03:33) - How COVID forced Dig Inn to rebuild as an ecommerce business overnight (06:55) - The math behind going after $500 catering orders vs. $15 walk-ins (10:33) - Building buyer personas for office admins, sports nutritionists, and universities (16:05) - Why Jessica switched from ChatGPT to Claude (and the breakthrough moment) (22:54) - Using AI for rapid product testing on a budget that wouldn't cover traditional research (30:06) - "Build the brand over time, drive sales overnight" and what that looks like at Bagel Brands (32:59) - Why you can't just copy a playbook from Taco Bell to Burger King (37:18) - The biggest lesson from working at brands with nearly 1,000 locations (40:46) - Google reviews as a source of truth for aligning marketing and operations (47:49) - Why organic-first content matters more in the age of AI and dead internet theory Join 50,0000 people who get Dave's Newsletter here: https://www.exitfive.com/newsletterLearn more about Exit Five's private marketing community: https://www.exitfive.com/***Brought to you by:AirOps - The content engineering platform that helps marketers create and maintain high-quality, on-brand content that wins AI search. Go to airops.com/exitfive to start creating content that reflects your expertise, stays true to your brand, and is engineered for performance across human and AI discovery.Customer.io - An AI powered customer engagement platform that help marketers turn first-party data into engaging customer experiences across email, SMS, and push. Learn more at customer.io/exitfive. Convertr - The enterprise lead data management platform that sits between your lead sources and your CRM, automatically validating, enriching, and standardizing every lead before it touches your systems. Check them out at convertr.io/exitfive.Compound Growth Marketing - A full-funnel demand generation agency that helps high-growth cybersecurity, DevOps, and enterprise software companies drive more pipeline through AI SEO, paid media, and go-to-market engineering. Visit compoundgrowthmarketing.com and tell them Dave sent you.***Thanks to my friends at hatch.fm for producing this episode and handling all of the Exit Five podcast production.They give you unlimited podcast editing and strategy for your B2B podcast.Get unlimited podcast editing and on-demand strategy for one low monthly cost. Just upload your episode, and they take care of the rest.Visit hatch.fm to learn more

There is a very big difference between having a good idea and actually owning it publicly. In this episode, a means to re-think your approach to crafting and publishing your content, no matter the channel or medium. The goal is to both clarify your thinking to yourself and build an audience of passionate fans along the way. Subscribe to my newsletter→***ABOUT ME, JAY ACUNZOI work with entrepreneurs, execs, and teams on the journey from competent to resonant. To do that, I help transform your thinking into clear, captivating ideas, speeches, and IP. Stop chasing attention. Become the one others seek.I'm a former marketing leader at Google and HubSpot and globally touring speaker and author. I've spent 20 years building the exact thought leadership I now help clients create—as a practitioner-peer, not a coach with templates.Work with me 1:1, book me to speak, or explore free resources at jayacunzo.comDon't market more. Matter more.Think resonance over reach.Don't be the best. Be their favorite.***ENJOY THE SHOW? PLEASE SAY THANKS!Leave a review on Apple Podcasts Leave a rating on Spotify Thanks for listening!

Today's MadTech Daily covers Netflix pulling out of the bidding war for Warner Bros, Dentsu naming Takeshi Sano as global CEO, and HubSpot expanding its media reach with a Starter Story deal.

For the first time, Google has publicly designated a core update as a "Discover Core Update," signaling a major shift in how content is surfaced to users. In this podcast episode of the We Don't PLAY!™️ Podcast, host Favour Obasi-ike, MBA, MS, unpacks the groundbreaking February 2026 Google Core Update with 200+ people in the Clubhouse Audio LIVE! room.This update, which rolled out over 22 days, emphasizes a move towards a more personalized, AI-driven, and visually-oriented search experience. Favour explains that the Discover feed functions like a recommendation engine for the entire web, proactively suggesting content based on a user's interests and online behavior, rather than just reacting to search queries. This means the success of your content is now heavily influenced by the end-user's activity.The episode delves into the critical importance of creating "people-first" content — content that is helpful, reliable, and genuinely valuable to the audience. Favour warns against the use of clickbait and spammy headlines, as the new algorithm is designed to penalize such practices.Furthermore, the discussion highlights the often-overlooked but crucial role of technical SEO. Using a real-world client example and citing HubSpot's past struggles with a core update, Favour illustrates how a weak technical foundation can undermine even the best content strategy.The episode provides a comprehensive overview of what this update means for businesses and marketers, offering actionable advice on how to adapt and thrive. From optimizing images for a visual-first platform to conducting thorough content audits, this episode is a must-listen for anyone looking to stay ahead in the ever-evolving world of SEO.Book SEO Services | Quick Links for Social Business>> ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Book SEO Services with Favour Obasi-ike⁠>> Visit Work and PLAY Entertainment website to learn about our digital marketing services>> ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Join our exclusive SEO Marketing community⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠>> Read SEO Articles>> ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Subscribe to the We Don't PLAY Podcast⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠>> Purchase Flaev Beatz Beats Online>> Favour Obasi-ike Quick LinksKey Takeaways1. A New Era of Search: The February 2026 Google Core Update is the first to be publicly named a "Discover Core Update," marking a significant shift towards a proactive, AI-powered content recommendation system.2. Content is Still King, but Context is Queen: The update prioritizes "people-first" content that is helpful, reliable, and engaging. The focus is on user intent and value, not just keywords.3. Technical SEO is Non-Negotiable: A solid technical foundation is more critical than ever. Issues with hosting, server response times, and website structure can severely impact your visibility.4. The Power of Personalization: The Discover feed is driven by user behavior and interests. This means your content's reach is now directly tied to how well it resonates with individual users.5. Visuals are Vital: The "Discover" update is inherently visual. High-quality, optimized images and videos are essential for capturing attention and driving engagement in the Discover feed.6. Say Goodbye to Gimmicks: Clickbait, spammy headlines, and other manipulative tactics will be actively penalized. Authenticity and value are the new currency of SEO.7. Embrace an Omnichannel Strategy: Relying solely on Google for traffic is a risky strategy. Building a strong presence across multiple platforms, including social media and email, is key to long-term, sustainable growth.Timestamps[00:00] Introduction to the Google Core Update[01:07] Google's First Publicly Labeled "Discover Core Update"[02:02] Timeline of the February 2026 Update[04:04] The Importance of Technical SEO[05:00] Case Study: HubSpot's Traffic Loss[06:02] The Lack of Information on Core Updates[08:12] Details of the Discover Core Update[10:15] The Role of AI in the Update[13:01] Impact on Different Industries[16:20] The "People-First" Content Strategy[20:01] The Importance of Visual Content[25:54] How User Activity Influences Search Results[27:37] Avoiding Clickbait and Spam[28:06] The Future of Search and ContentMemorable Quotes[01:07 - 01:19] "This is the first time Google has ever publicly mentioned about an update like this, especially to the open, because this doesn't usually happen all the time."[04:19 - 04:26] "I want to know about the core things that's going to either make or break your business online, especially when it comes to AI."[27:43 - 27:47] "You're going to avoid, avoid, avoid, avoid, avoid, avoid, by all means, avoid clickbait."[28:03 - 28:06] "If you're not people-first, it's gonna be quite hard."[26:11 - 26:15] "So the ball is not even in your court anymore. If you really think about it, the ball is in the activity of the user's court."FAQs1. What is the Google Discover Core Update?The February 2026 Google Discover Core Update is a major algorithm change that focuses on personalizing the content shown in the Google Discover feed. It uses AI to proactively recommend articles, videos, and other content based on a user's interests and online behavior, rather than just responding to search queries.2. What is "people-first" content?"People-first" content is content created primarily to provide value to the reader, rather than to rank in search engines. It should be helpful, reliable, well-written, and address the user's needs and interests. This is in contrast to content that is stuffed with keywords or uses clickbait headlines to attract clicks.3. Why is technical SEO important for this update?Technical SEO ensures that your website has a solid foundation for Google to crawl, index, and understand your content. With the Discover update, technical factors like site speed, mobile-friendliness, and structured data are more important than ever for getting your content recommended to users.4. How can I optimize my content for Google Discover?To optimize for Discover, focus on creating high-quality, people-first content with compelling headlines and high-quality images. Understand your audience's interests and create content that aligns with them. Also, ensure your website is technically sound and provides a good user experience.5. What are the key takeaways from the February 2026 update?The key takeaways are to prioritize people-first content, invest in technical SEO, embrace visual content, avoid clickbait, and build an omni-channel marketing strategy to reduce reliance on a single traffic source.More ResourcesGoogle Search Status DashboardGoogle Discover Core Update BlogWork and PLAY! Blog - What is SEO?Work and PLAY! Blog - Technical SEO CourseWe Don't PLAY!™️ Podcast Episode - Social Media Organic StrategiesSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

I take Perplexity Computer for its first real spin and test five use cases that founders can use right now to make money and move faster. I connect my Gmail live, let the AI send cold outreach on my behalf, set up daily competitive intelligence monitoring, research 50 VCs for a mock Series A, and kick off a full investment memo on Shopify, all in a single session. By the end, I walk away genuinely impressed and convinced the $200/month Max plan can pay for itself with one closed deal. Timestamps 00:00 – Intro 00:35 – What We're Testing Today 02:35 – Use Case 1: Warm Outbound at Scale 15:31 – Use Case 2: Automated Competitive Intel 25:11 – Use Case 3: Investor Pipeline Research (50 VCs) 26:58 – Use Case 4: Turn a Podcast Into a Content Machine 31:39 – Use Case 5: Live Market Diligence (Shopify Investment Memo) 34:17 – Bonus: Additional Use Cases Worth Trying 36:06 – Closing Thoughts and Takeaways Key Points Perplexity Computer runs multiple research tasks in parallel using sub-agents, skills, and tools — functioning like a virtual analyst working across the open internet. The cold outreach workflow found real email addresses, researched each prospect's recent activity, and drafted hyper-personalized emails that reference specific details — then sent them through a connected Gmail account. Setting up recurring competitive intelligence monitoring (daily reports, weekly sponsor tracking) is where the tool shifts from a one-off assistant to a persistent agent running on autopilot. The VC pipeline research use case demonstrates how founders who lack a warm network can still build a structured, targeted investor list with fund sizes, thesis alignment, and partner contacts. At $200/month on the Max plan, the cost pays for itself if even one sponsorship deal or investor meeting closes from the outreach. The platform already supports connectors for Gmail, Google Drive, Slack, HubSpot, Ahrefs, Reddit, and more — making it a serious contender for centralized founder workflows. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/

This week, Joe Pulizzi and Robert Rose tackle one of the boldest statements in recent marketing memory. The CEO of Unilever says big brand advertising is dead. Is he right? Or is this a Trojan horse for something much bigger? Big Brand Advertising: Dead or Disguised? When the head of one of the largest consumer goods companies in the world questions traditional brand advertising, it's not a throwaway comment. Joe and Robert unpack what's really happening: Are we witnessing the collapse of mass brand-building? Or is this a pivot toward creator-led, performance-driven, and retail media strategies? Is "brand is dead" just cover for short-term earnings pressure?     Facebook's Creator Monetization Shift Next, the hosts examine Facebook and its evolving creator monetization programs. Here's the surprising part: most of the creators earning real money aren't in the U.S. or Europe. What does that signal? Is Facebook optimizing for lower-cost content markets? Is this about global growth or cheaper engagement? Does this open the door to more synthetic and AI-generated content? Joe and Robert debate what this means for marketers investing in creator partnerships and for Western creators assuming they're at the center of platform economics. AI Actors, Hollywood, and Trademarking Yourself A fascinating conversation between Matthew McConaughey and Timothée Chalamet sparks a larger discussion: what happens when AI enters the craft of acting? Will we eventually see: Best AI Actor? Best Synthetic Film? Or entirely new creative categories? Joe raises a bigger issue for marketers and creators: should you trademark your name, image, and likeness? As AI-generated replicas improve, protecting your identity may become a business necessity rather than a vanity move. Winners and Losers Winner: The Creator Betting on Landline Phones Joe highlights a surprising trend: a creator sells old-school landline phones. Marketing Loser: U.S. Men's Hockey Robert explains why the United States men's national ice hockey team earns this week's marketing "L." Brand positioning, expectations, and execution all come under scrutiny. Rants, Raves, and Heated Debate Robert dives deep into Anthropic and its recent moves around AI safety. Is the company quietly shifting away from its core safety mission? Then things get heated. Joe and Robert spar over an article by Matt Shumer on the future of AI. Is exponential acceleration inevitable? Are we underestimating the timeline? Or overhyping the disruption? Subscribe and Follow: Follow Joe Pulizzi and Robert Rose on LinkedIn for insights, hot takes, and weekly updates from the world of content and marketing.  ------- This week's sponsor: Did you know that most businesses only use 20% of their data? That's like reading a book with most of the pages torn out. Point is, you miss a lot. Unless you use HubSpot. Their customer platform gives you access to the data you need to grow your business. The insights trapped in emails, call logs, and transcripts.  All that unstructured data that makes all the difference. Because when you know more, you grow more. Visit https://www.hubspot.com/ to hear how HubSpot can help you grow better. ------- Get all the show notes: https://www.thisoldmarketing.com/ Get Joe's new book, Burn the Playbook, at http://www.joepulizzi.com/books/burn-the-playbook/ Subscribe to Joe's Newsletter at https://www.joepulizzi.com/signup/. Get Robert Rose's new book, Valuable Friction, at https://robertrose.net/valuable-friction/  Subscribe to Robert's Newsletter at https://seventhbearlens.substack.com/ ------- This Old Marketing is part of the HubSpot Podcast Network: https://www.hubspot.com/podcastnetwork

Jessica Zwaan joined us on The Modern People Leader for MPL Build's first-ever AMA, alongside Jalene Vandermey-Jackson from Workleap. We talked about what traditional HR mindsets must be let go to become builders, how to collect lightweight employee feedback to help build the right products, and more.----  Downloadable PDF with top takeaways: https://modernpeopleleader.kit.com/episode284Sponsor Links:

Discover how AI is completely transforming sales coaching and why the old methods of manual call reviews are obsolete. Join us as Matt Doyon reveals the exact system that helped Triple Session reach $1M ARR by automating sales feedback.   In this episode of Born in Silicon Valley, we sit down with Matt Doyon, Co-founder and CEO of Triple Session. Matt shares his journey from scaling massive teams at HubSpot to building a revolutionary AI-powered coaching platform. He breaks down why traditional sales tools were failing his teams and how he decided to build a solution that automatically serves up best practice clips for top performers.   We also dive into the realities of running a rapidly growing tech startup from Guadalajara, Mexico. Matt provides incredible insights on evaluating geographical risk, building powerful non-competitive partnerships like their deal with Aircall, and the exact hiring framework he uses to find top-tier talent. Whether you are leading a sales team or building an AI startup, this conversation is packed with actionable takeaways.   Chapters 00:00 Introduction and Background 03:08 Matt Doyon's Journey to Entrepreneurship 05:54 Identifying the Need for Coaching Solutions 11:00 The Role of AI in Sales Coaching 14:12 AI Coaching: Seller Reactions and Insights 19:32 Building an AI-Driven Coaching Platform 21:55 Business Model and Market Positioning 23:26 Growth and Partnership Strategies 27:46 Challenges of Running a Startup in Mexico 28:07 Risk Perspectives in Entrepreneurship 30:50 Challenges in Hiring Qualified Candidates 32:56 Effective Hiring Strategies 37:40 Future of Sales and AI 43:42 Building Interconnected Systems in Business 46:10 Prioritizing Key Roles for Growth   Host: Jake Aaron Villarreal leads the top AI recruitment firm in Silicon Valley, www.matchrelevant.com, uncovering stories of funded startups and going behind the scenes to tell their founders' journeys. If you are growing an AI startup or have a great story to tell, email us at: jake.villarreal@matchrelevant.com

Send a textIn this episode of the Sidecar Sync, Mallory and Amith dive deep into two seismic shifts rocking the AI landscape for associations: the rise of “agent tollgates” in SaaS platforms and the growing security concerns around Model Context Protocol (MCP). Sparked by comments from HubSpot's CEO about monitoring and monetizing agent access to customer data, the conversation explores what happens when vendors start charging for AI agents to access “your” data—and why this may signal a broader shift in the software business model. Amith unpacks why true data ownership matters more than ever and explains how AI data platforms eliminate traditional ETL bottlenecks while preserving control. Then, the duo pivots to MCP security risks, breaking down real-world attack vectors—from prompt injection to supply chain compromises—and offering practical guardrails for safe experimentation. The message is clear: embrace AI boldly, but build with governance, ownership, and security top of mind. 

This episode is brought to you by B2B Better. Richard cut CAC by 27% by ditching billboards and investing in owned content — podcasts, videos, and customer interviews that actually moved the needle. That's exactly the kind of content engine we help B2B service businesses build. If you want a podcast that drives pipeline, not just downloads, visit b2bbetter.com. If you think B2B buying is purely rational, this episode is your wake-up call. In this episode of Pipe Dream, host Jason Bradwell sits down with Richard Dedor, Senior Client Strategist at Vericast, to unpack what a decade of B2C financial services marketing can teach B2B marketers about differentiation, storytelling, and cutting through a commoditised market. Richard's core point is clear: stop overthinking your product and start understanding the emotion behind the buying decision. Every purchase — whether it's a checking account or a six-figure SaaS contract — starts with a pain point. The businesses that win are the ones that lean into that pain and make the buyer the hero. The cheeseburger analogy says it all. McDonald's, In-N-Out, Wendy's — they're all selling the same thing but winning different customers by knowing exactly who they're for. B2B is no different. You don't need a revolutionary product. You need a sharper story built around the right ingredients for the right target market. The conversation gets tactical on CAC reduction. Richard's team cut acquisition costs by 27% by reallocating budget away from vanity spend — billboards chief among them — and investing in owned content instead. Podcasts, videos, webinar series, and customer interviews that spoke directly to real pain points. A billboard reaches everyone and no one. A customer interview that mirrors exactly what a prospect is feeling reaches the right person at the right moment. For B2B marketers dealing with long sales cycles and buying committees, hold the macro message steady and pivot the micro-messaging for each stakeholder in the room. And when compliance is standing between you and a good idea, make them your second-best friend — walk them through the concept one friction point at a time and help them get themselves to yes. People buy with emotion. Even in B2B. Especially in B2B. That's what you should be tapping into. Chapter Markers 00:00 - Introduction: Richard Dedor and a decade in B2C financial services 02:00 - The cheeseburger analogy: differentiation in commoditised markets 04:00 - Growing brand awareness by 50% and bridging it to conversion 06:00 - In-market moments and rare switching windows in financial services 08:00 - What B2B marketers should steal from the consumer playbook 09:00 - Micro-messaging pivots within a stable macro message 10:00 - Cutting CAC by 27%: stop spending on billboards 11:00 - Investing in owned content: podcasts, videos, and customer interviews 13:00 - Testing, killing, and doubling down on what works 14:00 - Working in regulated environments: making compliance your ally 16:00 - How to present ideas to legal and compliance teams 18:00 - Walking compliance through friction points one step at a time 20:00 - The one thing B2B companies get wrong about differentiation 22:00 - People buy with emotion — even in B2B Useful Links Connect with Jason Bradwell on LinkedIn Connect with Richard Dedor on LinkedIn Visit Richard Dedor's website Read Richard's writing on HubSpot and Medium Explore B2B Better and the Pipe Dream Podcast

Hey CX Nation,In this week's episode of The CXChronicles Podcast #278, we welcomed Ryan Wang, Co-Founder & CEO of Assembled based in San Francisco, CA.Industry leaders like Etsy, Robinhood, and Stripe trust Assembled to provide customer-facing AI agents and workforce planning at scale. Assembled automatically resolves millions of interactions through chat, email, and phone while optimizing staffing for hundreds of thousands of support professionals. Their mission is to elevate customer support through AI-powered software that makes life easier for customers and employees.In this episode, Ryan and Adrian chat through the Four CX Pillars: Team, Tools, Process & Feedback. Plus share some of the ideas that his team think through on a daily basis to build world class customer experiences.**Episode #278 Highlight Reel:**1. Building a high-performing team in the AI age 2. Shift towards AI-driven skill sets in the workforce 3. Creating a culture of continuous learning  4. Focusing on customer feedback early & often 5. Keeping your team lean & flexible as you scale Click here to learn more about Ryan WangClick here to learn more about AssembledHuge thanks to Ryan for coming on The CXChronicles Podcast and featuring his work and efforts in pushing the customer experience & contact center space into the future. For all of our Apple & Spotify podcast listener friends, make sure you are following CXC & please leave a 5 star review so we can find new members of the "CX Nation". You know what would be even better?Go tell your friends or teammates about CXC's custom content, strategic partner solutions (Hubspot, Intercom, & Freshworks) & On-Demand services & invite them to join the CX Nation, a community of 15K+ customer focused business leaders!Want to see how your customer experience compares to the world's top-performing customer focused companies? Thanks to all of you for being apart of the "CX Nation" and helping customer focused business leaders across the world make happiness a habit!Reach Out To CXC Today!Support the showContact CXChronicles Today Tweet us @cxchronicles Check out our Instagram @cxchronicles Click here to checkout the CXC website Email us at info@cxchronicles.com Remember To Make Happiness A Habit!!

This episode is brought to you by B2B Better. Ross helps businesses prove that their marketing is driving revenue — and that's exactly the problem we help B2B service businesses solve with video-first podcasts. We build content systems that don't just generate attention, they generate pipeline your sales team can actually point to. Visit b2bbetter.com to see how we do it differently. Your thought leadership campaign is running. People are watching, listening, and engaging — but when your CFO asks if it's actually driving revenue, you've got nothing to say. In this episode of Pipe Dream, host Jason Bradwell sits down with Ross Breckenridge, Managing Director of Breckenridge and HubSpot Platinum Partner, to tackle the attribution problem that almost every B2B marketing team has but nobody wants to admit. Ross's core point is clear: this isn't a marketing problem. It's a business problem. Until your marketing, sales, and customer success teams are operating from a single unified strategy and a single tech stack, you'll never get the visibility you need. The conversation starts where Ross always starts with clients: customer journey mapping. Before you touch an attribution model, you need to understand where each content asset sits in the buying process — lead gen, nurture, sales enablement, or renewals. Most companies skip this step and end up measuring the wrong things entirely. From there, Ross unpacks the dark funnel and explains why the HubSpot Campaigns tool is the home of the marketer's attribution reporting. Bundle your content assets into one campaign, track who was created as a new contact and who was simply influenced along the way, and map that all the way through to closed-won revenue — including renewals that happen two years after someone first engaged. But none of it works if sales is living in a different system. The connection between content and revenue only becomes visible when marketing, sales, and customer success are using the same tools and held to the same SLAs. One client found that leaving a lead for more than 48 hours dropped their conversation rate from 70% to 20%. That kind of clarity only exists when everyone is looking at the same data. If you're tired of defending your content budget with correlation and vibes, this episode gives you the framework to fix it for good. Chapter Markers 00:00 - Introduction: Ross Breckenridge and Breckenridge Agency 02:00 - HubSpot onboarding, integrations, and the RevOps focus 04:00 - Is attribution a tools problem, a strategy problem, or the wrong metrics? 05:00 - Customer journey mapping as the foundation of all attribution 06:00 - Picking one attribution model and staying consistent 08:00 - The dark funnel: what it is and how HubSpot brings it to light 10:00 - Content-sourced vs content-influenced pipeline: the key difference 11:00 - The HubSpot Campaigns tool as the marketer's attribution home 13:00 - Connecting content consumption to leads, deals, and closed revenue 15:00 - Why attribution is a business problem, not a marketing problem 16:00 - Building the business case to get sales and CS on the same page 17:00 - SLAs, shared accountability, and the 48-hour lead follow-up rule 19:00 - Working in silos vs being more than the sum of your parts 21:00 - AI, buyer research, and why being genuinely helpful never changes 23:00 - Where to find Ross and learn more about Breckenridge Useful Links Connect with Jason Bradwell on LinkedIn Connect with Ross Breckenridge on LinkedIn Visit Breckenridge — HubSpot Platinum Partner and RevOps specialists Email Ross directly at ross@breckenridgeagency.com Explore the HubSpot Campaigns tool for attribution reporting Explore B2B Better website and the Pipe Dream podcast

¿Marketing tiene la culpa? ¿O ventas?La respuesta está en los datos: el 63% de las empresas en LATAM los tiene completamente desconectados.En este episodio Dan Macías y Teresa analizan el reporte de HubSpot "Marketing y Ventas en LATAM: qué está frenando el crecimiento 2026", basado en 3 000 llamadas con líderes de la región.✅ El error #1 que hace que tu empresa pierda leads en el camino✅ Por qué tener herramientas desconectadas entre marketing y ventas te cuesta más de lo que crees (y cómo empezar a conectarlas HOY)✅ Cómo saber qué está pasando con tus leads de principio a fin sin depender de reportes manuales ni de WhatsApp✅ El sistema que Dan y Teresa implementaron para automatizar el proceso del call confirmer y ahorrar 2-3 horas diarias✅ Por qué el 33% de las empresas implementa tecnología ANTES de tener un proceso definido (y por qué eso es un error grave)Este episodio es para ti si eres líder comercial, director de ventas o dueño de empresa y sientes que marketing y ventas parecen dos planetas distintos en tu organización, los leads se pierden sin saber por qué y nadie tiene visibilidad real de qué está pasando con el pipeline.─────────────────────────────────

AI is shifting from assistant to teammate — and that changes everything. In this episode of Today in Tech, Keith Shaw sits down with Karen Ng, EVP of Product at HubSpot, to break down what “hybrid AI teams” actually are, how companies are deploying AI agents alongside humans, and what that means for your day-to-day work. You'll hear why hybrid teams are more than just “using AI tools,” how organizations should onboard agents like new hires, and why governance, guardrails, and trust are the difference between real adoption and risky chaos. Karen shares practical examples (including AI resolving a majority of support tickets), plus a simple three-phase blueprint for getting started: clean your data, focus humans on what they do best, and automate the right tasks. If you're wondering whether AI agents will count as headcount, how much autonomy is too much, and what skills matter beyond prompt engineering — this conversation is your roadmap. In this episode: What a hybrid human + AI team really looks like “Supercharged humans” vs. basic AI usage Where agents work best (and where risk spikes) Onboarding, observability, and human-in-the-loop guardrails Trust, outcomes, and why AI doesn't need to be perfect to be valuable What employees should do now to stay ahead

In this episode I explore how to elevate your LinkedIn presence with The Elevate Map - a practical, human-centred framework that helps you show up on LinkedIn with clarity and confidence. It's iterative by design: a cycle you return to as your goals, roles, teams or strategic priorities evolve. Some elements may already be familiar; others might be the missing piece that makes LinkedIn feel purposeful rather than performative.ResourcesRead the full article on this topic: https://thinkbespoke.com.au/elevate-your-linkedin-presence/Sign up to my newsletter (sent via Hubspot) and get your free LinkedIn Profile Checklist Follow me on LinkedIn https://www.linkedin.com/in/karenhollenbach/Think Bespoke's Knowledge Basehttps://thinkbespoke.com.au/insights-blog-2/Elevate with KPH (Substack) https://thelinkedinmarketer.substack.com/

 Partnership marketing requires more than co-branded campaigns.In this Belly2Belly episode, Bill Kenney talks with Christi Williams from ‪HubSpot about defining a joint value proposition, aligning on shared KPIs, clarifying swim lanes, and building recurring partnership frameworks that drive measurable growth.Christi shares practical advice on verticalization, accountability, and avoiding the “one-and-done” trap in ecosystem marketing.Christi Williamshttps://www.linkedin.com/in/christikeating/ ---Feel free to contact us with any questionsBill Kenney, bill@meetroi.comMEET, https://meetroi.com/ 

In this episode of the Grow A Small Business Podcast, host Troy Trewin interviews Gail Kasper, founder of Gail Kasper LLC, shares her journey from being fired and starting with no money to building a thriving speaking and training business. She reveals how authenticity became her competitive edge and how mastering professional sales transformed her income from free gigs to $25,000 keynotes and $600K contracts. Gail breaks down the power of referrals, structured sales systems, and strong core values in scaling sustainably. She also opens up about leadership lessons, hiring mistakes, and the mindset required to handle setbacks. This conversation is packed with practical insights for entrepreneurs who want real business success without losing who they are. Why would you wait any longer to start living the lifestyle you signed up for? Balance your health, wealth, relationships and business growth. And focus your time and energy and make the most of this year. Let's get into it by clicking here. Troy delves into our guest's startup journey, their perception of success, industry reconsideration, and the pivotal stress point during business expansion. They discuss the joys of small business growth, vital entrepreneurial habits, and strategies for team building, encompassing wins, blunders, and invaluable advice. And a snapshot of the final five Grow A Small Business Questions: What do you think is the hardest thing in growing a small business? According to Gail Kasper of Gail Kasper LLC, the hardest thing in growing a small business is dealing with failure and having the resilience to keep going despite repeated setbacks. She explains that as an entrepreneur you get "hit in the face" many times through failed projects, wrong decisions, or ideas that don't take off, and the real challenge is not letting those moments stop you. Instead of quitting, she believes the key is to keep pushing forward, learn from mistakes, take action, and stay committed even when things feel uncertain or discouraging. What's your favorite business book that has helped you the most? According to Gail Kasper, her favorite business book that has helped her the most is Atomic Habits by James Clear. She values its focus on small, consistent disciplines rather than just chasing big end goals, emphasizing that daily incremental improvements create real momentum. For Gail, the book reinforces that tiny wins build confidence, strengthen habits, and ultimately drive long-term business success. Are there any great podcasts or online learning resources you'd recommend to help grow a small business? According to Gail Kasper, she recommends podcasts and learning resources that strengthen mindset, sales, and brain-based performance, including Huberman Lab for its science-backed insights on stress and peak performance, and The Ed Mylett Show by Ed Mylett for its focus on growth, vulnerability, and high-level thinking. She values resources that blend psychology, communication, and practical application, believing that understanding how people think—especially in sales and leadership—gives small business owners a strong competitive edge. What tool or resource would you recommend to grow a small business? One highly recommended tool that Gail Kasper often points small business owners toward is HubSpot CRM, because it helps organize leads, track sales activity, automate follow-ups, and manage customer data in one place — all without needing a big tech team. Gail emphasizes that having a system that captures conversations, schedules reminders, and analyzes what's working versus what's not can dramatically improve consistency in sales and client relationships, which is essential for growth. If you're just getting started, HubSpot's free tier gives you powerful CRM basics, and you can scale into its marketing and automation tools as your business expands. What advice would you give yourself on day one of starting out in business? According to Gail Kasper, the advice she would give herself on day one of starting out in business is simple: move and take action. When she was suddenly on her own with no money in the bank, she learned that inaction is the real danger, not mistakes. She would remind herself to stay logical instead of emotional, keep pushing forward even when uncertain, and allow herself to fall and learn along the way, because consistent action is what ultimately creates momentum and success.   Book a 20-minute Growth Chat with Troy Trewin to see if you qualify for our upcoming course. Don't miss out on this opportunity to take your small business to new heights! Enjoyed the podcast? Please leave a review on iTunes or your preferred platform. Your feedback helps more small business owners discover our podcast and embark on their business growth journey.     Quotable quotes from our special Grow A Small Business podcast guest: Authenticity is the foundation of confidence and the gateway to real growth - Gail Kasper Failure is not the signal to stop, it is the signal to adjust and move forward - Gail Kasper Failure is not the signal to stop, it is the signal to adjust and move forward - Gail Kasper      

In this episode of the CPQ Podcast, we sit down with Dustin Anglen, Strategic Partnerships Manager at PandaDoc, to discuss how PandaDoc CPQ supports faster quoting for SMB teams (roughly 5–500 employees). PandaDoc is widely known for proposals and eSignature, and Dustin explains why CPQ is a natural extension—especially for organizations that want a practical, easy-to-administer approach without heavy configuration overhead. We cover where PandaDoc CPQ fits best (including SaaS, software & technology, professional services, and education) and how customers typically use it alongside their CRM. Dustin outlines PandaDoc's API-forward SaaSapproach and its key integrations with HubSpot, Pipedrive, and Salesforce. We also discuss what's available today—and what's still evolving—such as ERP connectivity (currently not a standard integration, with MVP work underway) and common customer expectations around implementation, which is often 8–12 weeks. On the capability side, Dustin shares the top requests he sees from the market: product configuration, contract-based pricing, and CRM integration. We talk about product structure support (including bundles), pricing flexibility across segments and regions, usage-based pricing, and how PandaDoc positions its CPQ as a rules engine that is largely no-code (with options for more advanced logic when needed). We also dig into PandaDoc's AI direction—template generation, OCR and document intelligence, metadata-driven automation, and an admin-focused AI feature for helping set up product and pricing rules (currently in testing, with broader availability expected later this year). You'll also hear a few personal moments from Dustin—from his early career in the Salesforce ecosystem (including starting at Apttus in 2014), to an unexpected chapter running a beekeeping business in Santa Barbara, to his passion for freediving near San Diego. A PandaDoc CPQ free trial is available on PandaDoc's website.

In this episode, we tackle a big question pest control owners face: should you run everything inside your pest control software—or use a dedicated CRM like HighLevel or HubSpot for lead management and marketing? We break down the pros and cons of major platforms including PestPac, FieldRoutes, Housecall Pro, BrioStack, Jobber, and GorillaDesk, and explain why the real key is building internal workflows first, then designing automation that supports your team—without forcing everyone to live with sub-standard workarounds.If you want help building a workflow-first pipeline, automation follow-up, and a system that connects lead generation to real sales results, reach out anytime:Casey Lewiscasey@rhinopros.com(925) 464-8383Follow and subscribe at the following links:https://www.youtube.com/@RhinoPestControlMarketinghttps://www.facebook.com/rhinopestcontrolmarketingLeave us a review on Google:https://g.page/r/CT9-E84ypVI0EBM/review

Companies like Meta and other social platforms are facing serious scrutiny over the effects of social media on mental health, teens, misinformation, and society at large. Lawmakers are circling. Hearings are happening. Headlines are dramatic. But is this real regulatory momentum… or political theater? Joe and Robert debate: Whether meaningful regulation is actually possible What history tells us about tech antitrust moments And what marketers should prepare for if something does change Are we watching the beginning of a structural shift, or just another PR cycle? OpenAI Buys OpenClaw OpenAI makes another strategic move, acquiring OpenClaw. Smart vertical integration or signs of pressure? Joe and Robert explore: What this signals about OpenAI's long-term positioning If this move strengthens the moat or exposes vulnerability Desperate land grab or calculated chess move? Apple Moves into Video. Too Late? Apple continues expanding its footprint in video podcasts and entertainment. But in a world dominated by established streaming giants and creator-driven platforms, is Apple behind? The discussion covers: Apple's historical pattern of entering late and winning anyway Whether hardware advantage still matters If brand trust gives Apple an edge in a saturated market What this means for content creators and marketers Is Apple playing the long game… or missing the moment? Marketing Winners and Losers Winners Joe shares a win from Surfside and what "winning" looks like in Key West. Sometimes the lesson isn't scale. It's positioning, timing, and owning a moment. Losers Robert discusses the Ring backlash and how they just didn't read the room. Rants and Raves Robert's Rant The evolving role of the AI creator. Is the curator the new role? Joe's Rave Differentiation is not louder messaging. It's clearer identity. In a world drowning in synthetic sameness, the brands and creators who stand for something specific will win. As always, Joe and Robert cut through the noise so you can focus on what matters. Subscribe. Share. And don't miss this one. Subscribe and Follow: Follow Joe Pulizzi and Robert Rose on LinkedIn for insights, hot takes, and weekly updates from the world of content and marketing.  ------- This week's sponsor: Did you know that most businesses only use 20% of their data? That's like reading a book with most of the pages torn out. Point is, you miss a lot. Unless you use HubSpot. Their customer platform gives you access to the data you need to grow your business. The insights trapped in emails, call logs, and transcripts.  All that unstructured data that makes all the difference. Because when you know more, you grow more. Visit https://www.hubspot.com/ to hear how HubSpot can help you grow better. ------- Get all the show notes: https://www.thisoldmarketing.com/ Get Joe's new book, Burn the Playbook, at http://www.joepulizzi.com/books/burn-the-playbook/ Subscribe to Joe's Newsletter at https://www.joepulizzi.com/signup/. Get Robert Rose's new book, Valuable Friction, at https://robertrose.net/valuable-friction/  Subscribe to Robert's Newsletter at https://seventhbearlens.substack.com/ ------- This Old Marketing is part of the HubSpot Podcast Network: https://www.hubspot.com/podcastnetwork

Diane Sadowski-Joseph, Co-Founder of Clarinet, joined us on The Modern People Leader. We talked about why most AI adoption stalls at “talking the talk,” how to choose the right AI use cases using the “trifecta” and the Five Frictions framework, and how “click cutters” can unlock compounding gains by removing cognitive and workflow friction.----  Here's everything Diane referenced: https://modernpeopleleader.kit.com/fivefrictionsSponsor Links:

Lula rebuilt property maintenance from the ground up by solving a fundamental problem: property managers spend 40% of their time coordinating maintenance with zero visibility into work order status. After pivoting from a B2C app when they discovered landlords were their actual users, Bo Lais and his team made a critical insight—deep PMS integration wasn't a feature, it was the entire go-to-market strategy. Today, Lula's 9,000-contractor network processes 1,000 work orders daily across 50 markets, performing 30 HVAC replacements per day at scale that enables direct manufacturer relationships. Now they're commercializing their internal tech stack as Foresight, a standalone SaaS platform launching Q1. In this episode of BUILDERS, Bo breaks down the strategic decisions behind building integrations as distribution, using network density to create pricing advantages competitors can't match, and knowing when to productize your internal tools. Topics Discussed: Why the B2C to B2B pivot happened after discovering usage patterns, not market research How PMS integration eliminated "swivel chair" friction and became the primary distribution channel Strategic partnership depth over breadth: enabling co-selling with AppFolio, Buildium, Yardi rather than partner proliferation The 250-door threshold where maintenance coordination breaks and technology becomes necessary Network density economics: 30 daily HVAC replacements creating leverage for direct manufacturer negotiations and flat-rate service catalogs The decision framework for commercializing Foresight based on upstream customer advisory group feedback Maintaining discipline around ICP when sales teams naturally want to expand GTM Lessons For B2B Founders: System of record integration is your distribution strategy, not a feature: Lula's standalone app created adoption friction because property managers refused to work outside their PMS. Bo's realization: "They need everything to live in their system of record...They don't want swivel chair. And then providing that real time visibility throughout the entire life cycle of the work order was really valuable because prior to that they assign it to a vendor, and then they cross their fingers and hope that it gets done." The integration solved both adoption friction and delivered continuous visibility their workflow demanded. For B2B founders: if your users live in Salesforce, HubSpot, or vertical-specific platforms all day, your integration strategy IS your distribution strategy—build there first, not alongside. Strategic partnerships require enablement infrastructure, not just signed contracts: Bo's approach rejects partnership sprawl: "It's not about stacking on another 10 partnerships, it's about how do we go deeper and enable those partners to co-sell with us and talk about the value props that together we can provide." This means building co-selling toolkits, joint value propositions, and partner success metrics. For B2B founders: one partnership where the partner's sales team actively sells your solution beats ten partnerships where you're just listed in a marketplace. Invest in making partners successful sellers, not collecting logos. ICP discipline requires sales team enforcement mechanisms, not just definitions: Lula knew their ICP but struggled with execution. Bo learned "it's one thing when we understood who our ICP was, but then it's a whole nother thing to adhere to that and get the sales team to adhere to that ICP." The specificity matters: residential (not multifamily), single-family, 250+ doors (where coordination breaks), capped at several thousand doors (before enterprise needs diverge). For B2B founders: document your ICP, but also build the compensation structures, deal approval processes, and CRM workflows that prevent sales from chasing deals outside the sweet spot—even when quota pressure hits. Message outcomes customers measure, not the technology delivering them: Bo's AI framing: "They care about the outcomes, right? If we're able to move the needle on the outcomes and provide a better experience for residents by automating communication, automating the time to schedule, automating the time to get resolution...it's not the how, it's the result." Lula's AI eliminates truck rolls through upfront troubleshooting and improves one-trip resolution rates—that's what property managers track. For B2B founders: if your customer's boss asks "how's that new tool working," they answer with metrics they're held accountable for (resolution time, truck rolls, resident satisfaction), not "it uses AI." Lead with those metrics. Productize internal tools when customer advisory groups request them and you have defensible advantages: Lula commercialized Foresight after upstream customers specifically asked for their tech during advisory sessions. Bo's competitive moat thinking: "Everyone else thinks they're going to do it better with the AI and automation they have. But our competitive moat is that our on-demand network is built inside this AI work order management system. And because of the scale of our network and the buying power, we can provide instant quotes for a lot of services...our competitors that are just doing software don't have this network of contractors nationwide." For B2B founders expanding product lines: customer pull plus operational advantages competitors can't replicate (Lula's contractor density, manufacturer relationships, 1,000 daily work orders of training data) create viable new products. Without both, you're just building undifferentiated software. // Sponsors: Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe. www.GlobalTalent.co // Don't Miss: New Podcast Series — How I Hire Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role. Subscribe here: https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM

Lenny's Podcast: Product | Growth | Career ✓ Claim : Read the notes at at podcastnotes.org. Don't forget to subscribe for free to our newsletter, the top 10 ideas of the week, every Monday --------- Brian Halligan co-founded HubSpot, ran it as CEO for about 15 years, and now coaches Sequoia's fastest-growing founders as their in-house CEO coach.We discuss:1. His LOCKS framework for evaluating founders2. Why you should build your team like the 2004 Red Sox3. Why hiring “spicy” candidates beats consensus picks4. Why enterprise sales will be the last white-collar job AI replaces5. Some of my favorite “Halliganisms”—Brought to you by:Sentry—Code breaks, fix it faster: http://sentry.io/lennyDatadog—Now home to Eppo, the leading experimentation and feature flagging platform: https://www.datadoghq.com/lennyWorkOS—Modern identity platform for B2B SaaS, free up to 1 million MAUs: https://workos.com/lenny—Episode transcript: https://www.lennysnewsletter.com/p/sequoia-ceo-coach-why-its-never-been—Archive of all Lenny's Podcast transcripts: https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0—Where to find Brian Halligan• X: https://x.com/bhalligan• LinkedIn: linkedin.com/in/brianhalligan• Delphi: https://www.delphi.ai/bhalligan• Podcast: https://sequoiacap.com/series/long-strange-trip—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Brian Halligan(03:56) The perpetual state of constructive dissatisfaction(05:25) Coaching CEOs(07:49) The art of interviewing and hiring(11:21) Getting the most out of reference calls(13:10) Homegrown talent vs. big company hires(16:31) Traits of successful CEOs(19:40) Brian's LOCKS framework for evaluating founders(21:34) Are great CEO's born or made?(23:41) Giving effective feedback(25:54) The future of go-to-market strategies(31:56) Understanding forward deployed engineers(34:17) How the CEO role has evolved over the last 20 years(38:10) Halliganisms(01:01:18) The CEO's role in scaling a company(01:02:41) Lightning round and final thoughts—Referenced:• Dev Ittycheria on LinkedIn: https://www.linkedin.com/in/dittycheria• HubSpot: https://www.hubspot.com• Parker Conrad on LinkedIn: https://www.linkedin.com/in/parkerconrad• McKinsey & Company: https://www.mckinsey.com• Brian Chesky's new playbook: https://www.lennysnewsletter.com/p/brian-cheskys-contrarian-approach• Jensen Huang on LinkedIn: https://www.linkedin.com/in/jenhsunhuang• Winston Weinberg on LinkedIn: https://www.linkedin.com/in/winston-weinberg• James Cadwallader on LinkedIn: https://www.linkedin.com/in/jsca• Gabriel Stengel on LinkedIn: https://www.linkedin.com/in/gabestengel• He saved OpenAI, invented the “Like” button, and built Google Maps: Bret Taylor on the future of careers, coding, agents, and more: https://www.lennysnewsletter.com/p/he-saved-openai-bret-taylor• Scaling Entrepreneurial Ventures: https://orbit.mit.edu/classes/scaling-entrepreneurial-ventures-15.392• OpenClaw: https://openclaw.ai• Ruth Porat on LinkedIn: https://www.linkedin.com/in/ruth-porat• Mike Krzyzewski: https://goduke.com/sports/mens-basketball/roster/coaches/mike-krzyzewski/4159• Dalai Lama's 18 Rules for Living: https://www.prm.nau.edu/prm205/Dalai-Lama-18-rules-for-living.htm• Zigging vs. zagging: How HubSpot built a $30B company | Dharmesh Shah (co-founder/CTO): https://www.lennysnewsletter.com/p/lessons-from-30-years-of-building• Kareem Amin on LinkedIn: https://www.linkedin.com/in/kareemamin• Glassdoor: https://www.glassdoor.com• Tobi Lütke's leadership playbook: Playing infinite games, operating from first principles, and maximizing human potential (founder and CEO of Shopify): https://www.lennysnewsletter.com/p/tobi-lutkes-leadership-playbook• Katie Burke on LinkedIn: https://www.linkedin.com/in/katie-burke-965767a• Jerry Garcia: https://en.wikipedia.org/wiki/Jerry_Garcia• Bob Weir: https://en.wikipedia.org/wiki/Bob_Weir• Phil Lesh: https://en.wikipedia.org/wiki/Phil_Lesh• Ron “Pigpen” McKernan: https://en.wikipedia.org/wiki/Ron_%22Pigpen%22_McKernan• Marc Andreessen: The real AI boom hasn't even started yet: https://www.lennysnewsletter.com/p/marc-andreessen-the-real-ai-boom• The American Revolution: https://www.pbs.org/kenburns/the-american-revolution• Delphi: https://www.delphi.ai• Sonos: https://www.sonos.com• Yamini Rangan on LinkedIn: https://www.linkedin.com/in/yaminirangan• The Boston Red Sox: https://www.mlb.com/redsox—Recommended book:• Marketing Lessons from the Grateful Dead: What Every Business Can Learn from the Most Iconic Band in History: https://www.amazon.com/Marketing-Lessons-Grateful-Dead-Business/dp/0470900520—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

This episode is brought to you by B2B Better. Most owned media audits produce 50-page reports with vague recommendations and zero next steps. We give you four questions, 90 minutes, and a clear decision: kill, fix, or scale.  If your podcast has downloads but no pipeline, this episode shows you how to audit your entire owned media strategy in 90 minutes and walk away knowing what's broken and how to fix it. Host Jason Bradwell breaks down the Four R Framework — Reach, Resonance, Revenue, and Repeatability — plus a decision tree to kill, fix, or scale. Jason's core point is clear: most owned media audits are useless. They take weeks and produce reports filled with vanity metrics. Today you get four questions that reveal everything in 90 minutes. Reach is the least important. It can be bought. If you turn off ads tomorrow, what happens? That tells you whether you have real distribution or rented attention. Resonance is where it gets interesting. Jason would rather have 100 views at 85% consumption than 10,000 views at 20%. The 100 who watch the whole thing are deeply engaged. The 10,000 who clicked away were never going to buy. For video, 50% consumption is good, 70% is excellent. For podcasts, 50% is good, 75% is excellent. Revenue asks: is your strategy generating commercial results? The benchmark: 30 to 50% of closed deals should have at least one content touch. Content-influenced deals should close 20 to 30% faster. If attribution is weak, you have an activation problem, not a content problem. Repeatability determines if your strategy works long term. You should produce content four to six weeks in advance without overtime. If you're in hero mode with one person holding everything together, you need systems, not heroics. The decision tree is simple. High reach but low resonance? Fix the content. Low reach but high resonance? Scale distribution. Low everything? Kill it. High everything but low repeatability? Fix operations first. Chapter Markers 00:00 - Why most owned media audits are useless 01:00 - The Four R Framework and why reach matters least 02:00 - Resonance and consumption rate benchmarks 03:00 - 100 views at 85% beats 10,000 at 20% 04:00 - Revenue attribution and pipeline influence 05:00 - Direct vs influenced vs self-reported attribution 06:00 - Repeatability and sustainability benchmarks 07:00 - Hero mode vs documented processes 08:00 - The decision tree: kill, fix, or scale 09:00 - High reach but low resonance means fix content 10:00 - What to do on Monday morning based on your audit 11:00 - Fix activation by emailing sales directly 12:00 - Four questions, 90 minutes, one action 13:00 - Get the full audit template with benchmarks Useful Links Connect with Jason Bradwell on LinkedIn Listen to Pipe Dream on Podbean Explore ABM reporting in HubSpot for tracking accounts touched Explore B2B Better website and the Pipe Dream podcast 

Hey CX Nation,In this CXWeekly Update episode #277 we walk through ideas, goals & CTAs the team at CXC has been focused on, not only internally but from the learnings we're being exposed to from clients & strategic partners on a regular basis. In this episode we walk through a few emerging trends around how AI is impacting the future of Sales, CX, Customer Success & Support + the future of work. Thanks to our friends at GoTo, Intercom & TriNet for supplying some amazing market reports that fuel this week's episodes. They collectively went out & interviewed & surveyed thousands of business leaders from across the world to see where they are in their AI foundation building efforts. Click here for GoTo Pulse of Work Report 2025Click here for Intercom Customer Service Transformation Report 2026Click here for Tri-Net State of Workplace Report 2025Don't worry we have a ton of amazing brand new guest interviews & episodes coming down the pipeline.We're also working on new forms & mediums of customer focused business content -- including my 2nd book "Make Happiness A Habit" that we are launching in the New Year. We've also been building a few new podcasts behind the scenes to take all that we've learned with CXCP & start finding other podcast areas ripe for more content. A big part of CXC's mission is to continue creating valuable customer & employee focused business leader content, including CXWeekly updates like this that are digestible, actionable & most importantly entertaining. The CXChronicles Podcast is approaching a huge milestone in the upcoming months that most podcasts will never achieve. We closing in on 300+ episodes of customer focused business content from incredible Founders & Executives from all over the world. CXC is partnered with several leading software & technology providers including Hubspot, Intercom, Freshworks, & several others who might be the difference in your CX/EX performance moving forward. We provide our clients with audits, assessments & scorecards and we provide custom CTAs centered around your content engine to drive CX/EX health, utilization & health performance for our partner solutions (Hubspot, Intercom, Freshworks), & on-demand managed services (partner led implementation, utilization performance & training for several of our partner solutions).If you enjoy The CXChronicles Podcast, stop by your favorite podcast player and leave us a review today.You know what would be even better?Go tell one of your friends or teammates about CXC's content, CX/CS/RevOps services, our customer & employee focused community & invite them to join the CX Nation!For you non-readers, go check out the CXChronicles Youtube channel to see our customer & employee focused video content & short-reel CTAs to improve your CX/CS/RevOps performance today (politely go smash that subscribe button).Contact us anytime to learn more about CXC at INFO@cxchronicles.com and ask us about how we can help your business & team make customer happiness a habit now!Reach Out To CXC Today!Support the showContact CXChronicles Today Tweet us @cxchronicles Check out our Instagram @cxchronicles Click here to checkout the CXC website Email us at info@cxchronicles.com Remember To Make Happiness A Habit!!

In this episode of The Digital Marketing Podcast, Daniel Rowles sits down with Kipp Bodnar, CMO of HubSpot, to discuss what may be the most disruptive year in marketing history. Kipp believes that 2026 could represent the biggest single wave of change our industry has ever seen. Weeks feel like months. Channels are fragmenting. Discovery is shifting. AI agents are entering workflows. And traditional attribution models are starting to break down. From Answer Engine Optimisation to AI agents, rising ad costs to workflow automation, this conversation explores how marketers can stay ahead when the pace of change is accelerating. In This Episode: Why 2026 may be the biggest year of change in marketing history Kipp explains why discovery, personalisation and team workflows are being reshaped simultaneously. Answer Engine Optimisation vs traditional SEO The shift from short keyword queries to ultra long-tail, conversational prompts of 40 to 60 words changes everything. Mentions vs citations in AI search Why brand visibility in ChatGPT, Gemini and Claude is more complex than link-based SEO ever was. The first mover advantage in AI discovery Early adopters can make exponential gains because competition is still low and optimisation is immature. Why AI agents are thriving in customer service but lagging in marketing Marketing problems are less formulaic and more complex, making agent adoption slower but highly promising. The practical AI workflow hack every marketer should try Record yourself completing a repetitive task, upload it to Google Gemini, and ask how to automate it. A simple but powerful shortcut to AI adoption Why attribution is becoming harder again The "golden age" of clean click-to-conversion tracking is fading as AI intermediates discovery. Rising ad costs and the need for new growth channels With paid media inflation increasing, marketers must adopt emerging channels such as AEO and AI-enabled creative optimisation. The importance of strategic conviction AEO cannot be treated as a side project. It must be embedded as a core capability. HubSpot's approach to AI and context Positioning HubSpot as the context layer for AI, enabling agents and assistants to work from real customer data. Key Takeaways: Discovery is changing faster than most organisations are adapting. Answer Engine Optimisation requires different content structures, including FAQs and machine-friendly formatting. Early adoption in AI search offers outsized returns. AI-assisted workflows are often more impactful than fully autonomous agents in marketing today. Marketing teams must bake experimentation and innovation into daily operations. The biggest risk is not AI itself, but failing to evolve working practices alongside it.

Brian Halligan co-founded HubSpot, ran it as CEO for about 15 years, and now coaches Sequoia's fastest-growing founders as their in-house CEO coach.We discuss:1. His LOCKS framework for evaluating founders2. Why you should build your team like the 2004 Red Sox3. Why hiring “spicy” candidates beats consensus picks4. Why enterprise sales will be the last white-collar job AI replaces5. Some of my favorite “Halliganisms”—Brought to you by:Sentry—Code breaks, fix it faster: http://sentry.io/lennyDatadog—Now home to Eppo, the leading experimentation and feature flagging platform: https://www.datadoghq.com/lennyWorkOS—Modern identity platform for B2B SaaS, free up to 1 million MAUs: https://workos.com/lenny—Episode transcript: https://www.lennysnewsletter.com/p/sequoia-ceo-coach-why-its-never-been—Archive of all Lenny's Podcast transcripts: https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0—Where to find Brian Halligan• X: https://x.com/bhalligan• LinkedIn: linkedin.com/in/brianhalligan• Delphi: https://www.delphi.ai/bhalligan• Podcast: https://sequoiacap.com/series/long-strange-trip—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Brian Halligan(03:56) The perpetual state of constructive dissatisfaction(05:25) Coaching CEOs(07:49) The art of interviewing and hiring(11:21) Getting the most out of reference calls(13:10) Homegrown talent vs. big company hires(16:31) Traits of successful CEOs(19:40) Brian's LOCKS framework for evaluating founders(21:34) Are great CEO's born or made?(23:41) Giving effective feedback(25:54) The future of go-to-market strategies(31:56) Understanding forward deployed engineers(34:17) How the CEO role has evolved over the last 20 years(38:10) Halliganisms(01:01:18) The CEO's role in scaling a company(01:02:41) Lightning round and final thoughts—Referenced:• Dev Ittycheria on LinkedIn: https://www.linkedin.com/in/dittycheria• HubSpot: https://www.hubspot.com• Parker Conrad on LinkedIn: https://www.linkedin.com/in/parkerconrad• McKinsey & Company: https://www.mckinsey.com• Brian Chesky's new playbook: https://www.lennysnewsletter.com/p/brian-cheskys-contrarian-approach• Jensen Huang on LinkedIn: https://www.linkedin.com/in/jenhsunhuang• Winston Weinberg on LinkedIn: https://www.linkedin.com/in/winston-weinberg• James Cadwallader on LinkedIn: https://www.linkedin.com/in/jsca• Gabriel Stengel on LinkedIn: https://www.linkedin.com/in/gabestengel• He saved OpenAI, invented the “Like” button, and built Google Maps: Bret Taylor on the future of careers, coding, agents, and more: https://www.lennysnewsletter.com/p/he-saved-openai-bret-taylor• Scaling Entrepreneurial Ventures: https://orbit.mit.edu/classes/scaling-entrepreneurial-ventures-15.392• OpenClaw: https://openclaw.ai• Ruth Porat on LinkedIn: https://www.linkedin.com/in/ruth-porat• Mike Krzyzewski: https://goduke.com/sports/mens-basketball/roster/coaches/mike-krzyzewski/4159• Dalai Lama's 18 Rules for Living: https://www.prm.nau.edu/prm205/Dalai-Lama-18-rules-for-living.htm• Zigging vs. zagging: How HubSpot built a $30B company | Dharmesh Shah (co-founder/CTO): https://www.lennysnewsletter.com/p/lessons-from-30-years-of-building• Kareem Amin on LinkedIn: https://www.linkedin.com/in/kareemamin• Glassdoor: https://www.glassdoor.com• Tobi Lütke's leadership playbook: Playing infinite games, operating from first principles, and maximizing human potential (founder and CEO of Shopify): https://www.lennysnewsletter.com/p/tobi-lutkes-leadership-playbook• Katie Burke on LinkedIn: https://www.linkedin.com/in/katie-burke-965767a• Jerry Garcia: https://en.wikipedia.org/wiki/Jerry_Garcia• Bob Weir: https://en.wikipedia.org/wiki/Bob_Weir• Phil Lesh: https://en.wikipedia.org/wiki/Phil_Lesh• Ron “Pigpen” McKernan: https://en.wikipedia.org/wiki/Ron_%22Pigpen%22_McKernan• Marc Andreessen: The real AI boom hasn't even started yet: https://www.lennysnewsletter.com/p/marc-andreessen-the-real-ai-boom• The American Revolution: https://www.pbs.org/kenburns/the-american-revolution• Delphi: https://www.delphi.ai• Sonos: https://www.sonos.com• Yamini Rangan on LinkedIn: https://www.linkedin.com/in/yaminirangan• The Boston Red Sox: https://www.mlb.com/redsox—Recommended book:• Marketing Lessons from the Grateful Dead: What Every Business Can Learn from the Most Iconic Band in History: https://www.amazon.com/Marketing-Lessons-Grateful-Dead-Business/dp/0470900520—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

Did your brand just spend $7 million on a 30-second ad that alienated or ignored half its potential audience? Agility requires a willingness to challenge long-held assumptions—like the idea that a celebrity and a massive budget are all you need for a winning Super Bowl ad. It demands that brands move from gut feelings to data-driven insights to understand what truly resonates with their audience. Today, we're going to talk about the biggest advertising event of the year: the Super Bowl. Millions of dollars are spent, careers are made, and brands have one 30-second shot to capture the zeitgeist. But beyond the spectacle and the morning-after buzz, what actually drives results? We'll dig into the data behind the ads, exploring which brands successfully connected with key audiences, what the data says about using celebrities, and how the smartest brands think about the Super Bowl not as a single event, but as a strategic play in a much larger game.To help me discuss this topic, I'd like to welcome, Nataly Kelly, CMO at Zappi. About Nataly Kelly Nataly Kelly is Chief Marketing Officer at Zappi, based in Boston, MA. Previously she served at HubSpot as Vice President of Marketing, Vice President of International Operations and Strategy, and Vice President of Localization. Nataly Kelly on LinkedIn: https://www.linkedin.com/in/natalykelly/ Resources Zappi: https://www.zappi.io Take your personal data back with Incogni! Use code AGILE at the link below and get 60% off an annual plan: https://incogni.com/agile The Agile Brand podcast is brought to you by TEKsystems. Learn more here: https://www.teksystems.com/versionnextnow Get the Zappi Lessons in Advertising: Super Bowl LX report: https://www.zappi.io/web/learnings-from-super-bowl-ads-2026/Drive your customers to new horizons at the premier retail event of the year for Retail and Brand marketers. Learn more at CRMC 2026, June 1-3. https://www.thecrmc.com/ Enjoyed the show? Tell us more at and give us a rating so others can find the show at: https://advertalize.com/r/faaed112fc9887f3 Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstromDon't miss a thing: get the latest episodes, sign up for our newsletter and more: https://www.theagilebrand.showCheck out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.com The Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company

I know referrals work. You just have to get them from the right people. In this episode, I am sharing three ways to get high quality referrals that will help you build your sales pipeline.Ask Your Happy CustomersThe most common way to generate referrals is by reaching out to customers who are thrilled with your service and asking for an introduction to their network. Here is the surprising part. While 90 percent of customers say they are willing to refer others, only 11 percent of salespeople actually ask. If you are not asking, you are leaving opportunities on the table.Request Referrals from Non BuyersDo not overlook the conversations that do not end in a sale. Even when someone tells you no, that does not mean the relationship is over. It is still perfectly reasonable to ask if they know someone who is dealing with the challenges your product solves. When you position it around helping others, the request feels natural and value focused.Leverage LinkedIn ConnectionsYou can also take a more proactive approach by using tools like LinkedIn Sales Navigator. Look at your customers' first degree connections and identify people who match your ideal client profile. Then ask for a specific introduction. This method takes more effort, but when you are intentional about who you want to meet, the results can be powerful."Your goal is to get them to be able to be your evangelists." — Donald KellyResourcesKeep track of your sales activity and boost your results with the Prospect Pro sales tool.Join the LinkedIn Prospecting Course to improve how you use LinkedIn and book more consistent, high-quality sales appointments.Visit Blue Mango Studios for help in creating podcast production content. Sponsorship OffersThis episode is brought to you in part by Hubspot.With HubSpot sales hubs, your data tools and teams join a single platform to close deals and turn prospects into pipelines. Try it for yourself at hubspot.com/sales.This episode is brought to you in part by LinkedIn.Are you tired of prospective clients not responding to your emails? Sign up for a free 60-day trial of LinkedIn Sales Navigator at linkedin.com/tse.This episode is brought to you in part by the TSE Sales Foundation.Improve your connection on LinkedIn and land three or five appointments with our LinkedIn prospecting course. Go to the salesevangelist.com/linkedin.CreditsAs one of our podcast listeners, we value your opinion and always want to improve the quality of our show. Complete our two-minute survey here: thesalesevangelist.com/survey. We'd love for you to join us for our next episodes by tuning in on

This week, Joe and Robert break down one of the boldest marketing decisions the NFL has made in years and why it continues to pay off. NFL + Bad Bunny: A Strategic Win The NFL's move to spotlight Bad Bunny wasn't just a halftime performance decision. It was a strategic signal about where the league is headed as it expands globally and looks to connect with younger, more diverse audiences. Joe and Robert explore whether this marks a broader repositioning of the NFL brand and what marketers can learn from a legacy organization willing to evolve in public. This isn't about one performance. It's about how institutions modernize without losing their core. Super Bowl Ad Winners & Losers The guys break down the biggest hits and misses from this year's Super Bowl ad lineup. Which brands actually created impact? Who played it too safe? Did AI-driven ads live up to the hype or feel automated and forgettable? Some advertisers made bold cultural bets. Others blended into the background. Spotify's Big Earnings and the Hidden Opportunity Spotify's latest earnings report might signal something bigger than a financial rebound. Joe sees a potential opportunity for creators and marketers who understand the long-term value of owned audio audiences. Is podcasting and direct subscription audio still undervalued? Are marketers overlooking one of the most durable attention platforms available today? If you care about building direct audience leverage, this segment matters. Winners and Losers Joe's Winner: Markiplier's Iron Lung Markiplier's direct-to-theaters success with Iron Lung shows what creator-led distribution can look like without traditional Hollywood gatekeepers. Is this a preview of the next decade of media? Robert's Loser: AI Ads at the Super Bowl AI promised scale and personalization. On the biggest stage in advertising, many of those spots felt soulless and generic. Scale without taste is not a strategy. Rants and Raves Joe's Rant: TikTok Privacy Are creators and brands ignoring long-term privacy and platform risk for short-term reach? Robert's Commentary: The Overblown SaaS Apocalypse Robert pushes back on the constant doom-and-gloom narrative around SaaS and tech. Is the so-called apocalypse real, or just another overreaction cycle? Big Takeaway Legacy institutions are adapting. Creators are bypassing gatekeepers. Platforms are redefining monetization. The question for marketers is simple: Are you reacting to change, or positioning yourself to benefit from it? Subscribe and Follow: Follow Joe Pulizzi and Robert Rose on LinkedIn for insights, hot takes, and weekly updates from the world of content and marketing.  ------- This week's sponsor: Did you know that most businesses only use 20% of their data? That's like reading a book with most of the pages torn out. Point is, you miss a lot. Unless you use HubSpot. Their customer platform gives you access to the data you need to grow your business. The insights trapped in emails, call logs, and transcripts.  All that unstructured data that makes all the difference. Because when you know more, you grow more. Visit https://www.hubspot.com/ to hear how HubSpot can help you grow better. ------- Get all the show notes: https://www.thisoldmarketing.com/ Get Joe's new book, Burn the Playbook, at http://www.joepulizzi.com/books/burn-the-playbook/ Subscribe to Joe's Newsletter at https://www.joepulizzi.com/signup/. Get Robert Rose's new book, Valuable Friction, at https://robertrose.net/valuable-friction/  Subscribe to Robert's Newsletter at https://seventhbearlens.substack.com/ ------- This Old Marketing is part of the HubSpot Podcast Network: https://www.hubspot.com/podcastnetwork

In this Marketing Over Coffee: Learn about building Brandoms, Creating Community, and How to Hold It All Together! Direct Link to File Her new book is: Transforming Customer–Brand Relationships: Use Emotional Connection To Build Loyalty Check out the previous interview with Christina on her time at Hubspot and transition to on demand Chief Customer Officer […] The post Transforming Customer-Brand Relationships with Christina Garnett appeared first on Marketing Over Coffee Marketing Podcast.

In this Marketing Over Coffee: Learn about building Brandoms, Creating Community, and How to Hold It All Together! Direct Link to File Her new book is: Transforming Customer–Brand Relationships: Use Emotional Connection To Build Loyalty Check out the previous interview with Christina on her time at Hubspot and transition to on demand Chief Customer Officer […] The post Transforming Customer Brand Relationships with Christina Garnett appeared first on Marketing Over Coffee Marketing Podcast.

This Week In Startups is made possible by:Hubspot - http://clickhubspot.com/twist2Deel - http://deel.com/twistIru - http://www.iru.com/Today's show: Today on TWiST we're joined by 3 founders building on Open Claw,  Presh Dineshkumar, Vishnu, and Sean Liu!First, long time friend of the pod, Presh Dineshkumar, shows us how he's using Open Claw to automate his work at The Wellness Company. His Open Claw agent, Eywa, lives in his email and in his product, able to compile user lists at his discretion.Then, we're joined by Vishnu, who brings Open Claw to the masses. Non-technical folks, it's your lucky day! Time to get Clawd-shotted! Last, Sean Liu joins the show to tell us about how he's connecting Meta glasses to his Open Claw instance to interact with context that users can physically see!Timestamps:(0:00) We're joined by Presh Dineshkumar of the Wellness Company, another OpenClaw fanatic(1:50) We meet Presh's Replicant — Eywa — who spies on all of his emails(2:53) How Eywa is helping Presh keep track of his app's most active users(4:35) LLMs have become very smart but they are trapped in the corner(6:10) How Presh gave Eywa its own email address and avoids prompt injections(8:56) Using Presh's Replicant to do daily research dives(10:40) Hubspot: Check out the guide “Advanced ChatGPT Prompt Engineering: From Basic to Expert in 7 Days.” Download it for free at http://clickhubspot.com/twist2(13:21) Presh also has Eywa hunting down and fix bugs in his apps, all from email(16:16) Way more startups can be profitable now that they don't need 10+ person teams(19:15) Deel - Founders ship faster on Deel. Set up payroll for any country in minutes and get back to building. Visit http://deel.com/twist to learn more.(20:36) We're joined by two more OpenClaw builders: Vishnu and Xiaoan (Sean) Liu(21:16) Sean hooked his Meta Ray Bans up to his OpenClaw!(29:53) Iru unifies identity, endpoint security, and compliance into one platform. Book a demo at http://iru.com/(31:05) Some dystopian thoughts on how to use VisionClaw technology(32:47) What kinds of startups will get the most value out of OpenClaw?(34:43) Why Vishnu made a product to simplify OpenClaw set-up and security(37:34) What inspires people to stop considering OpenClaw and go “all in” on the tech(40:17) Will Vishnu and Sean quit their jobs and take Jason's investment $125K investment deal… YESSubscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.com/Check out the TWIST500: https://twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcp*Follow Lon:X: https://x.com/lons*Follow Alex:X: https://x.com/alexLinkedIn: https://www.linkedin.com/in/alexwilhelm/*Follow Jason:X: https://twitter.com/JasonLinkedIn: https://www.linkedin.com/in/jasoncalacanis/*Thank you to our partners:(10:40) Hubspot: Check out the guide “Advanced ChatGPT Prompt Engineering: From Basic to Expert in 7 Days.” Download it for free at http://clickhubspot.com/twist2(19:15) Deel - Founders ship faster on Deel. Set up payroll for any country in minutes and get back to building. Visit http://deel.com/twist to learn more.(29:53) Iru unifies identity, endpoint security, and compliance into one platform. Book a demo at http://iru.com/Check out all our partner offers: https://partners.launch.co/