Podcasts about Embedding

Turbopuffer came out of a reading app.In 2022, Simon was helping his friends at Readwise scale their infra for a highly requested feature: article recommendations and semantic search. Readwise was paying ~$5k/month for their relational database and vector search would cost ~$20k/month making the feature too expensive to ship. In 2023 after mulling over the problem from Readwise, Simon decided he wanted to “build a search engine” which became Turbopuffer.We discuss:• Simon's path: Denmark → Shopify infra for nearly a decade → “angel engineering” across startups like Readwise, Replicate, and Causal → turbopuffer almost accidentally becoming a company • The Readwise origin story: building an early recommendation engine right after the ChatGPT moment, seeing it work, then realizing it would cost ~$30k/month for a company spending ~$5k/month total on infra and getting obsessed with fixing that cost structure • Why turbopuffer is “a search engine for unstructured data”: Simon's belief that models can learn to reason, but can't compress the world's knowledge into a few terabytes of weights, so they need to connect to systems that hold truth in full fidelity • The three ingredients for building a great database company: a new workload, a new storage architecture, and the ability to eventually support every query plan customers will want on their data • The architecture bet behind turbopuffer: going all in on object storage and NVMe, avoiding a traditional consensus layer, and building around the cloud primitives that only became possible in the last few years • Why Simon hated operating Elasticsearch at Shopify: years of painful on-call experience shaped his obsession with simplicity, performance, and eliminating state spread across multiple systems • The Cursor story: launching turbopuffer as a scrappy side project, getting an email from Cursor the next day, flying out after a 4am call, and helping cut Cursor's costs by 95% while fixing their per-user economics • The Notion story: buying dark fiber, tuning TCP windows, and eating cross-cloud costs because Simon refused to compromise on architecture just to close a deal faster • Why AI changes the build-vs-buy equation: it's less about whether a company can build search infra internally, and more about whether they have time especially if an external team can feel like an extension of their own • Why RAG isn't dead: coding companies still rely heavily on search, and Simon sees hybrid retrieval semantic, text, regex, SQL-style patterns becoming more important, not less • How agentic workloads are changing search: the old pattern was one retrieval call up front; the new pattern is one agent firing many parallel queries at once, turning search into a highly concurrent tool call • Why turbopuffer is reducing query pricing: agentic systems are dramatically increasing query volume, and Simon expects retrieval infra to adapt to huge bursts of concurrent search rather than a small number of carefully chosen calls • The philosophy of “playing with open cards”: Simon's habit of being radically honest with investors, including telling Lachy Groom he'd return the money if turbopuffer didn't hit PMF by year-end • The “P99 engineer”: Simon's framework for building a talent-dense company, rejecting by default unless someone on the team feels strongly enough to fight for the candidate —Simon Hørup Eskildsen• LinkedIn: https://www.linkedin.com/in/sirupsen• X: https://x.com/Sirupsen• https://sirupsen.com/aboutturbopuffer• https://turbopuffer.com/Full Video PodTimestamps00:00:00 The PMF promise to Lachy Groom00:00:25 Intro and Simon's background00:02:19 What turbopuffer actually is00:06:26 Shopify, Elasticsearch, and the pain behind the company00:10:07 The Readwise experiment that sparked turbopuffer00:12:00 The insight Simon couldn't stop thinking about00:17:00 S3 consistency, NVMe, and the architecture bet00:20:12 The Notion story: latency, dark fiber, and conviction00:25:03 Build vs. buy in the age of AI00:26:00 The Cursor story: early launch to breakout customer00:29:00 Why code search still matters00:32:00 Search in the age of agents00:34:22 Pricing turbopuffer in the AI era00:38:17 Why Simon chose Lachy Groom00:41:28 Becoming a founder on purpose00:44:00 The “P99 engineer” philosophy00:49:30 Bending software to your will00:51:13 The future of turbopuffer00:57:05 Simon's tea obsession00:59:03 Tea kits, X Live, and P99 LiveTranscriptSimon Hørup Eskildsen: I don't think I've said this publicly before, but I just called Lockey and was like, local Lockie. Like if this doesn't have PMF by the end of the year, like we'll just like return all the money to you. But it's just like, I don't really, we, Justine and I don't wanna work on this unless it's really working.So we want to give it the best shot this year and like we're really gonna go for it. We're gonna hire a bunch of people. We're just gonna be honest with everyone. Like when I don't know how to play a game, I just play with open cards. Lockey was the only person that didn't, that didn't freak out. He was like, I've never heard anyone say that before.Alessio: Hey everyone, welcome to the Leading Space podcast. This is Celesio Pando, Colonel Laz, and I'm joined by Swix, editor of Leading Space.swyx: Hello. Hello, uh, we're still, uh, recording in the Ker studio for the first time. Very excited. And today we are joined by Simon Eski. Of Turbo Farer welcome.Simon Hørup Eskildsen: Thank you so much for having me.swyx: Turbo Farer has like really gone on a huge tear, and I, I do have to mention that like you're one of, you're not my newest member of the Danish AHU Mafia, where like there's a lot of legendary programmers that have come out of it, like, uh, beyond Trotro, Rasmus, lado Berg and the V eight team and, and Google Maps team.Uh, you're mostly a Canadian now, but isn't that interesting? There's so many, so much like strong Danish presence.Simon Hørup Eskildsen: Yeah, I was writing a post, um, not that long ago about sort of the influences. So I grew up in Denmark, right? I left, I left when, when I was 18 to go to Canada to, to work at Shopify. Um, and so I, like, I've, I would still say that I feel more Danish than, than Canadian.This is also the weird accent. I can't say th because it, this is like, I don't, you know, my wife is also Canadian, um, and I think. I think like one of the things in, in Denmark is just like, there's just such a ruthless pragmatism and there's also a big focus on just aesthetics. Like, they're like very, people really care about like where, what things look like.Um, and like Canada has a lot of attributes, US has, has a lot of attributes, but I think there's been lots of the great things to carry. I don't know what's in the water in Ahu though. Um, and I don't know that I could be considered part of the Mafi mafia quite yet, uh, compared to the phenomenal individuals we just mentioned.Barra OV is also, uh, Danish Canadian. Okay. Yeah. I don't know where he lives now, but, and he's the PHP.swyx: Yeah. And obviously Toby German, but moved to Canada as well. Yes. Like this is like import that, uh, that, that is an interesting, um, talent move.Alessio: I think. I would love to get from you. Definition of Turbo puffer, because I think you could be a Vector db, which is maybe a bad word now in some circles, you could be a search engine.It's like, let, let's just start there and then we'll maybe run through the history of how you got to this point.Simon Hørup Eskildsen: For sure. Yeah. So Turbo Puffer is at this point in time, a search engine, right? We do full text search and we do vector search, and that's really what we're specialized in. If you're trying to do much more than that, like then this might not be the right place yet, but Turbo Buffer is all about search.The other way that I think about it is that we can take all of the world's knowledge, all of the exabytes and exabytes of data that there is, and we can use those tokens to train a model, but we can't compress all of that into a few terabytes of weights, right? Compress into a few terabytes of weights, how to reason with the world, how to make sense of the knowledge.But we have to somehow connect it to something externally that actually holds that like in full fidelity and truth. Um, and that's the thing that we intend to become. Right? That's like a very holier than now kind of phrasing, right? But being the search engine for unstructured, unstructured data is the focus of turbo puffer at this point in time.Alessio: And let's break down. So people might say, well, didn't Elasticsearch already do this? And then some other people might say, is this search on my data, is this like closer to rag than to like a xr, like a public search thing? Like how, how do you segment like the different types of search?Simon Hørup Eskildsen: The way that I generally think about this is like, there's a lot of database companies and I think if you wanna build a really big database company, sort of, you need a couple of ingredients to be in the air.We don't, which only happens roughly every 15 years. You need a new workload. You basically need the ambition that every single company on earth is gonna have data in your database. Multiple times you look at a company like Oracle, right? You will, like, I don't think you can find a company on earth with a digital presence that it not, doesn't somehow have some data in an Oracle database.Right? And I think at this point, that's also true for Snowflake and Databricks, right? 15 years later it's, or even more than that, there's not a company on earth that doesn't, in. Or directly is consuming Snowflake or, or Databricks or any of the big analytics databases. Um, and I think we're in that kind of moment now, right?I don't think you're gonna find a company over the next few years that doesn't directly or indirectly, um, have all their data available for, for search and connect it to ai. So you need that new workload, like you need something to be happening where there's a new workload that causes that to happen, and that new workload is connecting very large amounts of data to ai.The second thing you need. The second condition to build a big database company is that you need some new underlying change in the storage architecture that is not possible from the databases that have come before you. If you look at Snowflake and Databricks, right, commoditized, like massive fleet of HDDs, like that was not possible in it.It just wasn't in the air in the nineties, right? So you just didn't, we just didn't build these systems. S3 and and and so on was not around. And I think the architecture that is now possible that wasn't possible 15 years ago is to go all in on NVME SSDs. It requires a particular type of architecture for the database that.It's difficult to retrofit onto the databases that are already there, including the ones you just mentioned. The second thing is to go all in on OIC storage, more so than we could have done 15 years ago. Like we don't have a consensus layer, we don't really have anything. In fact, you could turn off all the servers that Turbo Buffer has, and we would not lose any data because we have all completely all in on OIC storage.And this means that our architecture is just so simple. So that's the second condition, right? First being a new workload. That means that every company on earth, either indirectly or directly, is using your database. Second being, there's some new storage architecture. That means that the, the companies that have come before you can do what you're doing.I think the third thing you need to do to build a big database company is that over time you have to implement more or less every Cory plan on the data. What that means is that you. You can't just get stuck in, like, this is the one thing that a database does. It has to be ever evolving because when someone has data in the database, they over time expect to be able to ask it more or less every question.So you have to do that to get the storage architecture to the limit of what, what it's capable of. Those are the three conditions.swyx: I just wanted to get a little bit of like the motivation, right? Like, so you left Shopify, you're like principal, engineer, infra guy. Um, you also head of kernel labs, uh, inside of Shopify, right?And then you consulted for read wise and that it kind of gave you that, that idea. I just wanted you to tell that story. Um, maybe I, you've told it before, but, uh, just introduce the, the. People to like the, the new workload, the sort of aha moment for turbo PufferSimon Hørup Eskildsen: For sure. So yeah, I spent almost a decade at Shopify.I was on the infrastructure team, um, from the fairly, fairly early days around 2013. Um, at the time it felt like it was growing so quickly and everything, all the metrics were, you know, doubling year on year compared to the, what companies are contending with today. It's very cute in growth. I feel like lot some companies are seeing that month over month.Um, of course. Shopify compound has been compounding for a very long time now, but I spent a decade doing that and the majority of that was just make sure the site is up today and make sure it's up a year from now. And a lot of that was really just the, um, you know, uh, the Kardashians would drive very, very large amounts of, of data to, to uh, to Shopify as they were rotating through all the merch and building out their businesses.And we just needed to make sure we could handle that. Right. And sometimes these were events, a million requests per second. And so, you know, we, we had our own data centers back in the day and we were moving to the cloud and there was so much sharding work and all of that that we were doing. So I spent a decade just scaling databases ‘cause that's fundamentally what's the most difficult thing to scale about these sites.The database that was the most difficult for me to scale during that time, and that was the most aggravating to be on call for, was elastic search. It was very, very difficult to deal with. And I saw a lot of projects that were just being held back in their ambition by using it.swyx: And I mean, self-hosted.Self-hosted. ‘causeSimon Hørup Eskildsen: it's, yeah, and it commercial, this is like 2015, right? So it's like a very particular vintage. Right. It's probably better at a lot of these things now. Um, it was difficult to contend with and I'm just like, I just think about it. It's an inverted index. It should be good at these kinds of queries and do all of this.And it was, we, we often couldn't get it to do exactly what we needed to do or basically get lucine to do, like expose lucine raw to, to, to what we needed to do. Um, so that was like. Just something that we did on the side and just panic scaled when we needed to, but not a particular focus of mine. So I left, and when I left, I, um, wasn't sure exactly what I wanted to do.I mean, it spent like a decade inside of the same company. I'd like grown up there. I started working there when I was 18.swyx: You only do Rails?Simon Hørup Eskildsen: Yeah. I mean, yeah. Rails. And he's a Rails guy. Uh, love Rails. So good. Um,Alessio: we all wish we could still work in Rails.swyx: I know know. I know, but some, I tried learning Ruby.It's just too much, like too many options to do the same thing. It's, that's my, I I know there's a, there's a way to do it.Simon Hørup Eskildsen: I love it. I don't know that I would use it now, like given cloud code and, and, and cursor and everything, but, um, um, but still it, like if I'm just sitting down and writing a teal code, that's how I think.But anyway, I left and I wasn't, I talked to a couple companies and I was like, I don't. I need to see a little bit more of the world here to know what I'm gonna like focus on next. Um, and so what I decided is like I was gonna, I called it like angel engineering, where I just hopped around in my friend's companies in three months increments and just helped them out with something.Right. And, and just vested a bit of equity and solved some interesting infrastructure problem. So I worked with a bunch of companies at the time, um, read Wise was one of them. Replicate was one of them. Um, causal, I dunno if you've tried this, it's like a, it's a spreadsheet engine Yeah. Where you can do distribution.They sold recently. Yeah. Um, we've been, we used that in fp and a at, um, at Turbo Puffer. Um, so a bunch of companies like this and it was super fun. And so we're the Chachi bt moment happened, I was with. With read Wise for a stint, we were preparing for the reader launch, right? Which is where you, you cue articles and read them later.And I was just getting their Postgres up to snuff, like, which basically boils down to tuning, auto vacuum. So I was doing that and then this happened and we were like, oh, maybe we should build a little recommendation engine and some features to try to hook in the lms. They were not that good yet, but it was clear there was something there.And so I built a small recommendation engine just, okay, let's take the articles that you've recently read, right? Like embed all the articles and then do recommendations. It was good enough that when I ran it on one of the co-founders of Rey's, like I found out that I got articles about, about having a child.I'm like, oh my God, I didn't, I, I didn't know that, that they were having a child. I wasn't sure what to do with that information, but the recommendation engine was good enough that it was suggesting articles, um, about that. And so there was, there was recommendations and uh, it actually worked really well.But this was a company that was spending maybe five grand a month in total on all their infrastructure and. When I did the napkin math on running the embeddings of all the articles, putting them into a vector index, putting it in prod, it's gonna be like 30 grand a month. That just wasn't tenable. Right?Like Read Wise is a proudly bootstrapped company and it's paying 30 grand for infrastructure for one feature versus five. It just wasn't tenable. So sort of in the bucket of this is useful, it's pretty good, but let us, let's return to it when the costs come down.swyx: Did you say it grows by feature? So for five to 30 is by the number of, like, what's the, what's the Scaling factor scale?It scales by the number of articles that you embed.Simon Hørup Eskildsen: It does, but what I meant by that is like five grand for like all of the other, like the Heroku, dinos, Postgres, like all the other, and this then storage is 30. Yeah. And then like 30 grand for one feature. Right. Which is like, what other articles are related to this one.Um, so it was just too much right to, to power everything. Their budget would've been maybe a few thousand dollars, which still would've been a lot. And so we put it in a bucket of, okay, we're gonna do that later. We'll wait, we will wait for the cost to come down. And that haunted me. I couldn't stop thinking about it.I was like, okay, there's clearly some latent demand here. If the cost had been a 10th, we would've shipped it and. This was really the only data point that I had. Right. I didn't, I, I didn't, I didn't go out and talk to anyone else. It was just so I started reading Right. I couldn't, I couldn't help myself.Like I didn't know what like a vector index is. I, I generally barely do about how to generate the vectors. There was a lot of hype about, this is a early 2023. There was a lot of hype about vector databases. There were raising a lot of money and it's like, I really didn't know anything about it. It's like, you know, trying these little models, fine tuning them.Like I was just trying to get sort of a lay of the land. So I just sat down. I have this. A GitHub repository called Napkin Math. And on napkin math, there's just, um, rows of like, oh, this is how much bandwidth. Like this is how many, you know, you can do 25 gigabytes per second on average to dram. You can do, you know, five gigabytes per second of rights to an SSD, blah blah.All of these numbers, right? And S3, how many you could do per, how much bandwidth can you drive per connection? I was just sitting down, I was like, why hasn't anyone build a database where you just put everything on O storage and then you puff it into NVME when you use the data and you puff it into dram if you're, if you're querying it alive, it's just like, this seems fairly obvious and you, the only real downside to that is that if you go all in on o storage, every right will take a couple hundred milliseconds of latency, but from there it's really all upside, right?You do the first go, it takes half a second. And it sort of occurred to me as like, well. The architecture is really good for that. It's really good for AB storage, it's really good for nvm ESSD. It's, well, you just couldn't have done that 10 years ago. Back to what we were talking about before. You really have to build a database where you have as few round trips as possible, right?This is how CPUs work today. It's how NVM E SSDs work. It's how as, um, as three works that you want to have a very large amount of outstanding requests, right? Like basically go to S3, do like that thousand requests to ask for data in one round trip. Wait for that. Get that, like, make a new decision. Do it again, and try to do that maybe a maximum of three times.But no databases were designed that way within NVME as is ds. You can drive like within, you know, within a very low multiple of DRAM bandwidth if you use it that way. And same with S3, right? You can fully max out the network card, which generally is not maxed out. You get very, like, very, very good bandwidth.And, but no one had built a database like that. So I was like, okay, well can't you just, you know, take all the vectors right? And plot them in the proverbial coordinate system. Get the clusters, put a file on S3 called clusters, do json, and then put another file for every cluster, you know, cluster one, do js O cluster two, do js ON you know that like it's two round trips, right?So you get the clusters, you find the closest clusters, and then you download the cluster files like the, the closest end. And you could do this in two round trips.swyx: You were nearest neighbors locally.Simon Hørup Eskildsen: Yes. Yes. And then, and you would build this, this file, right? It's just like ultra simplistic, but it's not a far shot from what the first version of Turbo Buffer was.Why hasn't anyone done thatAlessio: in that moment? From a workload perspective, you're thinking this is gonna be like a read heavy thing because they're doing recommend. Like is the fact that like writes are so expensive now? Oh, with ai you're actually not writing that much.Simon Hørup Eskildsen: At that point I hadn't really thought too much about, well no actually it was always clear to me that there was gonna be a lot of rights because at Shopify, the search clusters were doing, you know, I don't know, tens or hundreds of crew QPS, right?‘cause you just have to have a human sit and type in. But we did, you know, I don't know how many updates there were per second. I'm sure it was in the millions, right into the cluster. So I always knew there was like a 10 to 100 ratio on the read write. In the read wise use case. It's, um, even, even in the read wise use case, there'd probably be a lot fewer reads than writes, right?There's just a lot of churn on the amount of stuff that was going through versus the amount of queries. Um, I wasn't thinking too much about that. I was mostly just thinking about what's the fundamentally cheapest way to build a database in the cloud today using the primitives that you have available.And this is it, right? You just, now you have one machine and you know, let's say you have a terabyte of data in S3, you paid the $200 a month for that, and then maybe five to 10% of that data and needs to be an NV ME SSDs and less than that in dram. Well. You're paying very, very little to inflate the data.swyx: By the way, when you say no one else has done that, uh, would you consider Neon, uh, to be on a similar path in terms of being sort of S3 first and, uh, separating the compute and storage?Simon Hørup Eskildsen: Yeah, I think what I meant with that is, uh, just build a completely new database. I don't know if we were the first, like it was very much, it was, I mean, I, I hadn't, I just looked at the napkin math and was like, this seems really obvious.So I'm sure like a hundred people came up with it at the same time. Like the light bulb and every invention ever. Right. It was just in the air. I think Neon Neon was, was first to it. And they're trying, they're retrofitted onto Postgres, right? And then they built this whole architecture where you have, you have it in memory and then you sort of.You know, m map back to S3. And I think that was very novel at the time to do it for, for all LTP, but I hadn't seen a database that was truly all in, right. Not retrofitting it. The database felt built purely for this no consensus layer. Even using compare and swap on optic storage to do consensus. I hadn't seen anyone go that all in.And I, I mean, there, there, I'm sure there was someone that did that before us. I don't know. I was just looking at the napkin mathswyx: and, and when you say consensus layer, uh, are you strongly relying on S3 Strong consistency? You are. Okay.SoSimon Hørup Eskildsen: that is your consensus layer. It, it is the consistency layer. And I think also, like, this is something that most people don't realize, but S3 only became consistent in December of 2020.swyx: I remember this coming out during COVID and like people were like, oh, like, it was like, uh, it was just like a free upgrade.Simon Hørup Eskildsen: Yeah.swyx: They were just, they just announced it. We saw consistency guys and like, okay, cool.Simon Hørup Eskildsen: And I'm sure that they just, they probably had it in prod for a while and they're just like, it's done right.And people were like, okay, cool. But. That's a big moment, right? Like nv, ME SSDs, were also not in the cloud until around 2017, right? So you just sort of had like 2017 nv, ME SSDs, and people were like, okay, cool. There's like one skew that does this, whatever, right? Takes a few years. And then the second thing is like S3 becomes consistent in 2020.So now it means you don't have to have this like big foundation DB or like zookeeper or whatever sitting there contending with the keys, which is how. You know, that's what Snowflake and others have do so muchswyx: for goneSimon Hørup Eskildsen: Exactly. Just gone. Right? And so just push to the, you know, whatever, how many hundreds of people they have working on S3 solved and then compare and swap was not in S3 at this point in time,swyx: by the way.Uh, I don't know what that is, so maybe you wanna explain. Yes. Yeah.Simon Hørup Eskildsen: Yes. So, um, what Compare and swap is, is basically, you can imagine that if you have a database, it might be really nice to have a file called metadata json. And metadata JSON could say things like, Hey, these keys are here and this file means that, and there's lots of metadata that you have to operate in the database, right?But that's the simplest way to do it. So now you have might, you might have a lot of servers that wanna change the metadata. They might have written a file and want the metadata to contain that file. But you have a hundred nodes that are trying to contend with this metadata that JSON well, what compare and Swap allows you to do is basically just you download the file, you make the modifications, and then you write it only if it hasn't changed.While you did the modification and if not you retry. Right? Should just have this retry loops. Now you can imagine if you have a hundred nodes doing that, it's gonna be really slow, but it will converge over time. That primitive was not available in S3. It wasn't available in S3 until late 2024, but it was available in GCP.The real story of this is certainly not that I sat down and like bake brained it. I was like, okay, we're gonna start on GCS S3 is gonna get it later. Like it was really not that we started, we got really lucky, like we started on GCP and we started on GCP because tur um, Shopify ran on GCP. And so that was the platform I was most available with.Right. Um, and I knew the Canadian team there ‘cause I'd worked with them at Shopify and so it was natural for us to start there. And so when we started building the database, we're like, oh yeah, we have to build a, we really thought we had to build a consensus layer, like have a zookeeper or something to do this.But then we discovered the compare and swap. It's like, oh, we can kick the can. Like we'll just do metadata r json and just, it's fine. It's probably fine. Um, and we just kept kicking the can until we had very, very strong conviction in the idea. Um, and then we kind of just hinged the company on the fact that S3 probably was gonna get this, it started getting really painful in like mid 2024.‘cause we were closing deals with, um, um, notion actually that was running in AWS and we're like, trust us. You, you really want us to run this in GCP? And they're like, no, I don't know about that. Like, we're running everything in AWS and the latency across the cloud were so big and we had so much conviction that we bought like, you know, dark fiber between the AWS regions in, in Oregon, like in the InterExchange and GCP is like, we've never seen a startup like do like, what's going on here?And we're just like, no, we don't wanna do this. We were tuning like TCP windows, like everything to get the latency down ‘cause we had so high conviction in not doing like a, a metadata layer on S3. So those were the three conditions, right? Compare and swap. To do metadata, which wasn't in S3 until late 2024 S3 being consistent, which didn't happen until December, 2020.Uh, 2020. And then NVMe ssd, which didn't end in the cloud until 2017.swyx: I mean, in some ways, like a very big like cloud success story that like you were able to like, uh, put this all together, but also doing things like doing, uh, bind our favor. That that actually is something I've never heard.Simon Hørup Eskildsen: I mean, it's very common when you're a big company, right?You're like connecting your own like data center or whatever. But it's like, it was uniquely just a pain with notion because the, um, the org, like most of the, like if you're buying in Ashburn, Virginia, right? Like US East, the Google, like the GCP and, and AWS data centers are like within a millisecond on, on each other, on the public exchanges.But in Oregon uniquely, the GCP data center sits like a couple hundred kilometers, like east of Portland and the AWS region sits in Portland, but the network exchange they go through is through Seattle. So it's like a full, like 14 milliseconds or something like that. And so anyway, yeah. It's, it's, so we were like, okay, we can't, we have to go through an exchange in Portland.Yeah. Andswyx: you'd rather do this than like run your zookeeper and likeSimon Hørup Eskildsen: Yes. Way rather. It doesn't have state, I don't want state and two systems. Um, and I think all that is just informed by Justine, my co-founder and I had just been on call for so long. And the worst outages are the ones where you have state in multiple places that's not syncing up.So it really came from, from a a, like just a, a very pure source of pain, of just imagining what we would be Okay. Being woken up at 3:00 AM about and having something in zookeeper was not one of them.swyx: You, you're talking to like a notion or something. Do they care or do they just, theySimon Hørup Eskildsen: just, they care about latency.swyx: They latency cost. That's it.Simon Hørup Eskildsen: They just cared about latency. Right. And we just absorbed the cost. We're just like, we have high conviction in this. At some point we can move them to AWS. Right. And so we just, we, we'll buy the fiber, it doesn't matter. Right. Um, and it's like $5,000. Usually when you buy fiber, you buy like multiple lines.And we're like, we can only afford one, but we will just test it that when it goes over the public internet, it's like super smooth. And so we did a lot of, anyway, it's, yeah, it was, that's cool.Alessio: You can imagine talking to the GCP rep and it's like, no, we're gonna buy, because we know we're gonna turn, we're gonna turn from you guys and go to AWS in like six months.But in the meantime we'll do this. It'sSimon Hørup Eskildsen: a, I mean, like they, you know, this workload still runs on GCP for what it's worth. Right? ‘cause it's so, it was just, it was so reliable. So it was never about moving off GCP, it was just about honesty. It was just about giving notion the latency that they deserved.Right. Um, and we didn't want ‘em to have to care about any of this. We also, they were like, oh, egress is gonna be bad. It was like, okay, screw it. Like we're just gonna like vvc, VPC peer with you and AWS we'll eat the cost. Yeah. Whatever needs to be done.Alessio: And what were the actual workloads? Because I think when you think about ai, it's like 14 milliseconds.It's like really doesn't really matter in the scheme of like a model generation.Simon Hørup Eskildsen: Yeah. We were told the latency, right. That we had to beat. Oh, right. So, so we're just looking at the traces. Right. And then sort of like hand draw, like, you know, kind of like looking at the trace and then thinking what are the other extensions of the trace?Right. And there's a lot more to it because it's also when you have, if you have 14 versus seven milliseconds, right. You can fit in another round trip. So we had to tune TCP to try to send as much data in every round trip, prewarm all the connections. And there was, there's a lot of things that compound from having these kinds of round trips, but in the grand scheme it was just like, well, we have to beat the latency of whatever we're up against.swyx: Which is like they, I mean, notion is a database company. They could have done this themselves. They, they do lots of database engineering themselves. How do you even get in the door? Like Yeah, just like talk through that kind of.Simon Hørup Eskildsen: Last time I was in San Francisco, I was talking to one of the engineers actually, who, who was one of our champions, um, at, AT Notion.And they were, they were just trying to make sure that the, you know, per user cost matched the economics that they needed. You know, Uhhuh like, it's like the way I think about, it's like I have to earn a return on whatever the clouds charge me and then my customers have to earn a return on that. And it's like very simple, right?And so there has to be gross margin all the way up and that's how you build the product. And so then our customers have to make the right set of trade off the turbo Puffer makes, and if they're happy with that, that's great.swyx: Do you feel like you're competing with build internally versus buy or buy versus buy?Simon Hørup Eskildsen: Yeah, so, sorry, this was all to build up to your question. So one of the notion engineers told me that they'd sat and probably on a napkin, like drawn out like, why hasn't anyone built this? And then they saw terrible. It was like, well, it literally that. So, and I think AI has also changed the buy versus build equation in terms of, it's not really about can we build it, it's about do we have time to build it?I think they like, I think they felt like, okay, if this is a team that can do that and they, they feel enough like an extension of our team, well then we can go a lot faster, which would be very, very good for them. And I mean, they put us through the, through the test, right? Like we had some very, very long nights to to, to do that POC.And they were really our biggest, our second big customer off the cursor, which also was a lot of late nights. Right.swyx: Yeah. That, I mean, should we go into that story? The, the, the sort of Chris's story, like a lot, um, they credit you a lot for. Working very closely with them. So I just wanna hear, I've heard this, uh, story from Sole's point of view, but like, I'm curious what, what it looks like from your side.Simon Hørup Eskildsen: I actually haven't heard it from Sole's point of view, so maybe you can now cross reference it. The way that I remember it was that, um, the day after we launched, which was just, you know, I'd worked the whole summer on, on the first version. Justine wasn't part of it yet. ‘cause I just, I didn't tell anyone that summer that I was working on this.I was just locked in on building it because it's very easy otherwise to confuse talking about something to actually doing it. And so I was just like, I'm not gonna do that. I'm just gonna do the thing. I launched it and at this point turbo puffer is like a rust binary running on a single eight core machine in a T Marks instance.And me deploying it was like looking at the request log and then like command seeing it or like control seeing it to just like, okay, there's no request. Let's upgrade the binary. Like it was like literally the, the, the, the scrappiest thing. You could imagine it was on purpose because just like at Shopify, we did that all the time.Like, we like move, like we ran things in tux all the time to begin with. Before something had like, at least the inkling of PMF, it was like, okay, is anyone gonna hear about this? Um, and one of the cursor co-founders Arvid reached out and he just, you know, the, the cursor team are like all I-O-I-I-M-O like, um, contenders, right?So they just speak in bullet points and, and facts. It was like this amazing email exchange just of, this is how many QPS we have, this is what we're paying, this is where we're going, blah, blah, blah. And so we're just conversing in bullet points. And I tried to get a call with them a few times, but they were, so, they were like really writing the PMF bowl here, just like late 2023.And one time Swally emails me at like five. What was it like 4:00 AM Pacific time saying like, Hey, are you open for a call now? And I'm on the East coast and I, it was like 7:00 AM I was like, yeah, great, sure, whatever. Um, and we just started talking and something. Then I didn't know anything about sales.It was something that just comp compelled me. I have to go see this team. Like, there's something here. So I, I went to San Francisco and I went to their office and the way that I remember it is that Postgres was down when I showed up at the office. Did SW tell you this? No. Okay. So Postgres was down and so it's like they were distracting with that.And I was trying my best to see if I could, if I could help in any way. Like I knew a little bit about databases back to tuning, auto vacuum. It was like, I think you have to tune out a vacuum. Um, and so we, we talked about that and then, um, that evening just talked about like what would it look like, what would it look like to work with us?And I just said. Look like we're all in, like we will just do what we'll do whatever, whatever you tell us, right? They migrated everything over the next like week or two, and we reduced their cost by 95%, which I think like kind of fixed their per user economics. Um, and it solved a lot of other things. And we were just, Justine, this is also when I asked Justine to come on as my co-founder, she was the best engineer, um, that I ever worked with at Shopify.She lived two blocks away and we were just, okay, we're just gonna get this done. Um, and we did, and so we helped them migrate and we just worked like hell over the next like month or two to make sure that we were never an issue. And that was, that was the cursor story. Yeah.swyx: And, and is code a different workload than normal text?I, I don't know. Is is it just text? Is it the same thing?Simon Hørup Eskildsen: Yeah, so cursor's workload is basically, they, um, they will embed the entire code base, right? So they, they will like chunk it up in whatever they would, they do. They have their own embedding model, um, which they've been public about. Um, and they find that on, on, on their evals.It. There's one of their evals where it's like a 25% improvement on a very particular workload. They have a bunch of blog posts about it. Um, I think it works best on larger code basis, but they've trained their own embedding model to do this. Um, and so you'll see it if you use the cursor agent, it will do searches.And they've also been public around, um, how they've, I think they post trained their model to be very good at semantic search as well. Um, and that's, that's how they use it. And so it's very good at, like, can you find me on the code that's similar to this, or code that does this? And just in, in this queries, they also use GR to supplement it.swyx: Yeah.Simon Hørup Eskildsen: Um, of courseswyx: it's been a big topic of discussion like, is rag dead because gr you know,Simon Hørup Eskildsen: and I mean like, I just, we, we see lots of demand from the coding company to ethicsswyx: search in every part. Yes.Simon Hørup Eskildsen: Uh, we, we, we see demand. And so, I mean, I'm. I like case studies. I don't like, like just doing like thought pieces on this is where it's going.And like trying to be all macroeconomic about ai, that's has turned out to be a giant waste of time because no one can really predict any of this. So I just collect case studies and I mean, cursor has done a great job talking about what they're doing and I hope some of the other coding labs that use Turbo Puffer will do the same.Um, but it does seem to make a difference for particular queries. Um, I mean we can also do text, we can also do RegX, but I should also say that cursors like security posture into Tur Puffer is exceptional, right? They have their own embedding model, which makes it very difficult to reverse engineer. They obfuscate the file paths.They like you. It's very difficult to learn anything about a code base by looking at it. And the other thing they do too is that for their customers, they encrypt it with their encryption keys in turbo puffer's bucket. Um, so it's, it's, it's really, really well designed.swyx: And so this is like extra stuff they did to work with you because you are not part of Cursor.Exactly like, and this is just best practice when working in any database, not just you guys. Okay. Yeah, that makes sense. Yeah. I think for me, like the, the, the learning is kind of like you, like all workloads are hybrid. Like, you know, uh, like you, you want the semantic, you want the text, you want the RegX, you want sql.I dunno. Um, but like, it's silly to like be all in on like one particularly query pattern.Simon Hørup Eskildsen: I think, like I really like the way that, um, um, that swally at cursor talks about it, which is, um, I'm gonna butcher it here. Um, and you know, I'm a, I'm a database scalability person. I'm not a, I, I dunno anything about training models other than, um, what the internet tells me and what.The way he describes is that this is just like cash compute, right? It's like you have a point in time where you're looking at some particular context and focused on some chunk and you say, this is the layer of the neural net at this point in time. That seems fundamentally really useful to do cash compute like that.And, um, how the value of that will change over time. I'm, I'm not sure, but there seems to be a lot of value in that.Alessio: Maybe talk a bit about the evolution of the workload, because even like search, like maybe two years ago it was like one search at the start of like an LLM query to build the context. Now you have a gentech search, however you wanna call it, where like the model is both writing and changing the code and it's searching it again later.Yeah. What are maybe some of the new types of workloads or like changes you've had to make to your architecture for it?Simon Hørup Eskildsen: I think you're right. When I think of rag, I think of, Hey, there's an 8,000 token, uh, context window and you better make it count. Um, and search was a way to do that now. Everything is moving towards the, just let the agent do its thing.Right? And so back to the thing before, right? The LLM is very good at reasoning with the data, and so we're just the tool call, right? And that's increasingly what we see our customers doing. Um, what we're seeing more demand from, from our customers now is to do a lot of concurrency, right? Like Notion does a ridiculous amount of queries in every round trip just because they can't.And I'm also now, when I use the cursor agent, I also see them doing more concurrency than I've ever seen before. So a bit similar to how we designed a database to drive as much concurrency in every round trip as possible. That's also what the agents are doing. So that's new. It means just an enormous amount of queries all at once to the dataset while it's warm in as few turns as possible.swyx: Can I clarify one thing on that?Simon Hørup Eskildsen: Yes.swyx: Is it, are they batching multiple users or one user is driving multiple,Simon Hørup Eskildsen: one user driving multiple, one agent driving.swyx: It's parallel searching a bunch of things.Simon Hørup Eskildsen: Exactly.swyx: Yeah. Yeah, exactly. So yeah, the clinician also did, did this for the fast context thing, like eight parallel at once.Simon Hørup Eskildsen: Yes.swyx: And, and like an interesting problem is, well, how do you make sure you have enough diversity so you're not making the the same request eight times?Simon Hørup Eskildsen: And I think like that's probably also where the hybrid comes in, where. That's another way to diversify. It's a completely different way to, to do the search.That's a big change, right? So before it was really just like one call and then, you know, the LLM took however many seconds to return, but now we just see an enormous amount of queries. So the, um, we just see more queries. So we've like tried to reduce query, we've reduced query pricing. Um, this is probably the first time actually I'm saying that, but the query pricing is being reduced, like five x.Um, and we'll probably try to reduce it even more to accommodate some of these workloads of just doing very large amounts of queries. Um, that's one thing that's changed. I think the right, the right ratio is still very high, right? Like there's still a, an enormous amount of rights per read, but we're starting probably to see that change if people really lean into this pattern.Alessio: Can we talk a little bit about the pricing? I'm curious, uh, because traditionally a database would charge on storage, but now you have the token generation that is so expensive, where like the actual. Value of like a good search query is like much higher because they're like saving inference time down the line.How do you structure that as like, what are people receptive to on the other side too?Simon Hørup Eskildsen: Yeah. I, the, the turbo puffer pricing in the beginning was just very simple. The pricing on these on for search engines before Turbo Puffer was very server full, right? It was like, here's the vm, here's the per hour cost, right?Great. And I just sat down with like a piece of paper and said like, if Turbo Puffer was like really good, this is probably what it would cost with a little bit of margin. And that was the first pricing of Turbo Puffer. And I just like sat down and I was like, okay, like this is like probably the storage amp, but whenever on a piece of paper I, it was vibe pricing.It was very vibe price, and I got it wrong. Oh. Um, well I didn't get it wrong, but like Turbo Puffer wasn't at the first principle pricing, right? So when Cursor came on Turbo Puffer, it was like. Like, I didn't know any VCs. I didn't know, like I was just like, I don't know, I didn't know anything about raising money or anything like that.I just saw that my GCP bill was, was high, was a lot higher than the cursor bill. So Justine and I was just like, well, we have to optimize it. Um, and I mean, to the chagrin now of, of it, of, of the VCs, it now means that we're profitable because we've had so much pricing pressure in the beginning. Because it was running on my credit card and Justine and I had spent like, like tens of thousands of dollars on like compute bills and like spinning off the company and like very like, like bad Canadian lawyers and like things like to like get all of this done because we just like, we didn't know.Right. If you're like steeped in San Francisco, you're just like, you just know. Okay. Like you go out, raise a pre-seed round. I, I never heard a word pre-seed at this point in time.swyx: When you had Cursor, you had Notion you, you had no funding.Simon Hørup Eskildsen: Um, with Cursor we had no funding. Yeah. Um, by the time we had Notion Locke was, Locke was here.Yeah. So it was really just, we vibe priced it 100% from first Principles, but it wasn't, it, it was not performing at first principles, so we just did everything we could to optimize it in the beginning for that, so that at least we could have like a 5% margin or something. So I wasn't freaking out because Cursor's bill was also going like this as they were growing.And so my liability and my credit limit was like actively like calling my bank. It was like, I need a bigger credit. Like it was, yeah. Anyway, that was the beginning. Yeah. But the pricing was, yeah, like storage rights and query. Right. And the, the pricing we have today is basically just that pricing with duct tape and spit to try to approach like, you know, like a, as a margin on the physical underlying hardware.And we're doing this year, you're gonna see more and more pricing changes from us. Yeah.swyx: And like is how much does stuff like VVC peering matter because you're working in AWS land where egress is charged and all that, you know.Simon Hørup Eskildsen: We probably don't like, we have like an enterprise plan that just has like a base fee because we haven't had time to figure out SKU pricing for all of this.Um, but I mean, yeah, you can run turbo puffer either in SaaS, right? That's what Cursor does. You can run it in a single tenant cluster. So it's just you. That's what Notion does. And then you can run it in, in, in BYOC where everything is inside the customer's VPC, that's what an for example, philanthropic does.swyx: What I'm hearing is that this is probably the best CRO job for somebody who can come in and,Simon Hørup Eskildsen: I mean,swyx: help you with this.Simon Hørup Eskildsen: Um, like Turbo Puffer hired, like, I don't know what, what number this was, but we had a full-time CFO as like the 12th hire or something at Turbo Puffer, um, I think I hear are a lot of comp.I don't know how they do it. Like they have a hundred employees and not a CFO. It's like having a CFO is like a runningswyx: business man. Like, you know,Simon Hørup Eskildsen: it's so good. Yeah, like money Mike, like he just, you know, just handles the money and a lot of the business stuff and so he came in and just hopped with a lot of the operational side of the business.So like C-O-O-C-F-O, like somewhere in between.swyx: Just as quick mention of Lucky, just ‘cause I'm curious, I've met Lock and like, he's obviously a very good investor and now on physical intelligence, um, I call it generalist super angel, right? He invests in everything. Um, and I always wonder like, you know, is there something appealing about focusing on developer tooling, focusing on databases, going like, I've invested for 10 years in databases versus being like a lock where he can maybe like connect you to all the customers that you need.Simon Hørup Eskildsen: This is an excellent question. No, no one's asked me this. Um, why lockey? Because. There was a couple of people that we were talking to at the time and when we were raising, we were almost a little, we were like a bit distressed because one of our, one of our peers had just launched something that was very similar to Turbo Puffer.And someone just gave me the advice at the time of just choose the person where you just feel like you can just pick up the phone and not prepare anything. And just be completely honest, and I don't think I've said this publicly before, but I just called Lockey and was like local Lockie. Like if this doesn't have PMF by the end of the year, like we'll just like return all the money to you.But it's just like, I don't really, we, Justine and I don't wanna work on this unless it's really working. So we want to give it the best shot this year and like we're really gonna go for it. We're gonna hire a bunch of people and we're just gonna be honest with everyone. Like when I don't know how to play a game, I just play with open cards and.Lockey was the only person that didn't, that didn't freak out. He was like, I've never heard anyone say that before. As I said, I didn't even know what a seed or pre-seed round was like before, probably even at this time. So I was just like very honest with him. And I asked him like, Lockie, have you ever have, have you ever invested in database company?He was just like, no. And at the time I was like, am I dumb? Like, but I think there was something that just like really drew me to Lockie. He is so authentic, so honest, like, and there was something just like, I just felt like I could just play like, just say everything openly. And that was, that was, I think that that was like a perfect match at the time, and, and, and honestly still is.He was just like, okay, that's great. This is like the most honest, ridiculous thing I've ever heard anyone say to me. But like that, like that, whyswyx: is this ridiculous? Say competitor launch, this may not work out. It wasSimon Hørup Eskildsen: more just like. If this doesn't work out, I'm gonna close up shop by the end of the mo the year, right?Like it was, I don't know, maybe it's common. I, I don't know. He told me it was uncommon. I don't know. Um, that's why we chose him and he'd been phenomenal. The other people were talking at the, at the time were database experts. Like they, you know, knew a lot about databases and Locke didn't, this turned out to be a phenomenal asset.Right. I like Justine and I know a lot about databases. The people that we hire know a lot about databases. What we needed was just someone who didn't know a lot about databases, didn't pretend to know a lot about databases, and just wanted to help us with candidates and customers. And he did. Yeah. And I have a list, right, of the investors that I have a relationship with, and Lockey has just performed excellent in the number of sub bullets of what we can attribute back to him.Just absolutely incredible. And when people talk about like no ego and just the best thing for the founder, I like, I don't think that anyone, like even my lawyer is like, yeah, Lockey is like the most friendly person you will find.swyx: Okay. This is my most glow recommendation I've ever heard.Alessio: He deserves it.He's very special.swyx: Yeah. Yeah. Yeah. Okay. Amazing.Alessio: Since you mentioned candidates, maybe we can talk about team building, you know, like, especially in sf, it feels like it's just easier to start a company than to join a company. Uh, I'm curious your experience, especially not being n SF full-time and doing something that is maybe, you know, a very low level of detail and technical detail.Simon Hørup Eskildsen: Yeah. So joining versus starting, I never thought that I would be a founder. I would start with it, like Turbo Puffer started as a blog post, and then it became a project and then sort of almost accidentally became a company. And now it feels like it's, it's like becoming a bigger company. That was never the intention.The intentions were very pure. It's just like, why hasn't anyone done this? And it's like, I wanna be the, like, I wanna be the first person to do it. I think some founders have this, like, I could never work for anyone else. I, I really don't feel that way. Like, it's just like, I wanna see this happen. And I wanna see it happen with some people that I really enjoy working with and I wanna have fun doing it and this, this, this has all felt very natural on that, on that sense.So it was never a like join versus versus versus found. It was just dis found me at the right moment.Alessio: Well I think there's an argument for, you should have joined Cursor, right? So I'm curious like how you evaluate it. Okay, I should actually go raise money and make this a company versus like, this is like a company that is like growing like crazy.It's like an interesting technical problem. I should just build it within Cursor and then they don't have to encrypt all this stuff. They don't have to obfuscate things. Like was that on your mind at all orSimon Hørup Eskildsen: before taking the, the small check from Lockie, I did have like a hard like look at myself in the mirror of like, okay, do I really want to do this?And because if I take the money, I really have to do it right. And so the way I almost think about it's like you kind of need to ha like you kind of need to be like fucked up enough to want to go all the way. And that was the conversation where I was like, okay, this is gonna be part of my life's journey to build this company and do it in the best way that I possibly can't.Because if I ask people to join me, ask people to get on the cap table, then I have an ultimate responsibility to give it everything. And I don't, I think some people, it doesn't occur to me that everyone takes it that seriously. And maybe I take it too seriously, I don't know. But that was like a very intentional moment.And so then it was very clear like, okay, I'm gonna do this and I'm gonna give it everything.Alessio: A lot of people don't take it this seriously. But,swyx: uh, let's talk about, you have this concept of the P 99 engineer. Uh, people are 10 x saying, everyone's saying, you know, uh, maybe engineers are out of a job. I don't know.But you definitely see a P 99 engineer, and I just want you to talk about it.Simon Hørup Eskildsen: Yeah, so the P 99 engineer was just a term that we started using internally to talk about candidates and talk about how we wanted to build the company. And you know, like everyone else is, like we want a talent dense company.And I think that's almost become trite at this point. What I credit the cursor founders a lot with is that they just arrived there from first principles of like, we just need a talent dense, um, talent dense team. And I think I've seen some teams that weren't talent dense and like seemed a counterfactual run, which if you've run in been in a large company, you will just see that like it's just logically will happen at a large company.Um, and so that was super important to me and Justine and it's very difficult to maintain. And so we just needed, we needed wording for it. And so I have a document called Traits of the P 99 Engineer, and it's a bullet point list. And I look at that list after every single interview that I do, and in every single recap that we do and every recap we end with.End with, um, some version of I'm gonna reject this candidate completely regardless of what the discourse was, because I wanna see people fight for this person because the default should not be, we're gonna hire this person. The default should be, we're definitely not hiring this person. And you know, if everyone was like, ah, maybe throw a punch, then this is not the right.swyx: Do, do you operate, like if there's one cha there must have at least one champion who's like, yes, I will put my career on, on, on the line for this. You know,Simon Hørup Eskildsen: I think career on the line,swyx: maybe a chair, butSimon Hørup Eskildsen: yeah. You know, like, um, I would say so someone needs to like, have both fists up and be like, I'd fight.Right? Yeah. Yeah. And if one person said, then, okay, let's do it. Right?swyx: Yeah.Simon Hørup Eskildsen: Um. It doesn't have to be absolutely everyone. Right? And like the interviews are always the sign that you're checking for different attributes. And if someone is like knocking it outta the park in every single attribute, that's, that's fairly rare.Um, but that's really important. And so the traits of the P 99 engineer, there's lots of them. There's also the traits of the p like triple nine engineer and the quadruple nine engineer. This is like, it's a long list.swyx: Okay.Simon Hørup Eskildsen: Um, I'll give you some samples, right. Of what we, what we look for. I think that the P 99 engineer has some history of having bent, like their trajectory or something to their will.Right? Some moment where it was just, they just, you know, made the computer do what it needed to do. There's something like that, and it will, it will occur to have them at some point in their career. And, uh. Hopefully multiple times. Right.swyx: Gimme an example of one of your engineers that like,Simon Hørup Eskildsen: I'll give an eng.Uh, so we, we, we launched this thing called A and NV three. Um, we could, we're also, we're working on V four and V five right now, but a and NV three can search a hundred billion vectors with a P 50 of around 40 milliseconds and a p 99 of 200 milliseconds. Um, maybe other people have done this, I'm sure Google and others have done this, but, uh, we haven't seen anyone, um, at least not in like a public consumable SaaS that can do this.And that was an engineer, the chief architect of Turbo Puffer, Nathan, um, who more or less just bent this, the software was not capable of this and he just made it capable for a very particular workload in like a, you know, six to eight week period with the help of a lot of the team. Right. It's been, been, there's numerous of examples of that, like at, at turbo puff, but that's like really bending the software and X 86 to your will.It was incredible to watch. Um. You wanna see some moments like that?swyx: Isn't that triple nine?Simon Hørup Eskildsen: Um, I think Nathan, what's calledAlessio: group nine, that was only nine. I feel like this is too high forSimon Hørup Eskildsen: Nathan. Nathan is, uh, Nathan is like, yeah, there's a lot of nines. Okay. After that p So I think that's one trait. I think another trait is that, uh, the P 99 spends a lot of time looking at maps.Generally it's their preferred ux. They just love looking at maps. You ever seen someone who just like, sits on their phone and just like, scrolls around on a map? Or did you not look at maps A lot? You guys don't look atswyx: maps? I guess I'm not feeling there. I don't know, butSimon Hørup Eskildsen: you just dis What about trains?Do you like trains?swyx: Uh, I mean they, not enough. Okay. This is just like weapon nice. Autism is what I call it. Like, like,Simon Hørup Eskildsen: um, I love looking at maps, like, it's like my preferred UX and just like I, you know, I likeswyx: lotsAlessio: of, of like random places, soswyx: like,youswyx: know.Alessio: Yes. Okay. There you go. So instead of like random places, like how do you explore the maps?Simon Hørup Eskildsen: No, it's, it's just a joke.swyx: It's autism laugh. It's like you are just obsessed by something and you like studying a thing.Simon Hørup Eskildsen: The origin of this was that at some point I read an interview with some IOI gold medalistswyx: Uhhuh,Simon Hørup Eskildsen: and it's like, what do you do in your spare time? I was just like, I like looking at maps.I was like, I feel so seen. Like, I just like love, like swirling out. I was like, oh, Canada is so big. Where's Baffin Island? I don't know. I love it. Yeah. Um, anyway, so the traits of P 99, P 99 is obsessive, right? Like, there's just like, you'll, you'll find traits of that we do an interview at, at, at, at turbo puffer or like multiple interviews that just try to screen for some of these things.Um, so. There's lots of others, but these are the kinds of traits that we look for.swyx: I'll tell you, uh, some people listen for like some of my dere stuff. Uh, I do think about derel as maps. Um, you draw a map for people, uh, maps show you the, uh, what is commonly agreed to be the geographical features of what a boundary is.And it shows also shows you what is not doing. And I, I think a lot of like developer tools, companies try to tell you they can do everything, but like, let's, let's be real. Like you, your, your three landmarks are here, everyone comes here, then here, then here, and you draw a map and, and then you draw a journey through the map.And like that. To me, that's what developer relations looks like. So I do think about things that way.Simon Hørup Eskildsen: I think the P 99 thinks in offs, right? The P 99 is very clear about, you know, hey, turbo puffer, you can't run a high transaction workload on turbo puffer, right? It's like the right latency is a hundred milliseconds.That's a clear trade off. I think the P 99 is very good at articulating the trade offs in every decision. Um. Which is exactly what the map is in your case, right?swyx: Uh, yeah, yeah. My, my, my world. My world.Alessio: How, how do you reconcile some of these things when you're saying you bend the will the computer versus like the trade

In this episode, Helen is joined by Bridie O'Shea, Customer Insight and Excellence Specialist at Mansfield Building Society. Bridie shares how her role focuses on improving customer journeys and ensuring vulnerable customers receive the support they need.Together, they explore the importance of going back to basics — embedding vulnerability awareness into everyday practice, building networks of champions across teams, and recognising the often-overlooked needs of carers.  Helen and Bridie also discuss the vital role local branches play in their communities, how meaningful human connections help identify when customers may need extra support, and why this matters even more as financial services become increasingly digital.  From supporting colleagues through difficult conversations to simple acts of kindness that make a real difference, this episode highlights why vulnerability work is a continuous journey of learning, listening and improving. Why not join our free monthly Q&As and keep the conversation going - https://www.helenpettifer.com/category/events/live-q-and-a/Follow me for more episodes, resources and vulnerability insights - Email: helen@helenpettifer.com LinkedIn: https://www.linkedin.com/in/helen-pettifer-unlocking-vulnerability/ Website: https://www.helenpettifer.com/ 

Fixation on Histology: Understanding the Tools of Embedding Written based on the NSH Webinar: Embedding Basics & Troubleshooting To read the full blog, click here. 

What if being unmistakably human is your biggest competitive advantage in an AI-first world? In this episode, I sat down with Louis Carter, founder of Most Loved Workplace, to talk about why workplace culture is being tested and reshaped faster than ever. Louis shared how “most loved” isn't a slogan, it's a credibility signal grounded in real employee sentiment, and why being unmistakably human is becoming a serious competitive advantage in an AI-driven world. We also unpacked his idea of “inaction fatigue” (when leaders collect feedback but don't act), plus practical ways leaders can embed trust, respect, and emotional connection into the employee and customer experience so the world actually sees what's happening inside the company. Here are the highlights: -Culture as a competitive signal: “Most loved” works when it's validated by real employee sentiment, not just marketing. -Human advantage in an AI-first world: Being unmistakably human is becoming a standout differentiator as automation accelerates. -From feedback to follow-through: “Inaction fatigue” happens when employees share input but never see meaningful change. -The SPARK framework: Collaboration, shared vision, aligned values, respect, and outcomes create emotional connectedness at work. -Embedding love end-to-end: Culture should show up in onboarding, career paths, performance plans, and the customer experience.   About the guest: Louis Carter is a globally recognized organizational psychologist, author, speaker, and founder of Most Loved Workplace® and the Best Practice Institute (BPI). He created the Most Loved Workplace® certification and the Love of Workplace Index™, a data-driven methodology used by thousands of companies to build cultures where people feel deeply connected, respected, and engaged. Louis is the author of more than a dozen leadership and management books, including In Great Company: How to Spark Peak Performance by Creating an Emotionally Connected Workplace (McGraw-Hill), and his research has been featured in publications such as Forbes, Fast Company, Inc., and The Wall Street Journal. He has advised CEOs and executive teams from mid-sized firms to Fortune 500 organizations and is ranked among the top organizational culture thinkers in the world.   Connect with Louis: Website Business: http://www.mostlovedworkplace.com Personal: http://www.louiscarter.com LinkedIn Page: https://www.linkedin.com/in/louiscarter/ Facebook: https://www.facebook.com/louiscarter.bpi Instagram: https://www.instagram.com/louislcarter/ YouTube Channel: https://www.youtube.com/louiscarterchange X: x.com/louislcarter Books: https://louiscarter.com/leadership-books/   Connect with Allison: Feedspot has named Disruptive CEO Nation as one of the Top 25 CEO Podcasts on the web. LinkedIn: https://www.linkedin.com/in/allisonsummerschicago/ Website: https://www.disruptiveceonation.com/    #CEO #leadership #startup #founder #business #businesspodcast  Learn more about your ad choices. Visit megaphone.fm/adchoices

Sustainability pressures in banking are intensifying — even as ESG faces global pushback. In this episode, Heike Schmitz sits down with Ed Woolcock, Co‑Head of Energy Transition and Sustainability at Marsh Risk Consulting, to unpack why ESG‑related challenges continue to escalate across the banking sector. Drawing on insights from the Global Bank Review 2025, they explore how modern banks are navigating an operating environment defined by persistent complexity. From geopolitical fragmentation to rapid technological change and evolving workforce expectations, financial institutions increasingly find themselves at the centre of conflicting demands. A key theme of the discussion is how companies — and by extension, their banks — are being squeezed between diverging geopolitical priorities and mounting sustainability‑related risks. Ed and Heike examine the crucial role regulation may play in helping organisations manage these pressures, and why early recognition of sustainability‑driven risk trends is becoming a critical success factor for banks. The episode also connects to a wider article series produced by colleagues globally, which outlines why sustainability has shifted from a compliance exercise to a strategic imperative for banking operations. Read the full article: https://www.hsfkramer.com/insights/reports/2025/global-bank-review-2025/embedding-sustainability-into-banking-operations Read the Marsh report here: https://www.marsh.com/en/risks/climate-change-sustainability/insights/future-issb-sustainability-reporting.html Speakers: Heike Schmitz, Partner & Co Head of ESG EMEA at HSF Kramer Ed Woolcock, Co-Head Energy Transition & Sustainability of Marsh Risk Consulting

Is quality management the most thankless job in the organization? In many companies, QM teams want to be the Hermione Granger of the workplace—knowledgeable, prepared, and doing the right thing—but end up perceived as Argus Filch, the grumpy caretaker enforcing rules nobody asked for.This week's guest, Regina Haar, works at Q.Wiki (Modell Aachen), where she helps quality managers move from being considered annoying compliance police to becoming genuine enablers. She joins Roland to unpack why this role is so often stuck—and what it takes to change it from the inside out.In this episode we are talking about:The Harry Potter metaphor that lands every time: quality managers see themselves as Hermione (smart, principled, always prepared), but the organization experiences them as Filch—chasing people down, enforcing rules, and getting little recognition for it.The root cause of the image problem: when certification becomes the why of quality management, employees have no intrinsic motivation—usage spikes before audits and collapses after. Event-driven, not value-driven.Two formative lessons from Regina's career: a missing colleague's undocumented knowledge cratered a major production, and a well-meaning onboarding plan failed because it lacked a coherent big picture. Both point to the same conclusion—context and structure matter as much as content.The “Scribbler” trap: a LinkedIn poll found that 45% of respondents said only the quality or process management team designs processes—making QM the bottleneck and ensuring the business never emotionally owns what gets documented.The first lever for change is decentralized creation: replace “I write your processes” with “I coach you to write them.” Build a platform where content originates with the people doing the work.Intrinsic motivation requires three things—autonomy, self-efficacy, and social integration. Centralized modeling teams undermine all three and kill the very engagement QM is trying to build.The Marauder's Map metaphor: a management system should work like Fred and George Weasley's map—showing you where you are, where others are, and which hidden paths exist. Two clicks to the answer beats perfectly formatted documentation.Embedding process guidance into runtime systems—through a Chrome extension, a CRM integration, or a contextual sidebar—moves the mountain to the user instead of making users climb to the mountain.Combining knowledge management and process management is an underutilized power move: processes give structure, and knowledge gives detail. Together they raise relevance and adoption—but they typically live in separate tools and separate teams.Quality departments chronically underinvest in internal marketing. Projects die not because the work was bad, but because the wins were never communicated. The shift needed—from cost center to value creator—was told loudly, repeatedly, and in the language of business outcomes.You can find Regina on LinkedIn here: https://www.linkedin.com/in/regina-haar/.Please reach out to us by either sending an email to ⁠hello@whatsyourbaseline.com⁠ or signing up for our newsletter and reading articles about process and architecture on our Substack… Go and subscribe at ⁠whatsyourbaseline.substack.com⁠.And if you like to support “the little podcast that could,” become a Patron at ⁠https://www.patreon.com/c/whatsyourbaseline⁠. We appreciate you!

I'm Dr. Shelly Mahon, your host, and in this episode of the Parenting Well Podcast, I sit down with Stacey J. Acquavella, founder of Neurodivergent Uprising and speaker at our Stress & Anxiety Conference, to explore her powerful message: Regulation Is the Self-Care. Register Here Many parents, especially those raising neurodivergent children, are told to add more strategies, more routines, more coping tools. But when you're already functioning at a deficit, “doing more” only deepens the exhaustion. Stacey reframes overwhelm as a structural issue, not a personal one. You can't self-care your way out of structural overload. Instead, regulation must be embedded into how the day is designed. Things like how transitions happen, how expectations are set, how decisions are reduced, and how environments are shaped help immensely. We talk about survival mode and chronic bracing. The shame undiagnosed parents often carry. The stress of navigating school systems built for neurotypical learners. The difference between behavior management and regulation-based parenting. And why you don't need a diagnosis to begin reducing overload. If you've ever felt like you're constantly on edge or you're bracing for emails, appointments, or judgment, this conversation will help you understand why. And more importantly, it will show you where relief actually begins. In this podcast, we talk about: Self-regulation as the true mechanism of self-care Why adding habits doesn't work when you're already overloaded Removing demands and creating infrastructure instead of adding strategies Why burnout is often a structural problem, not a personal one “You can't self-care your way out of structural overload” Embedding regulation into how the day is designed Getting out of prolonged survival mode and chronic bracing How undiagnosed neurodivergent parents internalize shame Why overwhelm is a math problem; not a character flaw Mindset shifts versus accumulating more parenting strategies Neurodivergent people operating in misaligned systems Behavior management vs. regulation-based parenting Navigating schools and the stress of constant advocacy Standardized testing built for neurotypical brains Changing the environment when it feels locked in place Recognizing nervous system overwhelm without immediately labeling Understanding neurodivergence beyond stereotypes “We don't need a diagnosis to reduce overload.” Key Takeaways: Self-care isn't something you add — it's something you design. Regulation must be built into your daily structure, not layered on top of burnout. Overwhelm is often structural, not personal. When demand exceeds capacity, no amount of mindset work fixes the math. Behavior is often nervous system distress. Regulation-based parenting shifts the question from “How do I manage this?” to “What is overwhelming this nervous system?” You don't need a diagnosis to reduce overload. Support can begin with noticing when a child's (or parent's) nervous system is stretched beyond capacity. Slow signals safety. Fewer words. Lower body posture. Slower speech. These cues communicate “not under attack” to the brain. Systems matter. Instead of teaching children to cope with misaligned environments, we can redesign structures wherever possible. Advocacy without regulation increases stress. Parents navigating school systems need structural support too. Resources: Website: Neurodivergent Uprising Website: Mindfish - Neurodivergent Student Services LinkedIn

See omnystudio.com/listener for privacy information.

The host of episode 108 of Venture Everywhere is Harm-Julian Schumacher, co-founder and CEO of OneLot, a financing platform for used car dealers in the Philippines. He talks with Reto Bolliger, co-founder and CEO of Chaiz, an online marketplace for extended vehicle warranties. Reto shares how climbing Kilimanjaro led him to build a travel company, and how an investor in that business introduced him to the surprisingly profitable world of extended car warranties. He discusses how Chaiz challenges the industry consensus that warranties “must be sold” through aggressive tactics, instead building trust through transparency and offering consumers prices up to 40% cheaper than dealerships.In this episode, you will hear:Building the first online marketplace to compare and buy extended car warranties.Offering dealership products at 40% lower prices through digital channels.Replacing aggressive sales tactics with transparency and education.Leveraging AI for customer support and AI search optimization.Embedding warranty APIs for cross-selling through partner platforms.​​​​​​​​​​​​​​​​Learn more about Reto Bolliger | ChaizLinkedIn: https://www.linkedin.com/in/reto-bolligerWebsite: https://www.chaiz.comLearn more about Harm-Julian Schumacher | OneLotLinkedin: https://www.linkedin.com/in/harm-julian-schumacherWebsite: https://www.onelot.ph

In this Bright Spots in Healthcare episode, Medicare Advantage leaders confront a hard truth: high activity does not guarantee high impact. As Stars cut points rise and margins tighten, traditional segmentation and broad outreach strategies are no longer sufficient. This discussion explores how leading plans are shifting from static stratification to dynamic signal monitoring, identifying which members are realistically movable, and embedding behavioral intelligence directly into operational workflows. The focus is not on doing more. It is on doing what measurably drives lift. Our guests include: Amin Serehali, Chief Data and Analytics Officer, Independent Health Mike Leiper, Director of Government Quality Programs, Highmark Brendan Generelli, Director of Medicare Stars and Quality, Johns Hopkins Health Plans David Burianek, Chief Strategy Officer for Health Plans, MedOrion Together, they explore: How plans are distinguishing between theoretical risk and practical movability, concentrating outreach on members whose behavior can realistically change within a defined window. How leading organizations are integrating claims, pharmacy, grievance, complaint, and social drivers data with behavioral science modeling to move beyond rules based campaigns. Why simultaneous pressure across HEDIS, CAHPS, and Part D often reflects fragmentation in engagement strategy rather than isolated measure failures. How targeted pilots within defined populations create clarity before scaling enterprise wide changes. Why timing is emerging as a strategic lever, with continuous signal monitoring replacing annual segmentation refresh cycles. How embedding intelligence into frontline workflows improves alignment between engagement effort and measurable Stars influence. Panelist Bios: https://www.brightspotsinhealthcare.com/events/beyond-segmentation-how-medicare-advantage-engagement-is-being-rebuilt/ Download the Episode Guide: Get key takeaways and expert highlights to help you apply lessons from the episode. https://www.brightspotsinhealthcare.com/wp-content/uploads/2026/02/Updated-Episode-Guide-Beyond-Segmentation.docx.pdf  Key Insights Summary: Find the top six strategic insights from the discussion, including detailed speaker takeaways and moderator notes. https://www.brightspotsinhealthcare.com/wp-content/uploads/2026/02/Key-Takeaways-Beyond-Segmentation-2.12.26.docx.pdf    Resources: Companion Brief: From Segmentation to Signals This companion brief expands on the behavioral intelligence framework discussed in the episode, outlining how health plans can identify movable phenotypes, align engagement timing with readiness signals, and measure causal lift against specific Stars drivers. Inside you will find insights on: Shifting from annual risk stratification to continuous behavioral signal monitoring Identifying members whose behavior is realistically influenceable within a defined measurement window Reducing wasted outreach and improving ROI through precision targeting Embedding intelligence into operational workflows rather than post hoc reporting To request your copy, email nroberts@brightspotsventures.com. Thank You to Our Episode Partner, MedOrion: Medorion partners with Medicare Advantage plans to integrate behavioral science and advanced analytics into engagement strategy. By layering behavioral phenotyping onto clinical and utilization data, Medorion helps plans identify which members are movable, optimize outreach timing, and improve measurable Stars performance. Learn more at https://medorion.com/. Schedule a Conversation with MedOrion: To explore how behavioral intelligence can strengthen your engagement strategy and improve measurable lift across HEDIS, CAHPS, and Part D, reach out to nroberts@brightspotsventures.com  to schedule a discussion with David Burianek and the Medorion team. About Bright Spots Ventures: Bright Spots Ventures helps healthcare leaders separate signal from noise and accelerate the adoption of what works. We bring health plan, provider, and innovation leaders together through curated content and high-trust convenings to build meaningful relationships and turn insight into action. Explore our podcast at www.brightspotsinhealthcare.com.

Kiren Sekar (CPO @ Samsara) joins us to deconstruct the "Innovation Engine" behind Samsara, and how this system drives real-world impact and ROI across their products. We explore Samsara's decade-long compound product strategy and the mechanics of accelerating feedback loops in an era where the primary bottlenecks shift from code generation to customer feedback and absorption of change. Kiren details how their data flywheel expands the aperture of what is possible to build and we dive into the system of customer-driven innovation: advisory boards, “spark sessions” to test hypotheses and gain unfiltered feedback. Plus we talk about the power of embedding engineers in frontline environments (from truckyards to construction sites) to cultivate “taste,” customer empathy and trigger non-linear ideas. ABOUT KIREN SEKARKiren Sekar is the Chief Product Officer at Samsara (NYSE: IOT), where he has helped lead the company from a hardware-hacking startup in a basement to a global leader in Connected Operations with over $1.5B in ARR. An early leader at Meraki (acquired by Cisco for $1.2B) and an Apple veteran with multiple patents, Kiren specializes in the rare intersection of hardware, massive-scale data, and AI. He is the architect of a platform that now processes trillions of data points for the industries that keep the world running—trucking, construction, and logistics. This episode is brought to you by Retool!What happens when your team can't keep up with internal tool requests? Teams start building their own, Shadow IT spreads across the org, and six months later you're untangling the mess…Retool gives teams a better way: governed, secure, and no cleanup required.Retool is the leading enterprise AppGen platform, powering how the world's most innovative companies build the tools that run their business. Over 10,000 organizations including Amazon, Stripe, Adobe, Brex, and Orangetheory Fitness use the platform to safely harness AI and their enterprise data to create governed, production-ready apps.Learn more at Retool.com/elc SHOW NOTES:Real-world ROI The Intersection of Bits and Atoms: How Samsara supported customers through a once-in-a-century snowstorm using real-time AI insights (3:59)The Practicality Filter: Why low-margin, high-utility businesses are the best "BS detectors" for product builders (9:25)Deconstructing the compound product strategy: 10 years of feedback loops, scaling empathy, and technical capabilities (10:53)Accelerating your innovation flywheel, customer and product feedback loops (14:39)The New Bottleneck: Why writing code is no longer the constraint, and how to optimize for customer absorption of change (19:58)The Data Flywheel: Leveraging trillions of proprietary data points to solve new problems and expand your innovation engine into new capabilities (23:36)Embedding engineers in customer problems: Why there is no substitute for engineers seeing the frontline environment firsthand (29:56)How customer empathy and "taste" amplify the benefits of AI coding agents (33:26)Building a system of customer-driven innovation: Utilizing Advisory Boards and "Spark Sessions" to turn 10,000+ customers into co-creators (37:40)Rapid fire questions (47:50)This episode wouldn't have been possible without the help of our incredible production team:Patrick Gallagher - Producer & Co-HostJerry Li - Co-HostNoah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/ Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

What if the key to retaining women has nothing to do with women - and everything to do with how your organisation actually works? Joy shares insights from her landmark Why Women Leave study of 4,000 women, revealing that the top reasons - culture, career progression, line management and workload – aren't gender-specific at all. Her research with FTSE 350 organisations uncovered something fascinating: success wasn't about what organisations were doing, but who was doing it, how, when and why.  Joy explores how inclusion leaders navigate global turbulence through three shifts: changing language from diversity to belonging, embedding equity as a golden thread through business strategy, and maintaining compliance focus.  Looking ahead, Joy shares a powerful two-minute exercise: have someone talk whilst you visibly don't listen, then start again, and this time genuinely engage. The difference is transformative. Her wish is simple: practise the listening exercise and share it.   References:   Why Women Leave research report (2023) - Encompass Equality   FTSE 350 research report (conducted with FTSE Women Leaders Review and Chartered Management Institute) - Available at Encompass Equality   The Equality Conversation - Podcast   Don't Fix Women: The practical path to gender equality at work: By Joy Burnford   What actually drives progress for women in leadership? Encompass Equality's latest research   Thank you to Encompass Equality for sponsoring this episode.   Encompass is dedicated to creating better workplaces for women and building cultures where everyone benefits.   Powered by industry-leading research into women's lived experiences at work, Encompass turns real insight into targeted interventions that improve how people work together. Their latest research, conducted with the FTSE Women Leaders Review and Chartered Management Institute, reveals what actually works and how to make change happen in your organisation.   Download your free report from Encompass Equality  

Every leadership team craves alignment; no one wants the meetings. When executives hear "RevOps for Clients," they may picture more red tape and overhead. Courtney Baker, David DeWolf, and Mohan Rao argue that the right rigor doesn't slow business down—it slows bad decisions down. They unpack the "Minimum Viable Cadence," swapping hours of reactive fire drills for a single 30-minute triage, and discuss why exposing "dirty data" is the only path to shared accountability. Courtney also sits down with Alyssa Nolte of Ology to discuss AI in Customer Experience. Alyssa shares why the data you need is already there—just trapped in silos—and offers a "Kobe Bryant" approach to mastering the unsexy fundamentals of change management. All that, plus Pete Buer analyzes IBM's move to package its internal AI efficiency tool, IBM Consulting Advantage, as a client-facing product. Is it the ultimate example of productizing services? Get the resources to build your own RevOps for Clients discipline at our 2/25 webinar: www.knownwell.com/revops Watch the full episode on YouTube: https://www.youtube.com/watch?v=gwdcu54dfR4 

Episode web page: https://bit.ly/4k9H4fT Episode summary: In this episode of Insights Unlocked, design and research leaders from TruStage share how they transformed UX research from an inconsistent, ad-hoc effort into a scalable, trusted practice embedded directly within their design team. Through a creative “cookbook” framework, the team built shared standards, accelerated time to insights, and increased stakeholder confidence—without sacrificing flexibility or creativity. What you'll learn Why TruStage shifted from siloed research teams to an embedded UX research model How a visual “cookbook” system helped standardize research without making it rigid The power of shared language and artifacts to build stakeholder trust and buy-in How repeatable research “meal plans” enabled faster pivots and better decision-making What it takes to scale research volume while improving quality and consistency Key themes and ideas From potluck to practice. The TruStage team describes their early research approach as a “potluck”—rich in individual expertise but lacking consistency. By designing a shared system, they moved toward a polished, repeatable research practice that stakeholders could rely on. The research cookbook framework. Using food metaphors, the team created: Recipes for designers and researchers that explain how to run specific studies Menus for stakeholders that clearly outline value, effort, and outcomes Meal plans that bundle methods together across stages of the product lifecycle This framework helped align internal teams and external partners around expectations, scope, and impact. Embedding research into everyday workflows. By building the system directly in Figma and connecting it to their agile tooling, TruStage made research easy to plan, prioritize, and execute—removing friction that previously slowed teams down. Scaling impact through trust and clarity. Clear artifacts and shared standards made research easier to explain, faster to approve, and more likely to be requested. As a result, the team more than doubled the number of research stories completed year over year and shifted from “selling” research to responding to demand. Empowering teams through co-creation. Rather than dictating a process from the top down, the team involved designers across experience levels in shaping the system. This created stronger ownership, higher adoption, and a culture where research felt both accessible and fun. Advice for teams operationalizing research Lean into tools your team already loves and uses daily Invest time in shared philosophy and language—not just templates Co-create systems with the people who will use them Treat research operations as an evolving practice, not a one-time deliverable Resources & links TruStage's website (https://www.trustage.com/) Nick Higbee on LinkedIn (https://www.linkedin.com/in/nicholas-higbee-95540425/) Benny Brooks on LinkedIn (https://www.linkedin.com/in/thebenbrooks/) Betsy Drews on LinkedIn (https://www.linkedin.com/in/betsy-drews-4a30256b/) Natalie Padilla on LinkedIn (https://www.linkedin.com/in/natalie-weiner/) Nathan Isaacs on LinkedIn (https://www.linkedin.com/in/nathanisaacs/) Learn more about Insights Unlocked: https://www.usertesting.com/podcast

What exactly is strategic foresight? And how can it be effectively integrated into planning and management to help organizations think, act, and learn more strategically? Join host Michael J. Keegan as he explores these questions and more with Prof. Bert George, author of the IBM Center report Embedding Strategic Foresight into Strategic Planning and Management. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

BONUS: Why Embedding Sales with Engineering in Stealth Mode Changed Everything for Snowflake In this episode, we talk about what it really takes to scale go-to-market from zero to billions. We interview Chris Degnan, a builder of one of the most iconic revenue engines in enterprise software at Snowflake. This conversation is grounded in the transformation described in his book Make It Snow—the journey from early-stage chaos to durable, aligned growth. Embedding Sales with Engineering While Still in Stealth "I don't expect you to sell anything for 2 years. What I really want you to do is get a ton of feedback and get customers to use the product so that when we come out of stealth mode, we have this world-class product."   Chris joined Snowflake when there were zero customers and the company was still in stealth mode. The counterintuitive move of embedding sales next to engineering so early wasn't about driving immediate revenue, it was about understanding product-market fit. Chris's job was to get customers to try the product, use it for free, and break it. And break it they did. This early feedback led to material changes in the product before general availability. The approach helped shape their ideal customer profile (ICP) and gave the engineering team real-world validation that shaped Snowflake's technical direction. In a world where startups are pressured to show revenue immediately, Snowflake's investors took the opposite approach: focus on building a product people cannot live without first. Why Sales and Marketing Alignment Is Existential "If we're not driving revenue, if the revenue is not growing, then how are we going to be successful? Revenue was king."   When Denise Persson joined as CMO, she shifted the conversation from marketing qualified leads (MQLs) to qualified meetings for the sales team. This simple reframe eliminated the typical friction between sales and marketing. Both leaders shared challenges openly and held each other accountable. When someone in either organization wasn't being respectful to the other team, they addressed it directly. Chris warns founders against creating artificial friction between sales and marketing: "A lot of founders who are engineers think that they want to create this friction between sales and marketing. And that's the opposite instinct you should have." The key insight is treating sales and marketing as a symbiotic system where revenue is the shared north star. Coaching Leaders Through Hypergrowth "If there's a problem in one of our organizations, if someone comes with a mentality that is not great for us, we're gonna give direct feedback to those people."   Chris and Denise maintained tight alignment at the top level of their organizations through four CEO transitions. Their partnership created a culture of accountability that cascaded through both teams. When either hired senior people who didn't fit the culture, they investigated and addressed it. The coaching approach wasn't about winning by authority—it was about maintaining partnership and shared accountability for results. This required unlearning traditional management approaches that pit departments against each other and instead fostering genuine collaboration. Cultural Behaviors That Scale (And Those That Don't) "We got dumb and lazy. We forgot about it. And then we decided, hey, we're gonna go get a little bit more fit, and figure out how to go get the new logos again."   Chris describes himself as a "velocity salesperson" with a hyper-focus on new customer acquisition. This focus worked brilliantly during Snowflake's growth phase—land customers, and the high net retention rate would drive expansion. However, as Snowflake prepared to go public, they took their foot off the gas on new logo acquisition, believing not all new logos were equal. This turned out to be a mistake. In his final year at Snowflake, working with CEO Sridhar Ramaswamy, they redesigned the sales team to reinvigorate the new logo acquisition machine. The lesson: the cultural behaviors that fuel early success must be consciously maintained and sometimes redesigned as you scale. Keeping the Message Narrow Before Going Platform "Eventually, I know you want to be a platform. But having a targeted market when you're initially launching the company, that people are spending money on, makes it easier for your sales team."   Snowflake intentionally positioned itself in the enterprise data warehousing market—a $10-12 billion annual market with 5,000-7,000 enterprise customers—rather than trying to sound "bigger" as a platform play. The strategic advantage was accessing existing budgets. When selling to large enterprises that go through annual planning processes, fitting into an existing budget means sales cycles of 3-6 months instead of 9-18 months. Yes, competition eventually tried to corner Snowflake as "just a cute data warehouse," but by then they had captured significant market share and could stretch their wings into the broader data cloud opportunity. Selling Consumption-Based Products to Fixed-Budget Buyers "Don't believe anything I say, try it."   One of Snowflake's hardest challenges was explaining their elastic, consumption-based architecture to procurement and legal teams accustomed to fixed budgets. In 2013-2015, many CIOs still believed data would stay in their data centers. Snowflake's model—where customers could spin up a thousand servers for 4 hours, load data, while analysts ran queries without performance impact—seemed impossible. Chris's approach was simple: set up proof of concepts and pilots. Let the technology speak for itself. The shift from fixed resources to elastic architecture required changing not just technology but entire mindsets about how data infrastructure could work.   About Chris Degnan Chris Degnan is a builder of one of the most iconic revenue engines in enterprise software. As the first sales hire at Snowflake, he helped scale the company from zero customers to billions in revenue. Chris co-authored Make It Snow: From Zero to Billions with Denise Persson, documenting their journey of building Snowflake's go-to-market organization. Today, Chris advises early-stage startups on building their go-to-market strategies and works with Iconiq Capital, the venture firm that led Snowflake's Series D round.   You can link with Chris Degnan on LinkedIn and learn more about the book at MakeItSnowBook.com.

The idea of embedding various forms of non-emergency care in the emergency department makes a WORLD of sense.  If an older adult comes into the ED with a fall, the minimum the ED has to do is address the fall injury and send them out. But many emergency providers realize this is often a band aid.  They see that patient again the next time they fall.  And again.  And again.  The same could be said for the patient who is malnourished and dehydrated and admitted for "failure to thrive," again. And again. Our two guests today, Liz Goldberg and Lauren Southerland, both emergency medicine physician-researchers, have had enough.  On our podcast today they discuss how these sorts of experiences led them to argue that other services that can address the underlying causes that lead to ED visits.  Liz Goldberg developed the GAPcare model to address falls, which includes a physical therapist and pharmacist seeing patients on the spot in the ED.  Lauren Southerland got Columbus Ohio Office of Aging staff to re-locate from their desks to the emergency department, where they could sign patients up for home delivered meals, medical transportation, adult day services, home modification such as grab bars, and utility assistance for electricity, gas, and water bills. With GAPcare, Liz saw a 66% drop in ED visits for fall over 6 months from her pilot (subsequent fall outcomes of the GAPcare II study will be linked here when published).  Remarkable, particularly in the context of the primary care STRIDE intervention, which did not reduce injurious falls (e.g. the type that would result in an ED visit). Maybe the ED is just a better place to intervene? Patients are motivated to change. Get the physical therapist and pharmacist in there! In a study published in JAGS, Lauren found 50% of participants were linked to a new Office of Aging service initiated during the ED visit, with no increase in ED length of stay or hospital admission rate.  See also this terrific JAGS editorial on Lauren's paper by Liz.  Putting on my JAGS editor hat - both the study and editorial have terrific color figures. A great way to increase your odds of review and acceptance at JAGS is to include one or more high-impact color figures that convey the main findings or points of your manuscript. We talk about the potential downsides, real and perceived in embedding care in the ED.  Should everything be embedded? We talk about how these interventions relate to geriatric ED certification. Lauren talks about a remarkable model in Australia that includes a geriatric RN embedded in the ED. Most encouraging is that Liz and Lauren are finding other adopting these interventions. Word is spreading. Other emergency providers have had enough of the endless cycle. Enough. And I got to belt out Gravity, by John Mayer! -Alex  

In this episode, Kate Webber, Chief Solutions & Technology Officer at the PRI, is joined by Malea Figgins, Vice President at TCW, and David Klausner, ESG Specialist at PGIM Public & Private Fixed Income, to explore how responsible investment is being applied in securitised debt markets.Focusing on residential and commercial mortgage-backed securities (RMBS and CMBS), as well as emerging asset classes such as data centres, the discussion draws on insights from the PRI's Technical guide to Responsible Investment in securitised debt. Together, the guests unpack how environmental, social and governance risks and impacts are assessed in practice, where data gaps remain, and why securitised assets are central to financing the real economy.OverviewSecuritised debt is a core component of global fixed income markets, representing around US$14 trillion in outstanding issuance. By pooling underlying loans, such as home mortgages, commercial property loans or consumer credit, securitisation channels capital into housing, infrastructure and other real-economy assets.Despite its scale and relevance, securitised debt has historically been underrepresented in responsible investment discussions. This episode explains why environmental, social and governance considerations are not peripheral, but fundamental to credit analysis in this asset class, particularly given its exposure to consumers, real assets and climate risk.Detailed coverageWhy securitised debt matters for responsible investorsMalea and David explain how securitisation directly touches everyday assets, from homes and cars to student loans and commercial buildings. They argue that social risks such as predatory lending, affordability and loan servicing quality, alongside environmental risks like climate events and insurance availability, are core credit risks in these markets.Risk versus impactDavid outlines the importance of distinguishing between environmental, social & governance risk (financially material factors affecting credit quality) and impact (how investments affect society and the environment). The risks are integrated into bottom-up credit analysis across all portfolios, while impact overlays are applied where client mandates explicitly require them.Embedding sustainability in RMBS and CMBS analysisMalea discusses how sustainability considerations already align with credit fundamentals in many cases. In commercial real estate, green building certifications, energy efficiency and lower operating costs can support stronger net operating income and tenant stability. In residential markets, affordability metrics and borrower characteristics play a key role.Case study: data centres and climate riskThe episode explores the rapid growth of securitised data centre financing, driven by AI and digital infrastructure demand. David shares an example where climate-related insurance coverage and extreme weather risk directly influenced internal credit ratings, illustrating how environmental risks can be central, not secondary, to investment decisions.Private markets and improving data qualityBoth guests highlight how private asset-backed finance allows earlier engagement with issuers, creating opportunities to improve environmental and social data collection. Lessons from private markets may help drive better disclosure and transparency in public securitised markets over time.Labelled bonds and greenwashing risksMalea cautions that not all labelled securitised bonds are created equal. The discussion stresses the need for rigorous due diligence on use-of-proceeds and frameworks, with internal guardrails to avoid low-quality or misleading labelled issuance.Read more in the full technical guide on securitised debt: https://www.unpri.org/deep-dive?id=responsible-investment-in-securitised-debt-a-technical-guideChapters00:00 – Introduction to responsible investment in securitised debt02:40 – What securitised debt is and why it matters for investors06:10 – Why sustainability risks are core credit risks in securitised markets10:15 – Risk vs impact: a practical distinction for fixed income14:20 – Integrating sustainability into RMBS and CMBS analysis18:45 – Credit fundamentals and sustainability in commercial real estate23:30 – Case study: data centres, climate risk and insurance coverage30:10 – Private markets, early engagement and improving sustainability data36:05 – Labelled securitised bonds and avoiding greenwashing41:45 – Key takeaways for responsible investors in securitised debtDisclaimerThis podcast and material referenced herein is provided for information only. It is not intended to be investment, legal, tax or other advice, nor is it intended to be relied upon in making an investment or other decision. PRI Association is not responsible for any decision made or action taken based on information on this podcast. Listeners retain sole discretion over whether and how to use the information contained herein. PRI Association is not responsible for and does not endorse third parties featured on in this podcast or any third-party comments, content or other resources that may be included or referenced herein. Unless otherwise stated, podcast content does not necessarily represent the views of signatories to the Principles for Responsible Investment. All information is provided “as is” with no guarantee of completeness, accuracy or timeliness, or of the results obtained from the use of this information, and without warranty of any kind, expressed or implied. PRI Association is committed to compliance with all applicable laws. Copyright © PRI Association 2025. All rights reserved. This content may not be reproduced, or used for any other purpose, without the prior written consent of PRI Association.

Embedding workplace wellbeing takes more than good intentions and one-off initiatives. It requires people across the organisation who are willing to champion it every day. In this episode of the Wellness Works mini-series on The HR Room Podcast, Dave Corkery and Laura Barry, Head of People Development at Insight HR, are joined by special guest Brian Crooke, Founder of Workplace Wellbeing Ireland and The Work Well Institute, to explore how wellbeing champions can bring strategy to life on the ground. Together, they unpack what a wellbeing champion really is (and what they're not), why peer-led influence is so powerful, and how champion networks help bridge the gap between wellbeing policy and everyday employee experience. The conversation covers how to select, train and support champions, the importance of role clarity and leadership backing, and how to avoid common pitfalls such as overload, lack of structure or tokenism. Drawing on practical examples from organisations across Ireland, including Irish Life and ESB, this episode offers clear, actionable guidance for HR professionals and leaders who want to embed wellbeing in a sustainable, credible and inclusive way - not just as an initiative, but as part of organisational culture. Guests Brian Crooke – Founder, Workplace Wellbeing Ireland & the Work Well Institute Topics include: What wellbeing champions are, and how they differ from mental health first aiders Why peer influence is critical to embedding wellbeing Selecting champions through voluntary, inclusive processes The importance of role clarity, expectations and boundaries Training champions to take ownership and shape their role Supporting champions without overwhelming them Governance, structure and leadership sponsorship of champion networks Measuring impact without turning wellbeing into a tick-box exercise Common mistakes organisations make, and how to avoid them What “good” looks like when a champion network is working well Useful Links & Resources Workplace Wellbeing Ireland – Wellbeing Champion Programmes Workwell Institute – Postgraduate Certificate in Workplace Wellness Insight HR – Workplace Wellbeing Consulting & Support Wellness Works Live Webinar – Designing Your Wellbeing Strategy (February 17) Get in touch If you're not already following us on LinkedIn, please do. If you have suggestions for future episodes, or if you'd like to join us as a guest, reach out to Dave Corkery at dcorkery@insighthr.ie or connect with him on LinkedIn. If today's episode has you thinking about introducing or strengthening a wellbeing champion network in your organisation, you can arrange a confidential consultation with Laura Barry by emailing info@insighthr.ie. About The HR Room Podcast The HR Room Podcast is brought to you by Insight HR — where we speak with HR leaders, experts and practitioners across Ireland about the issues shaping the world of work today. If you're enjoying the podcast, please share it with colleagues or friends and leave us a review. We love your feedback and we're always here to support you with your HR challenges.

Gal Krubiner, CEO of Pagaya (PGY), discusses their lending work, AI implementation, and latest quarterly financials. Pagaya is a “first-mover AI technology” helping big U.S. lenders provide more loans to “the mainstream.” It reported a mixed quarter, beating on adjusted EPS but missing on revenue. Embedding their technology in the finance sector continues, and they expect to facilitate somewhere around $12 billion in loans in 2026.======== 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

Architect Lara Kaufman is a Design Principal based in Studio Gang's New York office. As the firm's Sustainability Lead, she directs teams on implementation of holistic design approaches for decarbonization, water conservation, site ecologies, and healthy materials. An advocate for urgent climate action within the building industry, Lara is currently co-lead for the Carbon Leadership Forum's NYC hub and engaged with other working groups promoting environmental policy, best practices, and education. Touching on reuse, Lara talked about “the alchemy of taking something that nobody cares about and turning it into something incredible that is transformed through adding on to it or collaging it with something else.”She shared about how she and Studio Gang teams get from big topics to benefits to people: “Often, we think about decarbonization, wellness, and biodiversity as these large priorities. But what's powerful about the design process is that it makes sustainability tangible. We're talking about real benefits that you can see and feel at the human and community level. If you integrate sustainability into the design concept, you'll have a better chance at implementing it and realizing it.”

Payments in emerging markets are often discussed as infrastructure.But the real differentiation happens in how deeply payments are embedded into business operations.In the final episode of this special Qatar Development Bank series of Couchonomics with Arjun, Arjun sits down in Doha with Saad Ishfaq, CEO of TESS Payments, to unpack how a payments company built for Qatar is scaling by solving real operational pain, not just processing transactions.TESS Payments is a QCB-licensed payment service provider designed specifically for the Qatari market. Rather than chasing regional expansion, Saad explains why the company chose to go deep instead of wide, focusing on enterprise-grade flexibility, managed services, and bespoke integrations for large organisations across real estate, government, and critical infrastructure.The conversation explores how payments sit at the centre of SME enablement, why micro and small businesses remain underserved across the GCC, and how fintechs and banks must collaborate rather than compete. Saad also shares how TESS evolved beyond payments into CFO tooling and digital lending, including a new sandboxed lending platform addressing Qatar's blue-collar workforce.From owning core infrastructure to navigating bank partnerships, regulatory sandboxes, and product adjacencies, this episode offers a grounded look at how fintech scale is built inside regulated markets.

Retail arbitrage on Amazon has allowed Kim and Perry Coghlan to sell over 8 figures in a single year selling shoes and clothing They manage a team of about 20 people across two cities while raising 13 kids. In this deep-dive interview, they reveal the exact systems, processes, and management philosophies that make it all work.CONNECT WITH KIM AND PERRY– Youtube: https://www.youtube.com/@EcomToolbox– Free Facebook group: https://www.facebook.com/groups/ecomtoolbox– Facebook page: https://www.facebook.com/ecomtoolbox1– Skool: https://www.skool.com/ecomtoolbox/about?ref=4adcf73740e949279874c4793504807c– Twitter: https://x.com/Pcoghlan, https://x.com/kimcoghlan4, https://x.com/ecom_toolboxRECOMMENDED TOOLS– SellerAmp SAS (14-day free trial): https://www.selleramp.com/oachallengeUse code OAC50 to save 50% off your first month.– Keepa Academy: https://www.oachallenge.com/keepa-academy– Boxem (14-day free trial): https://www.oachallenge.com/boxemTIMESTAMPS0:00 - Introduction and episode overview2:15 - Kim and Perry's business overview (10 years, 8 figures, 20 employees)4:30 - Shifting focus from top line revenue to bottom line profit6:00 - Why employees wanted data and metrics8:00 - Ecom Toolbox community and podcast launch11:00 - Helping intermediate sellers scale sustainably12:00 - The retail arbitrage renaissance14:30 - Know your numbers: why financial foundations matter first16:30 - Top metrics every Amazon seller should track17:30 - Velocity and cash flow management20:00 - Tracking stale inventory and learning from bad buys23:00 - The business scorecard explained (EOS framework)26:00 - Scorecard metrics: sales, spend, inventory value, margin28:00 - Returns tracking and seasonal variations31:00 - Finding the right tempo for tracking your numbers33:00 - Using AI in their Amazon business36:00 - Lean operations and spaghetti mapping explained39:00 - Real examples of process improvement41:00 - Bringing in a lean consultant for company-wide training43:00 - The eight wastes and eliminating extra processing44:00 - Mindset shift: accepting your process is wrong47:00 - Being the boss you never had49:00 - Elon Musk, staying in the weeds, and the Gemba51:00 - Book recommendations (Walter Isaacson, Ron Chernow)52:00 - Building systems through crisis response, not planning55:00 - Complete hiring process and personality testing59:00 - Phone screening, core values introduction, and filtering1:01:00 - Shopper training program overview1:04:00 - Warehouse training before field work1:07:00 - What makes a shopper field-ready1:09:00 - Compensation structure: item count vs percentage of spend1:11:00 - Bonus structure and incentivizing profitable behavior1:12:30 - Buying criteria for shoes and clothing (minimums, ROI)1:15:00 - Subcategories to avoid (dress shoes, small sizes)1:16:00 - Repricing strategy: buy box anchoring, not ROI-based1:18:00 - The rodeo jeans revelation: market doesn't care what you paid1:19:00 - Aging inventory repricing (30-day and 90-day rules)1:22:00 - Using ScanPower Mobile for pricing decisions1:23:30 - Holding inventory strategy and merchant fulfilled hack1:26:00 - Supplier profitability report as backbone of shopper metrics1:28:00 - Cross-collaboration and company averages1:30:00 - Honey holes and competitive bonuses1:31:00 - The four core values (TACO framework)1:34:00 - Quarterly conversations and the people analyzer1:36:00 - Embedding core values through repetition1:37:00 - Importance of outside perspectives and continuous learning1:39:00 - How lean and EOS clicked for them1:40:00 - EOS as the administrative equivalent of lean1:43:00 - Ecom Toolbox elevator pitch and who it's for1:44:00 - Where to find Kim and Perry1:45:30 - Time travel question: advice to their younger selves1:48:00 - Setting boundaries and not letting the business consume you1:48:30 - Recent impactful learning (Musk biography, learning to play)

“We need $2 from everyone so James can ship this dang mug.”That one line set the tone. A live stream, a packed chat, and a running joke about an $83.95 shipping fee to send a ceramic coffee mug from California to the UK. People laughed. People gave. And the room felt alive.That small, funny moment reminded everyone why live video works. It's real. It's messy. It's human. And when the community rallies, even a mug gets its moment.Melanie states, “…I'm easing my way back into streaming after a long break. Gear was in totes, cameras unplugged, and more cords than sense. But I missed the conversation — the unscripted moments, the people in the chat, the chance to be human-to-human. If you're thinking about getting back in or just trying to make your creator time count, here's the approach that's working for me: focus on the trifecta, protect the experience while you monetize, and design interactions that build culture, not noise.”The Trifecta: Short Form, Long Form, and LiveThe content trifecta is simple and non-negotiable if you want momentum: short form (discoverability), long form (depth and subscribers), and live (community and connection). Each serves a distinct purpose in the funnel.* Short form — Reels, Shorts, micro-clips. Top-of-funnel discovery. Pull the best two-minute nuggets from longer sessions and publish them where new people hang out.* Long form — Edited, produced episodes that show depth and keep people subscribing. This is where you explain ideas, build trust, and convert casual viewers into fans.* Live — The place to be raw, responsive, and relational. Live is where culture forms; viewers become participants and the audience helps make the show.I believe in doing all three, but you don't have to perfect every channel overnight. Experiment widely, then narrow in once you know where your people are and how they like to engage.Monetization: Respect the ExperienceAds and monetization are part of the creator economy. You should be paid for your work, but consider timing. Ads that interrupt a live conversation frustrate viewers and break the flow.One practical tactic: turn ads off while you're live and switch monetization back on immediately after the stream ends. That keeps the live experience clean and preserves the post-live revenue opportunity.Multi-Aspect Streaming: Vertical vs HorizontalPlatforms are trying to serve both quick-consumption vertical audiences and longer-form horizontal audiences simultaneously. That sounds great in theory, but it creates two different viewer experiences — and therefore two separate comment streams.If you're streaming to both vertical and horizontal feeds, you need a plan for each. Vertical is optimized for quick consumption — think TikTok or Instagram-style attention. Horizontal still wins for long-form conversation and comment engagement.* Vertical: bold visuals, tight framing, quick hooks. Comments can feel sparse and lonely compared to horizontal.* Horizontal: room for overlays, comments, richer production elements, and fuller audience interaction.As a producer, this multiplies configuration work. As a creator, think about where your core community lives and which format serves them best. If you're starting, cast a wider net. If you're established, pick one home base and make it great.Substack and the Newsletter-as-PlatformNewsletters have evolved. Substack in particular is no longer just email — it's becoming a social layer, podcast host, and even a live destination. You can push livestreams to Substack, embed videos in posts, and host premium tiers for people who want to comment and interact more deeply.Why this matters:* Control — You own your list and can create gated experiences without building complex tech.* Proof of authenticity — Embedding short, raw video clips inside a written post adds human proof that you are the person behind the content.* Monetization options — Substack takes a cut of paid subscriptions, but it handles payments, tiers, and distribution.Production: Keep It Scrappy, Not CrappyHigh production value helps, but content and energy win. Pat McAfee didn't become a phenomenon by upgrading every camera; he did it by staying authentic, consistent, and building a show people care about.Be scrappy. Just don't be crappy.Practical lighting and camera tips that won't break the bank:* Use a simple three-point setup: key light, soft fill, and a subtle hair or backlight to separate you from a dark background.* Control hot spots. If your forehead or scalp catches too much light, try lowering intensity, diffusing the light, or using a light grid to direct output.* A little mattifying powder or anti-shine product is a creator hack for reducing glare on camera.* Keep background practicals (lamps, RGB bulbs) subtle so the set feels moody without distracting the viewer.Community and Culture: The Real Competitive MoatCommunity isn't just about numbers. It's about culture. The way you moderate comments, which comments you surface, and how you respond shapes the environment people want to return to. Live video is the most powerful place to build culture because it creates back-and-forth connection in real time.Small audiences can be intimate and powerful. Learn names, call people out when appropriate, and reward contribution. If your community grows large, gated or paid rooms are a natural next step for bringing intimacy back.Examples of community strategies* Host a public 30-minute live and then a 20-minute members-only deep dive.* Clip the best live moments into short-form content for discovery, and link back to the longform episode or newsletter post.* Use merch or small gestures (signed items, shoutouts) to reinforce belonging.Simple Checklist to Return to Live (or Start One)* Decide your home base platform: where will the majority of your community experience you?* Map the trifecta: plan one longform episode, three short clips, and one live session per week or month.* Set monetization rules: ads off during live, ads on after; or enable memberships for exclusive interaction.* Optimize minimal production: key light, hair light, subtle background color, and a microphone that picks up voice cleanly.* Capture and clip: use an automatic clipping tool or your recording setup to pull shared short-form assets post-stream.* Schedule an outreach cadence: newsletter, social posts, and short clips to funnel viewers into the live room.Parting ThoughtGetting back into streaming doesn't require a full studio overhaul. Show up, be human, and keep the experience respectful for the people who choose to spend time with you. Start scrappy, iterate quickly, and protect the moments that matter. If you do that consistently, the rest — discovery, subscribers, and revenue — follow as feedback that you're on the right path.Thank you to everyone who tuned into my live video! Join me for my next live video in the app. Get full access to the Digital Collective at digitalcollective.media/subscribe

This is the first of a series of four podcasts (and associated blogs) about how we can integrate more physical activity across the NHS and what key actions health and care professionals can do to support the strategic shift from ‘Sickness to Prevention' and from ‘Hospital to Community'. The first podcast kicks off with an introductory episode, by Sarah Price, Director of Public Health for NHS England and Sasha Karikusevic, Director, NHS Horizons, who outline how we can harness the true potential of physical activity across the NHS to help to prevent ill-health and help people to live healthier, longer, and more independent lives, with best-practice examples across England to illustrate the benefits. A full transcript of this episode is available on our website - https://www.england.nhs.uk/long-read/four-ways-forward-podcast/ Please get in touch if you have any questions regarding this episode - england.medicalcomms@nhs.net

פרק מספר 511 של רברס עם פלטפורמה, שהוקלט ב-18 בינואר 2026. אורי ורן מקליטים בכרכור (הגשומה והקרה) ומארחים את נמרוד וקס - CPO ו-Co-Founder של BigID - שחצה את כביש 6 בגשם זלעפות כדי לדבר על אתגרים טכנולוגיים בעולם המופלא של Data Production ו-Security.

"Slow down. I think we move so fast and we're trying to go in straight to the solution and there could be multiple things that the customer needs and we miss opportunities when we move too fast." -Syvonia Brown  In this Spotlight episode, Syvonia Brown, Director of Sales at Sage 50 US, talks about emotional intelligence and why it matters more than most bookkeepers realize. She shares practical ways to handle tough client conversations, slow down reactive thinking, and build trust without taking on unnecessary stress. In this interview, you'll learn: How active listening changes difficult client conversations Why silence can be a powerful communication tool How to show empathy without absorbing client emotion To learn more about Syvonia, click here. Explore Sage at this link. Time Stamp 01:20 – What emotional intelligence really means in client work 02:10 – Checking in with yourself before client conversations 02:55 – Why jumping to solutions causes problems 04:25 – Using silence to help clients feel heard 05:17 – Simple techniques to avoid filling the silence 06:46 – Phone, video, or email how & tone changes everything 10:42 – Empathy without taking issues personally 12:21 – Why apologizing can make things worse 14:06 – De-escalating upset clients without matching their tone 16:14 – Taking accountability when mistakes happen 18:30 – Handling issues when you don't know the full story 20:01 – Embedding emotional intelligence into firm culture 21:22 – Training teams to lead with empathy 23:21 – How emotional intelligence drives loyalty & referrals 25:29 – Practical habits bookkeepers can apply immediately Your expertise has more value than you think, so Own Your Authority at The Successful Bookkeeper Summit 2026! It's a high-energy two-day virtual experience for bookkeepers ready to lead with confidence and elevate their impact. Join inspiring leaders on November 4th–5th to gain actionable strategies, powerful tools, and the clarity to shape the work you want, not just keep up with it. Don't miss this incredible opportunity! REGISTER TODAY!

In this episode of BrainFuel, Ruth is joined by Johanna Jefferies, Public Health Consultant and Associate Director at Hampshire County Council, and Jonathan Baker, Senior Insight Lead, to share how they've successfully embedded behavioural science into council and public health work in a way that's practical, memorable, and genuinely usable. Jo and Jonathan unpack what it really takes to roll behavioural science out across an organisation iincluding what didn't work at first, what they changed, and why training alone is never enough. You'll hear how Hampshire redesigned its approach to focus on real-world application, post-training support, and building confidence (not overwhelm). We also dive into their personal behaviour change stories, the biggest myth they'd throw into Room 101, and the three ingredients they believe every council needs if they want behavioural science to stick.

Episode 310 (January 2026) of China Manufacturing Decoded. Host Adrian is joined by Paul Adams, head of New Product Development at Agilian Technology, part of our group, for a practical walkthrough of how a strong NPD partner guides products from idea to mass production. The episode highlights key benefits of working with a strong NPD team and NPI process: faster time to market, built-in quality and reliability, better scope and cost control, and robust protection of intellectual property. Paul also discusses practical red flags to watch for when selecting a contract manufacturer and why the cheapest quote can become the most expensive option. To learn more or discuss a product, listeners are invited to contact Agilian and reach out to Paul and the NPD team for advice, prototyping support, and new product development services.   Episode Sections: 00:00 – Introduction & episode context Why NPD partnerships matter when going from idea to mass production 01:55 – Overview of the NPI / NPD journey Why new product development is a process, not a single milestone 02:36 – The six NPI phases explained Feasibility → Prototype → Tooling → Validation → Pre-production → Mass production 05:00 – Why pre-production runs are critical Real example: catching a potential 30% failure rate before mass production 07:30 – What an NPD team actually does Acting as both the customer's voice and the company's representative 11:10 – Managing scope, budget, and expectations Why scope creep quietly kills timelines, cost, and quality 14:10 – Transparency as a core NPD responsibility Why “telling customers what they want to hear” creates long-term risk 16:35 – Embedding risk mitigation into every phase Living risk registers, phase gates, and cross-functional reviews 21:00 – Risk goes beyond engineering Budget limits, internal constraints, and customer readiness 24:00 – Benefits of a strong NPD partner Faster time-to-market, built-in quality, and reliability by design 27:05 – Intellectual property protection and trust Why IP protection is foundational to long-term partnerships 30:10 – Order-takers vs true manufacturing partners What importers should look for when choosing a contract manufacturer 31:25 – Closing remarks & where to learn more   Related content… The New Product Introduction Process Guide Agilian - How we work (6 NPI Phases) Get assistance from Sofeast with your NPI 4 types of pre-production prototype to make before production 11 questions to ask before working with a contract manufacturer Get in touch with us Connect with us on LinkedIn Contact us via Sofeast's contact page Subscribe to our YouTube channel Prefer Facebook? Check us out on FB

Chris is a certified Shingo Institute Faculty Fellow, Academy member, master trainer, and Shingo examiner. He is a co-author of four Shingo Publication award winning books - "4+1 Embedding a Culture of Continuous, " The Essence of Excellence", ”Why Bother?”, and “Why Care?”. He is also editor of the Shingo Institute book “Enterprise Alignment and Results”. His sixth co-authored book “Leading Excellence-the 5 Hats of the Adaptive Leader” has been an Amazon best seller in Australia and is currently being translated into several languages.Link to claim CME credit: https://www.surveymonkey.com/r/3DXCFW3CME credit is available for up to 3 years after the stated release dateContact CEOD@bmhcc.org if you have any questions about claiming credit.

For more thoughts, clips, and updates, follow Avetis Antaplyan on Instagram: https://www.instagram.com/avetisantaplyanIn this episode of The Tech Leader's Playbook, Avetis Antaplyan sits down with Marcus East—Tech Executive and Author of Working with Dinosaurs—for a candid and thought-provoking conversation on the realities of digital transformation. With a career spanning leadership roles at Apple, Google, National Geographic, and more, Marcus brings a rare dual perspective from both Big Tech and legacy enterprises.They unpack why most digital transformation efforts fail despite heavy investment, what separates successful tech leaders from those who merely talk innovation, and how culture—not just code—can make or break your future. Marcus shares powerful real-world stories: from National Geographic's transformation into a digital juggernaut, to the organizational inertia that derails billion-dollar initiatives. He outlines the “three dinosaurs” that stall progress—legacy systems, outdated operating models, and people unwilling to change—and offers sharp insights into why customer obsession beats tech obsession every time.Whether you lead a startup or a Fortune 500, this episode will challenge your assumptions, sharpen your thinking, and equip you with frameworks to lead meaningful change in an AI-driven world.TakeawaysLegacy companies don't fail because of age—they fail when they refuse to update thinking while technology advances.Successful transformations require both visionary leadership and operational discipline across the org.Billions in digital investment are wasted when the right people aren't empowered to drive change.Embedding innovation into the core business beats isolating it in innovation labs.Flexible technology is a must—but without true cross-functional collaboration, it's not enough.Only about 5% of AI investments currently show ROI, largely due to legacy systems and poor org alignment.Top-performing organizations operate with tight accountability and a focus on measurable outcomes.Customer experience—not tech stack—should guide transformation priorities.Large “grand projects” that last years often fail to deliver value or ROI.Elite talent gravitates toward environments with high standards, fast iteration, and meaningful impact.Companies that can't attract top talent must either lead with a compelling mission or lean into strategic partnerships.People are the hardest "dinosaur" to evolve—fixing culture and mindset is harder than replacing tech.Chapters00:00 Intro & Guest Introduction01:30 Why Some Legacy Companies Transform & Others Fail03:45 The Real Problem: People & Culture06:20 The Innovation Lab Trap08:15 The First Domino: Flexible Tech & Cross-Team Collaboration10:25 Build vs. Buy in the Age of Cloud12:30 AI Hype vs. ROI Reality14:20 Leadership's Role in Driving Transformation17:55 Customer-First Thinking Over Tech Fetishism21:30 The Dangers of Tech-First Transformation23:45 Why Accountability is the Missing Link29:45 Why Elite Tech Talent Clusters (and Leaves)34:00 Rest & Vest vs. Impact-Driven Professionals41:45 What If You Can't Attract Top Talent?47:00 The Three Dinosaurs: People, Tech, Models53:30 Why Outdated Processes Are More Dangerous Than Tech57:00 Extreme Accountability as a Performance Driver59:15 Books, Billboards & Final ThoughtsMarcus East's Social Media Link:https://www.linkedin.com/in/marcuseast/Resources and Links:https://www.hireclout.comhttps://www.podcast.hireclout.comhttps://www.linkedin.com/in/hirefasthireright

Send us a textIs this the lost episode? No, but there is some "old news".We dig into how O&P is changing fast: major acquisitions, new L codes, and a fresh vision for education that blends clinical reality with digital tools. Adrienne Hill shares a grounded path for students and clinicians to build skills without burning out.• Hanger's acquisition of Point Designs and upper limb strategy• Medicare L codes momentum for partial hand coverage• Three education models and how to choose• Why residencies still define clinical growth• Embedding scanning, CAD, and 3D printing in coursework• Practical literacy vs making the "sausage" in-house• Shifts from plaster to digital and what's realistic• Workflows that prevent burnout and improve retention• Ownership dreams, debt realities, and timing• The modified seven-year rule for career moves• How to pick residencies that fit your EQ and IQ• Going rural or high volume to accelerate learning• Broadening applicant pipelines and faculty needsIf you need any help with additive manufacturing reach out to our sponsor, Advanced 3D.Support the show

About Christopher Sullivan:Christopher Sullivan is a senior executive with deep leadership experience across health, legal, and regulatory technology, currently serving as Vice President & General Manager of Pharmacy & Health Technology Solutions at Wolters Kluwer Health in New York. He brings over a decade of progressive responsibility within Wolters Kluwer, where he has led large commercial and product portfolios spanning pharmacy, healthcare, legal, transactional, and retirement solutions. His background is heavily strategy-driven, with prior roles overseeing partnerships, pricing, business intelligence, and corporate development, translating data and market insight into scalable growth. Before transitioning fully into executive leadership, he built a strong foundation in operations and logistics at DHL and gained strategic consulting experience at GE Capital. Christopher is a graduate of the United States Military Academy at West Point, where he studied international relations and systems engineering, and holds an MBA in finance and management from Fordham Gabelli, with additional studies at ESADE Business School.Things You'll Learn:Clinicians face up to 20 complex clinical questions daily, making fast access to trusted evidence essential. Embedding insight directly into workflow reduces delays and decision fatigue.Context switching across platforms significantly contributes to clinician burnout. Keeping evidence inside the tools clinicians already use improves efficiency and satisfaction.Trusted, expert-reviewed content is becoming more valuable as AI-generated information increases. Confidence in the source has a direct impact on clinical adoption.API-based delivery allows evidence to reach clinicians beyond traditional EMR systems. This supports modern, flexible workflows across digital health platforms.Partnerships between content experts and technology vendors accelerate innovation. Collaboration keeps solutions aligned with real clinical needs.Resources:Connect with and follow Christopher Sullivan on LinkedIn.Follow Wolters Kluwer Health on LinkedIn  and visit their website.

For episode 232, I'm excited to welcome Joshua Dávila, a longtime organizer, writer, and builder at the intersection of progressive politics and crypto. Josh is the host of The Blockchain Socialist podcast, the author of Blockchain Radicals, and a core contributor to Bread Cooperative, a worker-owned collective building real financial tools rooted in solidarity, not hype.In today's episode you'll learn:

In this episode, Nathan Fabian, Chief Sustainable Systems Officer at the PRI, examines rising economic inequality and why it poses a material, systemic risk for long-term investors. He is joined by Delaney Greig (Director of Investor Stewardship, University Pension Plan Ontario), Emma Douglas (Sustainable Investment & Stewardship Lead, Brightwell; BT Pension Scheme), and David Wood (Adjunct Lecturer in Public Policy, Harvard Kennedy School).Together, they explore how inequality affects economic stability, corporate performance, long-horizon portfolio returns, and what asset owners can do to respond.OverviewTen years after the adoption of the SDGs, inequality is increasing across major economies. The top 1% now holds over 40% of global wealth, and widening gaps in income, labour rights and access to opportunity are shaping economic and political outcomes.The guests discuss:Why inequality is a non-diversifiable, systemic riskHow it undermines growth, resilience and productivityThe implications for diversified investorsThe interplay between inequality, climate, nature and social outcomesHow asset owners can use stewardship, integration and policy engagement to address key driversDetailed Coverage1. Why inequality matters for investorsDelaney and Emma outline why rising inequality threatens long-term returns: weakening demand, increasing volatility, reducing workforce resilience, and fuelling political instability. Both highlight evidence linking excessive pay gaps and poor labour practices to weaker corporate performance.2. What the research showsDavid summarises major findings from the IMF, OECD and others showing that inequality constrains growth rather than accelerates it. He notes that investors have clearer data and frameworks today than ever before, and that social issues have become central to responsible investment.3. Making inequality actionableEmma discusses a new analysis tool developed with Cambri to map social risks across sectors, revealing under-examined areas such as technology, media and natural-resource-intensive industries.Delaney explains UPP's “top-and-bottom guardrails” approach, engaging on excessive executive pay at the top and fundamental labour rights at the bottom.4. Stewardship, integration and policyThe panel discusses:Embedding social risks into investment processesSector-level prioritisationCollective action on labour rightsThe emerging TISFD standardHow investors should (and should not) engage in political debates around taxation, labour markets and redistribution5. Looking aheadGuests reflect on:Strengthening investor–manager dialogueIntegrating inequality into capital allocation decisionsOpportunities in areas such as affordable housingAddressing market concentration and competition issuesThe need for aligned, collective advocacy from asset ownersChapters(0:00) - Introduction: Economic Inequality and Investment Risk (2:29) - Delaney Greg: Why Inequality Matters for Pension Plans (4:50) - Emma Douglas: Systemic Risk and Investment Opportunities (7:16) - David Wood: Research on Inequality and Growth (9:21) - Understanding the Drivers of Economic Inequality (11:51) - Emma's Approach: Using Data and AI for Social Risk Analysis (15:01) - Delaney's Strategy: Top-End and Bottom-End Guardrails (17:55) - Measuring Impact and Defining Success in Inequality Work (20:16) -...

Simba Khadder is the founder and CEO of Featureform, now at Redis, working on real-time feature orchestration and building a context engine for AI and agents.Context Engineering 2.0, Simba Khadder // MLOps Podcast #352Join the Community: https://go.mlops.community/YTJoinInGet the newsletter: https://go.mlops.community/YTNewsletter// AbstractFeature stores aren't dead — they were just misunderstood. Simba Khadder argues the real bottleneck in agents isn't models, it's context, and why Redis is quietly turning into an AI data platform. Context engineering matters more than clever prompt hacks.// BioSimba Khadder leads Redis Context Engine and Redis Featureform, building both the feature and context layer for production AI agents and ML models. He joined Redis via the acquisition of Featureform, where he was Founder & CEO. At Redis, he continues to lead the feature store product as well as spearhead Context Engine to deliver a unified, navigable interface connecting documents, databases, events, and live APIs for real-time, reliable agent workflows. He also loves to surf, go sailing with his wife, and hang out with his dog Chupacabra.// Related LinksWebsite: featureform.comhttps://marketing.redis.io/blog/real-time-structured-data-for-ai-agents-featureform-is-joining-redis/~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our Slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Simba on LinkedIn: /simba-k/Timestamps:[00:00] Context engineering explanation[00:25] MLOps and feature stores[03:36] Selling a company experience[06:34] Redis feature store evolution[12:42] Embedding hub[20:42] Human vs agent semantics[26:41] Enrich MCP data flow[29:55] Data understanding and embeddings[35:18] Search and context tools[39:45] MCP explained without hype[45:15] Wrap up

In this episode of Plugged In, host Chuck Hanna sits down with Kevin Rabinovitch, Global VP of Sustainability at Mars, to discuss the company's journey toward maintaining their environmental goals, with a special focus on Scope 3 emissions. The conversation covers insights from Rabinovitch's 31-year career at Mars, the evolution of their strategy, how it's integrated into business operations, and the challenges and opportunities of driving change across a global supply chain. Whether it's data systems, supplier engagement, renewable energy, or emerging technologies, this episode includes many insights for those looking to improve their Scope 3 strategy. Embedding sustainability into your business strategy (02:30) Discovering where sustainability objectives meet daily decisions (4:04) Why Mars prioritized Scope 3 emissions (09:36) Meeting challenges in aggregating data across the business and supply chain (12:26) Supplier engagement, estimation philosophy, and more (16:59) Driving efficiency, motivation, and business value (17:39) Tactics for adapting to different markets and risk appetites in renewable energy (23:42) Advice for those starting their own journey in the industry (44:12) For full episode show notes, click here. Connect with Kevin Rabinovitch On LinkedIn Kevin Rabinovitch is the Global VP Sustainability for Mars, Incorporated. In his role, he leads the Performance Acceleration and Shared Services team supporting the Mars Sustainable in A Generation Plan. Spanning the entirety of Mars' global sustainability impacts, Performance Acceleration focuses on creating new business capabilities and reengineering to accelerate and more efficiently deliver the SiG Plan. Shared Services leverages the global scale and power of Mars to support the segments of Petcare, Snacking and Food & Nutrition on subjects such as a global portfolio of renewable energy, sustainability data systems & tools, carbon removal projects and the Mars Sustainable Investment Fund.  Externally, among other roles, Kevin sits on the Board of the Livelihoods Carbon Fund 3, teaches Business & Sustainability at Virginia Tech and Georgetown University and frequently speaks externally on behalf of Mars' sustainability program. He has been with Mars for 31 years, 18 years in sustainability, having helped start Mars' program and the first 13 years in R&D functions of multiple Mars business segments in the U.S. and Europe, specializing in technology development, scale-up, and intellectual property. Connect with Mars, Inc. Follow Mars on LinkedIn Follow Kevin Rabinovitch on LinkedIn Connect with Constellation Follow Constellation on LinkedIn Follow Chuck Hanna on LinkedIn Follow Abhinav Krishna on LinkedIn Learn more about Constellation sustainability solutions. Connect with Smart Energy Decisions Smart Energy Decisions Follow us on LinkedIn Subscribe to Smart Energy Voices on Apple Podcasts, Google Podcasts, Android, Spotify, Stitcher, TuneIn Radio, aCast, PlayerFM, iHeart Radio. If you're interested in participating in the next Smart Energy Decisions Event, visit smartenergydecisions.com or email our Community Development team at attend@smartenergydecisions.com.

In this episode of The Steward Chair, Masami Sato, Founder & CEO of B1G1, shares her journey from an introverted backpacker to leading a global giving movement, exploring how the power of small, daily acts of kindness drives meaningful, long-term success. We discuss the philosophy of "business as usual" becoming a force for good, the importance of expanding our "family circle," and how integrating micro-impacts can transform company culture. This episode is full of actionable takeaways for leaders committed to stewardship, integrity, and impact. Key Takeaways The Power of Small: Masami explains how small, consistent contributions—like giving access to water for every cup of coffee sold—can collectively solve massive global challenges. The "Bee" Philosophy of Business: Just as bees pollinate flowers while collecting nectar, businesses can benefit their own growth while naturally enriching the global ecosystem through their daily operations. Expanding the Family Circle: Masami challenges leaders to widen their definition of "family" to include the global community, moving from a mindset of separation to one of connection and collaboration. Resources Mentioned Visit https://b1g1.com/ Follow Masami Sato on social media at LinkedIn https://www.linkedin.com/in/masamisato/ Facebook https://www.facebook.com/sato.masami Join the ConversationThe Steward Chair is about equipping and inspiring business leaders to build organizations that stand the test of time. If this episode resonated with you, share your biggest takeaway and tag us on LinkedIn: Chat With Leaders Media https://www.linkedin.com/company/chatwithleaders/ and End of the Line Productions https://www.linkedin.com/company/end-of-the-line-productions/. Elevate your podcast, company meeting, or industry event strategies to better engage stakeholders and drive meaningful growth! Visit ChatWithLeaders.com to learn more about how we can help.See omnystudio.com/listener for privacy information.

Title: Evaluating the Reverse Slide Embedding Method vs. Heat Extractor Embedding in the Mohs Laboratory: A Comparative Quality Review of 100 Cases Authors: Tashsa Cromedy, Heather Frye, Ochsner MD Anderson Cancer Center, St. Tammany Cancer Center A Campus of Ochsner Medical Center Abstract:  Overview Accurate tissue embedding is critical in Mohs micrographic surgery for complete margin assessment. This study evaluates the efficacy of a reverse slide embedding method compared to the conventional heat extractor technique. The goal was to determine which method yields fewer artifacts or discrepancies that may compromise histologic interpretation and margin assessment. Methods A total of 100 Mohs cases were retrospectively reviewed in a controlled laboratory setting. Two embedding techniques were compared: Reverse Slide Method: 50 cases were embedded by placing the tissue on a chilled slide before embedding, ensuring orientation preservation and minimizing heat exposure. Heat Extractor Method: 50 cases were embedded using the traditional heat extractor to flatten and orient tissue in the embedding medium. All slides were reviewed by a Mohs surgeon for processing artifacts, orientation challenges, and histologic discrepancies. Validation The Mohs surgeon identified a total of 17 artifact inconsistencies or discrepancies across all cases: 13 instances were associated with the heat extractor method. 4 instances occurred with the reverse slide method. These findings suggest that the reverse slide method may reduce artifacts and improve embedding accuracy compared to the heat extractor, offering potential benefits for tissue integrity and diagnostic confidence in the Mohs laboratory. Conclusion The reverse slide embedding method demonstrated a significant reduction in embedding-related artifacts compared to the heat extractor technique. These findings support its use in the Mohs laboratory to enhance tissue quality, reduce the risk of diagnostic errors, and improve patient outcomes. Further studies with larger sample sizes and multi-lab validations are recommended to confirm these results.  

This podcast is brought to you by Outcomes Rocket, your exclusive healthcare marketing agency. Learn how to accelerate your growth by going to⁠ outcomesrocket.com How do you build AI that actually feels loving to the people it serves? In this episode, Dr. Apurv Gupta, Founder and Board Member of A Loving Organization, explains that the Loving Organization Consortium aims to bring more love and compassion into healthcare by improving nine interconnected systems, people, processes, culture, workflows, and especially technology, through a framework called INTEGRATE. He and Ed Gaudet discuss how “loving AI” can ease clinician burden through tools like ambient listening, workflow automation, and emerging burnout-prediction technology, while emphasizing that tech alone is only 10–20% of the solution. Dr. Gupta stresses that effective technology requires human oversight, governance, feedback loops, and involvement from clinicians and patients in the design process. He highlights that organizations often miss these elements due to lack of awareness and capabilities, which the INTEGRATE framework seeks to build. Ultimately, he argues that love must be the foundational intention shaping systems, leadership, and AI, because technology is neutral but becomes “loving” only when embedded in a loving human environment. Tune in to explore how compassion-driven systems and “loving AI” can transform clinician well-being, patient care, and the future of healthcare! Resources Connect with and follow Dr. Apurv Gupta on LinkedIn. Follow A Loving Organization on LinkedIn and visit their website! Last Apurv Gupta RNS episode here!

New @greenpillnet pod out today!

On Episode 612 of Impact Boom, Jenae Tien of Expand Today discusses catalysing authentic, inclusive communities across education, media, health and corporate sectors, and how effective allyship, diverse storytelling, and early childhood education can drive long-term cultural and systemic change. If you are a changemaker wanting to learn actionable steps to grow your organisations or level up your impact, don't miss out on this episode! If you enjoyed this episode, then check out Jenae's first appearance on Impact Boom, Episode 450, on helping educators and parents spark conversations around diversity -> https://bit.ly/3KeaLPB The team who made this episode happen were: Host: Indio Myles Guest(s): Jenae Tien Producer: Indio Myles We invite you to join our community on Facebook, LinkedIn or Instagram to stay up to date on the latest social innovation news and resources to help you turn ideas into impact. You'll also find us on all the major podcast streaming platforms, where you can also leave a review and provide feedback.

Visual search optimization remains underutilized by 73% of small businesses despite growing consumer adoption. Helen Pollitt from iStock, who leads visual content strategy for Getty Images' stock platform serving over 1.5 million creative professionals, shares proven frameworks for integrating visual elements into comprehensive content strategies. The discussion covers location-based schema implementation for AI-generated imagery, unified content approach methodologies that eliminate silos between written and visual assets, and tactical opportunities for SMBs to gain competitive advantage in visual search before larger enterprises mobilize their resources.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode we're playing the 'connection' game again - using my favorite crayon, The Helpful Content System Analysis and how vector embedding explains in more engineering jargon the same thing I've been saying.Don't worry I explain what I mean so it makes sense to an non-SEO person.Beta Sign up - Google FormLast week's episodehttps://carolynholzman.com/breathing-through-the-noise-season-5-episode-46/Mentioned in the show:How HC and Gemini are alignedhttps://www.americanwaymedia.com/gemini-and-helpful-content-timelines/contains a playback of the episode as well as a graphic timeline of various events related to each one.Indexation Research - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Crawl Or No Crawl ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Tools that I use and recommend:Indexzilla -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.indexzilla.io⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ (indexing technology)GSC Tool -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://bit.ly/gsctool⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠SEO in ATX ⁠⁠⁠⁠- SEO as a serviceYoutube Channel -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Confessions of An SEO®⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://g.co/kgs/xXDzBNf⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠-------- Crawl or No Crawl Knowledge panelInterested in supporting this work and any seo testing?Subscribe to Confessions of an SEO™ wherever you get your podcasts. Your subscribing and download sends the message that you appreciate what is being shared and helping others find Confessions of an SEO™An easy place to leave a review ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.podchaser.com/podcasts/confessions-of-an-seo-1973881⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠You can find me on⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Carolyn Holzman⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ - Linkedin⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠American Way Media⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Google Directly⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠AmericanWayMedia.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Consulting AgencyNeed Help With an Indexation Issue? - reach out Text me here - 512-222-3132Music from Uppbeathttps://uppbeat.io/t/doug-organ/fugue-stateLicense code: HESHAZ4ZOAUMWTUA

Operators with 30 years of pattern recognition leave for competitors. Engineers carrying legacy system intelligence depart. Everyone understands the risk. Few solve the execution: Systematically extracting tacit intelligence that experts can't articulate because it operates below the conscious threshold.Dr. Refiloe Mabaso and Wisdom Ndashe architected what many struggle to build - knowledge-capture systems that function independently of voluntary participation. At ATNS, harvesting is mandated by policy and embedded in workflows. Their "Legends and Beneficiaries" program identifies critical expertise five years before departure, mapping tacit intelligence to next-generation operators through structured protocols. The execution breakthrough: embedding capture into SOPs makes retention automatic. Travel with Purpose demonstrates strategic reach - converting unaccounted expenditures into documented intelligence acquisition with measurable ROI. Cost centers become intelligence operations.Paradigm Shifts:

In this episode of MakingChips, we sit down with Charlie Hushek, President of Phoenix Heat Treating, whose family has been in the heat-Treating world for over a century. Charlie is a fifth-generation heat Treatinger—but his leadership story is anything but inherited. When he stepped into the business in 2020, he wasn't handed stability. He was handed a crisis. Within a matter of months, Phoenix Heat Treating lost its NADCAP certification—twice—suffered major operational setbacks, faced COVID turmoil, and endured the tragic loss of their general manager. For a company where more than 70% of revenue is tied to regulated aerospace work, this wasn't a stumble. It was a free fall. And it forced Charlie into leadership far earlier—and far harder—than he expected. But instead of shrinking from the challenge, Charlie transformed it into a total rebuild. He redesigned their QMS from the ground up, implemented true systems thinking, rewrote cultural standards, and introduced transparent, performance-driven practices that aligned every employee around shared values. The result? A thriving business, a revitalized culture, and a blueprint for how to rebuild a manufacturing company under extreme pressure. In this raw and energizing conversation, Charlie shares how Phoenix Heat Treatinging went from chaos to clarity, how culture becomes a competitive advantage, and what it takes to lead a team through uncertainty, fear, and burnout—and come out stronger on the other side. If you're leading a shop through change, growth, or crisis, this episode is a masterclass. Segments (1:29) Charlie's fifth-generation family history and the Phoenix Heat Treating story (2:19) The beginnings of Wesley Steel Treating and early industrial growth (3:43) Check out SMW Autoblok's massive catalog of products (5:15) Heat Treating as a long-standing, often overlooked "shadow industry" (5:45) Phoenix Heat Treating's early years, the move to Arizona, and generational transitions (7:34) Charlie's introduction to the business, working second shift, and learning operations (8:53) Phoenix Heat Treating's modern operations: five shifts, fast turn times, and business units (10:40) The importance of NADCAP certification and the challenges that come with losing it (12:45) Climbing out of crisis, stabilizing the business, and confronting hard truths (18:55) Internal emotions, team reactions, turnover, and the "burn the boats" mentality (22:06) Rebuilding from 50 employees to 80 through culture, transparency, and momentum (23:30) How primes issued waivers and partnered with Phoenix during the crisis (25:17) Working with customers to maintain flow on critical aerospace and defense parts (27:42) What's Your Method? 30-taper machines (34:43) The honesty and transparency you'll experience working with Phoenix Heat Treating (35:55) Building culture from the ground up and defining core values (39:01) Using employee surveys to define core values: teamwork, positivity, detail, work ethic (41:38) Embedding culture in hiring, onboarding, and daily expectations (45:30) Profit sharing, pay transparency, and rewarding performance (49:20) Applying the playbook to the newly purchased machine shop (52:53) Incentivizing change and gaining buy-in through aligned rewards (54:45) The importance of defining winning, alignment, and standards (58:23) Why we created Hire MFG Leaders (and why you should use it) (58:50) Charlie's "playbook," open-book management, and The Great Game of Business Resources mentioned on this episode The honesty and transparency you'll experience working with Phoenix Heat Treating Connect with Charlie Hushek on LinkedIn Where to check out SMW Autoblok's massive catalog of products Why we created Hire MFG Leaders (and why you should use it) The Great Game of Business Connect With MakingChips www.MakingChips.com On Facebook On LinkedIn On Instagram On Twitter On YouTube

Chad Dime, Co-Founder of DIFF Charitable Eyewear was raised in Los Angeles California. He was born into the eyewear industry thanks to his father who owned and operated an eyewear business for over 40 years. His dad passed down the knowledge of product design, import, manufacturing and wholesale to him throughout his entire life. On the manufacturing side, he was traveling to China by the time he was 15 years old to learn the ins and outs of what it takes to work with partners overseas. In wholesale he was attending major markets as a teenager to learn the ins and outs of what it takes to sell to major retailers both nationally and internationally. He was fortunate enough to know at that very young that he would be following in his family's footsteps. While attending college at San Diego State University he was the President of the nationally ranked SDSU Surf Team. His role there allowed him to work with many notable brands like Red Bull, Rip Curl and TOMS as he obtained sponsorship from each of these businesses. After years of building campus rep programs with these brands he learned the importance of both social media marketing along with social enterprise. The partnership with TOMS shoes was his motivation to build a business that gave back, and it became his dream to start a sunglasses brand that could help change the world. After graduating from SDSU he met his business partners. Together they began selling sunglasses at electronic music festivals across the country. It was here that they realized there was a massive void in the eyewear industry that they knew they could fill. Eager to disrupt the monopolized eyewear industry they founded DIFF with a mission to create affordable designer eyewear that gives back. In This Conversation We Discuss:[00:00] Intro[00:50] Blending value and mission to drive impact[04:00] Partnering purpose with product[06:09] Leveraging past experiences for team balance[08:56] Nurturing partnerships for smarter growth[11:44] Stay updated with new episodes[11:55] Embedding responsibility into brand DNA[14:11] Sponsors[19:43] Influencer partnerships for early marketing strategy[22:54] Prioritizing finance to avoid early pitfalls[24:57] Understanding finances for loss prevention[26:06] Highlighting first products for brick and mortar[28:42] Following your why to create impactResources:Subscribe to Honest Ecommerce on Youtube www.youtube.com/c/HonestEcommerce?sub_confirmation=1Charitable designer sunglasses that give back www.diffeyewear.com/Follow Chad Dime www.linkedin.com/in/chad-dime-59550258Schedule an intro call with one of our experts electriceye.io/connectReach your best audience at the lowest cost! discover.taboola.com/honest/Easy, affordable coverage that grows with your business www.nextinsurance.com/honest/  Turn your domestic business into an international business www.freightright.com/honestIf you're enjoying the show, we'd love it if you left Honest Ecommerce a review on Apple Podcasts. It makes a huge impact on the success of the podcast, and we love reading every one of your reviews!

In this episode of the HR Leaders Podcast, we sit down with Raj Verma, Chief Culture, Inclusion and Employee Experience Officer at Sanofi, to explore how culture, trust and co-creation became the foundation of one of the most ambitious AI transformations in the industry. Raj breaks down why culture is a verb, not a vibe, and how Sanofi intentionally shaped behaviors and values to support AI at scale. He explains how Sanofi began its AI journey before the ChatGPT wave, driven by a visionary CEO and a bold ambition to become the first pharma company to use AI at scale. Raj details how recognition, inclusion, and data-driven insights became critical levers for building trust, strengthening decision-making, and ensuring AI adoption across 100,000+ employees worldwide. The conversation also dives into psychological safety, bias detection, global recognition platforms, and why culture, inclusion and employee experience must be tightly integrated if companies want AI to stick and deliver real transformation.

In this episode of the Unlearn Podcast, I sit down with Cass Pratt, Chief Human Resources Officer at Progyny, to explore how HR is evolving into a design discipline that blends human connection with AI-powered productivity. From building bots to boost employee experience to reshaping how we think about roles in an automated world, Cass shares an honest look at how she's bringing people along on a transformation journey—with curiosity, experimentation, and heart.We discuss her pivotal decision to say yes to opportunities beyond her comfort zone, the strategic shifts she's leading inside a fast-scaling company, and why the future of HR is about enhancing humanity, not replacing it. If you're wondering what leadership looks like when AI meets empathy, this one's for you.Key TakeawaysUnlearning expertise-dependence: Cass shifted from relying on experts to co-creating solutions with AI tools before engaging others.AI as a force for elevation: At Progyny, AI is used to give employees time back, not take roles away—enabling deeper focus on human-centric work.Low-code leadership: Cass, a self-described non-technical leader, built HR bots and reimagined policies through practical AI applications.Scaling culture through consistency: AI chatbots improved response times, standardized answers, and gave insight into employee concerns.Embedding experimentation: Teams are encouraged to ask, "What should I stop doing?"—sparking a culture of reinvention and initiative.Additional InsightsProgyny's “Super Fans” initiative reframes AI gains as an opportunity to deepen customer and employee relationships.Training is done in cohorts to build shared understanding and reduce AI anxiety.Cross-functional collaboration with junior team members—like the intern who built the HR bot—shows how innovation can come from any level.Cass uses AI to simplify and globalize complex frameworks like competency models, improving alignment across teams and geographies.Episode Highlights00:00 – Episode Recap Cassandra Pratt shares how embracing discomfort led her to leap into healthcare, build a transformative HR function, and lead with AI—not to eliminate roles, but to elevate people and amplify their impact.02:37 – Guest Introduction: Cassandra Pratt Barry introduces Cass Pratt, Chief People Officer at Progyny, a fertility and family-building benefits company scaling rapidly with a human-first, tech-empowered culture.04:48 – Saying Yes to Growth Cass reflects on a missed opportunity that taught her the cost of saying no—and set her on a path to jump into unknowns with conviction.08:04 – Startup Lessons and Leadership Growth From 50 to 850 employees, Cass shares what it means to grow with a company and embrace mistakes as part of the journey.11:00 – Diving into AI Without a Tech Background Despite lacking technical skills, Cass threw herself into generative AI—learning by doing and discovering intuitive ways to drive value.13:10 – Unlearning the Expert Reflex Cass rethinks her default of turning to experts first—instead starting with AI to shape stronger ideas and bring others in as collaborators.15:13 – Redesigning Processes, Not Just Tools AI opened up opportunities to rethink workflows from scratch, not just automate existing inefficiencies.20:35 – Making AI Safe and Human Cass shares how transparent messaging, training, and cultural reinforcement helps ease AI anxieties and keep

SEO professionals must build lightweight tools to remain competitive in evolving search roles. Ryland M Bacorn from Boca De demonstrates how tool-building has become essential for SEO career advancement, with automation workflows now driving scalable enterprise search operations. The discussion covers practical coding implementation for SEOs, error troubleshooting methodologies for AI-powered tools, and workflow automation strategies using platforms like N8N and OpenAI's latest releases.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.