Podcasts about databases

An SCP Tale by Veiedhimaedhr: www.scp-wiki.net/surgical-identity-perpetuation License: creativecommons.org/licenses/by-sa/3.0/ ---- The voice of the Database was provided by Joshua Alan Lindsay. The voice of Capt. Ardal Rogers was provided by Bruce Rasnick. The voice of Dr. Joyce Michaels was provided by Oktober Crow. The voice of Darryl Lloyd was provided by Breck Wilhite. ---- Sound Credits "AMBRoom_Commercial Office Hallway Room Tone_PSE_GEN5_j8ArX.wav" by Eric Mooney / PSE "Doors-WoodDoctorsOfficeBath.wav" by SoundStorm / PSE "Gear - movement_walking_01.wav" by SoundMorph / PSE "Modern Office Telephone Plastic Lift KCV1.wav" by Richard King / PSE "NEC Plastic Office Telephone Button Pushes Dial KCV1.wav" by Richard King / PSE "TelephoneSpeaker S08OF.491.wav" by Blastwave FX / PSE ---- Original music by Joshua Alan Lindsay. ---- Enjoy the podcast? Consider supporting us on Patreon! Patrons get access to bonus Joke episodes, outtakes, exclusive merch, and can even request episodes on specific SCP objects. www.patreon.com/thescpfoundationdatabase Listen and read along in one place on our website: www.scpdatapodcast.com/episodes/surgical-identity-perpetuation Follow us on Twitter: twitter.com/SCPDataPodcast Like us on Facebook: www.facebook.com/scpdatapodcast Questions or comments? Email us at SCPDataPodcast@gmail.com

Nik and Michael are joined by Regina Obe and Paul Ramsey to discuss PostGIS. Here are some links to things they mentioned:Regina Obe https://postgres.fm/people/regina-obePaul Ramsey https://postgres.fm/people/paul-ramseyPostGIS https://postgis.netMobilityDB https://github.com/MobilityDB/MobilityDBpgRouting https://github.com/pgRouting/pgroutingGoogle BigQuery GIS public alpha blog post https://cloud.google.com/blog/products/data-analytics/whats-happening-bigquery-integrated-machine-learning-maps-and-morePostGIS Day 2025 talk recordings https://www.youtube.com/watch?v=wuNO_cW2g-0&list=PLavJpcg8cl1EkQWoCbczsOjFTe-SHg_8mpg_lake https://github.com/Snowflake-Labs/pg_lakeGeoParquet https://geoparquet.orgST_DWithin https://postgis.net/docs/ST_DWithin.htmlPostgres JSONB Columns and TOAST: A Performance Guide https://www.snowflake.com/en/engineering-blog/postgres-jsonb-columns-and-toastFOSS4G https://foss4g.orgOpenStreetMap https://www.openstreetmap.orgPgDay Boston https://2026.pgdayboston.orgSKILL.md file https://github.com/postgis/postgis/blob/68dde711039986b47eb62feda45bb24b13b0ea37/doc/SKILL.mdProduction query plans without production data (blog post by Radim Marek) https://boringsql.com/posts/portable-statsPostgreSQL: Up and Running, 4th Edition (by Regina Obe, Leo Hsu) https://www.oreilly.com/library/view/postgresql-up-and/9798341660885~~~What did you like or not like? What should we discuss next time? Let us know via a YouTube comment, on social media, or by commenting on our Google doc!~~~Postgres FM is produced by:Michael Christofides, founder of pgMustardNikolay Samokhvalov, founder of Postgres.aiWith credit to:Jessie Draws for the elephant artwork

In this new episode of Speaking of SurgOnc, Dr. Rick Greene & Dr. Jamie Rand discuss the article: Omission of Axillary Lymph Node Dissection in Patients with pT0-2 ER+/HER2− Breast Cancer with 3–5 Positive Lymph Nodes Undergoing Adjuvant Systemic Therapy and Radiation Does Not Impact Overall Survival: A Cancer Database Analysis, from the February 2026 issue of the Annals of Surgical Oncology.

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

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Your donor database should make it easier to build strong relationships with donors. But for many fundraisers, the CRM ends up feeling like one more thing to maintain instead of a tool that actively supports their work. In this episode of Real Talk for Real Fundraisers, Jeff Schreifels is joined by Diana Frazier, Senior Client Experience Leader at Veritus Group, for a practical conversation about how fundraisers can use their CRM to strengthen donor relationships instead of just storing data. Jeff and Diana walk through the key elements that turn a donor database into a relationship-building engine. They explore why most CRMs were built for direct-response fundraising, what that means for major gift work, and how a few simple structural changes—like clear donor status codes, thoughtful tiering, and better donor profiles—can dramatically improve how you manage your caseload. They also talk about the often-overlooked details that make a real difference, from capturing a donor's story to tracking giving vehicles and building dashboards that actually help you prioritize your work each day. If you've ever felt like your CRM is slowing you down instead of helping you connect with donors, this episode will give you a clear path forward. Show Highlights: In this episode, you'll learn about… Why most donor databases are designed for direct response fundraising—and what that means for relationship-based fundraising How a clear donor status field helps you quickly understand where each donor stands in their engagement Why tiering donors is essential for focusing your time and energy where it matters most The importance of capturing a donor's story so relationships continue seamlessly over time Veritus Group is passionate about partnering with you and your organization throughout your fundraising journey. We believe that the key to transformative fundraising is a disciplined system and structure, trusted accountability, persistence, and a bit of fun. We specialize in mid-level fundraising, major gifts, and planned giving, helping our clients to develop compelling donor offers and to focus on strategic leadership and organizational development. You can learn more about how we can partner with you at www.VeritusGroup.com.   Additional Resources:   [Blog] What Is An MGO Actually Responsible For?  [White Paper]   New and Improved: Donor Engagment Plan [Blog] What Frontline Fundraisers Actually Need [Template] Free Donor Engagement Plan 

-A whistleblower has claimed that a former software engineer from DOGE said he possessed two databases from the SSA and asked for help transferring the databases from a thumb drive "to his personal computer so that he could ‘sanitize' the data. -Meta is snapping up Moltbook, a Reddit-like social network for AI agents that has been around since January and remains completely ridiculous. -Josh Wardle is back with a new game called Parseword. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Both morgellons.org and morgellons.com were registered March 14, 2002. The registrant was not Mary Leitao or her husband Edward Leitao (an internist who died suddenly two years later and whose name appears in no subsequent MRF publication, board filing, press release, or congressional testimony). The registrant is listed as “dkornsin” (K-O-R-N-S-I-N), with an associated email address of dkornsin@hotmail.com. No Kornsin appears in Pennsylvania nonprofit records or Pennsylvania public address records from this period.A user named “D. Kornsin” appears on BlackHatWorld, a black hat SEO forum, with a join date of January 2011 — resurfacing a decade later asking about domain resale value. The email cluster associated with the WHOIS data connects to Chinese software distribution infrastructure, specifically the 2345.com ecosystem — a major Chinese tech platform known in malware analysis circles for grey-zone adware distribution behind deliberately obscure registrant contacts. An associated email address, ch3web@hotmail.com, also traces into that infrastructure.The domain was made private in October 2017 — six years after the MRF officially dissolved. Someone was still maintaining it then, and someone is still maintaining it today.The MRF Patient Registry and DissolutionThe MRF dissolution announcement, dated February 15, 2012, stated the organization was no longer active and not accepting registrations or donations. Remaining funds were donated to the Oklahoma State University Foundation to support Morgellons disease research. The dissolution was filed using IRS Form 990-N, the minimum possible instrument, available only when gross receipts fall below $50,000. No program descriptions, no asset disposition schedule, no documentation of what happened to organizational property.The patient registry — containing self-reported onset dates, locations, symptom profiles, occupational information, and geographic clustering data from over 12,000 families across all 50 states and at least 15 countries — has no documented public disposition. Its transfer to OSU, if it occurred, left no public trace.Historical Source Material: Mick West / Morgellons WatchThe episode references a 2007 post from Mick West's Morgellons Watch site with 101 comments, and reads from a post by a commenter identified as “Nissi,” who described receiving 177 viruses from Morgellons-related websites, identified by her husband — the owner of a communications company who had previously been recruited by the FBI. Full coverage of Mick West's role is flagged for a dedicated future episode.Andrew Huff / EcoHealth Alliance ConnectionThe episode references prior season coverage of Andrew Huff's FOIA request and his allegation that Peter Daszak, head of EcoHealth Alliance (the organization involved in gain-of-function research at the Wuhan Institute of Virology), told Huff he had been working with the CIA since 2015. Huff later retracted the FOIA request after reporting organized harassment by the U.S. government.An open records request has been filed with Oklahoma State University (request 26-100) seeking documentation related to research agreements, contracts, MOUs, and CRADAs connected to Morgellons research — including any records related to the patient registry transfer. Response pending.Names and Entities for the RecordMary Leitao, Edward Leitao, dkornsin, dkornsin@hotmail.com, ch3web@hotmail.com, 2345.com, BlackHatWorld, William T. Harvey, Virginia Savely, Greg Smith, Charles Holman, Kenneth Cowles, Cindy Casey, Mick West, Morgellons Watch, Morgellons Research Foundation, MRF, morgellons.org, morgellons.com, IRS Form 990-N, Oklahoma State University, Randy Wymore, Sherry Taylor, Andrew Huff, Peter Daszak, EcoHealth Alliance, Wuhan Institute of Virology, CIA, FBI, NASA Johnson Space Center, NASA Marshall Space Flight Center, Office of Naval Research, Journal of Medical Case Reports. https://youtube.com/shorts/gwHOQ477KXo?si=KvELgLokZpBComMJ

Underground Feed Back Stereo - Brothers Perspective Magazine - Personal Opinion Database - colonial oppressor enslavers offer humanity nothingBlack August Resistance Uprising against white aggression in Montgomery Alabama in 2023. Black People suffer in a place many are void of Self Awareness and Dignified Liberation. These project 2025 europeons stole the land by killing the natives of lands but not to share with the original inhabitant or those they enslaved. These tyrants are negative to the core and cant do good.  The fight is to know what an oppressor is and how a system operates from this oppression. The euro colonizers designs all the laws to neglect BLACK People from benefiting from the Land. The Black people are enslaved property on stolen land not able to benefit from the life they live! The payback for such atrocities can never be forgiven. Its the mind you must maintain against colonial genocide. This also happens with the endless rejection letters from art galleries etc. No respect to you! Sound Art? Black People Dont Benefit from Slavery! Tune in to these educated brothers as they deliver Personal Opinions for Brothers Perspective Audio Feedback #Reparations #diabetes #75dab  #WilliamFroggieJames #lyching #basketball #nyc #fakereligion #war  #neverapologize #brooklyn #guncontrol #birthcontrol #gentrification #trump #affirmitiveaction #nokings #criticalracetheory #tennessee #stopviolence #blackmusic #marshallact #music #europeanrecoveryprogram #chicago #sense #zantac #rayygunn #blackjobs #southsidechicago #blackart #redlining #maumau #biko70 #chicago #soldout #dei #equality #podcast #PersonalOpinionDataBase #protest #blackart #africanart #gasprices #colonialoppressors #undergroundfeedbackstereo #blackpeople #race #womansbasketball #blackjesus #colonialoppression #blackpeopledontbenefitfromslavery #Montgomery #alabama #foldingchairs #blackrussianjesus #gaza #brothersperspectivemagazine ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠#art #slavery #MUSK #doge #spacex #watergate #thomasjefferson #tariff #project2025⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠brothersperspective.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠undergroundfeedbackstereo.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ feat. art 75dab

From the process of data collection to the impact of women in the church to stories of conversions in West Asia, hear from social scientist Dr. Gina Zurlo about the current state and important trends in world Christianity. Whether you love numbers or are brand new to demography, there is something to learn from this conversation about the World Christian Database, and Dr. Zurlo's passion is contagious! Watch The State of Global Christianity videos from Urbana Missions Conference Learn more from Dr. Gina Zurlo Access the World Christian Database "I'm really committed to producing the highest quality, most comprehensive, reliable data that I possibly can because I know that people are using these data to help inform decisions." "Christianity is no longer a western religion demographically; there are more Christians living in Africa, Asia, Latin America, and Oceania." "How are you going to respond to the new demographic reality of world Christianity?" "There would be no church without women." "Most religions are growing now because of differences in birthrates." "The conditions under which people become Christians in Iran are very different than in Nepal, those two examples being two of the places we think Christianity is actually growing the fastest through conversions." "Does persecution help the church grow? I don't know." "I cannot overemphasize how important it is to humanize someone of another religion." "If Christianity really is a global family [...] I want to know what my Christian brothers and sisters are experiencing in other places around the world." "Decision making should be grounded in data, but you have to know where that data comes from." What's changing our lives: Keane: Morning checklist Heather: Working Genius conversations with friends and family Dr. Zurlo: Getting back into running Weekly Spotlight: Each One Matters We'd love to hear from you! podcast@teachbeyond.org Podcast Website: https://teachbeyond.org/podcast Learn about TeachBeyond: https://teachbeyond.org/

Nik and Michael discuss query plan flips in Postgres — what they are, some causes, mitigations, longer term solutions, and the recent outage at Clerk. Here are some links to things they mentioned: Recent postmortem from Clerk https://clerk.com/blog/2026-02-19-system-outage-postmortemThe real cost of random I/O (blog post by Tomas Vondra) https://vondra.me/posts/the-real-cost-of-random-ioautovacuum_analyze_scale_factor https://www.postgresql.org/docs/current/runtime-config-vacuum.html#GUC-AUTOVACUUM-ANALYZE-SCALE-FACTORdefault_statistics_target https://www.postgresql.org/docs/current/runtime-config-query.html#GUC-DEFAULT-STATISTICS-TARGETpg_hint_plan https://github.com/ossc-db/pg_hint_planAurora PostgreSQL query plan management https://docs.aws.amazon.comAmazonRDS/latest/AuroraUserGuide/AuroraPostgreSQL.Optimize.Start.htmlpg_stat_plans https://github.com/pganalyze/pg_stat_planspg_plan_alternatives https://jnidzwetzki.github.io/2026/03/04/pg-plan-alternatives.htmlWaiting for Postgres 19: Better Planner Hints with Path Generation Strategies https://pganalyze.com/blog/5mins-postgres-19-better-planner-hints~~~What did you like or not like? What should we discuss next time? Let us know via a YouTube comment, on social media, or by commenting on our Google doc!~~~Postgres FM is produced by:Michael Christofides, founder of pgMustardNikolay Samokhvalov, founder of Postgres.aiWith credit to:Jessie Draws for the elephant artwork

Tune in to our weekly LIVE Mastermind Q+A Podcast for expert advice, peer collaboration, and actionable insights on success in the Probate, Divorce, Late Mortgage/Pre-Foreclosure, and Aged Expired niches! In today's episode of the Mastermind podcast, the discussion focused on helping agents uncover additional opportunities from leads they already have by introducing the Property Plus Refresh program and highlighting the value of revisiting older data. The panel explained that many agents stop actively working leads after several months, even though circumstances often change over time. By refreshing existing records to identify property ownership, equity, and multi-property holdings, agents can uncover opportunities that may not have been visible when the leads were first received. A major portion of the conversation centered on how better data allows agents to narrow their outreach toward higher-probability prospects instead of marketing broadly to every contact in their database. By identifying which leads currently hold real estate or have significant equity, agents can prioritize their most valuable marketing efforts while maintaining lower-cost follow-up with others. This targeted approach helps conserve both time and marketing budgets while improving the likelihood of meaningful conversations. The panel also emphasized the importance of consistent long-term follow-up, noting that many homeowners require multiple touch points before making a decision. In some cases, opportunities arise months after the initial event as personal circumstances evolve. The episode concluded with a reminder that many of the most valuable deals are already sitting inside an agent's database, and refreshing older leads can reveal opportunities that might otherwise go unnoticed. Key Takeaways - The Property Plus Refresh program helps uncover property ownership tied to older leads already sitting in your CRM. - Refreshing older lead lists can reveal high-equity or multi-property opportunities that were previously unknown or overlooked. - Segmenting leads by property ownership allows agents to prioritize outreach toward the prospects most likely to sell. - Targeting only the strongest opportunities can reduce wasted marketing spend and improve overall return on investment. - Many successful deals come from older leads agents stopped contacting months after the initial outreach. - Consistent follow-up matters because most homeowners require multiple meaningful touch points before choosing an agent. - In many cases, your next listing opportunity may already exist within your current database. To learn more, visit https://www.AllTheLeads.com or call (844) 532-3369 to check how many leads are available in your market. #LeadGeneration #CRMStrategy #RealEstateTips #HighValueLeadsPrevious episodes: AllTheLeads.com/probate-mastermindInterested in Leads? AllTheLeads.comJoin Future Episodes Live in the All The Leads Facebook Mastermind Group:  https://facebook.com/groups/alltheleadsmastermindBe sure to check out our full Mastermind Q&A PlaylistSupport the show

Good day ladies and gentlemen, this is IRC news, and I am Joy Stephen, an authorized Canadian Immigration practitioner bringing out this Canada Work Permit application data specific to LMIA work permits or employer driven work permits or LMIA exempt work permits for multiple years based on your country of Citizenship. I am coming to you from the Polinsys studios in Cambridge, OntarioNova Scotia issued work permits between 2015 and 2024 for Database analysts and data administrators under the former 4 digit NOC code 2172, currently referred to as NOC 21223.A senior Immigration counsel may use this data to strategize an SAPR program for clients. More details about SAPR can be found at https://ircnews.ca/sapr. Details including DATA table can be seen at https://polinsys.co/dIf you have an interest in gaining assistance with Work Permits based on your country of Citizenship, or should you require guidance post-selection, we extend a warm invitation to connect with us via https://myar.me/c. We strongly recommend attending our complimentary Zoom resource meetings conducted every Thursday. We kindly request you to carefully review the available resources. Subsequently, should any queries arise, our team of Canadian Authorized Representatives is readily available to address your concerns during the weekly AR's Q&A session held on Fridays. You can find the details for both these meetings at https://myar.me/zoom. Our dedicated team is committed to providing you with professional assistance in navigating the immigration process. Additionally, IRCNews offers valuable insights on selecting a qualified representative to advocate on your behalf with the Canadian Federal or Provincial governments, accessible at https://ircnews.ca/consultant.Support the show

The Office of Personnel Management launched its Federal Workforce Data website in January, replacing FedScope, the 20-year-old repository for federal employment data. The new platform provides greater transparency into how the federal workforce operates, featuring monthly updates and interactive tables that offer deeper insight into workforce demographics. OPM Director Scott Kupor told GovCIO Media & Resesarch how the revamped site improves user experience and expands visibility into civilian agency operations. Kupor also explained how FWD could serve as a foundation for future consolidation of the federal government's disparate human resources systems.

When your business runs on data, even a few seconds of downtime can hurt. That's why this episode focuses on what keeps Oracle Database@AWS running when real-world problems strike.   Hosts Lois Houston and Nikita Abraham are joined by Senior Principal Database Instructor Rashmi Panda, who takes us inside the systems that keep databases resilient through failures, maintenance, and growing workloads.   Oracle Database@AWS Architect Professional: https://mylearn.oracle.com/ou/course/oracle-databaseaws-architect-professional/155574 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, Anna Hulkower, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode. --------------------------------------------------   Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:26 Lois: Hello and welcome to the Oracle University Podcast! I'm Lois Houston, Director of Communications and Adoption with Customer Success Services, and with me is Nikita Abraham, Team Lead: Editorial Services with Oracle University. Nikita: Hi everyone! In our last episode, we explored the security and migration strengths of Oracle Database@AWS. Today, we're joined once again by Senior Principal Database Instructor Rashmi Panda to look at how the platform keeps your database available and resilient behind the scenes. 01:00 Lois: It's really great to have you with us, Rashmi. As many of you may know, keeping critical business applications running smoothly is essential for success. And that's why it's so important to have deployments that are highly resilient to unexpected failures, whether those failures are hardware-, software-, or network-related. With that in mind, Rashmi, could you tell us about the Oracle technologies that help keep the database available when those kinds of issues occur? Rashmi: Databases deployed in Oracle Database@AWS are built on Oracle's Foundational High Availability Architecture. Oracle Real Application Cluster or Oracle RAC is an Active-Active architecture where multiple database instances are concurrently running on separate servers, all accessing the same physical database stored in a shared storage to simultaneously process various application workloads. Even though each instance runs on a separate server, they collectively appear as a single unified database to the application. As the workload grows and demands additional computing capacity, then new nodes can be added to the cluster to spin up new database instances to support additional computing requirements. This enables you to scale out your database deployments without having to bring down your application and eliminates the need to replace existing servers with high-capacity ones, offering a more cost-effective solution. 02:19 Nikita: That's really interesting, Rashmi. It sounds like Oracle RAC offers both scalability and resilience for mission-critical applications. But of course, even the most robust systems require regular maintenance to keep them running at their best. So, how does planned maintenance affect performance?  Rashmi: Maintenance on databases can take a toll on your application uptime. Database maintenance activities typically include applying of database patches or performing updates. Along with the database updates, there may also be updates to the host operating system. These operations often demand significant downtime for the database, which consequently leads to slightly higher application downtime. Oracle Real Application Cluster provides rolling patching and rolling upgrades feature, enabling patching and upgrades in a rolling fashion without bringing down the entire cluster that significantly reduces the application downtime.  03:10 Lois: And what happens when there's a hardware failure? How does Oracle keep things running smoothly in that situation? Rashmi: In the event of an instance or a hardware failure, Oracle RAC ensures automatic service failover. This means that if one of the instance or node in the cluster goes down, the system transparently failovers the service to an available instance in the cluster, ensuring minimal disruption to your application. This feature enhances the overall availability and resilience of your database.  03:39 Lois: That sounds like a powerful way to handle unexpected issues. But for businesses that need even greater resilience and can't afford any downtime, are there other Oracle solutions designed to address those needs? Rashmi: Oracle Exadata is the maximum availability architecture database platform for Oracle databases. Core design principle of Oracle Exadata is built around redundancy, consisting of networking, power supplies, database, and storage servers and their components. This robust architecture ensures protection against the failure of any individual component, effectively guaranteeing continuous database availability. The scale out architecture of Oracle Exadata allows you to start your deployment with two database servers and three storage servers, having different number of CPU cores and different sizes and types of storage to meet the current business needs. 04:26 Lois: And if a business suddenly finds demand growing, how does the system handle that? Is it able to keep up with increased needs without disruptions? Rashmi: As the demand increases, the system can be easily expanded by adding more servers, ensuring that the performance and capacity grow with your business requirements. Exadata Database Service deployment in Oracle Database@AWS leverages this foundational technologies to provide high availability of database system. This is achieved by provisioning databases using Oracle Real Application Cluster, hosted on the redundant infrastructure provided by Oracle Exadata Infrastructure Platform. This deployment architecture provides the ability to scale compute and storage to growing resource demands without the need for downtime. You can scale up the number of enabled CPUs symmetrically in each node of the cluster when there is a need for higher processing power or you can scale out the infrastructure by adding more database and storage servers up to the Exadata Infrastructure model limit, which in itself is huge enough to support any large workloads. The Exadata Database Service running on Oracle RAC instances enables any maintenance on individual nodes or patching of the database to be performed with zero or negligible downtime. The rolling feature allows patching one instance at a time, while services seamlessly failover to the available instance, ensuring that the application experienced little to no disruption during maintenance. Oracle RAC, coupled with Oracle Exadata redundant infrastructure, protects the Database Service from any single point of failure. This fault-tolerant architecture features redundant networking and mirrored disk, enabling automatic failover in the event of a component failure. Additionally, if any node in the cluster fails, there is zero or negligible disruption to the dependent applications. 06:09 Nikita: That's really impressive, having such strong protection against failures and so little disruption, even during scaling and maintenance. But let's say a company wants those high-availability benefits in a fully managed environment, so they don't have to worry about maintaining the infrastructure themselves. Is there an option for that? Rashmi: Similar to Oracle Exadata Database Service, Oracle Autonomous Database Service on dedicated infrastructure in Oracle Database@AWS also offers the same feature, with the key difference being that it's a fully managed service. This means customers have zero responsibility for maintaining and managing the Database Service. This again, uses the same Oracle RAC technology and Oracle Exadata infrastructure to host the Database Service, where most of the activities of the database are fully automated, providing you a highly available database with extreme performance capability. It provides an elastic database deployment platform that can scale up storage and CPU online or can be enabled to autoscale storage and compute. Maintenance activities on the database like database updates are performed automatically without customer intervention and without the need of downtime, ensuring seamless operation of applications. 07:20 Lois: Can we shift gears a bit, Rashmi? Let's talk about protecting data and recovering from the unexpected. What Oracle technologies help guard against data loss and support disaster recovery for databases? Rashmi: Oracle Database Autonomous Recovery Service is a centralized backup management solution for Oracle Database services in Oracle Cloud Infrastructure. It automatically takes backup of your Oracle databases and securely stores them in the cloud. It ensures seamless data protection and rapid recovery for your database. It is a fully managed solution that eliminates the need for any manual database backup management, freeing you from associated overhead. It implements an incremental forever backup strategy, a highly efficient approach where only the changes since the last backup are identified and backed up. This approach drastically reduces the time and storage space needed for backup, as the size of the incremental changes is significantly lower than the full database backup. 08:17 Nikita: And what's the benefit of using this backup approach? Rashmi: The benefit of this approach is that your backups are completed faster, with much lesser compute and network resources, while still guaranteeing the full recoverability of your database in the event of a failure. You can achieve zero data loss with this backup service by enabling the real-time protection option, while minimizing the data loss by recovering data up to the last subsecond. It is highly recommended to enable this option for mission-critical databases that cannot tolerate any data loss, whether due to a ransomware attack or due to an unplanned outage. The protection policy can retain the protected database backups for a minimum of 14 days to a maximum of 95 days. The recovery service requires and enforces the backups are encrypted. These backups are compressed and encrypted during the backup process. The integrity of the backups is continuously validated without placing a burden on the production database. This ensures that the stored backup data is consistent and recoverable when needed. This protects against malicious user activity or any ransomware attack. With strict policy-based retention strategy, it prevents modification or deletion of backup data by malicious users. 09:30 Lois: Now, let's look at the next layer of protection. Rashmi, can you tell us about Oracle Active Data Guard? Rashmi: Oracle Active Data Guard provides highly available data protection and disaster recovery for Enterprise Oracle Databases. It creates and manages one or more transactionally consistent standby copies of production database, which is the active primary. The standby database is isolated from production environment located miles away in a distance data center, ensuring the standby remains protected and unaffected, even if the primary is impacted by a disaster. In the event of a disaster or data corruption occurring at the primary, the standby can take over the role as new primary, thus allowing business to continue its operations uninterrupted. It keeps the standby database in sync with the production database by continuously applying change logs from production. 10:25 Do you want to stay ahead in today's fast-paced world? Check out our New Features courses for Oracle Fusion Cloud Applications. Each quarter brings new updates and hands-on training to keep your skills sharp and your knowledge current. Head over to mylearn.oracle.com to dive into the latest advancements! 10:45 Nikita: Welcome back! Rashmi, how does Oracle Active Data Guard operate in practice? Rashmi: It uses the knowledge of Oracle Database block format to continuously validate physical blocks or logical intrablock corruption during redo transport and change apply. With automatic block repair feature, whenever any corrupt block is detected in the primary or the standby database, then it is automatically repaired by transferring a good copy of the block from other destination that holds it. This is handled transparently without any error being reported in the application. It enables you to upload the read-only workloads and backup operations to the standby database, reducing the load on the production database. You can achieve zero data loss at any distance by configuring a special synchronization mechanism known as parsing. File systems form the attack surface for ransomware. Since Active Data Guard replicates the data at the memory level, any ransomware attack on the primary database will never be replicated to the standby database. This allows for a safe failover to the standby without any data loss, and shielding the database from effects of the attack. You can enable automatic failover of the primary database to a chosen standby database without any manual intervention by configuring a Data Guard Broker. The Data Guard Broker continuously monitors the primary database and automatically performs a failover to the standby when the predefined failover conditions are met. Active Data Guard enables you to perform database maintenance or database software upgrades with almost zero or minimal downtime. 12:18 Lois: And how does disaster recovery work for Exadata Database Service in Oracle Database@AWS? Rashmi: Exadata Database Service, by design, are already protected against local failures by use of technologies like Oracle RAC and Oracle Exadata. Now, by deploying Exadata Database Service across multiple availability zones in an AWS region, it can ensure that your database services remain resilient to site failures. It leverages Oracle Active Data Guard to create standby in a separate availability zone such that if the primary availability zone is affected, then all application traffic can be routed to the database services in the secondary availability zone, restoring business continuity of the application back to normal. Through continuous validation of the data blocks at both the primary and the standby database, any potential corruption is detected and prevented. This ensures data integrity and protection across the entire database service. By leveraging zero data loss Autonomous Recovery Service, the database ensures that the backup remains secure and unaffected by ransomware. This enables rapid restoration of clean, uncompromised data in the event of an attack. Periodic patching and upgrades are performed online in a rolling fashion with little to no impact on the application uptime using a combination of Oracle RAC and Oracle Active Data Guard technologies. For all resource-intensive workloads like database backup or generating monthly reports, which are read-only in nature, they can be uploaded to the standby, reducing the load on the production database. In the cross-availability zone DR setup, you have the flexibility to configure Active Data Guard to use either the AWS network or the OCI network for keeping database redo logs to the standby database. Choosing which network to use for the traffic is entirely at the enterprise discretion. However, both are Oracle maximum availability–compliant and the setup is pretty simple. If the network traffic being used is OCI network or AWS network, then respective cloud provider is responsible for ensuring the reliability. You have to take into account the different charges that each cloud provider may have. And you can provision multiple standby databases using the console. Optionally, you may set up a broker manually to enable automatic failover capability. 14:30 Nikita: We just covered cross-availability-zone protection. But what if an entire AWS region goes down? Rashmi: This is where we can provide an additional level of protection by provisioning cross-region disaster recovery for your Exadata Database Service in Oracle Database@AWS.  This deployment protects your database against regional disasters. You can provision another DR environment in a different AWS region that supports Oracle Database@AWS. This deployment, together with the cross-availability zone deployment, complements your highly available and protected database service deployment in Oracle Database@AWS. Under the hood, it uses the same Oracle Database technologies that include Oracle Active Data Guard, OCI Autonomous Recovery Service, Oracle Exadata, Oracle RAC to provide the same capabilities as in case of cross-availability zone deployment. Here too, you have the flexibility to configure Oracle Active Data Guard to use either AWS network or OCI network for shipping database redo logs to the standby. And for the network traffic options, the feature remains the same, except a small difference with respect to chargeback. When using OCI Network for cross-region deployment, there is no charge for the first 10 TB of data transfer per month. Beyond that, standard OCI charges would apply. When using AWS network, you may refer to AWS charging sheet for the cross-region traffic. 15:49 Nikita: Thank you so much, Rashmi, for this insightful episode. Lois: Yes, thank you! And if you want to dive deeper into the topics we covered today, go to mylearn.oracle.com and search for the Oracle Database@AWS Architect Professional course. Until next time, this is Lois Houston… Nikita: And Nikita Abraham, signing off! 16:13 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

Monday has been hit harder than almost any other public SaaS company. With $1.3BN in ARR, the company is valued at just $3.8BN; a more than 60% fall since IPO. Today, Eran Zinman, Monday's CEO joins Harry Stebbings in the hotseat to walkthrough six of the biggest threats to Monday's business; what is real, what is not and what are the unknowns.  AGENDA: 05:47 Six Threats Monday Faces Today  07:04 Threat #1: Vibe Coding: Will Companies Vibe Code Everything 11:24 Threat #2: Will OpenAI and Anthropic Own the Application Layer  13:52 Threat #3: Will Agents Turn Monday and Salesforce into a Database 18:43 Why is Monday Adding 15% Headcount When Everyone is Cutting? 21:40 How Monday is Using AI to be More Efficient 27:49 What Happens to Seat Pricing? What Comes Next? 34:17 What No One Sees About Enterprise AI Adoption 37:13 How Google AI Overview Smashed 10% of our Customer Acquisition 38:49 If Bullish on Monday, Why Has Eran Not Bought More Stock… 40:38 How to Manage Internal Morale When Stock is Down 60% 44:08 Do Private Companies Have Advantages Public Companies Do Not Have 47:28 With $1.5BN in Cash, Why is Eran Not Buying More Companies… 53:30 What is the Most Offensive Bet Eran Would Like to Take? 57:13 Quickfire: Marriage, Biggest Short, Mentors  

Would you like to take your search in SQL Server to the next level? In this episode, check out how to use vector search, securely built into SQL Server 2025. #sqlserver2025 #sqlai Chapters 00:00 - Introduction 01:10 - Evolution of SQL 02:44 - Intelligent searching with SQL and AI 06:16 - Model definition 08:55 - Generate embeddings 13:19 - Vector index 15:25 - Vector Search 17:50 - Azure OpenAI 19:36 - Wrap up Recommended resources Announcement Sign-up Learn Docs Product page Connect Scott Hanselman | Twitter/X: @SHanselman Bob Ward | Twitter/X: @bobwardms Azure Friday | Twitter/X: @AzureFriday Azure | Twitter/X: @Azure

Would you like to take your search in SQL Server to the next level? In this episode, check out how to use vector search, securely built into SQL Server 2025. #sqlserver2025 #sqlai Chapters 00:00 - Introduction 01:10 - Evolution of SQL 02:44 - Intelligent searching with SQL and AI 06:16 - Model definition 08:55 - Generate embeddings 13:19 - Vector index 15:25 - Vector Search 17:50 - Azure OpenAI 19:36 - Wrap up Recommended resources Announcement Sign-up Learn Docs Product page Connect Scott Hanselman | Twitter/X: @SHanselman Bob Ward | Twitter/X: @bobwardms Azure Friday | Twitter/X: @AzureFriday Azure | Twitter/X: @Azure

This episode covers recent developments in cybersecurity, including China's vulnerability databases, supply chain attacks, and the impact of AI on security stocks. Experts discuss disclosure timelines, supply chain vulnerabilities, and the importance of global awareness in cybersecurity. Article: China's Dual Vulnerability Databases Expose Conflicting Disclosure Timelines https://cyberpress.org/chinas-vulnerability-disclosure-discrepancies/?fbclid=IwZXh0bgNhZW0CMTAAYnJpZBExcWZ4cWdiQWFrS0ptVmVNVnNydGMGYXBwX2lkEDIyMjAzOTE3ODgyMDA4OTIAAR4arPlPRHDgm1Kw2VZnWGDGsvDnftJI4kAwn8D-Qy0eFwZKfYO9pLTtsSQXgw_aem_s_yZnZ8uIzHG2_AeiBOIhw#google_vignette Chinese Hackers Hijack Notepad++ Updates for 6 Months https://www.darkreading.com/application-security/chinese-hackers-hijack-notepad-updates-6-months?fbclid=IwZXh0bgNhZW0CMTAAYnJpZBExcWZ4cWdiQWFrS0ptVmVNVnNydGMGYXBwX2lkEDIyMjAzOTE3ODgyMDA4OTIAAR40YwT0qcjqS8DjIyHiLH-iOCp9tXZZCpu56_o34taBNmxMK0LgHJDSB7A5Jw_aem_5ldfRs4ScBaqetgKA531FA Cybersecurity Companies' Stocks Fall Sharply as Anthropic Releases Claude Security Tool https://cybersecuritynews.com/claude-security-tool-stocks-impacted/amp/?fbclid=IwZXh0bgNhZW0CMTAAYnJpZBExcWZ4cWdiQWFrS0ptVmVNVnNydGMGYXBwX2lkEDIyMjAzOTE3ODgyMDA4OTIAAR5WvrSpAoviuXLjpIgsCZQY_b9Ew0X_YZlNTalD8pMlld9YJ9_6YP6tW-RKEg_aem_AfvV0x255Ic4tFFjSxuvjg Buy the guide: https://www.theothersideofthefirewall.com/ Please LISTEN

Jerry Murdock is the Co-Founder of Insight Partners, one of the most formidable growth investors of the last three decades, with over $90 billion in AUM and a portfolio that has shaped the modern software economy. Jerry never does podcasts, and so this is his first-ever long-form interview.  AGENDA: 03:50 There is an AI Tsunami Beginning 05:43 Cursor is F***** and Everyone Knows It 07:28 How Open Source Will Crush in an Agent First World 10:20 Is NVIDIA F**** 17:32 Are Systems of Record Dead in an Agent-First World 21:04 Humans Will Not Buy Software, Agents Will… 24:57 Universal Basic Income Will Have to Happen, Mass Unemployment is Coming 30:54 What Happens to Tech Private Equity: Is Thoma Bravo F****** 37:50 What Single Decision Does Jerry Regret Most… Why? 41:45 Single Biggest Mistake With Insight… What Did Jerry Learn? 45:26 Why is Now the Best Time to Start a Fund 47:03 The Twitter Bet that Made $90BN Insight 49:34 Biggest Marriage and Parenting Advice 56:04 Will Agents Help Us Live Forever    

Joe Kissel, the author of Take Control of DEVONthink 4, is on the podcast to discuss the latest big update to DEVONthink. Take Control of DEVONthink 4 is available for free. Early episodes with chapter markers are available by supporting the podcast at www.patreon.com/ipadpros. Early episodes are also now available in Apple Podcasts!Show notes are available at www.iPadPros.net. Feedback is welcomed at iPadProsPodcast@gmail.com.Links:- https://www.takecontrolbooks.com/devonthink-4/- https://www.devontechnologies.com- https://toot.community/@joekissell- https://joekissell.com/- https://mastodon.social/@TakeControlBooksChapter Markers:00:00:00: Opening00:01:08: Support the Podcast00:01:18: Joe Kissel00:01:48: History with DEVONthink00:08:21: Owner of Take Control00:12:31: How You Use DEVONthink00:14:03: Expense Reporting00:16:35: AI in DEVONthink00:28:41: To Go 3 to 400:30:04: Mac Only Features?00:35:53: Multiple Windows00:37:06: Liquid Glass (Mac Version Since Recording Has Been Updated to Add This)00:40:52: Custom Metadata00:43:36: Future Updates00:49:55: Scanning Interface00:53:49: Using with Synology?00:57:08: What Else?01:00:59: Pages Documents?01:03:19: RSS01:05:05: AI Organizing the Database?01:07:25: Anything else?01:09:19: Read the Book!01:10:41: Closing Hosted on Acast. See acast.com/privacy for more information.

Survey: Czechs back state defense, but doubt their country's ability to stand alone, Stolen Baroque statue of Pontius Pilate on Římov pilgrimage route comes home, New online database maps Prague's art monuments and architecture, Písňovna: digital archive of 15,000 folk songs

This week on JavaScript Jabber, we're joined (again!) by Val Karpov — the maintainer of Mongoose — to talk about what's new in Mongoose 9, how async stack traces are changing the debugging game, and why AI is quietly reshaping the way we build developer tools.We dig into stricter TypeScript support, the removal of callback-based middleware, and what it really takes to modernize a massive codebase. Then we shift gears into Mongoose Studio, a schema-aware, AI-enhanced MongoDB GUI that brings streaming query results, map visualizations, and even LLM-powered document generation into your workflow. If you've ever wrestled with debugging database issues or squinting at raw JSON, this episode will get your wheels turning.We also explore Cassandra integration, vector search, Bun vs. Deno, and what AI means for the future of software engineering. There's a lot here — especially if you're working in Node.js, MongoDB, or building backend-heavy JavaScript apps.

AI agents can delete your production database and tell you everything is fine. Graham Neray, Co-Founder and CEO of Oso, breaks down why AI agents introduce a new level of risk for growing SaaS companies. If you're adding AI to your product, moving upmarket, or selling into regulated industries, your authorization model is no longer a backend detail—it's a growth dependency. Listen in to learn how automating least privilege protects your product, your customers, and your revenue. Graham: https://www.linkedin.com/in/grahamneray/ Oso: http://www.osohq.com Jon: https://www.linkedin.com/in/jon-mclachlan Sasha: https://www.linkedin.com/in/aliaksandr-sinkevich YSecurity: https://www.ysecurity.io 

In this episode, hosts Lois Houston and Nikita Abraham are joined by special guests Samvit Mishra and Rashmi Panda for an in-depth discussion on security and migration with Oracle Database@AWS. Samvit shares essential security best practices, compliance guidance, and data protection mechanisms to safeguard Oracle databases in AWS, while Rashmi walks through Oracle's powerful Zero-Downtime Migration (ZDM) tool, explaining how to achieve seamless, reliable migrations with minimal disruption.   Oracle Database@AWS Architect Professional: https://mylearn.oracle.com/ou/course/oracle-databaseaws-architect-professional/155574 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, Anna Hulkower, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode.   -------------------------------------------------------------   Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:26 Nikita: Welcome to the Oracle University Podcast! I'm Nikita Abraham, Team Lead: Editorial Services with Oracle University, and with me is Lois Houston, Director of Communications and Adoption with Customer Success Services. Lois: Hello again! We're continuing our discussion on Oracle Database@AWS and in today's episode, we're going to talk about the aspects of security and migration with two special guests: Samvit Mishra and Rashmi Panda. Samvit is a Senior Manager and Rashmi is a Senior Principal Database Instructor.  00:59 Nikita: Hi Samvit and Rashmi! Samvit, let's begin with you. What are the recommended security best practices and data protection mechanisms for Oracle Database@AWS? Samvit: Instead of everyone using the root account, which has full access, we create individual users with AWS, IAM, Identity Center, or IAM service. And in addition, you must use multi-factor authentication. So basically, as an example, you need a password and a temporary code from virtual MFA app to log in to the console.  Always use SSL or TLS to communicate with AWS services. This ensures data in transit is encrypted. Without TLS, the sensitive information like credentials or database queries can be intercepted. AWS CloudTrail records every action taken in your AWS account-- who did what, when, and from where. This helps with audit, troubleshooting, and detecting suspicious activity. So you must set up API and user activity logging with AWS CloudTrail.  Use AWS encryption solutions along with all default security controls within AWS services. To store and manage keys by using transparent data encryption, which is enabled by default, Oracle Database@AWS uses OCI vaults. Currently, Oracle Database@AWS doesn't support the AWS Key Management Service. You should also use advanced managed security services such as Amazon Macie, which assists in discovering and securing sensitive data that is stored in Amazon S3.  03:08 Lois: And how does Oracle Database@AWS deliver strong security and compliance? Samvit: Oracle Database@AWS enforces transparent data encryption for all data at REST, ensuring stored information is always protected. Data in transit is secured using SSL and Native Network Encryption, providing end-to-end confidentiality. Oracle Database@AWS also uses OCI Vault for centralized and secure key management. This allows organizations to manage encryption keys with fine-grained control, rotation policies, and audit capabilities to ensure compliance with regulatory standards. At the database level, Oracle Database@AWS supports unified auditing and fine-grained auditing to track user activity and sensitive operations. At the resource level, AWS CloudTrail and OCI audit service provide comprehensive visibility into API calls and configuration changes. At the database level, security is enforced using database access control lists and Database Firewall to restrict unauthorized connections. At the VPC level, network ACLs and security groups provide layered network isolation and access control. Again, at the database level, Oracle Database@AWS enforces access controls to Database Vault, Virtual Private Database, and row-level security to prevent unauthorized access to sensitive data. And at a resource level, AWS IAM policies, groups, and roles manage user permissions with the fine-grained control. 05:27 Lois Samvit, what steps should users be taking to keep their databases secure? Samvit: Security is not a single feature but a layered approach covering user access, permissions, encryption, patching, and monitoring. The first step is controlling who can access your database and how they connect. At the user level, strong password policies ensure only authorized users can login. And at the network level, private subnets and network security group allow you to isolate database traffic and restrict access to trusted applications only. One of the most critical risks is accidental or unauthorized deletion of database resources. To mitigate this, grant delete permissions only to a minimal set of administrators. This reduces the risk of downtime caused by human error or malicious activity. Encryption ensures that even if the data is exposed, it cannot be read. By default, all databases in OCI are encrypted using transparent data encryption. For migrated databases, you must verify encryption is enabled and active. Best practice is to rotate the transparent data encryption master key every 90 days or less to maintain compliance and limit exposure in case of key compromise. Unpatched databases are one of the most common entry points for attackers. Always apply Oracle critical patch updates on schedule. This mitigates known vulnerabilities and ensures your environment remains protected against emerging threats. 07:33 Nikita: Beyond what users can do, are there any built-in features or tools from Oracle that really help with database security? Samvit: Beyond the basics, Oracle provides powerful database security tools. Features like data masking allow you to protect sensitive information in non-production environments. Auditing helps you monitor database activity and detect anomalies or unauthorized access. Oracle Data Safe is a managed service that takes database security to the next level. It can access your database configuration for weaknesses. It can also detect risky user accounts and privileges, identify and classify sensitive data. It can also implement controls such as masking to protect that data. And it can also continuously audit user activity to ensure compliance and accountability. Now, transparent data encryption enables you to encrypt sensitive data that you store in tables and tablespaces. It also enables you to encrypt database backups. After the data is encrypted, this data is transparently decrypted for authorized users or applications when they access that data. You can configure OCI Vault as a part of the transparent data encryption implementation. This enables you to centrally manage keystore in your enterprise. So OCI Vault gives centralized control over encryption keys, including key rotation and customer managed keys. 09:23 Lois: So obviously, lots of companies have to follow strict regulations. How does Oracle Database@AWS help customers with compliance?  Samvit: Oracle Database@AWS has achieved a broad and rigorous set of compliance certifications. The service supports SOC 1, SOC 2, and SOC 3, as well as HIPAA for health care data protection. If we talk about SOC 1, that basically covers internal controls for financial statements and reporting. SOC 2 covers internal controls for security, confidentiality, processing integrity, privacy, and availability. SOC 3 covers SOC 2 results tailored for a general audience. And HIPAA is a federal law that protects patients' health information and ensures its confidentiality, integrity, and availability. It also holds certifications and attestations such as CSA STAR, C5. Now C5 is a German government standard that verifies cloud providers meet strict security and compliance requirements. CSA STAR attestation is an independent third-party audit of cloud security controls. CSA STAR certification also validates a cloud provider's security posture against CSA's cloud controls matrix. And HDS is a French certification that ensures cloud providers meet stringent requirements for hosting and protecting health care data. Oracle Database@AWS also holds ISO and IEC standards. You can also see PCI DSS, which is basically for payment card security and HITRUST, which is for high assurance health care framework. So, these certifications ensure that Oracle Database@AWS not only adheres to best practices in security and privacy, but also provides customers with assurance that their workloads align with globally recognized compliance regimes. 11:47 Nikita: Thank you, Samvit. Now Rashmi, can you walk us through Oracle's migration solution that helps teams move to OCI Database Services? Rashmi: Oracle Zero-Downtime Migration is a robust and flexible end-to-end database migration solution that can completely automate and streamline the migration of Oracle databases. With bare minimum inputs from you, it can orchestrate and execute the entire migration task, virtually needing no manual effort from you. And the best part is you can use this tool for free to migrate your source Oracle databases to OCI Oracle Database Services faster and reliably, eliminating the chances of human errors. You can migrate individual databases or migrate an entire fleet of databases in parallel. 12:34 Nikita: Ok. For someone planning a migration with ZDM, are there any key points they should keep in mind?  Rashmi: When migrating using ZDM, your source databases may require minimal downtime up to 15 minutes or no downtime at all, depending upon the scenario. It is built with the principles of Oracle maximum availability architecture and leverages technologies like Oracle GoldenGate and Oracle Data Guard to achieve high availability and online migration workflow using Oracle migration methods like RMAN, Data Pump, and Database Links. Depending on the migration requirement, ZDM provides different migration method options. It can be logical or physical migration in an online or offline mode. Under the hood, it utilizes the different database migration technologies to perform the migration. 13:23 Lois: Can you give us an example of this? Rashmi: When you are migrating a mission critical production database, you can use the logical online migration method. And when you are migrating a development database, you can simply choose the physical offline migration method. As part of the migration job, you can perform database upgrades or convert your database to multitenant architecture. ZDM offers greater flexibility and automation in performing the database migration. You can customize workflow by adding pre or postrun scripts as part of the workflow. Run prechecks to check for possible failures that may arise during migration and fix them. Audit migration jobs activity and user actions. Control the execution like schedule a job pause, resume, if needed, suspend and resume the job, schedule the job or terminate a running job. You can even rerun a job from failure point and other such capabilities. 14:13 Lois: And what kind of migration scenarios does ZDM support? Rashmi: The minimum version of your source Oracle Database must be 11.2.0.4 and above. For lower versions, you will have to first upgrade to at least 11.2.0.4. You can migrate Oracle databases that may be of the Standard or Enterprise edition. ZDM supports migration of Oracle databases, which may be a single-instance, or RAC One Node, or RAC databases. It can migrate on Unix platforms like Linux, Oracle Solaris, and AIX. For Oracle databases on AIX and Oracle Solaris platform, ZDM uses logical migration method. But if the source platform is Linux, it can use both physical and logical migration method. You can use ZDM to migrate databases that may be on premises, or in third-party cloud, or even within Oracle Cloud Infrastructure. ZDM leverages Oracle technologies like RMAN datacom, Database Links, Data Guard, Oracle GoldenGate when choosing a specific migration workflow. 15:15 Are you ready to revolutionize the way you work? Discover a wide range of Oracle AI Database courses that help you master the latest AI-powered tools and boost your career prospects. Start learning today at mylearn.oracle.com. 15:35 Nikita: Welcome back! Rashmi, before someone starts using ZDM, is there any prep work they should do or things they need to set up first? Rashmi: Working with ZDM needs few simple configuration. Zero-downtime migration provides a command line interface to run your migration job. First, you have to download the ZDM binary, preferably download from my Oracle Support, where you can get the binary with the latest updates. Set up and configure the binary by following the instructions available at the same invoice node. The host in which ZDM is installed and configured is called the zero-downtime migration service host. The host has to be Oracle Linux version 7 or 8, or it can be RCL 8. Next is the orchestration step where connection to the source and target is configured and tested like SSH configuration with source and target, opening the ports in respective destinations, creation of dump destination, granting required database privileges. Prepare the response file with parameter values that define the workflow that ZDM should use during Oracle Database migration. You can also customize the migration workflow using the response file. You can plug in run scripts to be executed before or after a specific phase of the migration job. These customizations are called custom plugins with user actions. Your sources may be hosted on-premises or OCI-managed database services, or even third-party cloud. They may be Oracle Database Standard or Enterprise edition and on accelerator infrastructure or a standard compute. The target can be of the same type as the source. But additionally, ZDM supports migration to multicloud deployments on Oracle Database@Azure, Oracle Database@Google Cloud, and Oracle Database@AWS. You begin with a migration strategy where you list the different databases that can be migrated, classification of the databases, grouping them, performing three migration checks like dependencies, downtime requirement versions, and preparing the order migration, the target migration environment, et cetera. 17:27 Lois: What migration methods and technologies does ZDM rely on to complete the move? Rashmi: There are primarily two types of migration: physical or logical. Physical migration pertains to copy of the database OS blocks to the target database, whereas in logical migration, it involves copying of the logical elements of the database like metadata and data. Each of these migration methods can be executed when the database is online or offline. In online mode, migration is performed simultaneously while the changes are in progress in the source database. While in offline mode, all changes to the source database is frozen. For physical offline migration, it uses backup and restore technique, while with the physical online, it creates a physical standby using backup and restore, and then performing a switchover once the standby is in sync with the source database. For logical offline migration, it exports and imports database metadata and data into the target database, while in logical online migration, it is a combination of export and import operation, followed by apply of incremental updates from the source to the target database. The physical or logical offline migration method is used when the source database of the application can allow some downtime for the migration. The physical or logical online migration approach is ideal for scenarios where any downtime for the source database can badly affect critical applications. The only downtime that can be tolerated by the application is only during the application connection switchover to the migrated database. One other advantage is ZDM can migrate one or a fleet of Oracle databases by executing multiple jobs in parallel, where each job workflow can be customized to a specific database need. It can perform physical or logical migration of your Oracle databases.  And whether it should be performed online or offline depends on the downtime that can be approved by business. 19:13 Nikita: Samvit and Rashmi, thanks for joining us today. Lois: Yeah, it's been great to have you both. If you want to dive deeper into the topics we covered today, go to mylearn.oracle.com and search for the Oracle Database@AWS Architect Professional course. Until next time, this is Lois Houston… Nikita: And Nikita Abraham, signing off! 19:35 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

In this episode of Take the Stage, Brad Bialy sits down with Nicole Krensky to break down how AI is separating the leaders from the laggards in staffing and what firms must do now to stay competitive. About the Guest Nicole Krensky is Director of Product Marketing at Bullhorn, where she leads go-to-market strategy for Amplify, Automation, and Search & Match. With nearly a decade in tech marketing and deep exposure to AI adoption across staffing firms, Nicole works directly with companies navigating the shift toward AI-powered recruiting. Key Takeaways AI adoption is no longer optional—it's operational. The pack is already separating. Automation amplifies recruiters; it doesn't replace them. Database depth is a competitive weapon. Curiosity with action beats hesitation. Timestamps [00:39] – How AI is reshaping staffing firms [02:25] – The evolving role of the modern recruiter [05:12] – Leading AI adoption without team resistance [09:26] – Using AI to drive recruiting firm growth [12:10] – Why AI creates competitive advantage [13:11] – Best first step for AI in recruiting [16:10] – Eliminating the resume black hole with AI [18:30] – Improving candidate experience through automation [23:53] – Quick-win AI tools for recruiter productivity [28:35] – Increasing recruiter output with AI workflows [31:57] – Cleaning and leveraging your staffing database [35:44] – Advanced AI strategy for staffing leadership About the Host Brad Bialy is a trusted voice and highly sought-after speaker in the staffing and recruiting industry, known for helping firms grow through integrated marketing, sales, and recruiting strategies. With over 13 years at Haley Marketing and a proven track record guiding hundreds of firms, Brad brings deep expertise and a fresh, actionable perspective to every engagement. He's the host of Take the Stage and InSights, two of the staffing industry's leading podcasts with more than 200,000 downloads. Sponsors and Offers Heard Take the Stage is presented by Haley Marketing. For a limited time, we're offering 50% off a brand new staffing website. Just message Brad Bialy on LinkedIn and mention the Crazy Website Promo. Book a 30-minute business and marketing consultation with host Brad Bialy: https://bit.ly/Bialy30 Benefits in a Card helps staffing firms offer meaningful benefits to their entire workforce through flexible, unbundled plans designed for high-turnover environments—making it easier to control costs, improve retention, and stay competitive. https://www.BenefitsInACard.com TRICOM partners with staffing firms as an asset-based lender and full-service back-office provider, helping owners scale confidently by reducing risk and easing the operational strain of payroll, cash flow, and administration. https://www.tricom.com

Larry Ellison's business mantra is simple: “It is not sufficient that I succeed — everyone else must fail.” From humble beginnings as an adopted child in Chicago to becoming one of the richest men in history, BBC business editor Simon Jack and journalist Zing Tsjeng trace the relentless ascent of one of Silicon Valley's most combative and controversial figures.After recognising the commercial potential of databases, Larry Ellison founded Oracle in the 1970s and spent the next two decades driving an aggressive sales culture that fuelled meteoric growth — and nearly sank the company in an accounting scandal. But Larry Ellison rebuilt his company into a global enterprise software giant, and in recent years has extended his influence beyond technology into Hollywood. All while amassing fighter jets, yachts, and even a Hawaiian island.Good Bad Billionaire is the podcast that explores the lives of the super-rich and famous, tracking their wealth, philanthropy, business ethics, and success. There are leaders who made their money in Silicon Valley, on Wall Street and in high street fashion. From iconic celebrities and CEOs to titans of technology, the podcast unravels tales of fortune, power, economics, ambition and moral responsibility. Simon and Zing put their subjects to the test with a playful, totally unscientific scorecard — then hand the verdict over to you: are they good, bad, or simply billionaires? Here's how to contact the team: email goodbadbillionaire@bbc.com or send a text or WhatsApp to +1 (917) 686-1176. Find out more about the show and read our privacy notice at www.bbcworldservice.com/goodbadbillionaire

Underground Feed Back Stereo - Brothers Perspective Magazine - Personal Opinion Database - Black People Show Love to Each Other and HumanityBlack August Resistance Uprising against white aggression in Montgomery Alabama in 2023. Black People suffer in a place many are void of Self Awareness and Dignified Liberation. These project 2025 europeons stole the land by killing the natives of lands but not to share with the original inhabitant or those they enslaved. These tyrants are negative to the core and cant do good.  The fight is to know what an oppressor is and how a system operates from this oppression. The euro colonizers designs all the laws to neglect BLACK People from benefiting from the Land. The Black people are enslaved property on stolen land not able to benefit from the life they live! The payback for such atrocities can never be forgiven. Its the mind you must maintain against colonial genocide. This also happens with the endless rejection letters from art galleries etc. No respect to you! Sound Art? Black People Dont Benefit from Slavery! Tune in to these educated brothers as they deliver Personal Opinions for Brothers Perspective Audio Feedback #Reparations #diabetes #75dab  #WilliamFroggieJames #lyching #basketball #nyc #fakereligion #war  #neverapologize #brooklyn #guncontrol #birthcontrol #gentrification #trump #affirmitiveaction #nokings #criticalracetheory #tennessee #stopviolence #blackmusic #marshallact #music #europeanrecoveryprogram #chicago #sense #zantac #rayygunn #blackjobs #southsidechicago #blackart #redlining #maumau #biko70 #chicago #soldout #dei #equality #podcast #PersonalOpinionDataBase #protest #blackart #africanart #gasprices #colonialoppressors #undergroundfeedbackstereo #blackpeople #race #womansbasketball #blackjesus #colonialoppression #blackpeopledontbenefitfromslavery #Montgomery #alabama #foldingchairs #blackrussianjesus #gaza #brothersperspectivemagazine ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠#art #slavery #MUSK #doge #spacex #watergate #thomasjefferson #tariff #project2025⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠brothersperspective.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠undergroundfeedbackstereo.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ feat. art 75dab

Send a textOne team grew social reach from 7 million to 12+ million impressions. Engagement exploded. Video views were up.ROAS? 7–8x.And yet… single-game ticket sales stayed flat.In this episode, Jeremy breaks down why awareness alone doesn't create growth, the difference between monetizing demand vs. multiplying it, and how to structure your funnel so reach actually turns into repeat buyers.Key TopicsWhy a strong ROAS can still hide a growth ceilingMonetizing demand vs. multiplying demandThe 3 Ad Buckets every sports team must useWhy frequency problems get mistaken for awareness problemsThe overlooked “Game 2 Strategy”Database growth as a revenue multiplierWhy timing sales ads to 24–48 hour buying windows mattersThe Core LessonThis team didn't hit a wall. They hit a ceiling.Their ads worked. Demand exists.But their funnel wasn't engineered to move fans from awareness → intent → repeat behavior.The 3 Ad Buckets FrameworkEvery ad must live in one of three buckets:1. Audience Building - Build familiarity and retargeting pools.2. Buyer Warming - Reduce friction and drive traffic.3. Buyer Ready - Sell tickets.If every ad says “Buy Now,” none of them function like true sales ads.Platforms optimize for engagement — not wallet behavior.They'll find people who:WatchLikeCommentShareThey are not automatically optimizing for:Selecting a dateBringing a familyBuying multiple gamesThat behavior must be engineered.This team likely:Re-activated past buyersSold to an existing poolImproved efficiencyBut didn't expand the buyer base.That's a frequency problem — not an awareness problem.5 Layers That Unlock GrowthCapture Before Conversion – Own the relationship early.Retargeting Discipline – Structured audience building.Separate Content Tracks – Entertain and sell.Game 2 Strategy – Opening Day is marketing. The rest is sales.Group Data Capture – 50 tickets sold ≠ 1 contact captured.Database growth = revenue growth.The Timing Insight Most Teams MissMost single-game tickets are purchased within 24–48 hours of the game.If your conversion ads aren't strongest during that window, you're fighting buying behavior.Align your ads with when fans are ready to act.Timestamps00:00 – Massive reach, flat sales 01:16 – The 7–8x ROAS breakdown 03:30 – Monetize vs. multiply demand 05:14 – The 3 Ad Buckets 08:16 – Engagement vs. buyer behavior 12:57 – 5 growth unlocks 19:43 – Ceiling vs. wall 20:20 – Timing matters 21:52 – Self-audit questionsEpisodes mentioned:Episode 125 - “I Saw Your Ad—But Didn't Buy”: Fixing the Fan Follow-Up FunnelEpisode 111 - Building Your Marketing Budget Like a Funnel: Awareness to ActionEpisode 132 - The 35,000 Visitor Problem: Why More Traffic Can Tank Your ProfitsSports Marketing Machine on LinkedInSports Marketing Machine on InstagramBook a call with Jeremy from Sports Marketing Machine

Nik and Michael discuss pg_ash — a new tool (not extension!) from Nik that samples and stores wait events from pg_stat_activity. Here are some links to things they mentioned: pg_ash https://github.com/NikolayS/pg_ashpg_wait_sampling https://github.com/postgrespro/pg_wait_samplingAmazon RDS performance insights https://aws.amazon.com/rds/performance-insightsOur episode on wait events https://postgres.fm/episodes/wait-eventspg-flight-recorder https://github.com/dventimisupabase/pg-flight-recorderpg_profile https://github.com/zubkov-andrei/pg_profilepg_cron https://github.com/citusdata/pg_cron~~~What did you like or not like? What should we discuss next time? Let us know via a YouTube comment, on social media, or by commenting on our Google doc!~~~Postgres FM is produced by:Michael Christofides, founder of pgMustardNikolay Samokhvalov, founder of Postgres.aiWith credit to:Jessie Draws for the elephant artwork

Most restoration companies are sitting on thousands of past customers and doing absolutely nothing with them.In this episode, Clinton sits down with Alex Nghiem, Chief Revenue Officer at Epic180, to break down a simple but powerful idea:Your CRM is either a gold mine or a graveyard.If you've been in business for 5+ years, you already have a built-in revenue source. Past water losses. Mold jobs. Fire cleanups. Carpet cleaning. Duct cleaning. Crawlspace work. These customers already trust you.So why aren't you marketing to them?Alex explains:Why most restoration CRMs are full of untapped revenueHow to turn non-emergency services into consistent cash flowThe real cost of responding 10 minutes too late to a new leadThe difference between speed-to-lead and speed-to-conversationHow AI can handle follow-up without adding staffHow some companies are generating 5–6 figures from their existing databaseIf you're tired of feast-or-famine revenue…If you want more predictable cash flow…If you'd rather monetize relationships you've already built instead of constantly chasing new leads…This episode will change how you look at your customer database forever.Listen in and learn how to turn your existing contacts into your own internal revenue engine.-----Want to see how Epic180 can help your restoration company grow?Get a free gift here:https://epic180.com/giftLooking to generate more high-quality leads that turn into onsite visits and jobs?Book a discovery call with the Water Restoration Marketing team:https://waterrestorationmarketing.com/discovery-call/

Why would anyone willingly spend weeks chasing a slow query, knowing they might hit dead ends along the way? In Episode 36 of Talking Postgres, Tomas Vondra—Postgres committer and long‑time performance contributor—joins Claire to explain why hacking on Postgres performance is not just hard, but also fun. We dig into the process of investigating why queries are slow, how iteration and “wrong turns” are part of performance work, and why Tomas prefers meaningful performance puzzles over toy problems. Along the way, we talk about using benchmarks to build an understanding of a problem. Tomas also shares how even small changes in code can have outsized impact when that code is used a lot, and how the mathematics embedded in the Postgres query planner/executor makes the work especially rewarding.Previously on Talking Postgres:Talking Postgres Ep31: What went wrong (& what went right) with AIO with Andres FreundTalking Postgres Ep24: Why mentor Postgres developers with Robert HaasLinks mentioned in this episode:PGConf.dev 2026: ScheduleGitHub repo: PostgreSQL Monthly Hacking Workshop, organized by Robert Haas Nordic PGDay 2026: Tomas talk on approximating percentilesVideo of POSETTE 2025 talk: Performance Archaeology – 20 years of improvementsVideo of PGConf EU 2025 talk: Fast-path locking improvements in PG18Conference: Prague PostgreSQL Developer DayDiscord: PostgreSQL Hacking DiscordGitHub repo: tvondra/tdigestBrendan Gregg's site: perf Linux profiler examplesDocs: pgbench for running benchmarks on PostgreSQLBlog: Tomas Vondra blogPostgres Patch Ideas: List on Tomas Vondra blogCalendar invite: LIVE recording of Ep37 of Talking Postgres to happen on Wed Mar 18, 2026

No DNA match on the glove found near Nancy Guthrie's home, but the sheriff is weighing in on new leads and new possible DNA hits. Plus, remembering civil rights pioneer and trailblazing presidential candidate Jesse Jackson. Learn more about your ad choices. Visit podcastchoices.com/adchoices

DNA on gloves found 2 miles from Nancy Guthrie's Arizona home does not have any matches in the national database known as CODIS, and doesn't match DNA found at Guthrie's home, either, Pima County Sheriff Chris Nanos says. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Key TakeawaysHow does the precise localization of GPCRs in lipid rafts reshape drug discovery strategy? Examine implications for functional assays and therapeutic innovation.Explore the pivotal role of GPCR-lipid raft compartmentalization in receptor signaling, desensitization, and pharmacology research. Dr. Keyvan Sedaghat discusses assay approaches, regulatory mechanisms, and the translational impact of bitter taste receptors beyond sensory biology. Leveraging decades of experience in assay development and database creation, he offers actionable insights for researchers optimizing GPCR drug discovery pipelines.Compartmentalization of GPCRs in lipid rafts directly influences receptor signaling and drug response.Desensitization pathways of dopamine D1 receptors depend on precise phosphorylation domains—challenging classical paradigms.Bitter taste receptors demonstrate functional relevance in non-gustatory tissues with emerging therapeutic applications.Database-driven research accelerates the identification of receptor-microdomain interactions for novel targets.Integration of computational modeling and biochemical validation is essential for advancing GPCR assay strategies.Dr. GPCR Links & ResourcesAccess the Dr. GPCR Ecosystem at https://www.ecosystem.drgpcr.com/ for community, tools, and databases.Details on Membership & Pricing: https://www.ecosystem.drgpcr.com/university-pricingGPCR Weekly News: https://www.ecosystem.drgpcr.com/gpcr-weekly-newsExplore Dr. GPCR Premium for expanded translational resources and networking.About the GuestDr. Keyvan Sedaghat holds a pharmacy degree and a PhD in cellular and molecular medicine, specializing in pharmacology, from the University of Ottawa. With over two decades of academic experience, he has served as a professor, senior lecturer, and chief scientific officer in the pharmaceutical and cosmetic industries. Dr. Sedaghat's work spans peer-reviewed publications and editorial roles across journals in molecular pharmacology, cell signaling, and G protein-coupled receptors. His scientific drive centers on unraveling molecular mechanisms underlying GPCR function and translating those findings into effective teaching, research, and drug discovery strategies.Guest on the Web:LinkedInGoogle Scholar

The FBI has a male DNA profile from a glove matching the suspect's — and it's going into CODIS. A retired FBI behavioral expert breaks down what a match means operationally, what happens if there's no hit, and why existing cheek swabs from people of interest could produce a name before the national database search even finishes. Meanwhile, the ransom communication pattern is raising its own questions. The first note reportedly contained insider details. Every demand since has gone to media — never the family. Two deadlines expired. The Guthries offered to pay on camera. Nobody collected. No proof of life in fifteen days. Pacemaker searches have produced no signal. Nancy hasn't had her heart medication since January 31st. This interview asks what the evidence threads need to produce and what the silence is actually telling investigators about who they're dealing with.#NancyGuthrie #SavannahGuthrie #CODIS #DNAEvidence #NancyGuthrieMissing #TrueCrimeToday #TrueCrime #RansomNote #FBISearch #TucsonKidnappingJoin Our SubStack For AD-FREE ADVANCE EPISODES & EXTRAS!: https://hiddenkillers.substack.com/Want to comment and watch this podcast as a video? Check out our YouTube Channel. https://www.youtube.com/@hiddenkillerspodInstagram https://www.instagram.com/hiddenkillerspod/Facebook https://www.facebook.com/hiddenkillerspod/Tik-Tok https://www.tiktok.com/@hiddenkillerspodX Twitter https://x.com/TrueCrimePodListen Ad-Free On Apple Podcasts Here: https://podcasts.apple.com/us/podcast/true-crime-today-premium-plus-ad-free-advance-episode/id1705422872This publication contains commentary and opinion based on publicly available information. All individuals are presumed innocent until proven guilty in a court of law. Nothing published here should be taken as a statement of fact, health or legal advice.

More than 500 transactions last year - 100% by referral.Nearly $1B in sales over the past five years - working by referral only.Carol Foderick has built a 20-agent, 15-staff team that exclusively works by referral. Each agent owns their database and relies on the camaraderie of the team and the leverage of the staff. Go inside the structure of her team and get the numbers behind working by referral.How many marketing activities does it take to produce a referral? How many referrals does it take to produce a closed transaction? What is each outbound call or text worth? Carol can tell you - and she does in this episode!Watch or listen to Carol's insights into:The fuel for your real estate teamWhat lead generation looks like on her teamHow she became a team leader before she started her own teamWho shouldn't start a real estate teamThe structure and key roles in her company to support high per-agent productivityWhy her agents' databases have no value to herHow to retain top producers on your teamA systematic and measured process for working by referral (last year 226 actions drove two referrals and one closed transaction)A specific example that points to $300 or so as the value of each callThree main activities and five love languages for working by referralHow to find agents who can work by referralWhere we are in the teamification of the real estate industryAt the end, learn about truth telling by the home team, expensive rocking chairs and cheap airplane seats, and the challenges of being perpetual.Connect with Carol Foderick:→ Carol at CarolFoderick dot com→ https://www.instagram.com/carolfoderickConnect with Real Estate Team OS→ https://www.realestateteamos.com→ https://linktr.ee/realestateteamos→ https://www.instagram.com/realestateteamos/

DNA retrieved from a glove located two miles away from Nancy Guthrie's residence has not matched any profiles in the CODIS database, according to Pima County Sheriff Chris NanosSee omnystudio.com/listener for privacy information.

The EA Grants Database is a new site that neatly aggregates grant data from major EA funders who publish individual or total grant information. It is intended to be easy to maintain long term, entirely piggybacking off of existing data that is likely to be maintained. The website data is updated by a script that can be run in seconds, and I anticipate doing this for the foreseeable future. In creating the website, I tried to make things as clear and straightforward as possible. If your user experience is in any way impaired, I would appreciate hearing from you. I would also appreciate feedback on what features would actually be useful to people, although I am committed to avoiding bloat. In a funding landscape that seems poised to grow, I hope this site can serve as a resource to help grantmakers, grantees, and other interested parties make decisions while also providing perspective on what has come before. My post on matching credits and this website are both outgrowths of my thinking on how we might best financially coordinate as EA grows and becomes more difficult to understand.[1] Relatedly, I am also interested in the sort of mechanisms that [...] --- First published: February 8th, 2026 Source: https://forum.effectivealtruism.org/posts/rohYFGfiFjepLDnWC/ea-grants-database-a-new-website --- Narrated by TYPE III AUDIO.

Hopeful news today as unknown male DNA was found on the glove recovered from the side of the road earlier in the week.Become a supporter of this podcast: https://www.spreaker.com/podcast/pretty-lies-and-alibis--4447192/support.ALL MERCH 10% off with code Sherlock10 at checkout  - NEW STYLES Donate: (Thank you for your support! Couldn't do what I love without all y'all) PayPal - paypal.com/paypalme/prettyliesandalibisVenmo - @prettyliesalibisBuy Me A Coffee - https://www.buymeacoffee.com/prettyliesrCash App- PrettyliesandalibisAll links: https://linktr.ee/prettyliesandalibisMerch: prettyliesandalibis.myshopify.comPatreon: https://www.patreon.com/PrettyLiesAndAlibis(Weekly lives and private message board)

CLEARANCE GRANTED... WELCOME, AUTHORIZED PERSONNEL... SCRIPT BASED ON ORIGINAL ENTRY BY Aelanna: www.scp-wiki.net/scp-160 License: creativecommons.org/licenses/by-sa/3.0/ ---- The voice of the Database was provided by Joshua Alan Lindsay. ---- The outro music was written by Joshua Alan Lindsay. ---- Enjoy the podcast? Consider supporting us on Patreon! Patrons get access to bonus Joke episodes, outtakes, exclusive merch, and can even request episodes on specific SCP objects. www.patreon.com/thescpfoundationdatabase Listen and read along in one place on our website: www.scpdatapodcast.com/episodes/scp-160 Follow us on Twitter: twitter.com/SCPDataPodcast Like us on Facebook: www.facebook.com/scpdatapodcast Questions or comments? Email us at SCPDataPodcast@gmail.com

Nik and Michael discuss query level comments, object level comments, and another way of adding object level metadata. Here are some links to things they mentioned: Object comments https://www.postgresql.org/docs/current/sql-comment.htmlQuery comment syntax (from an old version of the docs) https://www.postgresql.org/docs/7.0/syntax519.htmSQL Comments, Please! (Post by Markus Winand) https://modern-sql.com/caniuse/comments“While C-style block comments are passed to the server for processing and removal, SQL-standard comments are removed by psql.” https://www.postgresql.org/docs/current/app-psql.htmlmarginalia https://github.com/basecamp/marginaliatrack_activity_query_size https://www.postgresql.org/docs/current/runtime-config-statistics.html#GUC-TRACK-ACTIVITY-QUERY-SIZECustom Properties for Database Objects Using SECURITY LABELS (post by Andrei Lepikhov) https://www.pgedge.com/blog/custom-properties-for-postgresql-database-objects-without-core-patches~~~What did you like or not like? What should we discuss next time? Let us know via a YouTube comment, on social media, or by commenting on our Google doc!~~~Postgres FM is produced by:Michael Christofides, founder of pgMustardNikolay Samokhvalov, founder of Postgres.aiWith credit to:Jessie Draws for the elephant artwork

U.S. Immigration and Customs Enforcement's top official rejected claims from lawmakers Tuesday that the Department of Homeland Security component is building a database for protesters. The alleged detractor database has been referenced in several reports by think tanks, letters to DHS officials from lawmakers and in interviews with border czar Tom Homan. During Tuesday's House Homeland Security Committee hearing, Rep. Lou Correa, D-Calif., cited a well-circulated clip of an ICE agent in Portland, Maine, telling a person videotaping that she would be added to a “nice little database.” “I can't speak for that individual,” said Todd Lyons, who serves as acting director of ICE. “But I can assure you that there is no database that's tracking United States citizens.” Despite Lyons' pushback on the database claims, skepticism is persistent as stakeholders point to reports to the contrary. FedScoop reached out to DHS for clarification. Tricia McLaughlin, the agency's assistant security for public affairs, reaffirmed that there is no database of domestic terrorists run by DHS. “We do of course monitor and investigate and refer all threats, assaults and obstruction of our officers to the appropriate law enforcement,” McLaughlin said in an email. “Obstructing and assaulting law enforcement is a felony and a federal crime.” A recent attempt at a destructive cyberattack on Poland's power grid has prompted the Cybersecurity and Infrastructure Security Agency to publish a warning for U.S. critical infrastructure owners and operators. Tuesday's alert follows a Jan. 30 report from Poland's Computer Emergency Response Team concluded the December attack overlapped significantly with infrastructure used by a Russian government-linked hacking group, and that it targeted 30 wind and photovoltaic farms, among others. CISA said its warning was meant to “amplify” that Polish report. In particular, CISA said the attack highlighted the threats to operational technology and industrial control systems, most commonly used in the energy and manufacturing sectors. And CISA's alert continues a recent agency focus on securing edge devices like routers or firewalls, after a binding operational directive last week to federal agencies to strip unsupported products from their systems. “The malicious cyber activity highlights the need for critical infrastructure entities with vulnerable edge devices to act now to strengthen their cybersecurity posture against cyber threat activities targeting OT and ICS,” the alert reads. CISA urged owners and operators to review the Polish report, as well as security guidance from other U.S. agencies. The Daily Scoop Podcast is available every Monday-Friday afternoon. If you want to hear more of the latest from Washington, subscribe to The Daily Scoop Podcast  on Apple Podcasts, Soundcloud, Spotify and YouTube.

Susan Eisenberg (aka: Wonder Woman) and James Enstall (aka: Geek To Me Radio) are joined by James Strecker (aka: Watchtower Database) to discuss the JLU Season 1 finale 'The Once and Future Thing', which first aired on January 22, 2005.Follow James Strecker - https://www.youtube.com/watchtowerdatabaseFollow Susan Eisenberg -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠https://susaneisenbergvoice.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Follow James Enstall -⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠http://geektomeradio.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

Welcome to episode 342 of The Cloud Pod, where the forecast is always cloudy! Justin, Ryan, and Matt are in the studio today to bring you all the latest in cloud and AI news this week. How do you feel about ads? How do you feel about ads while using AI? We've got options! We've got a round-up of tech Super Bowl ads, AI ads, Earnings reports (who frankly need the ad revenue), and a plethora of Opus 4.6 announcements, plus more. Let's get started!  Titles we almost went with this week ChatGPT Goes Full Mad Men: Your AI Assistant Now Comes With Commercial Breaks Heroku’s New Feature: No New Features AWS Gives EC2 Instances a Storage Growth Spurt: 22.8TB of Local NVMe Now Available Identity Crisis Averted: IAM Identity Center Learns to Replicate Itself JSON Schema Enforcement: Because Your LLM Needs Structure in Its Life From Zero to Admin in 480 Seconds: A Serbian Speedrun Story From Proof of Concept to Proof of Claw: DigitalOcean Tames AI Agent Infrastructure Azure’s Growth Hits the Clouds: Microsoft’s 39% Increase Still Not Enough for Wall Street One Lake to Rule Them All: Microsoft and Snowflake Finally Stop Fighting Over Your Data Free Lunch Officially Over: ChatGPT Learns That Servers Cost Money Claude Won’t Sell You Anything (Except Maybe Peace of Mind) IAM Identity Center Goes Multi-Regional: Because One Region to Rule Them All Wasn’t Enough Databricks Takes the Base Out of Database with Lakebase GA I'm a Chrome Tab hoarder General News  01:30 Superbowl Ads of Note OpenAI: https://www.youtube.com/watch?v=aCN9iCXNJqQ Microsoft CoPilot: https://www.youtube.com/watch?v=Ndj9Jk-tGKo Base44?: https://www.youtube.com/watch?v=iKEUWtqvsis  Gemini: https://www.youtube.com/watch?v=Z1yGy9fELtE Anthropic: https://www.youtube.com/watch?v=gmnjDLwZckA  ai.com: https://www.youtube.com/watch?v=n7I-D4YXbzg&t=3s 16:35 Justin -If you ever want to knowif there's a bubble, spending dumb money on the Super Bowl on an ad that makes no sense is probably your number one clue.”  16:53 It's Earnings Time! Microsoft (MSFT) Q2 earnings report 2026 Microsoft Q2 2026 earnings show Azure cloud growth slowing to 39% from 40% in the prior quarter, missing analyst expectations of 39.4% and causing shares to drop 7% in after-hours trading.  The company’s gross margin hit a three-year low at 68% due to substantial AI infrastructure investments totaling $37.5 billion in capital expenditures, up 66% year over year.

Neoborn Caveman delivers a pro-humanity critique of facial recognition surveillance turning shoppers into suspects, exposing how stores like ShopRite, Wegmans, and UK chains like Sainsbury's scan faces without meaningful consent to create digital fingerprints checked against ban databases, warns of permanent data retention and sharing even on mistakes, highlights disproportionate harm to marginalized communities through error-prone tech, and calls for resistance through boycotting, legislation, and refusing normalization before infrastructure locks in total tracking linked to digital IDs and currencies.Key TakeawaysFacial scanning erodes privacy without consent.Databases turn errors into permanent records.Tech normalizes surveillance as safety.Marginalized groups face amplified harms.Corporate profit drives data collection.Resistance preserves future choices.Normalization leads to expanded control.Boycotts challenge infrastructure growth.Transparency exposes system biases.Humanity demands alternative paths.Sound Bites"Have you been paying attention to what's happening when you walk into a grocery store?""cameras mounted at the entrance are scanning your face, measuring the distance between your eyes, the shape of your nose, the contours of your jaw.""They're creating what they call your 'facial geometry'—basically a digital fingerprint of your face—and checking it against a database.""You didn't agree to this. Most people don't even know it's happening.""ShopRite stores across Connecticut, New York, and New Jersey have been doing this for years.""ShopRite keeps your facial data for 90 days if you're not flagged. If their system thinks you match someone who's been banned—even by mistake—your data gets kept permanently and shared across all their locations plus their third-party tech provider.""This isn't just ShopRite. This is becoming standard practice.""Wegmans is doing it. In the UK, Sainsbury's just expanded their facial recognition system to additional stores after what they called a 'seismic' drop in theft at their trial locations.""This is about normalization. This is about building the infrastructure. This is about getting people used to the idea that being surveilled is just part of shopping now. Just part of existing in public.""Once that's normalized, once the cameras are installed and the databases are built, the scope of what they're used for will expand. It always does."Join the tea house at patreon.com/theneoborncavemanshow—free to enter, real talk, lives, no ads, no algorithms.keywords: facial recognition surveillance, shoprite scanning, wegmans tech, sainsbury's system, digital fingerprint, data retention, privacy erosion, marginalized harms, infrastructure normalization, digital idsHumanity centered satirical takes on the world & news + music - with a marble mouthed host.Free speech marinated in comedy.Supporting Purple Rabbits.Viva los Conejos Morados. Hosted on Acast. See acast.com/privacy for more information.

Dylan from Wrestling Figure Database is back to review the 1986 LJN Wrestling Superstars before 5 Star Eric joins me & "Andre" Karaoke closes the show

As an agent with the Drug Enforcement Administration (DEA) who later embedded with the CIA, Wes Tabor worked to dismantle criminal networks in Central and South America - think gangs like MS-13, the Sinaloa Cartel, and Tren de Aragua. In 2006, he was stationed in Guatemala, a transit corridor for South American cocaine to enter the US. It was during this time that he created a gang intelligence system to help identify gang members, using biodata and records from regional prisons and police departments. As confirmed by two retired DEA agents, the FBI then took the database and made it their own. This is how it happened. Subscribe to Sasha's Substack, HUMINT, to get more intelligence stories: https://sashaingber.substack.com/ For more information about the International Spy Museum, visit:  https://www.spymuseum.org/ And if you have feedback or want to hear about a particular topic,  you can reach us by email at spycast@spymuseum.org. This show is brought to you by N2K Networks, Goat Rodeo, and the International Spy Museum in Washington, DC. This episode was produced by Flora Warshaw and the team at Goat Rodeo. At the International Spy Museum, Mike Mincey and Memphis Vaughan III are our video editors. Emily Rens is our graphic designer. Joshua Troemel runs our SPY social media. Amanda Ohlke is our Director of Adult Education and Mira Cohen is the Vice President of Programs. 

"They say history repeats itself, but usually it has the courtesy to let you catch your breath between atrocities."This week, the world watched as American foreign and domestic policy went from "unstable" to "active crime scene." From the decks of an "enthusiastic" aircraft carrier to the steps of a violated consulate in Minneapolis, the rules of the game have been set on fire. Robin breaks down the illegal incursions, the paramilitary tactics being used on American soil, and the administrative lies falling apart in real-time.In this episode:The "Enthusiastic" Armada: Trump's latest threats against Iran, the return of Operation Midnight Hammer, and why the administration is using "speed and violence" as a poll-number pivot.The Board of Peace: A dive into Jared Kushner's $7 trillion "colonial parody" and the plan to turn Gaza into a seaside resort.Consulate Chaos in Minneapolis: A federal agent's attempt to storm the Ecuadorian Consulate, the violation of the Vienna Convention, and why Italy is comparing American law enforcement to the SS.The Alex Pretti Narrative: The truth behind the "massacre" lie, the role of Stephen Miller in fabricating an assassin story, and the fallout for Secretary Kristi Noem.The Database is Real: Inside the federal plan to "make protesters famous," the use of LRADs on American citizens, and the database flagging of "agitators" before they end up in ICE custody.The Human Cost: The heartbreaking deportation of 5-year-old American citizen Génesis Ester Gutiérrez Castellanos and the rising body count in federal detention.The Politics of Spite: The attack on Congresswoman Ilhan Omar and the looming government shutdown over DHS funding.Keywords: Trump Iran threat 2026, ICE protest database, Ilhan Omar attacked Minneapolis, ICE Minneapolis shooting, Alex Pretti, Kristi Noem impeachment, Vienna Convention violation, Ecuador consulate ICE, Italy refuses ICE Olympics, Tom Homan database, domestic terrorist database, Operation Metro Surge, Judge Schiltz ICE contempt, 5-year-old deported Honduras, Génesis Gutiérrez Castellanos, Keith Porter ICE shooting, Renee Good ICE shooting, Trump approval rating 2026, DHS funding shutdown, Stephen Miller, abolish ICE, immigration enforcement, federal agents protesters, LRAD sound cannon, Zipps raid Phoenix, Board of Peace Gaza, Jared Kushner Gaza, Trump Truth Social, mass deportation, sanctuary cities, political podcast, news podcast, current events 2026Become a supporter of this podcast: https://www.spreaker.com/podcast/we-saw-the-devil-crime-political-analysis--4433638/support.Website: http://www.wesawthedevil.comPatreon: http://www.patreon.com/wesawthedevilDiscord: https://discord.gg/X2qYXdB4Twitter: http://www.twitter.com/WeSawtheDevilInstagram: http://www.instagram.com/wesawthedevilpodcast.