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The ultra-wealthy get access to private equity, private credit, and pre-IPO deals the rest of us don't. Now, suddenly, those same deals are being marketed to you. Coincidence? Maybe. Cause for suspicion? Absolutely. Joe, OG, and Doug settle in at the basement desk (yes, Joe's mom's basement — the most prestigious financial address in podcasting) to dig into a Wall Street Journal headline asking whether everyday investors should be chasing the same private deals as the 1%. OG breaks down why "exclusive access" and "higher returns" can also mean binary outcomes, illiquidity traps, and a failure rate that the ultra-wealthy can absorb — and you probably can't. Oh, and there's a Ty Lopez–led retail investment that allegedly became a Ponzi scheme. So that's fun. What's in today's episode: Why private equity and private credit are suddenly being pitched to regular investors — and what that timing might tell you The real difference between risk-free returns, stock market investing, and private bets (they are not the same thing, no matter what the brochure says) How "exclusive opportunity" can be a polite way of saying "binary outcome with limited exits" A real-world look at regulation risk using Airbnb as the example What liquidity actually means — and what happens when you need your money back and the market says "no" The Ty Lopez distressed retail saga and how it allegedly went full Ponzi Why private credit often means lending to borrowers who couldn't get money elsewhere The uncomfortable truth about who gets targeted by aggressive investment marketing (hint: it's people who feel behind) OG also walks through an SEC-inspired framework for evaluating any investment before you hand over a dollar: Build a financial roadmap before chasing complex deals Know your actual risk tolerance (not the aspirational version) Diversify — for real, not just in theory Handle your emergency fund and high-interest debt first Grab every employer match on the table Rebalance regularly How to spot the early signs of fraud before it costs you Also in the basement: Doug drops Mustang trivia (the 1964 Ford kind, not the horse kind). The TikTok Minute rides off into the sunset, replaced by a shiny new back-to-basics segment. There are community meetup updates — including Benjamins After Dark in Boston. And somehow, against all odds, Kool-Aid nostalgia becomes a conversation. Because sometimes the most dangerous investment isn't the one that looks risky. It's the one that sounds like something only smart, wealthy, connected people get access to. Pull up a chair. The basement is open. FULL SHOW NOTES: https://stackingbenjamins.com/how-to-avoid-the-wrong-investments-1813 Deeper dives with curated links, topics, and discussions are in our newsletter, The 201, available at https://www.stackingbenjamins.com/201 Enjoy! Learn more about your ad choices. Visit podcastchoices.com/adchoices
⭐ Get my coaching & community to achieve financial freedom → https://www.coachcarson.com/rpm-pod-478 ⚒️Get my best investor tools for FREE → https://www.coachcarson.com/toolkit-pod-478 ▶️Next Episode: How One Investor Quit His Job With $100k Rental Cash Flow Apple: https://podcasts.apple.com/us/podcast/456-how-one-investor-quit-his-job-with-%24100k-rental-cash-flow/id1448707654?i=1000735018807 Spotify: https://open.spotify.com/episode/3BNPqg4d7lkFVeHBlaS2MC?si=2v6Go6Z0TVyey46HS5HFag EPISODE NOTES:
As much as we prepare students with practice passages and strategy review, many performance struggles happen before students even answer a question.When test anxiety sets in, students may skim or skip directions entirely, misread what's being asked, or overlook key details like “not,” “compare,” or “from least to greatest.” In this episode, Sara and Emily discuss why this happens and how teachers can intentionally build direction-reading habits long before test day. They share practical tips and insights to make test season less stressful for both teachers and students.Key Takeaways: Importance of reading test directions carefully (and activity ideas for practice)Strategies to teach students to interpret instructionsBuilding student confidence and reducing anxiety during testsResources Connected to this Episode: Free Test Prep Email Series at www.stellarteacher.com/testprepTest Taking Strategies Bundle on TPTStay connected with us! Follow us on Instagram @thestellarteachercompanyLooking for quick, actionable PD? Visit our YouTube channel!
In this episode, Staci, Davin, and Sanna explore Colorado's famous Million Dollar Highway, one of the top rated motorcycle rides in the country. Find out why we can't get enough of this road, even though it's only 25 miles long. We also cover the best times of year to ride MDH, our favorite restaurants along the road, and some detours and side quests to make your next road trip even better. For visuals and additional info, follow @thescenicride on Instagram, Facebook, TikTok, and YouTube.
2. Jeremy Zakis explains Australia's T20 World Championship exit and critiques England's expensive, aggressive "Bazball" strategy. He notes lessons learned for the struggling Australian national side. (27)
BARE WITH US! Between a breaking Mic and freezing equipment, life at the Noah and Lenora Apartment is all TAPE AND GLUE PEOPLE! Nonetheless, the show MUST GO ON! Today on COUPLES THERAPY, Noah and Lenora take a break from the hustle and recap their opinions on the Grammys last month, as well as an Oscar nomination NEXT WEEK and unearth a roommate DOORDASH FIASCO GONE HAYWIRE, and EXPENSIVE! It may be a messy Sunday but spend it with us if you need some friends in your speakers today. See omnystudio.com/listener for privacy information.
Gary sits down with style coach Caleb London to talk personal style, confidence, and dressing in alignment—especially for busy execs and public-facing pros. They break down personal style vs visual branding, plus why your clothes are always sending a message. Caleb weighs in on designer labels (don't be a walking billboard) and shares easy tips like mixing high/low pieces and rocking one color head-to-toe to look expensive. They also bond over old-school fashion TV and Caleb shares where to find him on LinkedIn and Instagram. Learn more about your ad choices. Visit megaphone.fm/adchoices
The largest and most expensive Lego set currently on sale in Ireland and the UK is the Star Wars Death Star, coming in at a staggering €999.99, and recommended for over 18s only.Joining Seán is a man who spent a lot of time getting it built: Nathan Spendelow, Tech Editor for Telegraph Recommended.
Plus Brittany Spears has been arrested and could a DUI law have prevented it??
The largest and most expensive Lego set currently on sale in Ireland and the UK is the Star Wars Death Star, coming in at a staggering €999.99, and recommended for over 18s only.Joining Seán is a man who spent a lot of time getting it built: Nathan Spendelow, Tech Editor for Telegraph Recommended.
General Blaine Holt explains "missile math," where cheap drones force expensive defensive responses, requiring a strategy of targeting adversary production capabilities and launch sites directly. (2)1905 CAIRO BAZAAR
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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
In this episode of Your Retirement Planning Simplified, Joe Curry outlines seven expensive retirement planning mistakes affluent Canadians make in their 60s. From CPP and OAS timing to RRSP and RRIF withdrawal strategies, tax-efficient investing, and purposeful spending, this conversation will help you protect your retirement income plan and avoid costly missteps. Thank you for listening! You can get a full breakdown of each episode on our blog: https://www.retirementplanningsimplified.ca/blog Don't forget to like, comment, and subscribe for more simplified retirement planning insights! Ready to take the next step? Identify your retirement income style with the RISA questionnaire at https://account.myrisaprofile.com/invitation-link/88QG1TMQ12 Want a retirement plan that adapts as your life evolves? Discover our True Wealth Roadmap — a step-by-step process to align your finances with your ideal retirement. Learn more here: https://matthewsandassociates.ca/vsl/ About Joe Curry Joseph Curry, also known as Joe, is the host of Your Retirement Planning Simplified, Canada's fastest-growing retirement planning podcast, where he provides accessible, in-depth financial advice. As the owner and lead financial planner at Matthews + Associates in Peterborough, Ontario, Joe and his team are committed to helping people secure both financial stability and purpose in retirement. His mission is to ensure people can sleep soundly knowing they have a solid plan in place, covering both financial and lifestyle aspects of retirement. A Certified Financial Planner and Certified Exit Planning Advisor, he values true wealth as more than money—it's about creating meaningful experiences with loved ones and fostering opportunities for the future. You can reach out to Joe through: LinkedIn: https://www.linkedin.com/in/curryjoe Website: https://www.retirementplanningsimplified.ca/ Website: https://matthewsandassociates.ca/vsl/ About Retirement Planning Simplified Founded in 2022, its mission is to empower people to plan for retirement confidently, focusing not only on finances but also on a meaningful life. RPS wants everyone to have access to simple, reliable tools that reflect their values and priorities, helping them create True Wealth—the freedom to do what they love with those they love. By simplifying retirement planning and aligning it with the retiree's purpose, RPS aims to support building a retirement that feels fulfilling and secure. To know more about RPS you can visit the links below: ● LinkedIn: https://www.linkedin.com/company/retirement-planning-simplified/ ● Instagram: https://www.instagram.com/retirement_planning_simplified ● Podcast/Blog: https://www.retirementplanningsimplified.ca/blog ● Youtube: https://www.youtube.com/@retirementplanningsimplified Disclaimer Opinions expressed are those of Joseph Curry, a registrant of Aligned Capital Partners Inc. (ACPI), and may not necessarily be those of ACPI. This video is for informational purposes only and not intended to be personalized investment advice. The views expressed are opinions of Joseph Curry and may not necessarily be those of ACPI. Content is prepared for general circulation and information contained does not constitute an offer or solicitation to buy or sell any investment fund, security or other product or service.
Kee’s pit this week is a classic plans fail - a babysitter stuff-up that turns into instant FOMO. Kel’s pit is the kind of body situation you never expect to be dealing with, until suddenly you’re googling, doing the mental maths, and realising this is going to be a whole thing. And somehow, in between all of that, there are a couple of proper heart-squeeze wins. If you want to play along each week (and read other parents’ peaks/pits), come join the Facebook group: https://www.facebook.com/groups/eatsleepshitrepeat/ LINKS TO EVERYTHING WE MENTIONEDCharlotte’s Web - StanIt’s Not Her - Mary KubicaReality Check Inside America’s Next Top Model - Netflix HOSTS & PRODUCERSKelly McCarren @kelly_mccarrenKee Reece Searles @keereece AUDIO PRODUCTIONMadeline Joannou - Mylk Media See omnystudio.com/listener for privacy information.
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Michael Sansoterra talks about his top stock picks in AI and healthcare. He names Nvidia (NVDA) as one stock that has more room to the upside, so long as it continues to hand out "picks and shovels" in the AI trade. He expects Eli Lilly (LLY) to remain a leader in the healthcare space due to its GLP-1 drug profitability. While he labels Palantir (PLTR) as "expensive," Michael says AI growth justifies the cost. ======== Schwab Network ========Empowering every investor and trader, every market day.Options involve risks and are not suitable for all investors. Before trading, read the Options Disclosure Document. http://bit.ly/2v9tH6DSubscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/About Schwab Network - https://schwabnetwork.com/about
We risked $1,700 worth of wine to answer one question: is expensive wine worth it?In this episode of Got Somme, Angus O'Loughlin and Master Somm Carlos Santos open two Grand Cru Burgundies (around $800 a bottle) and taste them side by side. No posturing, no wine snobbery, just an honest test of what you're paying for when the label gets serious.We talk:- What “Grand Cru” actually means in Burgundy- Why producers matter as much as terroir- The difference between a great $30 bottle and an $800 bottle- Whether expensive wine is “worth it” or just status- How to find underrated regions that deliver insane valueBIG thanks to The French Wine Centre for providing the bottles
Demi Moore Sparks Fresh Concern Over 'Skinnier-Than-Ever' Appearance at Actor Awards - 'Food Must Be Very Expensive in L.A.'Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy
Stav, Abby & Matt Catch Up - hit105 Brisbane - Stav Davidson, Abby Coleman & Matty Acton
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Are your facial results fading too quickly? Struggling with acne, hyperpigmentation, or chronically dry skin even after professional treatments?In this episode, a licensed professional esthetician breaks down the three most common skincare mistakes that prevent facials and advanced skin treatments from delivering long-term results.You'll learn:• Why washing your face too soon after a facial can remove active ingredients before they fully absorb• How internal hydration directly impacts your skin barrier repair and moisturizer effectiveness• The hidden damage caused by aggressive cleansers and over-stripping your skin at home• Why barrier repair is the foundation for treating acne, hyperpigmentation, and inflammation• How to create a gentle, results-driven post-facial routineMany clients unknowingly sabotage their own skin by disrupting the skin barrier, over-cleansing, or failing to hydrate properly. This episode explains the science behind skin barrier health and gives practical guidance on how to protect your investment after a professional facial.If you want longer-lasting results from your skincare treatments and a healthier, more resilient complexion, this episode is for you.Perfect for anyone searching for:skin barrier repair tips, how to make facial results last, acne prevention routine, hyperpigmentation skincare advice, post-facial care instructions, and professional esthetician skin advice.
Haven't you been wrong before? Haven't you done stuff that in retrospect seems dumb or weird? Of course you have.
A year ago this month, the travel and motherhood world lost Elise Caffee — blogger, adventurer, mother of three, and the woman behind the hashtag "take the trip." Elise believed, down to her bones, that making memories with your kids was always worth it — the chaos, the cost, the exhaustion, all of it. This episode is for her. This week's guest is Tiffany Rosenhan, Elise's dear friend, co-author, and co-founder of Jumelle Press. Together, they wrote Pippa and Poppy Adventure — a beautiful children's book about two identical twins exploring Europe — and Tiffany is here today to carry Elise's message forward. With spring break just around the corner, her three takeaways feel especially timely — whether you're heading somewhere far or just loading up the car for a day trip an hour from home. In this episode, you'll hear:
Hey, Comedy Lovers! ✤ Welcome to "Ian Lara" ⭐ All advice is bad advice, please do adult things and put this podcast on in the background.
Episode #371 – Is a More Expensive Email Platform Actually Worth It? Is paying more for an email marketing platform actually worth it - or is that just industry hype? I've seen so many ecommerce brands choose tools based on price alone… and then regret it later when their strategy outgrows the platform. In this episode, I break down when investing more makes sense - and when it doesn't. Because your email platform isn't just a monthly subscription. It's infrastructure. And infrastructure decisions compound. If you're serious about email and SMS becoming revenue channels (not just newsletters), this is a decision that deserves more thought than "what's the cheapest option?" You'll learn: Why brands rarely regret investing in a stronger platform upfront The hidden cost of choosing a cheaper tool (it's not the subscription price) What "infrastructure decisions compound" really means in email marketing The real example of a brand locked into an annual deal that no longer fits What you're actually paying for in a premium email platform When it's perfectly fine to start with a lighter platform The question you should ask instead of "What's the cheapest option?" Price usually reflects capability in email marketing tools. And when your email program starts working, the last thing you want is to rebuild your foundation mid-growth. Work with Joy Joya: https://joyjoya.com
In this episode of the show Gary discusses the true costs associated with electric vehicles and debunks common myths surrounding their affordability.He highlights the CODE Report indicating that many consumers are deterred from purchasing EVs due to perceived high upfront costs, limited range, and expensive battery replacements.However, he presents data showing that the majority of EV owners actually save money over time, especially those with home charging capabilities. The conversation emphasizes the importance of education in changing public perception about EV pricing and ownership.TakeawaysExpensive upfront costs deter many from choosing EVs.Limited range and battery replacement costs are common concerns.Education is crucial in countering misconceptions about EVs.80% of people save money by switching to EVs.Home charging significantly increases savings with EVs.Public charging costs can affect overall savings.Used EVs often provide better value than ICE vehicles.Many consumers have never driven an electric vehicle.The cost of running an EV is significantly lower than ICE cars.Pre-registered EVs can be found at substantial discounts.Key Sound bite"The average saving is £5,850 with an EV."Chapters00:00 The Cost of Electric Vehicles: An Overview05:09 Understanding Savings with Electric Vehicles07:02 CODE Quotes08:01 What do other sources say11:22 Debunking Myths: Education on EV Costs12:41 Recent pricing Examples15:16 Dealer Preregistrations16:28 Conclusion: The Future of EV AffordabilityThe EV Musings Podcast is sponsored by Zapmap, the go-to app for EV drivers, helping you find and pay for public charging with confidence.Links in the show notes:The Cost of Driving Electric (CODE) ReportPetrol and diesel buying intent rises despite BEV growth | EY - UKAverage range of new electric cars now 300 miles | Electrifying.comEpisode produced by Arran Sheppard at Urban Podcasts: https://www.urbanpodcasts.co.uk(C) 2019-2026 Gary ComerfordSupport me: Patreon Link: http://www.patreon.com/evmusingsKo-fi Link: http://www.ko-fi.com/evmusingsThe Books:'So, you've gone electric?' on Amazon : https://www.amazon.co.uk/dp/B07Q5JVF1X'So, you've gone renewable?' on Amazon : https://amzn.to/3LXvIckSocial Media:EVMusings: Twitter https://twitter.com/MusingsEvInstagram: @EVmusingsOctopus Energy referral code (Click this link to get started) https://share.octopus.energy/neat-star-460Upgrade to smarter EV driving with a free week's trial of Zapmap Premium, find out more here https://evmusings.com/zapmap-premiumMentioned in this episode:ZapmapThe EV Musings Podcast is sponsored by Zapmap, the go-to app for EV drivers, helping you find and pay for public charging with confidence. Zapmap is free to download and use, with subscription plans for enhanced features such as using Zapmap in-car on CarPlay or Android Auto, and discounted charging across thousands of charge points. Download the app from the Apple App Store or Google Play Store or find out more at www.zapmap.com.Zapmap EV Guide
If you've ever been called “airport dad” or married to one, this episode is for you. From school attendance to airport stress to the worst-case scenarios we play out in our heads, Ryan and Sam talk about the cost of constantly expecting something to go wrong and what might change if you didn't.
Nico the Lefty reacts to the massive moves in the 2026 Major League Pickleball Draft. Anna Bright goes for $1.23 Million, Jorja Johnson says bye-bye to big bro and joins Gary Vee and Anna Leigh Waters in Clown Town. Plus the MLP youth movement is in full effect. More Teams are taking chances on teenage players both international and domestic. There's a completely new way to optimize your health. Give Blue Cannatine a try at https://troscriptions.com/DINK or enter BETTER at checkout for 10% off your first order. Be the first to try Zane's new course here: https://tzpickleball.com/#Pickleball #PPATour #PickleballPodcast Leave your voicemail for the PicklePod at (512) 200 - 4299 ------------------ Like the ep? Do us a favor: subscribe to our channel and leave a review on Apple or Spotify -Subscribe to our 'all things pickleball' free e-newsletter at https://www.thedink.beehiiv.com / thedinkpickleball -Follow us on IG -Continue the convo in our private FB Group: / thedi. . -For everything else we do, visit https://linktr.ee/dinkfam -Read more about Zane and subscribe to his newsletter at https://zanenavratilpickleball.com/ -Follow Zane on IG @zanenavratilpickleball #pickleball #pickleballcourts Learn more about your ad choices. Visit megaphone.fm/adchoices
Henry says it's the end of an era as the final D'Amico & Sons locations are set to close, being a sports fan is costing you more money and it needs to be looked at, plus we have Bite of the Night.
* Sponsor read Bart Merrick Team and market confusion * Longtime advertiser becomes platinum client * Advice on buying and selling during rate changes * Friday Free Show opening * BDM Appreciation Week announced * $5 shirt presale and signup info * April 11 members party details * Dad hat merch sale * Construction noise outside studio * Seth absent due to renovation stress * Discussion of stress tolerance and burnout * Stress without recovery worsens coping * Beard turning gray conversation * Biggest regret was starting renovation * Previous mansion sale repair disputes * Video tour of unfinished house * Smart fridge ovens and propane range * Expensive decorative upgrades * Range caused house fire incident * Gaudy luxury house jokes * Wood ceiling beams and playroom prep * Project far behind schedule * Screaming in car lost voice * Wrong appliance finish frustration * Bad contractor work and service issues * Smart oven wifi and Sabbath mode * Limestone tile sealed incorrectly * Entire floor covered in hardened spots * Contractors refused repair job * Chemical strip then mechanical polish * Repair cost about five thousand * Regret selling old house * Marriage strain and cramped rental life * Wife now works at Disney hotel * Increased workload at dojo * Castleberry neighborhood comparison * Broken ride on car giveaway * Boat dock lift completed * Boat stuck in driveway tire issues * Childcare juggling during move * Sleep Number bed delivery trouble * Plumbing and wiring disputes * Move in maybe one to two weeks * Six figures over budget * Savings emotionally drained * Pool dig discovered large root * Extra charges expected * Spiral staircase delivery problems * Karate of Orlando business plug * Dojo pricing confusion email * Premium materials admiration * Tease armed speedboat near Cuba * Cuban Coast Guard shootout story * No child on the boat * Armed men attacked patrol boat * Cuba labeled infiltration * Attackers killed after gunfire exchange * Amateur invasion disbelief * Miami exile groups discussed * Childhood neighbors ran drills * Teen transporting guns to Everglades * Shooting watermelons no ear protection * Guns and Melons joke * Parent loss reflection * Growing up minority in Miami * Kids had access to guns and alcohol * Debate nature vs parenting influence * Listener sent Bentons country ham * Country ham traditions and funerals * Quick fry biscuits serving method * Anniversary restaurant indecision * Tease feeding alcohol to hawk * Man gave BuzzBall to hawk arrested * Alcohol toxic to birds * Old beer drinking camel story * Animals seeking intoxicants discussion * Mid level cruelty debate * Marijuana smoke harms birds * Dead pelican car prank * Amoeba infection fears * Pee hole fish myth debunked * Amazon travel fears comparison * Upcoming show plugs and events ### Social Media [https://tomanddan.com](https://tomanddan.com) [https://twitter.com/tomanddanlive](https://twitter.com/tomanddanlive) [https://facebook.com/amediocretime](https://facebook.com/amediocretime) [https://instagram.com/tomanddanlive](https://instagram.com/tomanddanlive) Tom & Dan on Real Radio 104.1 Apple Podcasts: [https://podcasts.apple.com/us/podcast/a-corporate-time/id975258990](https://podcasts.apple.com/us/podcast/a-corporate-time/id975258990) Google Podcasts: [https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkLnBvZGJlYW4uY29tL2Fjb3Jwb3JhdGV0aW1lL3BvZGNhc3QueG1s](https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkLnBvZGJlYW4uY29tL2Fjb3Jwb3JhdGV0aW1lL3BvZGNhc3QueG1s) TuneIn: [https://tunein.com/podcasts/Comedy/A-Corporate-Time-p1038501/](https://tunein.com/podcasts/Comedy/A-Corporate-Time-p1038501/) Exclusive Content [https://tomanddan.com/registration](https://tomanddan.com/registration)
#366: Skeery's moving and can't part with old junk he doesn't need; Brody's Chat GPT has amnesia and forgot everything it knew about him; Skeery's 19 year old sofa sold for an insane amount of money; Brody goes nuts trying to find the poop smell in his house: Skeery had an idea for his co worker Nate who has been flirting with a woman who lives in the building across the way from their office; The boys BOTH get free dessert: Brody bit into a piece of metal in his trail mix and the paint store gave Skeery's painters the wrong color causing them to screw up his wall.See omnystudio.com/listener for privacy information.
On this week's show Braden is on vacation but don't worry! We still have a show for you. Ara reads your emails and takes a look at the week's news. He also takes a look at an article in CNET that claims: The LG Evo AI G5 OLED is the new standard for TVs. News: Amazon is finally rolling out some much-needed upgrades to Fire TV New TV before 'RAMageddon'? Prices expected to rise Others: Take Over Tuesday: Featuring Buzz Schneider of the 1980 Miracle Team 1980miraclemonument.org Home Theater Geeks: Sacramento Sanctuary Sacramento Sanctuary - Home Theater of the Month Interview! The LG Evo AI G5 OLED the New Standard for TV OLED TVs have consistently delivered the best picture quality in our head-to-head tests -- with the best shadow detail, contrast, color and black levels. Yet, there is one thing LCD-based TVs have always done better: sheer brightness. That is, until the 2025 LG G5 came along. Finally, OLED can reclaim its place at the top of the TV technology leader board with a model that performs brilliantly in almost every single respect. Maybe the forthcoming LG G6 will be even better? Full article here… PROS Highest brightness of any OLED TV yet Stunning image quality Best color accuracy of every TV in 2025 CONS Brightness boost not visible in all content Remote is not as good as previous versions Expensive
Hawaii's Best - Guide to Travel Tips, Vacation, and Local Business in Hawaii
Is spring break in Hawaii actually worth it, or are you setting your family up for a trip that costs way more than you planned?
It takes all of us to organize against racism in our communities. In this episode, Nick sits down with Dr. Valeriah Big Eagle and Wizipan Little Elk Garriott to discuss the ruling in the federal lawsuit trial against the owners of the Grand Gateway hotel. After years of advocacy, racism was on trial and on full display in the courtroom. The verdict? Racism is expensive. SUPPORT OUR WORK:Help us continue this vital truth-telling media work, donate to NDN Collective's For the People.
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If you've ever thought… “I want a beautiful home, but I don't trust myself.” “What if I make expensive mistakes?” “What if this costs more than I can afford?” “What if I ask a dumb question?” This episode is for you. Today, I'm joined by one of my students, Loraine, and we're having an honest conversation about what it's really like to work together inside my decorating framework. We talk about: How she went from second-guessing every decision to decorating with confidence The rooms she's worked on and the progress she's made Why having a step-by-step plan changed everything How gentle guidance (and a few nudges!) helped her avoid costly mistakes The fear she had about the cost — and why it turned out to be more doable than she expected Why no question is ever a “dumb” question If you've been stuck in analysis paralysis… If your rooms feel unfinished… If you're afraid of wasting money… If you want someone to walk beside you without judgment… Loraine's story will show you what's possible. Decorating isn't about having perfect taste. It's about having a plan and the confidence to follow it. And sometimes, the right guidance makes all the difference. Thinking About Taking the Next Step? If you're ready to stop guessing and finally create a clear, practical decorating plan for your home, there are two ways to begin: ✨ Join my upcoming live workshop where I'll teach you the 3 Steps to Creating a Home you Can't Stop Gushing About OR ✨ Book a call with me to talk through your space and see what working together could look like in YOUR home: Decorating SOS Call You don't have to figure this out alone. And as Loraine shares in this episode — it might be more accessible than you think!! ✨✨ REGISTER for the FREE WORKSHOP ✨✨ 3 Steps to Creating a Home you Can't STOP Gushing About March 11 and 12 9am PST | 10 am MST | 11am CST | 12 pm EST // Links mentioned in show: // Learn your design style: https://bit.ly/ffdesignguide Email: hello@figandfarmathome.com Website: https://figandfarmathome.com Join The Collective (monthly membership): https://www.figandfarmathome.com/thecollective Book a Decorating SOS Coaching Call: https://www.figandfarmathome.com/decorating-sos Instagram, where I rarely hang out: https://www.instagram.com/figandfarm/ FREE Facebook Community: https://www.bit.ly/design101group
I'm not paying for _______anymore because it's too expensive! What are you skipping now because of rising costs? Liza Minelli's autobiography preview; Lisa Rinna allegedly was drugged at the premiere of the show, Traitors; One star reviews and the five second rule! See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
Things we USED to buy but don't anymore because they're just to darn EXPENSIVE! And a Canine Crime! That's what Paul is BuZzin' about today on The Daily BuZz!!See omnystudio.com/listener for privacy information.
We are already at the end of February! Today we celebrate 30 years of Pokemon. I talk about the reveal of Pokemon Wind and Waves and reflect on my history with the series.Timestamps(00:00) Intro(03:00) Pokemon Pokopia(06:45) Pokeon Winds and Waves Reveal(11:10) Gale of Darkness(12:12) FireRed and LeafGreen(15:40) My Pokemon Journey(19:00) Pokemon Crystal memories(24:45) Serebii and early internet pokemon(27:30) Gameboy Advance SP story(30:35) Young rob dropped the cards(33:06) Discussing pokemon generations(42:00) Expensive day and Pokemon Go(45:00) Slow decline(48:40) Hopeful for future(53:41) Favorite Starter Pokemon(57:00) Final Thoughts______________________________Follow meMy website: https://dadneedstotalk.com/Blue Sky: dadneedstotalk2.bsky.socialTwitter: https://twitter.com/DadNeedsToTalkInstagram: https://www.instagram.com/dadneedstotalkpodcast/If you enjoy what I do and want to supportKofi: https://ko-fi.com/dadneedstotalk
Margarine money grab, Crowdsourced landlords, Liquidity at the laundromat, Banana bills, Kosovo crackdowns, Expensive password recovery, Algorithmic landlord, Cash comparisons. Jennifer, Angie, Way, and Bradley discuss a variety of curated links from the archives. Please consider supporting this ad-free content on Patreon.
Hour 1 opens with the Miami Hurricanes baseball staying hot to start the season as they gear up for a rivalry matchup with the Florida Gators baseball this weekend. With the NFL Combine underway, the rumor mill heats up as Joe and Hollywood debate whether a reported $30 million price tag for Malik Willis is too rich for Miami and if familiarity with the Dolphins' new “Green Bay guys” could lower the cost. The hour also touches on South Florida sports business and fan frustrations, including streaming overload, stadium progress for Inter Miami CF, and optimism surrounding the Miami Marlins despite years of low payroll. Draft talk continues with buzz around Mel Kiper Jr. projecting Francis Mauigoa to the Dolphins, plus expectations that several Hurricanes could hear their names called, before Joe reacts to Kirby Smart and Mario Cristobal trading jabs
What's something you used to buy but don't anymore because it's too expensive?
Your next laptop is about to cost a lot more. So is your next phone, your next SSD, and pretty much every piece of consumer tech you've been planning to buy. The reason is not what you'd expect. The global memory supply is being devoured by AI. Samsung, SK Hynix, and Micron, the three companies that make 95 percent of the world's RAM, have been redirecting their manufacturing toward high-margin AI chips. The result is a consumer memory shortage so severe the industry is calling it RAMmageddon. In this episode, we break down what's actually happening behind the scenes, why data centers are now consuming 70 percent of all memory chips produced, and why Intel's CEO says there's no relief until 2028. We also look at the real-world price impact that's already hitting: Laptop prices up $55 to $765 depending on specs SSD prices surging 90 percent in one quarter Fewer smartphones being produced at higher price points The PC market projected to decline up to 9 percent in 2026 Possible delays for next-gen gaming hardware including the PS6 Plus, what this means for your tech purchasing decisions right now, and why this might actually be a good moment to rethink your relationship with upgrading. If you're planning any tech purchase in 2026 or 2027, this is the episode to listen to first. Subscribe to The Healthier Tech Podcast wherever you listen so you never miss an episode. This episode is brought to you by Shield Your Body—a global leader in EMF protection and digital wellness. Because real wellness means protecting your body, not just optimizing it. If you found this episode eye-opening, leave a review, share it with someone tech-curious, and don't forget to subscribe to Shield Your Body on YouTube for more insights on living healthier with technology.
Colion Noir addresses comments that he only reviews "expensive" guns.
Most investors think their biggest losses come from bad picks. They don't. They come from blind spots. In this episode, Andy Tanner, Corey Halliday, and Noah Davidson unpack the psychological traps that quietly sabotage traders and investors. Sunk cost fallacy. Anchoring to past prices. Averaging down to "get back to even." Overconfidence disguised as conviction. These aren't strategy problems. They're belief problems. You'll hear why price alone tells you nothing about value. Why holding a loser to avoid admitting you're wrong is often the costliest decision you can make. And why the real edge in trading isn't prediction — it's risk management. The conversation moves beyond tactics and into self-awareness. Because markets don't just test your capital. They test your identity. Are you managing risk — or defending your ego? Are you following a plan — or reacting to discomfort? This episode isn't about a new indicator or a better entry signal. It's about understanding how your own thinking can distort decision-making — and how disciplined investors structure their process to prevent small errors from becoming permanent damage. The market is rarely the enemy. Unexamined assumptions are. Want to Learn More? – Explore free education and tools at cashflowbonus.com to strengthen your investing foundation – Keep building your financial education at yourinvestingclass.com.
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Joe's Premium Subscription: www.standardgrain.comGrain Markets and Other Stuff Links —Apple PodcastsSpotifyTikTokYouTubeFutures and options trading involves risk of loss and is not suitable for everyone.Trade drama is back in the headlines. President Trump is threatening higher tariffs on countries that fail to honor trade agreements. Following last week's Supreme Court ruling, the EU announced it would pause ratification of its agreement, while India is deferring talks on its own deal. Despite the legal setback, the White House says it remains committed to its trade agenda and is exploring alternative tools to implement tariffs. Markets clearly reacted to the renewed uncertainty, with stocks under pressure to start the week.Grain markets felt the ripple effects. Soybean and wheat futures moved lower Monday as traders weighed the potential impact of trade disruptions and retaliation tied to the newly announced 15% global tariff. Corn futures, meanwhile, managed to hold steady. When policy uncertainty rises, volatility often follows — and that theme remains firmly in play.Export data offered a few surprises. US corn shipments exceeded expectations for the third straight week, posting a very strong year-over-year gain. Wheat inspections also came in above trade guesses. Soybean shipments, however, disappointed and continue to reflect uneven demand patterns. China remained a major buyer, accounting for roughly half of weekly inspections.USDA also reported a fresh flash sale of corn to Colombia, adding to an already solid sales pace this marketing year. Demand for US corn has been a notable bright spot recently, especially when compared to other segments of the export complex.Weather and field conditions remain a major talking point in South America. Brazil's soybean harvest is advancing at its slowest pace in several years, with rains and longer crop cycles creating delays. Planting progress for Brazil's second corn crop is also lagging last year's pace, which could become increasingly important for global feed grain supply expectations.Outside of grains, US consumers continue to show remarkable resilience in the face of high beef prices. Despite record price levels, demand remains strong as buyers adapt by shifting toward more affordable cuts and smaller portions. The protein story remains a powerful force across the broader agricultural landscape.As always, volatility, policy, and global production trends remain key market drivers.
Four-year college isn't the default anymore… but saving for your kid's future absolutely is. Today, Nicole breaks down the modern playbook for affording college whether your kid is a newborn, or if they're applying to colleges now. This is your simple guide to 529 plans, custodial accounts, Coverdells, prepaid tuition plans, and the newest government-backed savings option making headlines. If you've ever wondered, “What happens to a 529 plan if my kid doesn't go to college?” Nicole will teach you a smart move there, too. Check out Nicole's financial literacy course The Money School Find a Financial Advisor or Financial Coach from Nicole's company Private Wealth Collective Watch video clips from the pod on Money Rehab's Instagram and Nicole Lapin's Instagram Here's what Nicole covers today: 00:00 Are You Ready for Some Money Rehab? 01:11 Where To Start If You Have a Newborn 01:28 Everything You Need to Know About 529s 04:44 Where To Start If Your Kid Is in Grade School 05:42 The Pros and Cons of Custodial Accounts 08:17 Where to Start if Your Kid Is in High School 10:32 Tip You Can Take Straight to the Bank All investing involves risk, including loss of principal. This episode is for informational purposes only and does not constitute financial, investment, or legal advice. Always consult a licensed professional before making financial decisions.
In This Hour:-- Is talking about expensive guns elitist?-- How to protect your hearing from loud gunshots in a gunfight.-- Ammo's expensive. Consider buying used reloading equipment.Gun Talk 02.22.26 After ShowBecome a supporter of this podcast: https://www.spreaker.com/podcast/gun-talk--6185159/support.
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