Podcasts about Confluence

What can we expect from Atlassian Team '26 Europe?In this episode, we break down our predictions for the biggest announcements, product updates, AI developments, and themes that could shape Atlassian's 2026 European event.From AI teammates and the future of teamwork to Jira, Confluence, Rovo, and the broader Atlassian ecosystem, here's what we'll be watching when Team '26 Europe takes over Amsterdam.Team '26 Europe takes place October 6–8, 2026 at the RAI Amsterdam Convention Center.What are you expecting to see at Team '26 Europe? Let us know in the comments.The Jira Life=====================================Having trouble keeping up with when we are live? Sign up for our Atlassian Community Group!https://ace.atlassian.com/the-jira-life/Or Follow us on LinkedIn! / the-jira-life Become a member on YouTube to get access to perks: / @thejiralife .Hosts:Alex "Dr. Jira" Ortiz / alexortiz89 / @apetechtechtutorials Rodney "The Jira Guy" Nissen / rgnissen https://thejiraguy.comSarah Wright / satwright Producer:"King Bob" Robert Wen / robert-wen-csm-spc6-a552051 Executive Producer: Lina OrtizMusic provided by Monstercat:=====================================Intro: Nitro Fun - Cheat Codes / monstercat Outro: Fractal - Atrium / monstercatinstinct

9.24.26 - Live from Confluence Prep Academy - Student Xyaire Phillips and teacher Haley Brueck; Titan Talk by

9.24.26 Melanie Johnson - Anchor with KSDK 5 on Your Side ; This summer hosted Confluence students in a Media Workshop by

The Heidi Glaus Show - 9.24.26 - Live from Confluence Prep Academy by

In this special episode of The Jira Life, we're talking about Build IT Together 2026 (BIT 2026) before the event kicks off.What does it take to bring the Atlassian community together for an event like this? We'll explore the story behind BIT 2026, how the event is being built, what attendees can expect, and the people working behind the scenes to make it happen.We'll also dive into the speakers, sessions, topics, and experiences that will be part of this year's event from Jira and Confluence to Jira Service Management, automation, AI, Rovo, Forge, Marketplace apps, and the evolving role of Atlassian technology.But BIT is about more than technology.It's about the people building, administering, developing, consulting, and innovating with Atlassian every day. We'll talk about the community coming together, what makes an event like this different, and why creating opportunities for people to share ideas and learn from one another matters.And, of course, we'll get into what The Jira Life is bringing to Build IT Together and what we're looking forward to most when the doors open in Dallas.Whether you're already registered, thinking about attending, part of the Atlassian ecosystem, or simply curious about what happens behind the scenes of a community conference, this episode is your preview of BIT 2026.The Jira Life=====================================Having trouble keeping up with when we are live? Sign up for our Atlassian Community Group!https://ace.atlassian.com/the-jira-life/Or Follow us on LinkedIn! / the-jira-life Become a member on YouTube to get access to perks: / @thejiralife .Hosts:Alex "Dr. Jira" Ortiz / alexortiz89 / @apetechtechtutorials Rodney "The Jira Guy" Nissen / rgnissen https://thejiraguy.comSarah Wright / satwright Producer:"King Bob" Robert Wen / robert-wen-csm-spc6-a552051 Executive Producer: Lina OrtizMusic provided by Monstercat:=====================================Intro: Nitro Fun - Cheat Codes / monstercat Outro: Fractal - Atrium / monstercatinstinct

BONUS: Real-Time Research for Change Leaders Using AI AI is changing how Scrum Masters, Agile coaches, and change leaders make sense of organizations. In this BONUS episode, Ari-Pekka Skarp shares how he uses AI as a research assistant, a workspace partner, and a way to bring qualitative research into day-to-day change leadership. From Curiosity to Research Assistant "It felt like having a research assistant."   Ari-Pekka's first serious AI use did not start in his full-time change leadership role. It started with side projects, research, psychotherapy-related work, and watching his son build websites with Lovable. That curiosity became practical when Ari-Pekka began using AI to support his PhD research. Instead of spending a full day scanning articles, he could find relevant sources, generate useful summaries, and decide where to go deeper in about half an hour. The key was not that AI replaced his judgment. Because he already knew the research area, he could evaluate the quality of what the AI returned and use it as a complement to his own expertise. AI Expands the Research Surface "With the help of AI, I could actually make a little more of these sidetracks."   One of the biggest changes Ari-Pekka noticed was that AI made side paths cheaper to explore. In research and change work, we often ignore interesting but uncertain threads because time and attention are limited. AI gave him a way to examine adjacent ideas without losing the main direction. At the same time, he points out a real risk: AI can guide us toward something too quickly. Sometimes a slower, more intuitive decision is more aligned with the deeper research goal. For Scrum Masters and coaches, that is an important distinction: AI can widen the field of inquiry, but it should not quietly take over the choice of where to look next. Workspaces for Change Leadership "I can create this kind of bird's eye perspective of the organization or the given project quite quickly."   Ari-Pekka describes a major shift when he started using Visual Studio Code and AI agents as a workspace for knowledge work, not only for software. In his workspaces, he organizes goals, themes, source material, Jira data, Confluence material, meeting notes, and other organizational signals so that AI can help him analyze and visualize the big picture. This gives him a practical way to represent relationships, dependencies, open threads, and organizational responses to interventions. For change leaders, the point is not the tool itself. The deeper idea is to structure the work so AI can help process the data while the human still owns the interpretation. Bringing Qualitative Research Into Daily Change Work "I try to form a hypothesis of what I find from the data, and then I see whether those hypotheses are correct or not."   Ari-Pekka uses his qualitative research background to teach AI how to process organizational data in a consistent way. He is not just asking for a summary. He is thinking like a researcher: what is the question, what data is available, what method should be used, and what output format will make interpretation possible? Vasco connects this to the work Scrum Masters already do: hypothesis thinking, looking for evidence beyond our own biases, and using data to test what is really happening in the system. AI makes it possible to bring those research habits into day-to-day work, instead of reserving them for long academic projects. PDCA With Larger and Messier Data Sets "Now we can just use far more extensive data sets from many different sources and integrate it with the help of AI."   Ari-Pekka links AI-supported change work to PDCA: plan, do, check, act. The cycle is familiar, but the available data has changed. Teams and organizations now generate large amounts of textual, conversational, and workflow data across tools like Jira, Teams, Slack, and Confluence. AI can help integrate those sources, but Ari-Pekka warns that organizations are missing an understanding of research methodology. When the same AI tool can produce different answers from the same data, small changes in the research question, method, and prompt matter. Scrum Masters do not need to become full-time researchers, but they do need enough discipline to ask better questions and separate method from interpretation. A Small Experiment: Analyze Power Relations in Meeting Transcripts "With the help of AI, anybody can have a little bit of this kind of experiment in real time."   For a practical experiment, Ari-Pekka suggests starting with meeting transcripts, with explicit consent from the people involved. A Scrum Master or Agile coach can ask AI to perform a power-relation or discourse analysis of the conversation and look for patterns in who speaks, who defines the agenda, which ideas are ignored, and how decisions emerge. Organizational psychologists and researchers have studied these dynamics for years, but the work has traditionally been slow and specialized. AI makes it possible to try a lightweight version of that analysis quickly, then use the results as a prompt for reflection, not as a final judgment. About Ari-Pekka Skarp Ari-Pekka is not only a very experience Agile Coach, but he's also a Psychotherapist, and Organizational Psychologist with over 20 years of experience working with organizations. As an author of several books on topics such as Complexity, the mind, and Mindfulness, Ari-Pekka blends deep psychological insight with practical expertise to help leaders and teams navigate the evolving landscape of work.   You can link with Ari-Pekka Skarp on LinkedIn. You can read Ari-Pekka's Finnish writing at Mielen laboratorio and his English blog at Fractal Sauna. You can also find Ari-Pekka's previous Scrum Master Toolbox Podcast episodes on his guest page.

Cybercrime costs Americans an estimated $200 billion a year, and AI is supercharging it. The U.S. government's newest response is one of the oldest tools in the Constitution, one Congress hasn't used since the War of 1812.This episode covers letters of marque and privateers: their role in the American Revolution, how prize courts and bonds kept privateers from becoming pirates, and the White House memo that trends toward implementing a modern version for cyberspace.Sponsors:This episode is presented by Altitude, visit altitude.xyz/law to learn more about their global payments platform.Sponsors also include: The law firm Cahill Gordon & Reindel. Cahill is hosting Confluence 2026, its flagship emerging tech conference, in New York City on September 24, 2026. You can apply to attend here: https://www.cahill.com/confluence2026.Thank you as well to the Solana Policy Institute and the Hyperliquid Policy Center for supporting the podcast.Guests:Chris Perkins (President of Franklin Crypto at Franklin Templeton, Naval Academy graduate and Marine Corps veteran)Ari Redbord (Global Head of Policy at TRM Labs and former federal prosecutor)Michael Coates (CISO of the Solana Foundation and previously Twitter's first CISO)Camelia Lopez Shoemaker (Holland & Knight, former DOJ)Nelson Rosario (Rosario Tech Law)Timestamps:(0:00) The $200 billion problem(2:16) The Model T and the FBI(4:18) Pig butchering(7:03) History(7:50) The high seas and the internet(8:30) Marque vs. reprisal(11:35) American Revolution(14:08) Building a (private) navy(17:25) The Constitution(18:40) The Paris Declaration(20:34) Pirates or privateers?(22:12) The five-part system(22:40) Why government can't scale(23:30) The Fourth Amendment(25:26) Suspicious Activity Reports(28:23) Recent memorandum(30:40) The bond(32:34) The blockchain(33:49) Latest from U.S. gov't(34:56) The attribution problem(36:30) Who's involved today?(37:49) The Beacon Network(39:16) Pre-clearance and due process(41:10) Reporting cybercrime(44:26) International lawThis should be the internet's best explainer on letters of marque. You don't need to be a lawyer, historian or security expert to follow along.Disclaimer: This podcast is for informational and educational purposes only and does not constitute legal or investment advice. Views expressed by guests are their own and do not necessarily reflect those of their employers. Listening to this podcast does not create an attorney-client relationship.

The Good Medicine Confluence returns October 12–15, 2026, at the breathtaking Ghost Ranch in New Mexico.  In this special episode, I'm joined by cofounder Jesse Wolf Hardin to explore what makes this gathering so much more than an ordinary herbal conference. Now in its 18th year, the Confluence brings together herbalists, healers, teachers, makers and plant lovers from around the world. This year's gathering features more than 120 classes led by 50 teachers, along with plant walks, a tea tent, botanical meads, a healers market and the Plants & Fairies Masquerade Ball. Jesse also shares the history of the gathering, why its name has evolved over the years and the deeper meaning of "good medicine"—not simply something we carry in bottles or pouches, but something we embody through our lives and work. We're also giving away four free tickets! One grand-prize winner will receive a free year of HerbRally Schoolhouse and a HerbRally dandelion hoodie. Please enter only if there's a good chance you can attend the gathering in New Mexico. We hope you can make it!  ~Mason

Atlassian is raising prices, and if you use Jira, Confluence, or other Atlassian tools, you are probably asking the same question we are: What does this actually mean for me and my team?In this episode of The Jira Life, we are having a real conversation about the price increases, what is changing, who is likely to feel it the most, and whether the added cost makes sense.We will talk about what this means for admins, teams, companies, and the people responsible for making those “Do we really need this?” budget decisions. And, of course, we will share our thoughts on whether Atlassian is giving us enough value to justify paying more.No corporate spin. No complicated pricing charts. Just a conversation about what is happening, how we are looking at it, and what we think Atlassian customers should be thinking about next.The Jira Life=====================================Having trouble keeping up with when we are live? Sign up for our Atlassian Community Group!https://ace.atlassian.com/the-jira-life/Or Follow us on LinkedIn! / the-jira-life Become a member on YouTube to get access to perks: / @thejiralife .Hosts:Alex "Dr. Jira" Ortiz / alexortiz89 / @apetechtechtutorials Rodney "The Jira Guy" Nissen / rgnissen https://thejiraguy.comSarah Wright / satwright Producer:"King Bob" Robert Wen / robert-wen-csm-spc6-a552051 Executive Producer: Lina OrtizMusic provided by Monstercat:=====================================Intro: Nitro Fun - Cheat Codes / monstercat Outro: Fractal - Atrium / monstercatinstinct

According to LinkedIn’s Workplace Learning Report, 49% of L&D professionals say their executives are concerned that employees don’t have the right skills to execute their business strategy. And in busy, fast-paced industries, that gap is becoming a real problem. Because if the product, market, and go-to-market motion are all evolving at once, organizations are left asking the same question: what does it actually look like to build an enablement and a go-to-market model that can keep up and build those skills as they’re needed? Riley Rogers: Hi, and welcome to the Win/Win Podcast. I’m your host, Riley Rogers. Join us as we dive into changing trends in the workplace and how to navigate them successfully. Here to discuss this topic is Julia Townsend, Go-to-Market Enablement and Business Development Leader at DataRobot. Julia, thank you so much for joining us today. I really appreciate the time. Super excited to hear about the work you’re doing in this arena today. Before we jump in, though, I’d love if you could tell us about yourself, your background, and your role. Julia Townsend: Yeah, great. Thanks for inviting me, and Riley, really appreciate it, and excited to share more about what I do at DataRobot. So yes, I lead the go-to-market enablement and business development function at DataRobot, and if you’ve not heard of us, we are the only end-to-end agent workforce platform for secure, scalable, and production-grade agents. We are based out of Boston, although I am based in the UK, so we do have a global workforce. So when it comes to enablement, I own it globally. Plus, as I said, I also have the business development piece. Pretty interesting role that is fairly unusual within the enablement space. But day-to-day, what that means is a few things. So I run our enablement team, so within that, I have a BDR and sales revenue enablement specialist, I have a go-to-market readiness specialist, and I also have a technical enablement data scientist, which is brilliant. And then I also have our BDR team who are based in Boston. So a little bit about me. So prior to making a career change to working in enablement in the AI ML space, I actually did start out as a BDR myself, then I was an enterprise seller in the SAS observability market for many years. I’ve been with DataRobot for five years. I’ve been through quite a few different distinct eras of where we’ve been. And so started out very early with very hiring-heavy model. We did a lot of in-person boot camps, then we had a bit of a restructure within our business, which is very typical within the AI space. It’s very much up and down, so we had to rebuild the enablement in a much more of a leaner type of practice. And now within the AI agentic era, where the products in the market are moving so, so, so quickly, any of the other early enablement models that we’ve had, it’s really, there’s been a lot of changes. RR: And that leads us very well to kind of the first topic we were gonna touch on, which is the fact that change is abundant and everywhere, especially when you’re working in the AI space. So as you’ve been navigating the enablement journey for the last five years at DataRobot, what has shifted about how you think about enabling sellers from when you first started to what it looks like now? JT: So I guess the biggest shift when I think back to those years is moving away from a very calendar-driven compliance type model towards something that’s much more embedded where the seller is and is very continuous. In previous older years, we were very much all about completion tracking, which in hindsight looks a lot like compliance monitoring. So there were lots of weekly reports on showing who had or hadn’t finished a learning module. We were very big on the stick piece back in the day. And then I guess after we had our organizational restructure a couple of years back, our hiring volume dropped and the business model changed, and the need for big recurring cohort in-person boot camps really evaporated. So that meant that it forced enablement to start pivoting towards much more of a leaner targeted delivery. Tracking forward to today, enablement definitely lives now inside the same sorts of tools and the cadence that sellers already have. We use Highspot, we have the content management and the learning management modules. So that means we’re able to offer very much bite-sized content. So it means that rather than the field having a separate training destination that they have to go into, what we’re providing is very much just part of the weekly workflow for them to be successful. So they’re not visiting stuff occasionally, they’re always in it. So it’s less about building a big curriculum and running it once a year, and it’s much more about treating enablement like a live product. RR: We kind of talked about what it means for enablement as a function to be working amidst this change, but like you alluded to, DataRobot is a company in a market that never really stops moving. So what does that kind of environment demand from you? JT: It is really about speed because we operate in a very competitive environment. There’s a ton of companies out there that are specialist agent builders, they’re there to sell you some sort of agent to help you in a day-to-day life. But then there’s also companies at our level who are also providing platforms, and it’s very, the language is very similar, so it’s very hard to stand out. So when you have an edge with your product development, those USPs, you really have to get the sales team on board with it and talking that language, that new messaging, that new positioning to customers as soon as it’s been created. So speed is very important. What that means for enablement and content is that it has to ship in days or weeks, not quarters. For example, two Sales Plays that we launched last quarter, our Dell seller-to-seller play and our customer expansion play, they both went from kickoff, initial conception, to the field launch on very, very tight dated project plans with weekly status checks, which meant we could launch them in a matter of weeks, whereas in the past, it would take us a lot longer to do that. RR: I’d love to drill down into an example that you mentioned as you were speaking to the speed piece, in a recent instance where that became a necessity. So the Dell partnership. You shipped a Sales Play for it, you enabled the team quickly on the messaging. What did that look like to build, and can you tell us a little bit more about the scenario around it? JT: So DataRobot, we have a fairly new strategic partnership with Dell and Nvidia. As this was a new business drive for us, we had to create a very specific Sales Play that was focused on our reps engaging with Dell reps. And I think this is a little bit different maybe to other enablement functions or what we also did in the past, where plays tend to more focus on the sales process, so things like objection handling play, first meeting play. Whereas this play had a pipeline generation target attached to it, and so the play centered on building early-stage pipeline with Dell sellers, and it was very, very specifically around that. The Dell engagement with our Sales Play ended up being quite a few different types of enablement requirements that are stacked on top of each other for different audiences, but all around roughly the same timeline. So for example, we first launched the Dell seller-to-seller play. This was equipping our own sellers to target and partner with the Dell sales team. We launched this towards the end of Q1. But then coupled with that, we then did some event-specific BDR training. Our BDRs were going to some of these Dell networking events with the sellers and meeting them, and they needed to have the right narrative. They needed to understand some of the vertical specific use cases that would get a Dell seller interest. So we did lots of live role play practice with them to make sure they were able to do that effectively. But yeah, I guess to summarize that piece, it wasn’t just one enablement deliverable, it was four or five different audiences that were wrapped into one Sales Play, but it was very much focused on a pipeline generation target. RR: What was the timing like from we have this partnership to now I need to enable the field to I have enabled the field? How does that differ from maybe a year ago what that would’ve looked like? JT: Yes. So I guess a year ago, it felt like there was more luxury in terms of time, because the Sales Plays then weren’t so much aligned to a specific pipeline target. So if your Sales Play is more around objection handling or first meeting deck, that’s important, but it doesn’t quite have the same impact on what the business needs in terms of a north star metric that will translate into real business revenue and deals closed. So that was one thing that was different. In terms of the timeline, probably took us about four weeks. We really put the heads down with the team. We had a daily project call to work on the content, test it, and ship it out. We ran it like we would a product launch, so using the same sorts of methodologies around that with reviewing, iterating, building, testing, those sorts of things. So that was also different. We had a very tight project management approach to it, which enablement led. Because this was tied to a real revenue metric, it really had the ear of the CRO. It was his prerogative to drive this. So that also was super helpful, was having executive sponsorship all over it, encouraging the reps to lean in, and being the voice of enablement, helping us amplify what we did to help them, and that’s all because the Sales Play was attached to a real revenue goal. RR: Four weeks, that’s a pretty crazy turnaround, I imagine. Like you said, very heads down. So we’ve established then speed is the name of the game. I’d love to talk about how that shows up in training, because it used to be that it was very common to have standalone platforms, training existed in a specific location that sellers had to go to, had to go find, and it was hard to build. But now a lot of organizations are moving away from that very complex approach. So why do you think, with this context of speed in mind, that traditional training tactics aren’t quite working, and why organizations are shifting away. JT: It’s a real shift in how our industry is around learning development. There still is a place for it. In the sort of company that I work in, that older model hasn’t really worked for us. So I would say that you need something that flexes quickly when the business changes, and in our industry, AI and machine learning, as I said before, it changes all the time. So having standalone systems that fragment that seller experience, in our own house, for example, over the years we’ve had MindTickle, Confluence for reference, InPartner for partner region enablement. Each of those systems required quite specialist knowledge to build training content, do the certification, manage all those different pieces to make sure they’re accurate and up to date. It’s very difficult to do that in a fast-changing industry with very specific knowledge. You need to be able to scale it across an enablement team so that anyone in the team can be competent enough to build and design something when it’s needed. And in small enablement teams, which we have, in companies like ourselves, we need to be able to pivot and have more ownership across that. So we needed something that could really simplify and scale out learning and training that was accessible to as many people as possible. And that, for us, has been Highspot, and that’s why we invested not only in the content management side, but the learning management side of things. So it’s very easy now for the team to work on pieces that we need them to. It’s very simple and easy to use. RR: As part of that shift to agility, you brought on Highspot’s training capabilities to democratize building, to make it easy for anyone to create a course, to create a Role Play, to do whatever they need to do to train up a team. So what has that switch made possible? How has it helped you? What have you seen? JT: It moved us from a couple of years ago, from a small number of very specialized roles in enablement, to now much more of a, I guess you’d call it, a hub-and-spoke model. So our– someone in the enablement team like myself or one of the other team members builds out the general master course and certification structure within Highspot. But our subject matter experts in product marketing or product, et cetera, they can update the content directly. So dropping in an updated video, some deck messaging content that needs to be done, it can all be done in real time, which we really appreciate. It’s also shortened the time between deciding on the content and publishing it. So reviews, edits, uploading it to Highspot can all happen much more quickly, sometimes just in one conversation over Slack, which again means we can move a lot faster. The other bit is the easy governance piece, which is really important. So rather than having learning spread across lots of different platforms, now we have it in one platform. So the Highspot analytics piece around governance means that we can track zombie content on a rolling basis. In fact, we’re halfway through now another content cleanup and governance pass. So it means it’s easier for us to do that as well. The other area is the AI coaching side. That’s opened up a lot more for us on learning too. So you can author and do coaching in the same tool, which is brilliant. So we’ve got AI Role Play. All of that feedback can sit in the same space as the content itself. So building, practicing, certifying, all of those things, testing can all happen in one place. RR: I think that’s our goal, right. Everything is centralized. You can go from one part of the learning process to the next within a click. And if you feel like you need to go back, you can easily do so. Curious what kind of use cases you’ve been using Role Play and the AI coaching elements for? JT: Well, we had a lot of fun with AI Role Play. We launched it at sales kickoff back in February, and we just did a silly Role Play to begin. We did something like sell me the cowboy boots because we were in Nashville. But I think one of the projects, more serious projects, is around our new discovery deck, which is designed to support better qualification at early-stage pipeline generation. As part of this program in Q3, we’re also launching a new revised sales process and the structure of how we’re doing it. We do a mix of live and self-paced learning, so we’ll launch it live, through our Friday session. Then the seller is then encouraged to move to the self-paced piece, and we’re going for a multi-stage learning experience to ensure that reps don’t just know the pitch. So stage one is know it, then we go to stage two, which is see it in action. So we provide a gold-standard recording for reps to follow, to aim for a North Star. Then stage three is to do it, which is more the hands-on side of things. So reps need to submit recorded pitches. They need to participate in the interactive AI Role Play that we set up for them. All of that is shipped within the Highspot Sales Play kit, so the rep has one place to go before and after the discovery call. RR: One of the other priorities I know we talked about in terms of training was onboarding. So knowing that was an early test of this new way of training, how has that changed for you? JT: Yeah, for sure. So past was very much in-person, multi-day boot camp model, and that was paired with these compliance, weekly completion checks. But then when hiring started slowing down, that model didn’t work for us anymore, so we replaced it early on with much more of a self-paced approach. So now it’s self-paced, but it’s very tightly tracked through a four-week ramp-in period. So you have a day-by-day, week-one-to-four tasks, basically things like email signature, tool setup, but then coupled with things such as the welcome video from our CRO, company go-to-market strategy content type things, and then the sales-based specific courses that we want them to do. They get paired with a sales mentor as well as an enablement partner. Basically, we provide– although it is self-paced, we still bring that personal coaching, but it’s all driven through Highspot. All of the pieces for the onboarding are driven through there. RR: Now, we’ve heard a little bit about how training is structured, and we’ve talked a little bit about how you don’t want to be compliance testing of did you do it. But once training is built and launched, you do still have to get folks using it, getting folks practicing, and getting them internalizing the learning that you’re providing, and that’s hard. So how are you thinking about what AI makes possible on that side of the training function? JT: So the first thing that comes to mind is the AI Role Play feature. You know what it’s like. Reps, myself included, it’s horrible doing Role Plays with managers and peers because of that social pressure aspect. There is space for it at sales kickoff and fun experiences. But if you’re going to continuously practice, you wanna do that in a safe space. The AI Role Play really is the way to go. In the past, it would’ve been a heavy lift for enablement, so we would’ve had to have listened to everybody’s recordings, manually graded them, sent feedback continuously, which is hard with a small team. With AI Role Play and features like that, it means it’s a lot quicker, and it’s easier now to have a baseline to track things like pace, objection handling, how someone’s told a customer’s story, have they hit on the key points of the messaging we want them to do? So it’s a lot easier now. With the AI Role Play feature, sellers get that automated feedback. They get given that immediately right after they practice. They don’t have to wait days for enablement to listen or their manager to then review it. It’s all there. So I’d say that’s a really big change to how coaching happens. So reps still get in-person coaching with their sales lead or with an enablement person, but it’s not the same as having you practice something and then immediately getting the feedback back. That’s been a good change. Some of the team attended a, I think it was a roundtable workshop with Highspot recently around skills in AI Role Play, and that really helped us narrow what the skills should be. Before we were thinking about up to nine skills to build into the AI Role Play. But after some coaching, we were told that up to three would be best, so we’ve rethought how we do that. So now it’s just a lot easier for enablement and sales leaders to offer coaching because it’s done, some of it is done through the AI Role Play, and it means it’s continuous rather than just happening again once a quarter. RR: Have you seen any change in either the way that sellers engage with training because they have this lower stakes opportunity to try, try again, fail, try again, succeed? And has it, on the enablement side, saved you time? Curious, both sides of the equation, how has that worked out for you? JT: It saved the enablement team a ton of time. As I said, having to go through lots of reps’ recordings and manually listen to them, pause it, check the rubric, come back, what did they say, go back again. It’s very time-consuming to do, and it adds a lot of pressure to the enablement team and also to the sales leaders as well. They’ve got a large sales team. And enablement is pushing out this stuff they need to be certified in. It makes it quite difficult. So there’s been a big time saving there for sales leaders, but also for enablement in how we assess reps. Then also having that standard baseline. So before, you’re coming at it from your own biases in how you feel that day and how you listen to someone’s submission, whereas with the AI piece, it doesn’t work like that. So it’s always assessing at the same baseline, which is great. In terms of reps engaging with training in general, it’s definitely helped, for sure. As I said, we offer bite-sized training that is self-paced, and reps can use that just in time when they have the requirement for that piece of training, which is helpful. The AI Role Play just extends that further. It gives them just the chance to practice things before they go into the wild. RR: On a broader scale, you’ve made this shift, you’ve created these programs that fit every angle of training and skill development into one place, and you’ve rolled it out in a number of different programs. What sort of impact have you seen from this shift in how you approach training, all up? JT: So definitely the confidence one. The go-to-market team sentiment is trending upwards, which is great. So our recent company-wide EFPS in June was our highest to date, and it had a four-point jump month over month, which is good. And specifically, a driver was called out as learning development skills related to generative AI, so that’s a great one. And then secondly, as I mentioned before, we talked about that Dell Sales Play. So enablement were held to a pipeline creation bar, not just training delivered there. And as we look back and start looking at the quarterly business reviews, we can see, working with the rev ops team, that we’re definitely hitting, overachieving, the pipeline goal set by our CRO, which is great. So yeah, two really good signals. RR: I imagine that must have felt quite nice to look at the results of that survey and see the work that you’re doing called out as a key lever for improving confidence. So bravo to that. Hearing that you have these two measurable signals, you’re seeing that it’s working. The shift has been positive for both your team saving time and the sales team having a lower stakes way of engaging before, as you said, they go out into the wild. For anyone who’s looking at their training setup and is going, “I wonder if there’s a different way I can do it,” what would you want them to hear? JT: Avoid acting like an academic institution, and start acting like an agile product team. So we know that sellers don’t really want 45-minute courses. I don’t want that. They want to have the minimum viable capability just in time required to find and win their next deal. That’s really important. So what we’ve learnt, and industry best practice as the trends are starting to emerge, is to embed that learning directly into their workflow. So meet the sellers where they are. Empower the enablement team to build quickly, give them the tools to do that, the confidence, the buy-in, and then measure the success through things like conversation quality, pipeline creation conversion. That’s how you’ll see the results. RR: Julia, thank you for taking the time to chat with us today. This was wonderful. I think for anybody who’s looking to modernize their training or just reimagine, this will be super, super valuable. To our audience, thank you for listening to this episode of the Win/Win Podcast. Be sure to tune in next time for more insights on how you can maximize go-to-market success with Highspot.

Photo: Alaska Native Medical Center in May 2026. (Courtesy Alaska Native Tribal Health Consortium) The Indian Health Service officially handed ownership of the state’s biggest tribal hospital, the Alaska Native Medical Center, to the Alaska Native Tribal Health Consortium, as Alaska Public Media’s Rachel Cassandra reports. The transfer happened on August 24, according to the consortium. ANTHC CEO Natasha Singh, a Stevens Village tribal citizen from Fairbanks, says the transfer is the result of decades of advocacy. “This marks a historic achievement. It advances tribal self-determination in healthcare, and it’s achieved through the direct advocacy by Alaska tribal leaders.” Singh says, beyond practical implications, the symbolism of ownership is powerful. She says it is rare that tribes truly have self-governance over something so critical to their lives. “You don’t see it in management of our traditional territories or our fish resources. You don’t see it in education and public safety, but you see it in healthcare. Having this ability to control our future is allowing us to address the historical impacts of colonialism.” Singh says the hospital endured decades of underinvestment from the federal government and the transfer will allow the hospital to pursue funding only available to tribally owned facilities. Wilson Justin is a shareholder of the Ahtna Regional Corporation and has advocated for the rights of Indigenous people in the health care system since the 1990s. He says the ownership transfer is momentous. “It’s been a long wait, and I really appreciate the fact that it’s finally occurring. We’ve been waiting for it for half a generation, basically.” He says he hopes that the transfer allows the hospital to strengthen healthcare for Indigenous Alaskans across the state, especially for smaller tribes. The Little Colorado River, a tributary of the Colorado River, flows during the springtime through the Navajo Nation near Cameron, Arizona. (Photo: Gabriel Pietrorazio) The Navajo Nation Council has taken a major step toward protecting one of its most precious water resources. KJZZ's Gabriel Pietrorazio has more on the recent measure that formally recognizes the Confluence – where the Colorado and Little Colorado rivers meet – as a sacred site under tribal law. Doing so formally documents what Navajos already know – the spiritual and natural significance of where these two life-giving rivers converge. This information may be used to potentially deter future commercial development by industries like hydropower or dams. Erik Stansfield testified on behalf of the tribe's Historic Preservation Office. “When that comes forward, we can show what impairment of those resources look like.” He likens the Confluence to its council chambers, which is listed on the National Register of Historic Places. “Like the murals in this room, changing that would be an impairment to the sort of historical and cultural importance of this place. It’s very much the same with the plants and animals, water quality and offerings that have been made at that place. We detail that out, and that helps us kind of defend this area.” Ratified Indian Treaty 70. And on this day in 1815, leaders from eight Native Nations signed the Treaty of Spring Wells with the United States near Detroit. The agreement formally restored peace following the War of 1812 and returned certain rights and possessions Native Nations held before the war. The treaty involved the Wyandot, Delaware, Seneca, Shawnee, Miami, Chippewa, Ottawa, and Potawatomi Nations. Get National Native News delivered to your inbox daily. Sign up for our daily newsletter today. Download our NV1 Android or iOs App for breaking news alerts. Check out today’s Native America Calling episode Tuesday, September 8, 2026 — Life after a wrongful murder conviction for Santiago Ventura Morales

Vaults might be finance's next trillion-dollar opportunity. But what are they? How do they work? What regulation might apply? You'll hear from the creator of crypto vaults, Andre Cronje (Flying Tulip, Yearn), alongside builders Adrian Cachinero Vasiljevic (Steakhouse Financial) and Charles St. Louis (Ethereum Foundation). You'll also hear from SEC Commissioner Hester Peirce and top lawyers Lewis Cohen (Cahill), Tuongvy Le (Veda Labs), Rodrigo Seira (Cooley) and Linda Jeng (Aave). Thank you to the presenting sponsor of this episode, Altitude (altitude.xyz/law), a payments platform for the next generation.This should be the internet's best podcast on vaults. You don't need to be a lawyer, developer or finance expert to follow along. Timestamps:(0:00) Intro(4:27) What is a vault?(9:34) History of onchain vaults(11:55) The first vault, with Andre Cronje(21:05) The SEC's early interest(22:30) Investment contracts and Howey(31:28) Notes and Reves(37:10) The strategist(48:54) The curator(58:30) Investment company?(1:12:40) Investment adviser?(1:20:00) Separately managed accounts(1:30:30) Custody rules(1:55:43) What's next Thank you as well to the law firm Cahill Gordon & Reindel for sponsoring this podcast. If you'd like to join Cahill's flagship emerging tech conference, Confluence, you can apply here: https://www.cahill.com/confluence2026.Thank you as well to the Solana Policy Institute and the Hyperliquid Policy Center for supporting the podcast. Nothing in this podcast is legal or investment advice.

This podcast is made possible by our listeners and viewers. If this show has brought you value, you can support it by becoming a member of The Way Forward, our platform designed to help you find the health and freedom community (people, practitioners, schools, farms, and more) near you. Your membership directly supports the podcast and the work we do.Click here to order The Primordial Code. Use code TWFSHIP for free shipping in the USA. When Brian Costello lost everything, he was able to understand what true healing is.Brian Costello is the author of The Primordial Code, a former CrossFit gym owner, and a multi-time national beach sprinting champion who rebuilt his life from rock bottom into something he never planned for.We open with the body, because the way you're sitting right now is training how you'll walk into every conversation this week. Brian throws light on the root, heart, and crown, and how couches and cushions mask the signals your spine has been sending for decades. He shows why back chain dominance changes how people respond to you before you even speak.From there we move into his story. A 250-pound snatch PR started the collapse, followed by a surgery he wouldn't do today. His wife had an affair with a close friend, and for nearly two years anger was the only emotion he could reach. A 30-day fast with his wife reset them both. Plant medicine and a move to Costa Rica followed. His book came through once he stopped trying to write the one he thought he owed people.His brother Danny also gets real time here. Danny was vaccine-injured at 18 months and spent 20 years without a voice, but at age five he had a dream that his answer would come in the form of a board… You'll want to hear this one!You'll Learn:[0:00] Introduction[10:37] Fully taking up your space as physical and spiritual practice[26:29] How the GOATa blueprint decodes durable human movement[36:06] Primordial Flow turns the floor into a conversation with the body[1:00:31] How CrossFit and a betrayal led Brian to rock bottom[1:16:20] Finding a way out one bite at a time[1:23:17] The 30-day fast that redefined abundance and healing[1:31:04] Ancient healing discoveries that led Brian to write The Primordial Code[1:49:58] The Primordial Code's fictional society and the real Confluence community it's inspiring[3:03:17] Brian's brother, a nonverbal speller, and what spellers can teach usRelated The Way Forward Episodes:The Lies About Anarchy & Politics The Media Want You To Believe with Catherine Bleish Bonandin | PodcastResources Mentioned:All We Know… ...Is In The Air by Danny Costello | BookMy Words Are My Voice | PodcastFast Like A Girl by Dr. Mindy Pelz | Book or AudiobookFind more from Brian:Brian Costello | WebsiteThe Primordial Code | Audio SeriesFind more from Alec:Alec Zeck | Instagram | XThe Way Forward | InstagramDonate to The Way Forward here.The Way Forward is Sponsored By:Want more crypto insights and a community to back you up?Join the Crypto Freedom Academy today. It's 100% free and designed to help you master the markets.

Commissioner Hester Peirce joins the podcast to discuss Regulation Crypto Assets, as well as secondary market trading, DePIN and vaults. If you haven't listened to the full Reg Crypto explainer, that's episode 207. This episode is presented by Altitude. Visit altitude.xyz/law to learn more about their financial operating system.Timestamps:0:00 Intro2:22 Secondary transactions3:23 Promises and representations5:05 Essential managerial efforts8:27 Regulatory arbitrage10:29 Form TR16:59 Existing token projects and Form TR18:27 Compliance costs21:48 Secondary markets24:12 DePIN27:02 Vaults35:31 Accredited investors40:25 Tokens and equityThank you to the other sponsors of this episode: Cahill Gordon & Reindel, the Solana Policy Institute and the Hyperliquid Policy Center.On Thursday, September 24, 2026, CahillNXT will host Confluence 2026, its flagship conference, in New York City. This year's theme, Leading the NXT Frontier, brings together regulators, institutional investors, founders, policymakers and industry leaders to examine digital assets, market structure, regulation and the emerging technologies transforming financial markets. To register your interest, email events@cahill.com. Newsletter: Stay updated on emerging tech law for free at lawofcode.fm. Any feedback on this episode? Or how to improve the podcast? Click here: https://forms.gle/yFFN66e8iy8shQkAA Disclaimer: This podcast is for informational and educational purposes only and does not constitute legal or investment advice. Commissioner Peirce's views are her own and do not necessarily represent those of the SEC or her fellow Commissioners. Listening to this podcast does not create an attorney-client relationship.

BONUS: How AI Took the Boring Out of Agile Coaching—Where Scrum Masters Should Actually Start, With Michael Dougherty Today we speak with Michael Dougherty — "Agile Mike" — about how a 30-year veteran of solution development and product leadership made AI a working part of his Agile coaching practice. Michael walks us through the journey from early ChatGPT curiosity, to documentation as the first real win, to the personal-passion project that built his comfort with the tools, and finally to where every Scrum Master should start: the retrospective. From Curiosity to Toolbox: A Slow Burn That Started With User Stories "I tried, and I thought it sucked at that. I'd rather write this by hand."   Michael's AI journey started in late 2022 with ChatGPT — like most coaches, he tried to make it write user stories and acceptance criteria. It didn't work. The output wasn't usable, and he went back to writing them by hand. What looks like a failure was actually the first lesson: not every coaching task is a good fit for AI, and the way to find out is to try. He kept experimenting in the background through 2023 and 2024 — Claude, Grok, Perplexity — while keeping personal use and business use cleanly separated. The real shift came at the Department of Homeland Security, where he sat alongside ex-Googlers, ex-OpenAI people, and an Anthropic alumnus on the team building DHS's internal chatbot. Watching what AI could do inside a heavily-protected enterprise environment changed his frame: this wasn't a productivity hack anymore, it was infrastructure. The Boring, Tedious, Now Quicker: Documentation as the First Real Win "AI has taken all those boring, tedious tasks and made them quicker, more valuable, and more fun to boot."   The first AI practice that stuck was documentation — the part of Agile coaching nobody enjoys but every client demands. Michael had spent years writing SDLC docs from blank pages, and his co-author on Shift: From Product to People used to look at empty docs and ask for help getting started. AI removed that blank-page problem. He'd give the model the team context, the client's documentation requirements, and a template — and get a draft to edit. He stayed in the loop as the human, bringing context, judgment, and final shape, but he no longer started from zero. The same shift happened with presentations: instead of fighting PowerPoint spacing, he tells the AI to drop content into a template and gets back a formatted deck. Small tasks, but multiplied across a coaching week, they bought back real time. The Personal Project Trick: Find Something You Love First "Find something you have a passion with, something you really enjoy. That made me feel comfortable with AI so I could do more."   Michael's strongest advice for coaches who feel intimidated by AI isn't to start at work — it's to build something for yourself, in a domain you care about. His own example: the Nordic Metal Tour Tracker, a personal AI agent for tracking heavy metal bands across Northern Europe (and Spain and Portugal). It plays music. It maps tours by country. It exists purely because he loves heavy metal. The trick isn't the tool — it's that working on something he actually cared about removed the fear and built the muscle memory. Once the comfort was there, transferring it to work became a small step instead of a leap. He references the rundown AI as a daily input that keeps him aware of how others — even people in their 80s — are using AI for everything from gardening to balanced school lunches. A Week With Preppy Paul: Agents, Connectors, and the End of Inbox Drudgery "Preppy Paul gives me a list of all my meetings today and the top three items I should have on each one — based on my notes, my email, my calendar."   Michael's current weekly routine looks nothing like his Agile coaching week from three years ago. He works at Zion Cloud Solutions as a Tier 1 Google AI partner, splitting time across three roles: about 20–30% traditional Agile project management (coaching a Scrum Master on a state of Illinois project), and the rest as an AI Growth Engineer and AI delivery lead on short 4–6 week projects with 3–5 person teams. The backbone is Google Gemini Enterprise — a platform that lets him run Claude, ChatGPT, or any major model behind enterprise protection (Model Armor, the SAIF framework). Inside it, connectors pull in Gmail, Outlook, Calendar, Confluence, Jira, Slack, Teams, monday.com, and thousands of other tools — each agent inherits only the permissions the user already has. A few practical patterns he runs every week:   Preppy Paul — an agent that prepares him for the day's meetings, pulling top topics per meeting from his notes, email, and calendar. Meeting-to-email — AI records and summarises every meeting, and he asks the agent to draft updates to specific team members directly from the summary. LinkedIn drafts in his voice — hashtags, formatting, and tone all match his style; he edits lightly and posts.   The pattern across all of these: the agent isn't replacing the work. It's removing the friction between the meeting and the next conversation. The Retrospective: The Best Place for Every Scrum Master to Start "Don't have it be the same darn Jira spreadsheet of the same darn three questions every time. Go to AI and eat your heart out with it."   When pushed for one thing a Scrum Master could try tomorrow morning, Michael was clear: the retrospective. It's the one Scrum event where creativity is usually welcome, where format experimentation has a low cost, and where teams are already expecting something new. Ask AI for retrospective formats that fit the team's current situation — review five or ten options, pick one, run it. The signal you watch for within a week is double: how many improvements the team generated, and how many of them actually got done. The simpler signal is the team's reaction. If at the end someone says "that was fun" — and then you tell them you used AI to design the format — you've shown the team what AI is good for without a single slide or framework. It's the smallest possible experiment with the largest possible upside. Experiment Like a Scientist, Not a Spectator "Don't be afraid of it. Try whatever you can with it. Have the viewpoint of a scientist."   The trap Michael sees most coaches falling into is curiosity without commitment — reading about AI, watching demos, talking about it, but never building anything. His framing is the opposite: be a scientist. Run experiments. Some will fail (his user-story attempt did). Some will quietly become essential (documentation did). The way to find out which is which is to keep trying, in low-stakes contexts, with both personal projects and small work experiments. The coaches who'll be useful to their teams in 18 months aren't the ones who can describe AI accurately — they're the ones who've built enough small things to know what AI is bad at, what it's surprisingly good at, and where the human in the loop has to stay.   About Michael Dougherty   "Agile Mike" has over 30 years of experience with solution development and product leadership, working in nearly every IT role that exists and literally hundreds of companies during his career. Michael has taught multiple Agile courses to over 1000 people, spoken at multiple events and podcasts, written dozens of blogs, and has been recently serving the US Government. He is the other co-author of Shift: From Product to People.   You can link with Michael Dougherty on LinkedIn and find more about his work at shiftingpeople.com and AP8XGlobal.com.

On today's newscast: The Navajo Nation Council has designated the Confluence of the Colorado and Little Colorado rivers as a sacred site, the FBI has set a minimum $25,000 reward for help solving some cold cases in which people went missing or were killed on tribal lands, the Navajo Nation Council unanimously voted to remove the tribe's acting attorney general Kris Beecher, and more.

The Navajo Nation has passed legislation designating the confluence of the Colorado and the Little Colorado rivers near the Grand Canyon as a sacred site.

Every legal dispute comes down to a judgment call made with incomplete information — and wherever there's judgment, there are mental shortcuts quietly shaping the outcome. Host Dr. Laura Scherck Wittcoff sits down with Tricia Schafer, a full-time neutral who mediates and arbitrates cases nationwide, ahead of her TechTainment panel on implicit bias in tech-driven mediation. Together they unpack what implicit bias actually is (a normal function of the human brain, not a character flaw), why it matters most in entertainment and intellectual property disputes where there's rarely one objectively correct answer, and the practical, sometimes surprising strategies practitioners can use to design bias out of a process instead of pretending it isn't there. Tricia Schafer, Tricia Schafer Dispute Resolution PLLC: A full-time neutral and former litigator with 31 years of experience across all aspects of commercial controversies, Tricia is known for connecting people and concepts to outcomes that transcend the sum of their parts. She mediates and arbitrates cases nationwide, both privately and through the American Arbitration Association, handling commercial, real estate, health care, and consumer matters, and was recently approved as a mediator for the United States Postal Service. Based in Arizona, she also volunteers with the state court system in civil and probate matters and offers reduced-rate work to select Arizona nonprofits. She first attended TechTainment in 2024 at a friend's suggestion — arriving knowing exactly one person and leaving with roughly two dozen new friends — and has been a loyal follower since. At this year's conference, she co-presents on implicit bias with longtime friend and colleague Maria Crimi Speth, a partner at Jaburg Wilk in Phoenix and a career intellectual property litigator. What is TechTainment? TechTainment is an annual, one-day conference produced by LAIPLA, now held in partnership with the Sandra Day O'Connor College of Law at Arizona State University (ASU) at ASU's California Center in downtown Los Angeles. The conference brings together leaders in technology, entertainment, business, academia, and law to discuss the issues reshaping every industry, long before those issues become mainstream news. This year's conference: Friday, October 16, 2026, at ASU's California Center in downtown Los Angeles Tricia's panel: "Implicit Bias in Dispute Resolution and Mediation", co-presented with Maria Crimi Speth of Jaburg Wilk What implicit bias actually is: Implicit bias is not prejudice or intentional discrimination. It's a mental shortcut the brain uses to make decisions under incomplete information, limited time, or uncertainty — a normal part of being human, not a character flaw. Tricia's example makes it concrete: a Mercedes pulls into your driveway versus a beat-up pickup truck, and you've formed a judgment about the driver before you've seen them. It doesn't matter until you have to help that person resolve something that matters in their life. Why "neutral" is a noun: Tricia explains that "Neutral" is the catch-all for someone who serves as both mediator and arbitrator — a private-pay, secure way to resolve disputes outside of court. She also walks through the tradeoffs of arbitration: it's faster, it's private, it never becomes public record, and critically, you get to choose your decision-maker. File in court and you may draw a judge who spent 20 years in family law and just moved to the civil bench. Through the American Arbitration Association or another provider, you can ask for an environmental lawyer, an engineer, or a water lawyer. The cost: you pay your neutral's hourly rate, and there is almost no right to appeal. Positions versus interests, and the last orange in the house: Tricia walks through the foundational mediation exercise: two kids fighting over the last orange, and a parent's instinct to cut it in half. The better move is to ask each child why they want it — one is hungry, the other needs it for a science project — and suddenly there's a solution that makes both of them happy. As she puts it, a position is what you say you want and an interest is why you want it. Do you really want the money, or do you want the security of knowing you can keep the house? The related insight: "No" is never permanent. "No simply means I'm not going to change my position based upon the available information that I have right now." Designing bias out of the process: Tricia describes wanting software that would strip law firm letterhead off position statements before she reads them, and assign parties fake names, so she isn't forming judgments about counsel or making assumptions from the ethnicity of a surname — the same logic behind employers removing photos from resumes. She also shares a technique she uses now: she dumbs the fact pattern down, renames everyone, and spends half an hour working through the dynamic with an AI assistant. Mr. Jones and Mr. Smith fighting over a commercial building becomes Bob and Larry fighting over a pickup truck. The AI has no idea who anyone is, which is exactly the point. Where implicit bias shows up in entertainment and IP: Assumptions about how long creative work should take a human, and whether AI could do it faster. Assumptions about what a market wants and will pay for, made without consulting anyone who lives and works in that market. Confirmation bias in data used to argue for one direction over another. And the structural disadvantage facing independent creators, who often lack the resources to register, protect, or aggressively enforce their intellectual property — so their disputes get read as less significant. Tricia names the persistent disconnect between the rooms where decisions get made and the people actually watching and streaming the content. Dispute resolution is dispute prevention: One of the episode's most quotable lines, and the practical center of Tricia's advice. It's not if a dispute arises, it's when. Mediation clauses are now common in contracts — and, Tricia notes, most people don't realize those clauses are negotiable in any contract involving personal services or securing talent. "We'll mediate before we arbitrate before we litigate" means very little on its own. For how many days? What kind of mediator — an entertainment lawyer at $1,000 an hour, or a court-appointed one? In person or on Zoom? In good faith, and what does good faith mean? She points listeners to the sample clause language published by the major providers, including the AAA's ClauseBuilder tool, and notes you can even name the specific mediators you'd accept. Strategies for creators and practitioners without deep pockets: For anyone younger, newer, or under-resourced walking into a negotiation: go in without defensiveness, but look in the mirror first and ask what the other side is likely to assume about you — then stay ahead of it. On the other side of the table, for the corporations and the streamers: you know statistically what your audience does, but you don't know what's in their heads or why they're watching what they're watching. Follow the data, and also build a team of decision-makers with genuinely different perspectives. Normalizing bias instead of denying it: Tricia's hope for what people take away from her session: bias is not bad. Bias is not negative. She'd like to see the same shift the culture has already made around therapy and health tracking — from something you'd never mention to something you say out loud. Her image of what that looks like in practice: a mediator who can say "I feel like I'm getting a little biased from this room, I need to take a five-minute break." Laura's response: when you pretend it doesn't exist, it creeps in anyway. How to Get Involved Register and learn more: LAIPLA.net/techtainment Pricing: Multiple tiers are available, including discounted rates for in-house attorneys, law students, LAIPLA members, and ASU alumni Attend: The conference includes breakfast, lunch, and extensive networking opportunities Connect with Tricia: TriciaSchafer.com Connect with Small & Gutsy Website: SmallandGutsy.org Email: Laura@SmallandGutsy.org Do you know a nonprofit or social enterprise doing incredible work? Send them our way!

Send us Fan MailWe catch up with Lark Elliott one year after opening Tuxedo Falls to learn what it takes to turn a rare waterfall property near Asheville into a high-demand glamping retreat. We dig into design choices like open air soak tubs, heated toilet seats, brutal infrastructure realities, and the operating and marketing decisions that drive reviews, pricing power, and direct bookings. • How exceptional land and location can do your selling • Choosing Bushtec safari tents and building true treehouses around living trees • Guest experience details that lift reviews and return visits • The hidden horizontal infrastructure budget: stormwater, roads, rock, wells and septic • Zoning, utility availability and fire access as early deal killers • Financing a proof of concept while building infrastructure for future units • The whiplash shift from builder to operator and what to fix first • Handing off social media marketing and using paid social to find the right guest • Dynamic pricing and revenue management trade-offs at different unit counts • Leveraging tourism board PR and avoiding costly OTA surprises • Mentoring, books and practical habits that make operations saner • Using travel insurance messaging to reduce cancellation pain Check out tuxedofalls.com or reach out to lark at lark@tuxedofalls.comWe work really hard to bring you the best content from the best operators in our industry and we do it all absolutely free of charge. All we ask is that you consider leaving us a review on Apple Podcasts or Spotify so we can keep the momentum going. Simply go to the homepage of the podcast and scroll down till you see the stars. Thanks for your support and let's keep getting more people outside.Newbook - www.newbook.cloudInterested in learning more about Newbook? Book a software demonstration with one of their market consultants today and don't forget to mention you came from the Outdoor Hospitality Podcast to receive 15% off your Newbook subscription and your first month free. This offer is for Newbook Signature subscriptions only.This podcast is powered by Sage Outdoor Advisory, the industry leaders in feasibility studies and appraisals. 

You have spent years analyzing the intersection of retail, commerce, and organizational strategy. From your perspective, what are the biggest assumptions about modern commerce that leadership teams still have wrong?A lot of organizations continue trying to optimize individual channels while the market increasingly behaves as one interconnected commerce ecosystem. What do you think executives are underestimating about that shift?Many leadership teams talk about omnichannel maturity, but internally they are still operating through fragmented incentives, reporting structures, and budget ownership. What organizational tensions are becoming most visible right now?One thing we are hearing more often is that commerce infrastructure decisions are now strategic decisions, not just technology decisions. How should executives think differently about platform architecture, data ownership, and ecosystem dependency?If you look out over the next three to five years, what do you think separates the organizations that compound advantage from the ones that slowly become operationally irrelevant?

En marzo de 2020, casi todas las empresas pensaban en cuándo volver a la oficina. Atlassian decidió hacerse otra pregunta ¿y si no volviéramos? Así nació Team Anywhere, una estrategia de trabajo distribuido diseñada para convertir la flexibilidad en una ventaja competitiva y no simplemente en una política de bienestar. En este episodio de Código Abierto analizamos el caso de Atlassian, la compañía detrás de Jira, Confluence y Trello, y cómo convirtió su propia forma de trabajar en un laboratorio para entender qué hace que los equipos funcionen realmente. Lo que descubrirás en este episodio + Qué es Team Anywhere y por qué Atlassian decidió hacerlo permanente. + Por qué el trabajo distribuido fue una decisión de negocio. + Qué descubrieron sobre flexibilidad, productividad y conexión. + Por qué estar en la misma oficina no garantiza trabajar mejor juntos. + Qué riesgos aparecen cuando el trabajo remoto no está diseñado deliberadamente. Suscríbete a Hackers del Talento si quieres más análisis reales de estrategias de talento. ______________________________________________________________________

In this episode, Confluence reviews the Asset Allocation rebalance for the third quarter of 2026, featuring a brief economic analysis and insights on asset class and security selection for the firm's Asset Allocation portfolios. Joining the podcast to recap the rationale for this quarter's changes is Kaisa Stucke, analyst and chair of the Asset Allocation Committee's quarterly investment meetings.

Finding and forging one's identity and purpose can be challenging enough. Doing that while also being a member of a marginalized identity living in a conservative milieu can add more complexity to this experience. For former state Senator Cole LeFavour, that was very much a reality. LeFavour chronicles their life in a new book, In the Arms of Mountains: A Memoir of Land, Love, and Queer Resistance in Red America. As Idaho's first out LGBTQ+ lawmaker, LeFavour explores a journey through gender, power, and rebellion against a reactionary system. When LeFavour was 11 years old, their parents uprooted the family and purchased a ranch in the rugged landscape of Idaho. Cole and their sister came of age in the remote backcountry, learning about themselves and the world in the wilds of a rural environment situated within a larger system of inequality. By the time they left for college, Cole was starting to grapple with their queer and nonbinary identity and was concerned about what lay ahead in their red home state. In the Arms of Mountains traces the contours of Cole's life—from formative years connected to the land to working as a fire lookout and lone ranger, to joining anti-apartheid protests, and later becoming Idaho's first openly queer legislator. LeFavour's memoir aims to be a cautionary yet inspiring story of the power of political resistance in places you least expect it. Cole Nicole LeFavour is an activist, an award-winning journalist, and a writer whose stories and essays have appeared in The North American Review, Idaho Wilderness Considered, Confluence, Sawtooth-White Cloud, among others. In 2004, LeFavour became the first openly LGBTQ+ member of the Idaho Legislature, serving as an Idaho State Senator for 8 years and leading multiple acts of civil disobedience at the State Capitol. Buy the Book In the Arms of Mountains: A Memoir of Land, Love, and Queer Resistance in Red America (Hardcover) Elliott Bay Book Company

This week, Art Hounds is devoted to the Minnesota Fringe Festival. More than 100 individual plays will run on stages across Minneapolis Thursday through August. Fringe is the largest non-juried theater festival in the U.S.; amateur and professional theater makers alike pitch shows that are chosen by lottery. Each show must be fewer than 60 minutes, and there are up to seven slots a day for shows to run. For many, it's the wild diversity of shows itself that is the draw. Performances this year span from musicals to improv, dance to clowning, one-person shows to full casts. Most performers are local, but there are visiting performers who travel to Minnesota to take part. Each show runs five times throughout the 12-day period. Interested in going? There are ticketing options for single shows as well as a range of multi-show options. Check out the shows and ticketing options on the Minnesota Fringe website. For those attending with families, each show page includes recommended minimum ages and content warnings. And while it's hard to select just one or even a few shows to highlight, we asked Art Hounds to do just that. Tech: What could go wrong? Actor Taj Ruler recommends the improv comedy show, Tech. Set on the night before an opening Fringe show, anything can and will go wrong in this ensemble led by Mike Fotus at Strike Theater. "I'm excited because I think it is a stellar cast of improvisers, the best in the Twin Cities. So I think you're in for a good time, and it'll be different every time for the five shows that they have." Watership Down: An authorized musical based on the classic novel Actor and writer Isabella Dunsieth is looking forward to seeing "Watership Down." The musical is based on the 1972 novel by Richard Adams; Rachel Ropella and Timothy Kelly worked with Adams' estate as they adapted it for the stage. Bee Davis of Minneapolis wrote the music and lyrics. The novel tells the story of a band of rabbits on a perilous journey to find a new home. This show by Melancholics Anonymous runs at the Rarig Stoll Thrust Theatre. "I can't wait to see what they do with this. 'Watership Down' with Melancholics Anonymous is a little something different for that company. Typically, they're doing silly tongue-in-cheek coming-of-age type stories. Last year at Fringe, they did Joan of Arc for Miss Teen USA, which was, you know, very funny, but also really grounded in community and girlhood and caring for others. It was very beautiful. I feel like Watership Down is maybe a little darker for melancholics, and so I'm very interested to see how they make that tonal shift." And three more ... Sarra Beckham-Chasnoff and her wife treat the Fringe as a staycation, taking time off work to see a show in every time slot over the next 12 days. Pressed to name a few shows she particularly wanted to see, she cited "Watership Down" and "Tech," as well as these: Bay Creek by the Miller Company, written and performed by Derek Lee Miller, at the Barbara Barker Center for Dance "I've seen this show performed at another fringe festival and at the Twin Cities Horror Festival, and in my mind, I forget that he's the only person on stage. It's creepy and well-acted, written beautifully, and has some surprises in it." A Confluence of Magical Arseholes by the Winding Sheet Outfit, at Rarig Stoll Thrust Theatre. "Winding Sheet Outfit have always done beautiful productions that really highlight why coming to a theater is so much different than going to a movie or listening to music. They often have music in their performances. Their presentations are beautiful, and I always come away feeling moved and learning something new. It appears that this one may be more comedic, and I'm really excited to see how they weave comedy into their shows." Leave Room for Jesus by Hannah Wydeven, at Barbara Barker Center for Dance "It's an improvised comedy musical where Hannah Wydeven takes on the role of a pastor who believes that she is very charismatic and does a revival. Her hang-ups become very clear early in the show, and she, of course, uses some information that she gets from the audience. It's just a wild romp."

This podcast is made possible by our listeners and viewers. If this show has brought you value, you can support it by becoming a member of The Way Forward, our platform designed to help you find the health and freedom community (people, practitioners, schools, farms, and more) near you. Your membership directly supports the podcast and the work we do.You need to let God purify you, and you're about to find why. Garrain is one of America's top 25 personal development coaches, a bestselling author, and a speaker who has reached over 4.7 million people across 100 countries.When I invited him to Confluence, everything in his life was being stripped away. His business and investments were cut in half, and his identity was dissolving right along with them. In retrospect, he realized that's what it looks like when God purifies every part of your life that's out of alignment. He said yes anyway, and that trust became the thread of our entire conversation.We got into the reason he changed his last name from Jones, what really happened at a Los Angeles club with Britney Spears at the height of her career, and why he spent years avoiding the music he was born to create. He sang a song in this room; it shifted something in me I didn't know needed to move.If you're in the middle of a personal storm right now, this conversation is for you.You'll Learn:[0:00] Introduction [6:42] Why Garrain trusts the unspeakable world more than the human mind[14:59] How a lack of trust is really a mismanagement of energy[21:41] The Britney Spears story Garrain has never shared on a podcast before[28:55] The kind of trust it takes to know you are the eclipse[40:35] Michael Jackson as the prophet frequency and why he's back now [55:07] Why Garrain changed his last name from Jones to Asé [1:25:28] The Negro Slave Bible and the split of Christianity most people don't know [1:34:46] A trans woman on the train, the Charlie Kirk shooting, and the labels that keep us divided [1:46:27] Denied expression mutilates into sex, drugs, porn, and killing[1:58:19] The album Garrain calls the most impactful of all time[2:20:16] Big dreams require big excavation, and resistance comes with the ecosystemFind more from Garrain:Garrain Asé | Website Tribe of Creators | WebsiteChange Your Mindset, Change Your Life by Garrain Jones | BookFind more from Alec:Alec Zeck | Instagram | XThe Way Forward | InstagramDonate to The Way Forward here.The Way Forward is Sponsored By:Want to grow your podcast but not sure what's actually working? Podigy helps me produce The Way Forward. Take their free assessment to get clear on your next move—and a chance to win a call with their founder.Earth Runners: Reconnect with the earth's natural charge and move naturally by using code FWRD10 for 10% off here.New Biology Clinic: Redefine Health from the Ground UpExperience tailored terrain-based health services with consults, livestreams, movement classes, and more. Use code THEWAYFORWARD (case-sensitive) for $50 off activation.The Way Forward members get the $150 fee waived.Want more crypto insights and a community to back you up?Join the Crypto Freedom Academy today. It's 100% free and designed to help you master the markets.

#360: Assume your production systems go sideways at 3:00am. Your phone doesn't ring. You wake up to a clean incident report - the system caught the problem, fixed itself, and left a Slack note saying it handled things at 3:15. Would you trust it? Viktor wouldn't, not at first. Same as a new hire, a new tool, a new anything. Trust gets earned. A few months in, if it hasn't messed up, then maybe. So what's actually new? We had self-healing in decades past, and Kubernetes brings a crashed pod back without anyone awake to watch. Birol Yildiz, co-founder and CEO of ilert, puts the line where it belongs: the old stuff runs on predefined patterns - known problem, known fix, automate it. The new part is diagnosing a root cause nobody wrote a rule for and then knowing what to do about it. And no, ilert isn't training models on your data. The agent runs on foundational models from the frontier labs, feeds them the same context any SRE would pull - telemetry, recent changes, the health of your infra - runs the investigation loop, and hands you a root cause with the evidence attached. Then the real argument starts, and it's about knowledge. Viktor keeps circling the blind spot he sees at every company: the wiki, the runbooks, the tribal stuff nobody keeps current. Birol's answer is blunter than you'd expect from a guy selling this - dump your Confluence and your hundred stale runbooks into the agent and you cause more damage than results. Code is the documentation that's actually true. ilert's agent doesn't even read runbooks. It builds a live service topology straight from tracing data and rebuilds it when things drift. What happens when a bad incident month turns your $100 bill into $10,000 - Birol's answer is a credit budget with a human paged when you blow past it. Who's accountable when the agent makes it worse? Has to be a human. Agents are tools. You don't get to blame your AI coding agent for shipping garbage code, and ilert doesn't get to blame the model either. Trust is binary - five good runs and one bad one, and you strip its write access. But even in observe-only, the value is real, because the time sink in an incident was never the fix, it was finding the needle. Cut root cause from 45 minutes to a few. And the closer nobody wants to hear: if you skipped observability and fifteen years of homework, an AI SRE isn't going to save you. You can't skip the parts you skipped.   Birol's contact information: LinkedIn: https://www.linkedin.com/in/birolyildiz/ X: https://www.linkedin.com/in/birolyildiz/   YouTube channel: https://youtube.com/devopsparadox   Review the podcast on Apple Podcasts: https://www.devopsparadox.com/review-podcast/   Slack: https://www.devopsparadox.com/slack/   Connect with us at: https://www.devopsparadox.com/contact/

Here we are on July 22nd, two-ott-twenty six and I have for you a DBG from July 22nd, uno-nine-ninety five the title of which shall be: A Confluence of Corny Contestants We begin with the treasured DBG Theme. Players: Tony Nesbitt on the phone from parts unknown Jack Harte in Traffic Hope Schauer producing and playing in studio Paul from Dorchester, ONT Sonja in Newcastle, PA Jim from Lowell Bdays: Orson Bean Alex Trebek Danny Glover Albert Brooks Robert Dole Sparky Lyle NNVoS could use your support so please visit the links below for options. Ep 297, A Confluence of Corny Contestants, shucks its way to your ears in 3, 2 & 1. Buy Me a Coffee https://buymeacoffee.com/normnathan Patreon https://www.patreon.com/normnathanvos Castos https://norm-nathans-vault-of-silliness.castos.com/donate?_gl=1*12szy98*_gcl_au*NDc3NDU0Mzc1LjE3MjI4Nzc4ODk

What happens to intimacy, nostalgia, and creative power when a world-class filmmaker decides to step away from the camera and help reimagine their masterpiece for the live stage?  In this episode of TRUST ME I KNOW WHAT I'M DOING, I sit down with award-winning filmmaker, writer, and director Ritesh Batra. Celebrated globally for his masterpiece debut feature film, The Lunchbox, Ritesh has spent the last decade crafting incredibly delicate, human-centered stories. Now, he has brought that same quiet magic to the theater stage, serving as the book writer and co-lyricist for the highly successful musical adaptation of The Lunchbox.Ritesh shares unique process of rewriting a beloved indie film for a live theatrical medium. He shares why he deliberately avoided rewatching his own movie to allow a fresh, organic confluence of creative energy to take over with his collaborators. He also shares his personal philosophy on "artistic fingerprints"—explaining why true success in any creative field requires leaving your own distinct, irreplaceable mark rather than chasing past commercial formulas or letting executive gatekeepers dictate the narrative.  Ritesh shares insights on:• Nostalgia & Friction: Why he prefers focusing his storytelling on the compelling friction of characters "left behind" by rapid societal changes rather than those keeping up with them.  • Stage vs. Screen Intimacy: How the live stage provides a unique canvas to showcase unspoken connection and stillness in ways the cinema camera cannot.  • The Fingerprint Philosophy: Why elite artists must own their distinct perspective, and how to protect your creative power in a system obsessed with past commercial formulas.  • Songs Hidden in the Seams: The organic process of discovering musical numbers hidden in the quiet, empty spaces between film scenes.  • Overcoming the Fear of Collapse: Navigating the intense vulnerability of a production's first week and learning to trust your internal compass.  Whether you're a filmmaker, a theater lover, a creative professional navigating a highly public career, or someone looking to practice deeper mindfulness and trust in your everyday life, Ritesh's thoughts on artistic conviction provides an invaluable blueprint.  If you enjoyed this, please hit that subscribe button, leave a comment, and share this video with someone looking to realize and transform their own vision! --------------------------Chapters-00:00 Introductions02:40 Nostalgia, Change, and Telling Stories of Those Left Behind05:41 Translating the Intimacy of The Lunchbox to the Stage08:04 An Organic Transformation: Working with the Lazours10:09 Finding Songs in Between the Seams of the Story11:43 The Writer's Medium: Curating the Confluence of Creative Energy14:35 Discovering New Skills and Instincts in Musical Theater16:32 Sponsor Breaks - TRAVELOPOD and LOTUS LANE COFFEE17:31 Managing a Public Career: Owning Successes and Failures21:14 Leaving Your Fingerprints Over Everything You Create25:10 Wielding Artistic Power and Collaborating with Actors27:56 Thriving on the Unknown: Ritesh's Operating Mantra29:55 Lessons from Parenting and the Cost of Creative Focus31:42 Quick Hitters: Greatest Fears, Mingling, and Hamnet33:07 Cultivating Trust in Yourself and the Unseen End Goal35:18 Conclusions & Shoutouts#RiteshBatra #TheLunchbox #IndieFilmmaking #SouthAsianRepresentation #Storytelling #TrustMeIKnowWhatImDoingShoutouts:✉️ Mitra Kalita for making this incredible connection happen!

HerbRally listeners save 25% on tickets to the 2026 Good Medicine Confluence (October 12–15 at Ghost Ranch, New Mexico) with discount code HERBRALLY26. LEARN MORE & REGISTER Welcome back to The Plant Healer's Path — Episode 25. In this hour-long episode Dr. Kenneth Proefrock is joined by Jesse Wolf Hardin, together presenting at the 2023 Confluence in Colorado.  Here they meld forces to cast light on the history, future and spirit of botanical medicine...exposing some of the fallacies of the medical establishment, helping to further inspire your personal path, and catalyzing your potential role in the essential healing of our bodies, our societies, and the natural world that we're a part of.  This audio was extracted from the video version available on the HerbRally YouTube channel. This episode is brought to you by The Good Medicine Confluence October 12–15, 2026 Ghost Ranch, New Mexico Join herbalists, healers, wildcrafters, visionaries, misfits, and medicine makers for four unforgettable days of learning, celebration, connection, ritual, and more than 100 classes from over 40 teachers. You're warmly invited to gather, study, celebrate, and dance under the stars in the Land of Enchantment.

Bill O'Grady and Mark Keller explore why investors should resist the temptation to abandon their core investment style during periods of market momentum. They unpack how oil prices surprisingly avoided a spike given recent events in the Strait of Hormuz, with a note of caution for future changes as the world adjusts. The conversation turns to Chair Warsh's first FOMC meeting and a likely shift toward reduced Fed transparency, closing with a look at the economic tradeoffs in today's world of no recessions and their long-term outlook for gold.

What gives one enterprise an AI advantage over another? According to Atlassian Chief Product & AI Officer Tamar Yehoshua, it’s not simply access to the latest models, it’s the depth of enterprise context. In this episode of Technovation, Tamar joins Peter High to discuss how Atlassian is leveraging decades of workflow history through its Teamwork Graph to power AI across Jira, Confluence, and Rovo. She explains why enterprise context is becoming the defining ingredient for AI success, how software must now be designed for both humans and AI agents, and why leadership judgment becomes even more valuable as AI accelerates software development. Tamar also shares Atlassian’s approach to AI Builder Weeks, measuring AI productivity, building open agent ecosystems, and helping customers realize measurable business value from AI investments. This episode is presented by Mailtrap — Modern Email Delivery for developer & product teams. Learn more at mailtrap.io

What if the biggest barrier to successful AI isn't the model itself, but the lack of context behind every decision your teams make? As AI agents become more capable, how do organisations ensure they understand the people, projects, documentation, and history that shape real work? In this episode of Tech Talks Daily, recorded at Team '26, I'm joined by Taroon Mandhana, CTO of AI and Teamwork at Atlassian. His responsibilities span engineering for products including Jira, Confluence, Loom, and Trello, alongside the company's AI strategy and the development of Rovo. Our conversation explores why Atlassian believes AI should become a teammate rather than simply another chatbot. Taroon explains why enterprise context has become one of the most valuable assets in the AI era. While today's foundation models continue to improve at an incredible pace, they still lack the organisational knowledge that human teams naturally accumulate over time. Atlassian's Teamwork Graph aims to bridge that gap by connecting people, projects, documentation, code, goals, and conversations into a living knowledge network that AI agents can use to produce more accurate, relevant outcomes. We also discuss why Atlassian has chosen an open approach, making its Teamwork Graph available through technologies such as MCP rather than limiting it to its own AI products. Taroon shares why interoperability will become increasingly important as businesses adopt multiple AI platforms and why organisations should be free to use the agents that best suit their needs without losing access to valuable business context. Another fascinating part of our conversation focuses on how Atlassian's own engineering teams are changing the way they build software. Smaller teams, tighter collaboration, AI-assisted development, and faster iteration cycles are allowing products to move from concept to release in weeks rather than months. Taroon explains how AI is changing both software development and the structure of engineering teams themselves. We also examine where AI should take ownership of work inside platforms like Jira, where human judgement remains essential, and why successful organisations are treating AI adoption as an ongoing product journey rather than a one-time technology deployment. If your business is looking beyond isolated AI experiments and wondering how to build AI into everyday work, this conversation offers valuable insight into the role context, openness, and organisational change will play in the next generation of enterprise software. As AI becomes part of every workflow, what do you think will become the real competitive advantage: better models, or better organisational knowledge?

In our latest episode, the Confluence Macroeconomic Team breaks down the six geopolitical trends that we believe will shape the international landscape in the second half of 2026. From the disruptions in the Strait of Hormuz and the future of the dollar's reserve currency status, to the government's growing role in AI and the rise of quantum computing, the conversation covers the issues most likely to move markets in the months ahead.

History is rhyming. The last time dividend stocks were this out of favor, the dot-com bubble was peaking. Portfolio Manager Tom Dugan joins Director of RIA Relationships Emily D'Agostino to discuss why that dynamic looks a lot like 1999, what the historical data says about what comes next, and why the Confluence IDEA strategy's quarter-century of consistent philosophy and construction may be precisely what this moment calls for. If history is any guide, patient investors may be about to be rewarded.

On this date in 1929, Joseph Blanding was still living in the family farmhouse at the south end of Wahpeton. He gave a talk to the Wilkin County Historical Society that was later published in the local paper. Joseph came to the area in 1872 at age nine, before Wahpeton was settled.

How does a program built around relationships, adventure, and the outdoors evolve over ten years while staying true to its mission? In this episode, Will sits down with Foster Post, co-founder of Confluence Behavioral Health, as the Vermont-based program celebrates its 10th anniversary. Foster shares his journey into outdoor mental health treatment and reflects on the lessons learned from building a small, owner-operated program during a time of unprecedented change. From its early years featuring multi-day wilderness expeditions to its current model serving young adults through residential treatment, adventure-based programming, and community engagement, Confluence has continually adapted while staying true to its core belief in the healing power of relationships and the outdoors. Foster and Will also explore the changing needs of young adults, including rising anxiety, social isolation, self-doubt, and the impact of technology on mental health. Together, they discuss how outdoor behavioral healthcare is evolving, why community and experiential learning remain essential for growth, and what the future may hold for nature-based treatment programs. This conversation offers valuable insights for parents, clinicians, educational consultants, and anyone interested in young adult mental health, outdoor therapy, and the future of behavioral healthcare. This podcast is supported by White Mountain Adventure Institute (wmai.org), offering adventure inspired retreats and coaching facilitated by Will White.

BONUS: The Communication Tax — Why Your Team Collaborates Too Much and What to Cut First In this BONUS episode, Roman Nikolaev challenges one of the most deeply held beliefs in the agile world: that more collaboration is always better. As Head of Technology at Cambri, Roman has watched teams burn their best hours in meetings and handoffs that create the feeling of productivity without the outcomes. He shares practical tools — from the vacation test to RFC processes — that help teams find the minimum viable level of collaboration. From Senior Engineer to Accidental Manager "I kind of accidentally ended up in management. I didn't want to lead anyone, I wanted to be just a senior engineer doing my stuff. But somehow, four months in the job, I was already leading a team, and then one year after, I was head of technology."   Roman's career in engineering goes back to the early 2000s. When he changed jobs during COVID, he specifically didn't want a management role — he wanted to code. But within months he was leading a team, and within a year he was running the entire technical organization at Cambri. That unexpected shift from hands-on engineering to leading teams gave him a front-row seat to how collaboration actually works — and how often it doesn't. What he noticed was that the most important differentiator for technical teams isn't technical knowledge — it's communication, and the tax you pay when communication goes wrong. The Communication Tax Is Real "The communication tax is real. The less we need to pay for communication, the more we can concentrate and own things end to end."   Roman describes a pattern most teams will recognize: stakeholders inside and outside the team — product managers, QA, scrum masters, product owners — and at some point, it becomes a game of telephone. The people doing the actual work don't have the context they need. The result? Unnecessary features, wrong implementations, suboptimal technical solutions that don't scale. His argument isn't that collaboration is bad. It's that every handoff, every meeting, every "quick sync" has a cost — and most teams aren't honest about how much they're paying. Handoffs Aren't Collaboration "If you look at a typical software development lifecycle — a ticket created by a product owner, refinement with the team, development, code review, QA, acceptance — there are quite many handoffs. If we can reduce some of this, we get a more effective workflow."   Roman walks through the standard ticket lifecycle and counts the handoffs: PO creates ticket, team refines, developer picks it up, code review with other developers, QA phase, acceptance phase. Each transition is a potential information loss. His provocation: instead of involving more people when someone struggles with a task, give the person working on it the tools and knowledge to complete it independently. The trigger for his thinking was a real team conversation where someone suggested everyone should "jump on the ticket" to help. Roman's response: wouldn't it be better to equip the individual rather than create more dependencies? Async Tools That Actually Work "Instead of gathering a meeting where people come unprepared or with some raw ideas, we have ownership for a task. Someone takes their time, writes down their thoughts, options in a document, and then we assign people to review it."   Roman shares two async practices his teams use at Cambri. First, the RFC (Request for Comments) process on Confluence — one person owns a decision, writes it up with options, and assigned reviewers sign off asynchronously. It turns out to be more effective at finding better technical solutions while spreading knowledge without requiring synchronous deep-dives. Second, his Monday written updates: every week, he spends about 90 minutes writing a detailed post covering all project statuses, what happened last week, what's coming, and business context. The team feedback in skip-level meetings is consistently positive, and he fields far fewer questions about business context and priorities than before the practice started. The Vacation Test "One heuristic would be that if one of the team members goes on vacation, the rest of the team can continue working on their task."   Roman learned this the hard way. He went on a typical Finnish one-month vacation. Before leaving, he explained the architecture and intent for a key task to his team. He came back to discover they'd built the completely wrong thing — wasting one month of a two-month project. He spent the remaining time working weekends, on planes, on trains, just to hit the deadline. The lesson wasn't that he needed more collaboration or synchronous communication before leaving. It was that he needed better communication — and a way to test whether shared context actually exists. His heuristic: if Alice goes on vacation, can Bob continue from where she stopped? If not, you don't need more meetings. You need better async context-sharing. Where to Start: Ownership First, Then Cut Meetings "I would probably first look into if a particular initiative, a feature, or some kind of process has an owner and well-defined roles. Usually, if there is no clear owner, that leads to a lot of synchronous meetings."   For Scrum Masters and team leads looking for a practical starting point, Roman offers a two-step approach. First, ensure every initiative, feature, and process has a clear owner with well-defined roles. Without clear ownership, meetings multiply because nobody is sure who's responsible, so everyone attends everything. Second, look at the team calendar starting with the biggest meetings and ask: can this be an RFC? A message? An email? Then experiment — cancel a meeting, replace it with an async channel, and see what happens. You can always bring it back. In the agile world, Roman argues, we should embrace experimentation with our own processes, not just our products. Recommended Resources Roman recommends Team Topologies by Matthew Skelton and Manuel Pais. The book gave him a clear mental model for independent teams that own their area end to end — teams aligned to value streams that own the customer problem completely. For more of Roman's thinking on collaboration, check out his Substack newsletter: Is Your Collaboration Good or Evil? on High Impact Engineering. About Roman Nikolaev Roman Nikolaev is Head of Technology at Cambri. He's spent his career thinking about how teams actually get work done — and his contrarian view that most teams collaborate too much has sparked real debate in the agile community.   You can link with Roman Nikolaev on LinkedIn.

In this episode of Liminal Phrames, Darren/Exo and Nathan go where the current societal conversation around UFOs and NHI has yet to go: into questions around the abduction and hybridization phenomenon. What's happening, and how is it more complex and multifaceted than most people are ready to metabolize?

Researcher, artist, and curator Pietro Consolandi traces the ‘wetland turn' in art, ecology, and environmental justice, via Giovanni Pellegrini's 2025 documentary film, The Venice Lagoon, a legal person.Nature Speaks: Listening for Rights of Nature in Venice and Europe is at Ocean Space in Venice until 11 October 2026. The Research Unit, curated by Pietro Consolandi and Amalia Rossi, is co-produced by TBA21–Academy and NICHE Centre for Environmental Humanities, Ca' Foscari University of Venice, in collaboration with IDRA (Initiative for the Rights of Water) and the Confluence of European Water Bodies. You can join the next Citizens' Assembly for the Rights of the Lagoon on 10 October 2026.The Venice Lagoon, a legal person (2025) is available to watch online.For more about water bodies in Europe, hear Klima Biennale Wien festival director Sithara Pathirana on climate justice, public space and the rights of the river Danube through Austria, Central, Eastern, and Southeastern Europe, in the episode about Superflux's sculptural installation, Nobody Told Me Rivers Dream (2025): pod.link/1533637675/episode/ZWQ4Mzg0Y2MtMWFkMy00ZmJkLWIyZjUtNGU3MmJmODM2ODExOn the flows between Wales and Venice, listen to artist ⁠Taloi Havini⁠, winner of Artes Mundi 10, on their film Habitat (2017) at Mostyn in Llandudno, and work with Ocean Space in Venice: pod.link/1533637675/episode/e30bd079e3b389a1d7e68f5e2937a797On archaeologist Marija Gimbutas, hear Emilija Škarnulytė on their film installation, Burial (2022), part of Folkestone Triennial 2025: pod.link/1533637675/episode/ZmJmZTIzMGItOTg0OC00YjhhLThkMjMtMWQ3Y2E5ZDU5MDAzAnd for more about Southampton's coastal connections to Europe, hear curators Ros Carter and Sofie Krogh Christensen on Pia Arke's Camera Obscura (1990) at John Hansard Gallery in Southampton and KW Institute for Contemporary Art in Berlin: pod.link/1533637675/episode/OWVhZjc3YWItNDRiYy00MTYyLTk0ZmItZmE5MmJlZDY1YmI1PRODUCER: Jelena Sofronijevic.Follow EMPIRE LINES on Instagram: ⁠⁠instagram.com/empirelinespodcast⁠⁠Support EMPIRE LINES on Patreon: ⁠⁠patreon.com/empirelinesEMPIRE LINES is a project within the ecosystem of ⁠Radical Ecology⁠ (2025-2026).

The new AIEWF website is live! CFPs close in 2 days and we will run our first New Engineer Orientation this weekend, get your tickets booked ASAP as they -will- sell out. Take the AI Engineering Survey and get >$2k in credits and free AIE WF tickets!One of the central tensions in the agents industry is that even while there are major decacorn agent labs like Sierra, Decagon, Notion and Cursor being built up, it is also true that it has never been easier to DIY agents, with a plethora of agent frameworks like LangGraph and Pydantic and Flue, and managed agents from Anthropic and Gemini and Amazon. There has been a wave of companies building their own background agents from Shopify to Stripe to Paradigm to Razorpay, and even Cognition's friends Ramp have built their own coding agent with other friend Modal.You'd think Cognition might feel a bit threatened, but they're not - even after all this, they were way oversubscribed for the $1B Series D they just announced:Walden Yan, coiner of context engineering and Chief Product Officer/Cofounder of Cognition, invited OpenInspect's Cole Murray to talk about why the Devin is in the Details.Full conversation live on the pod today: In retrospect, async agents were the most AGI pilled bet you could make in 2024 - the models weren't good enough yet to vibecode, and people didn't trust AI enough to let it rip, nobody (including early Cognition) was sure about the form factors. Now it is obvious:* The first wave of AI coding tools made the developer faster but remain heavily in the loop. Copilor and Cursor's tab autocomplete are prime examples However, the workflow was still heavily centered around and bottlenecked by the developer's local workflow: a developer in an IDE, watching the model, accepting or rejecting changes, and pushing code one interaction at a time.* The second wave was local agents: Claude Code, Windsurf, Cursor's agents pane: first one and increasingly many terminals all running concurrently.* The current Age of Async Agents points to a different future focused more on agent orchestration which drives end-to-end development.According to previous guest Steve Yegge, there are finer-grained 8 levels to agent adoption, but we have collapsed it into three.As Cursor's Michael Truell put it in The third era of AI software development:Cursor is no longer primarily about writing code. It is about helping developers build the factory that creates their software. This factory is made up of fleets of agents that they interact with as teammates: providing initial direction, equipping them with the tools to work independently, and reviewing their work.The agent should not sit solely inside the developer's flow. It should be setup to work in the background so that you can give it a task, a repo, a machine, a shell, a browser, tests, memory, and review loops to go do the work somewhere else.In less than a year, the sentiment has shifted from avoiding multi-agent systems:to suggesting approaches that actually work:From coining “context engineering” to building the infrastructure behind Devin's 7x PR growth and jump from 16% to 80% of commits across Cognition repos, Walden Yan has had a front-row seat to the background-agent shift. In this episode, Cognition co-founder and CPO Walden Yan joins swyx alongside Cole Murray, creator of OpenInspect, to unpack why everyone is building their own Devin, what changed after the December 2025 model inflection, and why “spec to pull request” is now becoming a real production workflow.We go deep on the architecture of background agents: harness-in-the-box vs out-of-the-box, why Devin separates the “brain” from the machine, why repo setup is still one of the hardest problems, why Docker is not always enough, and how full VMs, snapshots, scoped secrets, GitHub bots, Slack integrations, and video-based testing all fit together. Walden and Cole also dig into memory, MCP limitations, multi-agent orchestration, AI code review, SRE auto-triage, PMs shipping code from Slack, Windsurf 2.0, hybrid frontier/sub-frontier systems, and the real failure mode of uncontrolled vibe coding: your codebase regressing to your worst engineer.And as agents eat software… and software eats the world… you can draw the conclusion on what is next:We discuss:* Why the engineering world is waking up to background agents and cloud agents* The December 2025 model inflection that made spec-to-PR workflows practical* Devin's 7x merged PR growth and rise from 16% to 80% of commits* Why Cole built OpenInspect as an open-source background-agent system* The economics of $20/seat agent products and why monetization is tricky* What Cognition actually sells beyond Devin: infra, onboarding, integrations, and adoption* Harness in the box vs out of the box, and why architecture matters* Why Devin separates the brain from the machine for security and permissions* Repo setup, scoped secrets, Docker Compose, and agent-ready dev environments* Why full VMs matter when agents need to run real applications and test them* Android, macOS, Windows, nested virtualization, and machine-specific agent work* Why testing is much harder than “computer use”* Screenshots, video verification, and the “I know it works” merge moment* GitHub UX, Devin Review, AI reviewers, and agents responding to PR comments* Why MCP alone is not enough for first-class Slack and enterprise integrations* Memory, Knowledge, skills, Claude.md, and why retrieval is still unsolved* Devin's auto-generated memories and the challenge of memory pruning* Always-on agents as permanent PMs for issues, tickets, and product areas* Sub-agents, meta-Devin management, and what multi-agent systems actually add* Why pure auto-merge vibe coding breaks down after about two weeks* AI code smells, lint rules, reward hacking, and Semgrep for agent-written code* GitAI, inline context, and preserving the “why” behind code changes* Local testing, mock servers, older codebases, and preparing companies for agents* Windsurf 2.0 and the handoff between local foreground agents and cloud background agents* SRE auto-triage, support workflows, and agents as first responders* PMs, marketing, and non-engineers creating pull requests from Slack* AI agent budgets, $1k-$5k per engineer spend, and hybrid frontier/sub-frontier systems* The rise of autonomous coding factories and who Cognition is hiringWalden Yan* X: https://x.com/walden_yan* LinkedIn: https://www.linkedin.com/in/waldenyan/Cole Murray* X: https://x.com/_colemurray* LinkedIn: https://www.linkedin.com/in/colemurray/* OpenInspect / Background Agents: https://github.com/ColeMurray/background-agentsTimestamps00:00:00 Introduction00:00:43 Why Everyone Is Building Their Own Devin00:01:57 Devin's 2025 Ramp: 7x PR Growth and 80% of Commits00:03:49 OpenInspect and the Rise of Open-Source Background Agents00:07:59 What Cognition Actually Sells Beyond Devin00:09:56 Background Agent Architecture: Harness In vs Out of the Box00:12:08 Separating the Brain from the Machine00:14:07 Repo Setup, Secrets, Docker, and Full VMs00:19:13 Why Testing Is Harder Than Computer Use00:22:40 Video Verification and the “I Know It Works” Merge Moment00:23:19 GitHub UX, Devin Review, and AI Code Review00:25:42 MCP, Slack, and Enterprise Agent Integrations00:28:59 Memory, Knowledge, and Always-On Agents00:36:16 Sub-Agents, Multi-Agent Orchestration, and Meta-Devin00:43:55 Vibe Coding, Auto-Merge, and Codebase Decay00:48:38 Agent Infra, VPCs, Cloud Providers, and Fast VM Restore00:52:25 AI Code Smells, Reward Hacking, and Code Review Systems00:56:10 Making Codebases Agent-Ready00:58:30 Windsurf 2.0 and the Local-to-Cloud Agent Handoff01:01:15 SRE Auto-Triage, PMs Shipping Code, and Agent Use Cases01:04:32 Agent Budgets, Hybrid Models, and Autonomous Coding Factories01:06:51 Hiring at Cognition and OpenInspect Consulting01:07:45 OutroTranscriptIntroduction: Walden Yan, Cole Murray, and Context EngineeringSwyx [00:00:00]: All right, we're in the studio with Walden Yan, co-founder of Cognition, CPO.Walden [00:00:08]: Happy to be here.Swyx [00:00:09]: Which is a cool title. And coiner of context engineering.Walden [00:00:15]: Although I think there are many people who'd used the terms in various ways beforehand, but I did find that people, both internally and externally, enjoyed the upgrade from prompt engineering or model wrapping into maybe a more thoughtful way to build agents.Swyx [00:00:33]: For those who haven't caught up on that, I have on screen the Don't Build Multi-Agents post, which you should go read on and we might refer to, and Cole Murray, who created OpenInspect.Cole [00:00:43]: Great to be here.Swyx [00:00:43]: So let's talk about it. Everyone is building their own Devins. What's going on?The December Shift: From Handholding Models to Autonomous PRsCole [00:00:51]: So I think the engineering world is waking up to this idea of background agents, cloud agents, whatever you'd like to call it. And I think we saw a shift around the December timeframe of 2025, where the models Opus 4.5 and GPT 5.2, they reached a capability where we moved away from handholding the model and being able to actually more or less autonomously drive the model. And what I mean by that is that we could pretty much go from a specification to a completed pull request, assuming the spec was good enough, with very little friction. And that paradigm alone, I think, changed a lot of how we interact with agents, and opened this world where background agents became more practical.Swyx [00:01:41]: I think for Cole, everyone experienced this in December, but I feel like there was just this increasing ramp, right? There was this moment which was, I think, Sonnet 3.7, where, You guys rewrote Devin in one night or something. So describe 2025 or how it felt from your side.Walden [00:02:01]: In retrospect, we always thought it was ramping up, but then even now, over the last three, four months from today, it's been ramping up even faster. So it's almost funny to be talking about how, big of a leap Sonnet 3.7 was, and honestly, a lot of it was stripping out parts of Devin that were no longer needed with that jump in of intelligence. But I also just think that a lot of the recent leaps, especially, you look at, models like Opus and the latest GPT models, they are reaching levels of autonomy where people are actually finding that they actually can just be hands-off. And people who were once debating, “Oh, do I need to be in the weeds with my model in the IDE? Can I just completely move it off into the cloud?” That's a more serious conversation, and we've seen that in all of our growth charts. Internally there's this funny graph where our usage has, of PRs, our merged PRs, has grown 7X since I forget what it was called.Swyx [00:02:57]: I think Dev, maybe tweeted that. Yes.Walden [00:03:01]: it grew like 7X over, the last, I think it was, two months, three months, something like that. And then you see our engineering headcount growth. It's, gone up by, 10% or something.Swyx [00:03:11]: We were, we were afraid To release this. So this is Devin commit percentages on all Devin repos, was 16% in January and now 80% in March.Walden [00:03:25]: It's a big shift right now. And so it makes sense that a lot of people are now thinking about, buying Devin, but also maybe, trying to build their own and there's Lots of I have a lot of fun building Devin, so I can see why other people would want to build their own cloud agents as well. Matt, well, maybe it's good to hear, what initially inspired you to try to build OpenInspect?OpenInspect: Ramp, Cloud Agents, and Open SourceCole [00:03:49]: OpenInspect came about, through primarily my clients observing how they were using tools like Claude, OpenAI's Codex at the time, and seeing some of the friction that they were having with it. Primarily the Claude was being used through Slack, and a big issue they ran into was that the sessions that were launched were specific to whoever called it via Slack. And so if a PM was the one who invoked the session and they would then go to pass context to engineering can't see the session. And that in itself was a deal breaker because the PM, “Hey, engineering, can you jump in?” But there's nothing to jump in on unless they're copy-pasting out or the single response that came back. And so seeing some of these problems, I had built a similar architecture internally, just to experiment with, test out different ideas as this trend of moving off of localhost was starting to become, And as Ramp released their blog post, I had a lot of the pieces for this already in place, and just thought it would be funny to, see what Claude could do just purely from the blog post. And on my X account, there's actually a thread of where I live tweeted, going through thisCole [00:05:14]: comparing GPT and Claude as both of them are going through it.Swyx [00:05:17]: On the announcement thing or something else?Cole [00:05:19]: right after it got released. We can put it in the show notes. Yeah, it was helpful that I had already knew how to verify the system. I knew what I was looking for. I think Ramp did a great job of really illustrating, the technical aspects of how to build something. It was much more than just like, “Hey, we built a great system.” It was, “And here's how you can build it too.” And so, I resonated a lot with that, just with the problems that I was already seeing, and I thought that, looking around, I didn't really see anything in the open source community that, met this type of system. I think there's a lot that run, in localhost like Superset, Conductor, and many others.But nothing that was actually running in the cloud. And so, I built it, and I thought it was interesting to just open source it and allow anyone to then have a foundation that they can mix and match on top of.The Business of Background Agents: Open Source vs. DevinSwyx [00:06:16]: So literally after Devin was launched was, there was OpenDevin Which became All Hands. I don't know if you tried that orWalden [00:06:22]: I was going to say, one of the things that interested me a lot with OpenInspect was, you didn't try to go make it then something you monetize. There are a lot of, I think, these open source projects would then go and really try to, raise VSwyx [00:06:36]: That's why no OpenDevin. Yeah.Walden [00:06:38]: yeah, and how did you think about that? I thought that was very interesting.Cole [00:06:44]: I thought, and just what I had seen across my clients, was that having a background agent system is going to become a critical infrastructure within their company. And so because of that, I think that I wanted to open source it so that they could fork it and put in whatever customization they wanted. To that question though, I get asked all, “Oh, are you going to raise? Are you going to turn this into a service?”Walden [00:07:08]: I'm sure you've gotten offers.Cole [00:07:09]: but primarily I don't want to do that for a few reasons. One, I think that I don't want to compete for, $20 a seat. I think that is just a really difficult business. I think it's very easy to copy the main pieces of it. Again, I built this fairly quickly. And I think because you are not owning, I guess, the entire stack, it's hard to monetize. You have money being made at the sandbox layer with Daytona, E2b, many other players. You have money being made at the model layer. And you sit in this weird in-between gray area where what are you actually selling? You're selling, I guess, the infrastructure. You're selling, the integrations maybe.Swyx [00:07:55]: let's ask the guy. What are you What are you selling?Walden [00:07:59]: Well, yeah, there's multiple layers to this in practice, and actually it's funny you mentioned the infrastructure, ‘cause when we got started building Devin as well, we had to go figure out how to make the infrastructure as well because,Swyx [00:08:10]: You had to build this two years before everyone else,?Swyx [00:08:15]: Including, the model sideWalden [00:08:17]: It was not, it was not very polished at the start, when we just built it off of raw VMs from cloud providers like EC2, the boot up time was so slow, I think, And especially then, turning off the machines, saving them, and then to be able to bring them back up again when the, when you want Devin to wake up again later. It would just be out cold for like 10 minutes because that's just how long these systems took. They were not built for this repeated down and up usage. And so we actually had to go do all of that. And as a result now, one thing we offer when we go and sell Devin to people is, you don't have to worry about all the compute side of things. We'll make it work. We'll make it work in your cloud if you want it to. But aside from the product, and I want to go into the agents and the tuning of the intelligence part later, but I think a big part of what we do at Cognition as well is to just make sure that your company learns and uses and adopts these coding agents. ‘Cause I think for especially the largest enterprises in the world, you find that there is a lot of people who want to move over to using AI for their day-to-day workloads. But because of the way projects are planned, because, not everyone is literate in using AI in these ways, having a team of engineers who can actually go in and onboard you, set up all the integrations you need, the automations you need to really get to that level of, leverage with AI, is super helpful. And so We do that. We show thought partners to the customers that we work with as well.Swyx [00:09:56]: So let's talk about, architectural stuff. I think that's always, that is something that was the topic of conversation between the two of you. Is this, the mental model that you want to start with or something else? I'll just leave the floor open to you guys.Agent Architecture: Harness in the Box vs. Out of the BoxCole [00:10:11]: I think, maybe we can start here as just a general what are the pieces of a background agent system. And then maybe we can go into some of the nuances of, Decisions that you can make.Swyx [00:10:22]: But I guess I also Like, what, maybe what Walden is saying is the agent is like in this open code box, I guess. Right? This is infra, and then there's, that's the agent. And you had this discussion about whether you put the agent in here or in Out externally. Can you tease that out?Cole [00:10:39]: In a background agent systems, you have a decision to make of where the agent is actually going to run. This is typically described as the harness in the box or out of the box. With running the agent in the box, you're making some trade-offs by doing that. The negative trade-off you're making is primarily security. Because the agent is running in that box, unless you otherwise design it, all of your secrets need to go into that box as well. And given the nature of AI, it can be unpredictable, and you could very easily end up accidentally exfilling your secrets, or other unintended behavior. Now, the out of the box is the idea that we are going to have the actual agent running not directly in the sandbox, and we will have, quote-unquote, the brain of the agent running in some type of worker, control plane. That sandbox then is going to serve as the hands where the brain is basically operating and making tool calls into that environment to manipulate it. I guess other trade-off that you're making between the two systems is that, in my opinion, running it out of the box is much more complex because, you have state that has to be managed, whereas if you're running it in the box, all of the state of that agent is actually in the box, and yes, it's you could persist it elsewhere, but it's all localized and you have less concerns to worry about.Walden [00:12:08]: I think a lot of that, what you mentioned, is why we actually from the start built Devin to what we called separate the brain from the machine. The other thing that this allows you to do is reuse any existing infrastructure you have for dev boxes Perhaps. And so you don't have to worry as much about making a new type of dev box that has all the dependencies the brain needs, as you mentioned, the secrets the brain needs as well. One thing that we've seen some customers run into is, you have a GitHub app and you want Devin, your agent, whatever, be able to interact with GitHub through this application, but then you have different users with different actual permissions. If they are all interacting through the same GitHub app and there's no actual, separation between the system that decides, what it does and the actual secrets on the machine, then you run into an issue where, okay, it's hard to do the separation. But in practice, with Devin, it's much easier because we just say whatever you put on the machine, that is, the scope of basically what the user is free to do, what the agent is free to do. So only put the most scoped secrets on that machine, and then the brain is fully not accessible from the machine. So you don't have to worry about messing with the, any of the most secure parts of the brain if the user is free to do whatever they want with the machine.Swyx [00:13:31]: I was going to just bring, I have this, chart from OpenAI, where I don't know if this is, in the box, out of the box. That is something that they do use to describe it. And then also recently Anthropic did, managed agentsSwyx [00:13:44]: Which is, this is their thing. I don't know. It's all, it's all variations of the same pattern, right?Cole [00:13:49]: So this would be out of the box.Swyx [00:13:51]: Which, is preferable for them because it's less work?Cole [00:13:56]: I would say it's more work.Swyx [00:13:58]: It's more work?Cole [00:13:58]: But it, in my opinion, it is the better architecture of the two. It's just, you're taking on a bit of complexity by doing that.Repo Setup, Docker, and VM-Based Development EnvironmentsWalden [00:14:07]: One thing I've not seen a lot of other players do well is how do you manage what's actually on the box? And this can be complex for many reasons. Let's say you have a big repository that's changing and updating a lot with changing dependencies. How do you make sure that the working environment of the agent actually stays up to date, has all the credentials it needs to, let's say, run the app and test it, and all the things you want your autonomousSwyx [00:14:34]: So a repo setup.Walden [00:14:35]: Exactly. So in, internally At Cognition, we call this repo setup.Cole [00:14:39]: The hardest part ofWalden [00:14:40]: It's been a perennial problem since the start of the company, of how do we help people get this set up? Because not everyone just has, working cloud environments working out of the box. And do you find this to be a common problem withSwyx [00:14:53]: How do you solve it?Walden [00:14:53]: Your clients?Cole [00:14:54]: This is a very common problem, and through my consulting, this is a lot of what I help teams do. A lot of teams don't really have great developer environment setups, if any. A lot of the times it's, “Go talk to Bob and get the secrets,” and that obviously doesn't work when the agent needs to actually set this up. And so a lot of that, most teams are using Docker Compose or some type of microservices. And so for theSwyx [00:15:19]: Even in prod?Cole [00:15:20]: Not in prod. With the OpenInspect, you are using this primarily to interact, and make code changes. There is other use cases, but you can hook, whether through CLI, MCPs, other tools, you can then hook that into your production systems primarily for, SRE type use cases. But you are not, necessarily, trying to test your prod internal microservice through the system.Walden [00:15:48]: And you mentioned Docker Compose. I think one direction we saw some of our friends take early on was, using Docker containers as the level of abstraction for their models. There's lots of reasons, I think, why Docker containers are not great. One thing is, Docker container's not really a true security boundary, for one. But the other is, if you are running real applications, a lot of times those applications use Docker, and then you have to think about Docker in Docker, which is, really weird. And so I think part of, the really hard challenge of getting VMs to work, why did we do that? Well, it was because we realized that you actually needed, full VMs to be able to do these types of things. And especially nowadays where there's actually value in running the application and clicking around and sending you screen recordings of these things. The value just, keeps adding on top of that. But it is a decision I see people run into when they try to build their own systems, is, “Oh, do we, in addition to this, do we put the agent in the machine or out of the machine? Do we use Docker? Do we use something else?” What do you recommend people nowadays?Cole [00:16:57]: I think Docker is a good solution for maybe not running the agent, but running your infrastructure, because that is more or less the same setup your engineers are probably already using. If they're not, then I don't know what they're using. But they're probably already using Docker Compose.Swyx [00:17:14]: I've always had a small candle for web containers. I don't know if you guys have tried them before.Swyx [00:17:19]: To me, they were, supposed to be like Docker Light.Cole [00:17:22]: Is it?Swyx [00:17:22]: I don't know.Cole [00:17:22]: No, I haven't tried it. But yeah, I think any environment that you've set up that is a good experience for your developer naturally lends itself to being easy to set up for the agent. And once you figure out that local developer story, you've more or less solved the agent in a sandbox, environment setup. OpenInspect does have hooks as well, where you can, run a setup SH script that will pre-install everything. You can then pre-snapshot that build so it starts instantly, and then there is a second hook to actually then, restore the state of the sandbox when it comes back. And so you can already have all of those microservices running and basically get the same experience that you would on your machine within the sandbox.Testing Agents: Computer Use, Screenshots, and Real App WorkflowsWalden [00:18:08]: Another thing that we've been thinking a lot about is like Different VM service offerings. Have you had customers where they needed like macOS specific VMs or like Windows specificWalden [00:18:20]: VMs?Walden [00:18:22]: There are like many technologies in the world that only work on specific types of machines, right? If you're building a.NET application that has to run on Windows or like, maybe more commonly if you want to build iOS or macOS Does that workSwyx [00:18:32]: Does Commission supportSwyx [00:18:33]: Choices like that?Walden [00:18:35]: The fundamental architecture we do, because we do the separation, it does support, but the actual work in progress is happening right now on these. Another thing that we've actually recently added support now for, it's in beta, is doing Android development. To do that, we needed to support, I think, nested virtualization within our machines because the VM itself is like a, is a virtualized Firecracker instance, and then you had to then run another Android emulator inside. And there's like weird performance issues that like, it, which is why it's like still in beta. We have to think through these problems, but it unlocks a lot for anyone who wants to do Android development.Swyx [00:19:13]: I was trying to find like a reference video for the testing thing. I couldn't find it, but I think you worked on the testing, capability. Why call it testing and not like computer use or I don't know, it's, what's the general Category of problem?Walden [00:19:26]: I think that when people think about the ability of an AI to run your app and test it, I think they actually over-index on the computer use part of it because computer use in my mind is the literal, okay, you want what button you want to click. Can you emit the right coordinates to go click that button? I think testing is actually a really interesting likeWalden [00:19:48]: Problem-solving, challenge for these AIs because if you wanted to do arbitrary testing, imagine you make a change that spans the frontend and the backend, maybe, even some other like even more deeply nested service. To actually test that change, we have to reason through what-- how do you first run these applications to orchestrate with each other with the right version of the code? Then, okay, how do I trigger the feature or how do I make the thing actually happen? And this can get arbitrarily hard, maybe you have to be an admin. Maybe a certain thing has to be feature flagged on. Maybe, you have to like run two sessions and then send us a very specific word into one of them to trigger a specific behavior. And figuring out how do you do that requires a lot of code base context, requires, a lot of orchestration that we've specifically done. And in some cases, we found that you actually, no one frontier model can actually do this full end-to-end task itself.Walden [00:20:42]: We've seen cases where we actually had to orchestrate different frontier models together to solve this problem together. That is where we spend most of our time when we think about this testing problem, not so much the computer use part. Computer use for what it's worth has gotten a lot better with recent models and it's made that part of the job certainly easier.Swyx [00:20:58]: Especially with like even 4.7, that they released yesterday, apparently like way better in terms of the vision stuff, which is going to be encompassing computer use.Walden [00:21:08]: Having evals for all these as well is something that like takes a while to build up. And having the evals be right is tricky as well. Do you ever see like, clients who are building their own agents have to start standing up evals to make sure things don't regress?Swyx [00:21:25]: Not so much evals in the traditional sense, but specific to the testing part that has just gone in. I just added support for screenshots And in theory you can also do video. I need to put in a plugin to do that. But they do show up natively, and it was a very heavily requested feature, especially after Cursor's recording came out. I think that was very enlightening for everyone of like, “Oh, this is a very good feature to actually have.”, I think with Devin you guys have had this for a while.Swyx [00:21:57]: Oh, yeah. See how screenshots work. Yeah, I don't know if there's anything, super and not obvious. It's like once what feature to build, you can just prompt it and it Will mostly work.Walden [00:22:09]: I think to Walden's point, though, the computer use is a subset of the larger testing problem, and I think that's very specific to the code base that you're working and it's not something that, out of the box that you could just solve it. The-- you do need the code base context to actually know how to test it. And I think in the case of a background agent system, you fortunately do have that code base locally that what is changing and could then inspect it and use that to drive the model.Swyx [00:22:40]: For those who haven't seen it before, this is an example of how it works. You, after the PR is done, you click testing approved, and then it sends you back a video. What I really like is that it labels, It's very small here, but it actually labels what it's testing. And then it-- and then you actually see the cursor and everything. So I don't know, yeah, the engineering in this, just Whatever you want to show. ‘cause this is like, this is one of those like, oh, few of the AGI moments, right? ‘cause Once I look at this, I actually don't I wish I can just merge inside Of Slack instead of going to GitHub ‘cause I don't need to see the code. I know it works.Walden [00:23:19]: Maybe a new feature in Cursor. Yeah, the annotations at the bottom was also a big difference for me when I, when I added those.Swyx [00:23:27]: It's just like, what am I looking at? What are you trying to demonstrate?Walden [00:23:30]: Exactly. There's a surprisingly long tail of small details that ends up making a big difference for this end metric of like how fast do you actually merge the code in. One experience that we spent a lot of time tuning early on was what is the right experience on GitHub for these tools. Because I think, most tools out there when you build the agent, you'll think about, oh, it'll create the PR for you. We try to take that a step further and say, “Oh, what if we actually made sure you could interact Devin, with direct Devin directly on GitHub?” And so we made sure that you can comment on GitHub, and Devin would actually receive those comments and address them back. But there's actually quite a bit of tuning you have to do here because you can imagine that actually like-We recently have Devin Review, for example. Devin Review will post comments on his own PR And then Devin has to then goGitHub Workflows: Devin Review, Comments, and PR AutomationSwyx [00:24:23]: He answers his own comments, which is Really loopy. So like, yeah, I like that it just updates here that it's, that I have commented But usually it's just me saying like, “Hey, merged, fix any merge conflicts.”Walden [00:24:37]: The, so when Devin fixes his own comments, you might be scared that, oh, maybe I'll infinite loop. But we've put a lot of work into making sure it doesn't, both by making sure that the comments are high signal, but also that the agent is thoughtful about what comments it immediately goes and tries to fix, and what comments it's like, “Wait a second, I think you're wrong.” Actually, that's one of my favorite moments is when Devin tells me that I'm wrong, when I try to get it to do something different. But tuning that behavior, actually makes a big difference in terms of how useful the actual GitHub experience is.Cole [00:25:06]: I think to touch on that as well, I think having the AI reviewer integrated into the system is a critical part of this background system. OpenInspect does have that. It has a GitHub code reviewer that you can control the prompt. It does do comments as well. It doesn't do them automatically yet. The capability is there, but it's not fully used.Swyx [00:25:27]: So you have to ask for it?Cole [00:25:28]: you do, yeah. You can tag it on GitHub, and then whatever you named your, GitHub bot, it will then follow up on it. It will then, if you have merge conflicts or whatever you have asked it to resolve, it will then resolve it, but it doesn't do it automatically yet.Integrations: Slack, MCP, and First-Party Agent InterfacesWalden [00:25:42]: Well, I'm curious, what is, the most common thing that people end up requesting, that they still need on top of OpenInspect when you help them go implement it?Cole [00:25:52]: I think a lot of it comes down to actually integrating it into the company. It's one thing to have the background agent system set up, but if it isn't actually integrated into your larger ecosystem, it isn't that useful. It is useful to be able to kick off sessions, but what we really want to be able to do is hook it into all of our other systems, whether that is the production database with read-only credentials, the logs, a Confluence or internal knowledge-based system. I think that is where I see the huge leap for companies, and that can be a challenge for companies as well who are maybe not familiar with exactly how to approach it, especially if they're in environments that have more compliance type things where, access control can be pretty big and how do you deliberately think about these problems, I find to be, one of the problems that comes with a system like this.Walden [00:26:46]: The thing we found is So, MCPs, obviously it has been like this, really big explosion of, oh, you can go, integrate it with all these different things. But to actually get the integration right and the and get the right experience, oftentimes we found that we had to go build our own ad hoc things. I think Slack is a great example of this. You could give your agent a Slack MCP and okay, it can post messages back to you on Slack. But we actually use Devin like a coworker in Slack, and that's how it's been built from the ground up. But to do that, you actually need to, support webhooks that come back, right? And then Devin has to respond in a natural way and then hopefully don't spam your threads too much and annoy the people in your company. So you got to tune that experience just right. Especially when there's a lot of back and forths, we find that we actually have to go beyond the simple MCP integrations in these places.Swyx [00:27:39]: I just pulled up the MCP marketplace. I know this is a Fair amount of work. Is the answer to eventually take first party control of all the top MCPs? Is that theWalden [00:27:48]: I would love a world where you could have something that's more expressive than MCP. That, goes both ways, not just a set of tools, but a proper system that interacts back and lets it Have the right experience with all these interfaces.Swyx [00:28:03]: So there actually is sampling in the MCP spec, but nobody Uses it, right?Walden [00:28:07]: And so I think that's the other part is, actually we found that when the MCP spec starts to get too complicated, it starts to lose its original promise of Being like a simple one-step connect. Now then we have to go figure out how to support all these different variations of things and It starts to look a lot like just building the first party integrations in a lot of these cases now.Cole [00:28:29]: I think it matters, too, how critical it is to your company, right? If this is something that nearly every session is going through, it probably makes sense to own it so that you can make optimizations on top of it Versus just whatever is off the shelf.Swyx [00:28:43]: Awesome. Other than MCPs, what else, sorry, well, I don't know if that's Narrowing in too much on, integrations. But what else? What other elements of building OpenInspect or Devin that you guys really sink on?Memory and Knowledge: What Agents Should RememberCole [00:28:59]: I think, a problem that comes up very frequently is this idea of memories or knowledge base.Swyx [00:29:05]: Oh, boy. How do you solve it?Cole [00:29:08]: so not solved yet, is the short answer.Cole [00:29:11]: it's something, there's a open issue for it, someone asking about it.Swyx [00:29:16]: There's, I, D Wiki hasn't indexed anything about memory yet.Cole [00:29:20]: how I'm seeing it solved across my clients is primarily through skills. I find that skills can be a good gap within that or updating Claude MD, but I think memory as a whole is a pretty unsolved problem, and it is why I've been hesitant to add it. I think there is parts of memory and that can be addressed, but I think as a whole it's a very difficult retrieval problem.Swyx [00:29:44]: Oh my God. RAMP didn't write anything about memory? I see zero search results.Walden [00:29:50]: No. Memory can be quite tricky to get right because it's the retrieval, but also the generation of the memories that can be really tricky. You don't want it to just like Remember very specific details.Swyx [00:29:59]: Walk us through the Devin memory journey because I know there's been a journey.Walden [00:30:03]: the first version of memory that like stuck around for a while was A system we have called Knowledge. And the idea was we wanted it to pick up things over time and not need the user to be proactive about teaching Devin things. So, okay, any time you remind Devin, “Wait, no, that's not quite the way you're supposed to use Git”Like, we actually want Devin to say, “Hey, do you want me to actually just remember this for the future?” And for you to just basically quickly approve or reject and for it to build up over time. ‘Cause I find that, 95%, I think, or some crazy stat like that of the memories that Devin has are all through these auto-generated things. Very few people actually just want to sit down and write big docs on Here's how you're supposed to work with the technology, et cetera. The generation and the retrieval has been something that we've been trying to tune a lot over the years. Generation, you don't want it to remember something like, if you asked one time to like, “Oh, please open as a draft PR,” you don't want to be like, “Oh, everyone forever now should get their PRs as draft PRs.” But you do want some, conveyor. Maybe you want to say like, “Oh, Cole generally likes, things to be created as draft PRs.” Same with retrieval, if you have thousands of these memories, how do you actually make sure they're retrieved at the right time? And that can be quite tricky to do right without exploding the context with a bunch of useful yeah, useless information. Surprising amount of just, eval work to just make sure that, memory is, remains a reliable system as new models come and go.Cole [00:31:31]: Do you have anything that you could share on, memory pruning? And like the temporal aspect of memory?Swyx [00:31:36]: Deleting and forgetting?Walden [00:31:39]: The, today, the, So the things they could do is it could edit memories. And so if your memory used to say like, “Oh, Cole likes to open everything as like a draft PR,” then you can imagine, “No, don't do that.” And then it'll say, “Oh, do you want me to update the memory to be Cole now want everything as, open PRs?” I think that at the same time we don't know if this is going to be the final version of the system. Whatever we have here will probably, translate into the new system that we'll be coming up with. But I think one big difference between two years ago and today is these agents are really good at using anything that resembles a file system natively. And so part of us are, is thinking, “Oh, should we rebuild memories to feel more like a file system that we let the agent navigate on its own?” That's been an interesting exploration. Also similar ideas in the scale space.Swyx [00:32:35]: I am pulling up OpenClaude's memory thing right now. So memory, OpenClaude has like this like daily memory journal thing, right? And you can I mean, that is a file system you can grep through and is a source of truth. I don't know if it's the best. It's probably super noisy, but at least, if you lose something you can discover it or you can apply some, forgetting algorithm to, more ancient memories that don't get recalled again or something. I don't know.Walden [00:33:01]: One thing we've been trying to do to push the boundaries of how you use agents at your company is letting an agent basically have a very similar file, a memory.md or something, and just like be your permanent PM for a specific set of issues maybe. So we have like some Slack channels internally, maybe a Slack channel dedicated to, a specific product like DeepWiki maybe. And you can imagine that, or you want a Devin that never stops, it's just always awake, but it has this like memory dock that it can just maintain for itself about, okay, what are like the number one priorities of what we have to fix and prioritize? Who is responsible for some upcoming work? Maybe they'll even Devin will even tag you on some recurring basis. And so it's been an interesting move to see, okay, how can we actually use Devin for more than just engineering? Can we actually upstream above the engineering process and maybe it's just Devin creating tickets, which then maybe some humans do, but then maybe other Devins do.Swyx [00:34:00]: One of my more fun automations is go research competitors and just suggest stuff to me on a weekly basis. That's the automation. I can't find it right now, but basically it just like, “Look at competitors and suggest things.” “And here are three things that you've suggested that I don't want any more of,” and you just stick that in the prompts. But like I wish actually So for like when I, for example, when I reject a PR, I wish that it updated memory so that I can then just not have to go up, go back and update the scheduled, sync, but anyway, feature request.Walden [00:34:31]: what? We might change it soon. I guess OpenInspect, in the time you've been around, has there been anything you tried to implement but then you had to like undo and like do a different way?OpenInspect Architecture: Webhooks, Control Planes, and Agent StateCole [00:34:41]: Nothing yet, but something that is on my mind. The initial way that I built it was that each of the integrations lives as its own package. And so you have The Slack bot, which is what's handling the webhooks, and then is basically interacting with the control plane. As I'm seeing the system starting to be more integrated, specifically with the GitHub bot integration, I'm considering bringing that all into the central control plane because especially now I want to start, And a request that I'm getting is the ability to monitor, the actual, pull requests being merged, as well as just tracking ofSwyx [00:35:19]: What do I have open?Cole [00:35:21]: What do I have open? How many of these are getting merged? How many comments are showing up? To just understand the health of the system. And so in the case of a GitHub app, you only have one webhook. And so then it's a question of do I put that webhook in that GitHub bot package? That's weird. It doesn't really make sense to live there because that package is more for like the code reviewer. Or do I like centralize it? So that's something that's on my mind of, making that decision. I think the other one we touched on earlier is the harness in the box versus out of the box. I think long term the architecture will eventually come back out of the box. Some of the newer tools that I've added are calling back into the control plane so that you don't have the secrets in the sandbox. And so I think long term I probably will pull the actual, agent out of the box, but I think for now it's fine.Subagents and Multi-Agent Systems: When Parallelism Helps or HurtsSwyx [00:36:16]: Just, a quick question on pulling the agent out of the box. I'm One thing I'm very bullish on this year is agents calling other agents or spawning sub-agents or Whatever you want to call it. Does that make it harder or easier? I can't tell. Because if the harness is in the box, you can just spin up more boxes. If the harness is outside the box, then you're, it's less easy because you are, you have a unicorn pet of a, of a harness that's, living outside the box.Cole [00:36:45]: In theory it would be the same way, right? Whether, one agent has launched many, sub-sessions within it, OpenInspect, for example, can launch sub-sessions and actually create other environments and then monitor them. In the case where it is out of the box, that would basically just be an additional session that's running. And so that session is also running outside of the box. It's running in your worker plane, wherever you're running this. And then you really just have to think about how does your top level agent then interact with it. I do think it can be more complex, just ‘cause again, you have now a more difficult architecture. But I think if you figured it out once, it's probably fine.Swyx [00:37:26]: Well, then I'm just, throwing it open to you in terms of, I call this like meta Devin management. Which is like the, Devin's calling Devins or Devin scheduling Devins or querying trajectories or anything like that. What have you built or unshipped, anything?Cole [00:37:46]: I think one of the surprising things we've seen is that a lot of the ways that, these, separate agents work with each other, and you want them to, parallelize their work, has still mostly followed the same manager sub-agents regime. And a lot of people I think are excited about this world where you have swarms of agents that, talk with each other all over the place. We've actually given Devin an MCP so they can just go arbitrarily message other Devins And create new Devins, et cetera. But I guess, it somehow creates, a really chaotic world in that sense. And so we've still found that most practical use on a day-to-day basis has been one single Devin.Cole [00:38:33]: Figuring out how to segregate the work and get, have other Devins work on it in, a relatively isolated sense, each with their own boxes Not sharing machines, so there's, a very little room for conflict is the regime that you have to create today.Swyx [00:38:50]: I'll call out, the experiments from Cursor, right? This is Wilson Lin's work on Single agent to multi-agent, and you're obviously famously on the side of don't build multi-agent. But they went through the whole thing, only to arrive at, this Which is exactly what Devin has, I think.Cole [00:39:08]: I think there will be a revision to that post at some point AboutSwyx [00:39:12]: Tell us about itCole [00:39:12]: I think multi-agents were very much not at all possible a year ago. You do see more multi-agent experiments today, but you can argue, are they really multi-agents, or are they just just, tool calls,? There are people who, will create sub-agents to go look for XYZ file, XYZ implementation. Has really nice context management benefits because all of the tool calls and tokens that it spends then get collapsed back to just the answer for the main agent. There's a lot of benefits to doing this. We basically have Devin do this with Deep Bookie, make a call out to Deep Bookie, give you back the results, but that feels like a tool call,? It's not like these, two collaborators actually talking back with each, back and forth with each other. But I think the thing that gives me the most bullishness that multi-agents might actually be possible is actually what I said earlier about Devin will actually sometimes tell me I'm wrong and push back, and I think that demonstrates a level of maturity and communication today that makes a multi-agent world possible. One, can two agents who have seen different information come back to each other and actually figure out who is right, what is the correct implementation? They're not just, yes men. Claude, I guess is like, used to just say, what is it? “You're right,” or,Swyx [00:40:25]: “You're absolutely right.”Cole [00:40:26]: “You're absolutely right.” Yeah.Swyx [00:40:28]: The Have you seen, did you seeCole [00:40:29]: The age is overSwyx [00:40:30]: The Codex app troll in Topic? This is the Codex app. Inside of Settings, there's a little, there's a little Easter egg, right? So if you go to, the Themes or Appearance, right? There's all these, color codes, and the top is absolutely, and it's the Topic's colors. Which is such a troll. Anyway.Model Behavior: Pushback, Adversarial Prompts, and Agent SkepticismCole [00:40:53]: I love that Easter egg. Did you discover that yourself?Swyx [00:40:54]: No, it was, someone was, tweeting about it And I was like, I was like, “Is this true?” Because, sometimes people just tweet stuff to, get a rise out of you. But yeah, there you go, in Topic colors.Cole [00:41:06]: Yeah. So yeah, we're out of this regime where, it just says you're absolutely right, and they can have real conversations and real back and forths.Swyx [00:41:13]: You can prompt it as well to be more adversarial or whatever. Yeah. Okay. Yeah, that, I mean, to me, that is more intelligence, right? That is not just something that's, a dumb tool, it's actually pushing back on you I think. Yeah.Cole [00:41:24]: when you mentioned, of course, the blog posts. There was one blog they had where they fed a swarm of agents together and built a browser.Swyx [00:41:34]: That was I think that was the one.Cole [00:41:36]: You can have, likeSwyx [00:41:37]: I think it's the same oneCole [00:41:37]: Creation of it. We found a surprising success of, don't do a swarm or anything, just have one Devin, it does its own context management. Just let it keep running for a while and give it some crazy tasks. I think we asked it to, rebuild, a Windows OS system. And it managed to do it just like, going on for long enough. It'sSwyx [00:41:55]: Was this Andrew's thing?Cole [00:41:58]: there were lots of demos that we ended up not posting, ‘cause at some point we'd just be posting way too much a bunch of, Demos. But I love that because it shows that I think the multi-agent thing still has, a bit of exciting sexiness to it, which is maybe still beyond still, the actual delta it adds to the capabilities of these systems. But it's absolutely the future. I think we're heading in that direction and we can see the progress being made there already.Swyx [00:42:25]: If I were to, make one super minor pushback because I don't feel that confident about it yetCole [00:42:33]: Go for itSwyx [00:42:33]: But I've had Ryan Lopopolo from OpenAI on the pod And he's a super slop cannon, right? Oh my God, that's my coding agent being done. I downloaded this, Peon Ping. I don't know if you guys have heard this. It takes like-, sound packs from popular games like, Command and Conquer and Warcraft, and then it plays it whenever it's done. And so it's like, “Work,” or whatever, “At your command,” or something. Anyway, what I got from the Cursor code base and from Ryan's thing was that there's a slop cannon approach where you try to loosen the single agent's, bottleneck, and I feel like that is, probably an, a very important thing to try to figure out. I don't think anyone's, really solved it. Because then you just have more reviewer slop on top of the agent slop To try to wrangle it all. Ryan will probably very strongly object that I say that he hasn't solved it, but he thinks he's He thinks he's completely solved it. But I think it's still I think it's, very important, ‘cause, that is a bottleneck, right? I feel Devin is slow sometimes Because I'm like, well, yeah, this is very readable and very sensible, but also it is slower than it could be if I just, I want a button to just say, “Just ramp this up 1,000 next parallel, in parallel and just, see what happens,”? And I don't know if that's, feasible at some point in the future.Code Review, Entropy, and AI SlopWalden [00:43:55]: I And we've also run experiments internally where we've basically tried to build entire products, true products that we knew we would eventually ship, but for now, let's try to see if we can do it just by purely, vibe coding on top of each other, auto merge, no code review at all. And then there's this benchmark of how many weeks can you go onto this for Before you say, “We have the trashiest code base.”Walden [00:44:18]: “Let's actually rewrite it from scratch.”Swyx [00:44:19]: Start a new factory, yeah. What'd you find?Walden [00:44:21]: I think we found that the state-of-the-art in December was you can probably, run this for about two weeks. By the end of those two weeks, you'd find that, hey, you want to, change the color of a button. Well, it turns out this button is implemented in, 10 different places, and they, have All these different variations, and oh, you forgot one of them, and actually it's a slightly different color in one spot. And you're like, “Okay, this is too much to work with. Let's actually try to do code review at the same time.” And make sure that we're on top of our software, actually cleaning it up a bit And making sure it's done in a scalable way.Cole [00:44:54]: I think building on that, the idea of, you don't have to look at code, I think is generally a bad idea. And the meme that I have for thatWalden [00:45:03]: What timeline, all right, is Do you think that statement will be true on?Cole [00:45:06]: I think probably for a while it'll be true that you should continue to look at your code. A problem that I see a lot of teams run into that I work with who are embracing AI native, AI first coding, is The meme that I have is that your code base regresses to your worst engineer, because that engineer who is, very gung-ho about AI and is not auditing their code, their pattern starts cementing into the code, and now the AI is referencing their patterns. And so now their if/else block that, is 20 if/elses back and forth, the AI is seeing that as the pattern of how things are done and starts to then exponentially grow this slop. And I find to your point, a pretty good approach to that is having scheduled cleanup, whether by humans or through systems, that are looking for duplication. They then address that. You'll end up with like 12 helpers for how to format a date. And you need to address that, because otherwise it will continue to sprawl.Swyx [00:46:09]: Within balance, I think it's fine to have some duplication, and then sometimes To have garbage collection, right? Yeah. The What I've been, talking about with a lot of engineering leaders is that you want to be very strict about the boundaries between modules, and it's your job as an architect, as a CTO, whatever, to say like, “Okay, here's the hard contract between you guys and you guys. Whatever you do inside this black box is your business. You do whatever. But between these guys, let's be, really damn clear, and any movement must be signed off by a human or me,” or. Then, and like that's that. I don't know if you have any other modifications or advice.Walden [00:46:44]: Well, I guess generally on the topic of, where humans can be useful, I found that ‘cause, some of these, really deep infra problems, sometimes just having a human that just has, really deep expertise can make a big difference. I've actually seen this come into play when actually building agents. So we've had a few friends now, try building their own coding agents, and I think one same problem that I recurringly heard a lot of them run into was this problem of like, “Oh, Grep is really slow on our agents' machines.” And so a lot of them, I assume because they're using AI and they themselves don't have, super deep infra background knowledge, say, “Okay, we're going to go build our own custom Grep index. It's going to be really fast,” and use that as a way around this problem. When we ran into this problem About like, maybe like a year and a half ago when we were, in the early days of building Devin, we obviously didn't have AI then. We just asked our, how to, how to do this. You can just swap out a new Grep index, so.Infrastructure Details: Grep, File Systems, and SandboxesSwyx [00:47:45]: What do you mean you hand-coded Devin? What?Walden [00:47:48]: It's like, can you believe we hand-wrote this code? And we had, our infra people who are really amazing, they were looking into it and they're like, “Oh, what? We realized that actually the root cause of this problem is actually super simple, but like fine-grain detail,” which is that a lot of these virtual machines actually underlying them don't use real file systems. They use these, network file systems where things are actually cached over the network actually in S3. So when you're Grepping, you're actually making network calls Every time you're doing these things, and that's why Grep is extremely slow on these machines. And so again, goes back to, what is all of the crazy infra work that we had to do to actually get these machines working. If you try to do this yourself, there are tons of small details like this, and so we had to eventually go swap out that network file system. ButSwyx [00:48:35]: I think there's a write-up about it, right? Silas did one about the virtual file system.Walden [00:48:38]: Oh, that was a whole other thing. TheSwyx [00:48:39]: Oh, that's a different thingWalden [00:48:40]: The BlockDev file storage formatSwyx [00:48:42]: I'll bring it upWalden [00:48:42]: Which is, a file system format that we built so that the VMs could be spun up and down very quickly. Basically, the intuition behind this is-Imagine you have, a terabyte of disk, and your agent only, wrote, a hundred lines of code on top of that disk. How long does it, say, take to, save and re-bring up that disk? And most systems, because you're not optimizing for this case, it's just, on the order of a terabyte of work because you have to Save all of that and bring it back up. In our system, we try to build a file system that incrementally builds on top of each other. So every time you save and bring the machine back up, you're only doing work that is proportional to effectively the diff in the file system. And so this, shaves off a lot of time in the boot-up process of Devin. I think we This is actually now outdated. We have a newer system inside of Devin. But yeah, there's a lot of tiny details you have to get right here to actually get the day-to-day experience of Devin to be good.Swyx [00:49:39]: It's, not technically agents, but it is agent infra, and when you sell an agent as a company, you sell agent plus agent infra.Walden [00:49:46]: At least the way we do it be And the other The nice thing about having the agent infra being done together is, you We get to deploy Devin in whatever environment we want now. We don't need to wait for some underlying infra provider to also go and support VPC or on-prem or FedGovCloud, for instance. So we can actually go and figure out, okay, since we own the infrastructure, how can we get that set up for you?Cloud Providers: Modal, Daytona, and Enterprise SandboxesSwyx [00:50:12]: Whereas you're Cloudflare dependent.Cole [00:50:15]: so Cloudflare runs the control plane. The sandboxes, Modal is supported. A contributor just added Daytona. E2B is on the roadmap, and I think there's an abstraction in place that if any contributor wants to add a new provider, they can add that in.Walden [00:50:32]: Well, what are, How are the customers you work with Do they generally try to then go set up a contract with another one of these third-party providers? Do they try to do the VMs in-house?Cole [00:50:44]: most of them I see using Modal. I think Modal has a greatWalden [00:50:48]: Shout out Modal.Swyx [00:50:48]: Shout out Modal.Cole [00:50:50]: I think Modal has a great offering. It captures all of the sandbox pieces you need, snapshots being a pretty big piece of that, and given that they also offer GPUs, I think it's a pretty nice offering as a whole.Swyx [00:51:04]: no debate there.Walden [00:51:07]: Modal is great, especially, I think their container offering is, the most natural, and so especially if you are willing to, forego, the full VM requirements Modal is, a really vast place you can spin something up on.Swyx [00:51:20]: Is there a point So Modal's very Python, and I feel like most workload, has really shifted to JavaScript. I don't know if you guys Get the same feeling. So, okay, when I started Landspace and IE and all these things, I was like 50/50 Python and JS, right? That's roughly. I think that's wrong now. I think JS has won. I don't know if you guys Like, I Maybe I'm overstating it, and maybe for cognition, there's, C# and Java and what have you. But for, new greenfield apps, do you feel that Do you get that sense? Does it matter?Cole [00:51:52]: I think that most of the libraries that I see in this space are Python native first, especially in theCole [00:51:58]: Observability space. That said, I think that there is a pretty big appeal of having your entire system in one language. Especially when you have both your frontend and backend communicating, you can have one central type Which is very nice.Swyx [00:52:11]: That's my case against Modal, which is Then you have to run JS. You can run JS inside Modal. It's just, one extra step That, isn't native to the runtime. I don't know ifWalden [00:52:22]: I don't knowSwyx [00:52:23]: Reviews. Do you have numbers? I don't know.Walden [00:52:25]: the one thing I don't like about Python is whenever AI, whenever it writes Python, it always does, the weirdest patterns, andSwyx [00:52:32]: Oh, because it's, mixing two and three or what?Walden [00:52:34]: I think it's something mixing two and three, yeah. The I don't know if you see this. It always tries to do, has attribute on objects as likeCole [00:52:41]: Oh, my God.Walden [00:52:41]: But it's like But that you shouldn't be doing that. It should error if there wasSwyx [00:52:45]: Because it's training on library code?Cole [00:52:47]: I think it's more of, likeCole [00:52:48]: From what I've seen, it's more of, a reward hacking mechanism where it doesn't want to basicallyWalden [00:52:54]: It'll never error.Cole [00:52:54]: It doesn't want the code to fail. And so it Even when it knows it has the attribute, it'll call getattr on a, and for a lot of my clients who have moved towards more autonomous coding, we've put that in as a lint rule That if you do getattr, your pull request is going to fail.Slop Signatures: Comments, Backwards Compatibility, and TypesSwyx [00:53:12]: Ooh, this is a fun topic. Can you tell me more about this? What else is a sign of AI coding that you have to put guards in?Walden [00:53:21]: So we were talking just before this about Opus 4.7. One of the things this new model likes to do is it writes lots of comments. Not like, it'll, comment every line, but it'll write, paragraph, PRDs, on top of every function. But I will say, to its credit, these aren't slop, descriptions like they were before. “Oh, here's what this function does.” It's like, “Oh, here's actually the r

In the latest Confluence Mailbag, Bill O'Grady and Mark Keller revisit their long-held forecast that US hegemony is in decline and consider what a return to a multipolar world order could mean for investors, outlining the shifts and surprises that may shape the evolving geopolitical landscape. The discussion examines the underappreciated economic risks of the Iran conflict, the implications of a 100% debt-to-GDP ratio, and the factors that could challenge their bullish commodity outlook, before closing on a cautionary read of narrowing market breadth as a signal that AI momentum may be nearing its peak.

Get more from the experts our community loves. There is a reason Jacob Diaz and Liev Dalton are community favorites. Their monthly Terrain Wellness Club calls have become a staple for our members, providing a space for interactive learning, presentations, and terrain-based health deep-dives that you won't find anywhere else. Become a Platinum member of The Way Forward Community today to see why these calls are the highlight of the month.Use code FWRD for 10% off Beyond Terrain Academy.Diseases like Lyme and mold illness do not work like they told us.Liev Dalton and Jacob Diaz join me on this episode to discuss what happens when terrain-based thinking collides with chronic diagnoses, parasite cleanses, and the wellness industry's obsession with magic bullets. Both of them walked away from systems that promised answers, Liev from licensed therapy, Jacob from organized religion, and ended up somewhere most practitioners never reach. Liev is a biochemist-turned-terrain educator whose work focuses on unlearning modern misconceptions and returning to simplicity. Jacob is a terrain-based Naturopathic Physician practicing in Queens, NYC, and the creator of the UnderCoverVirologist platform.Our conversation moves through Lyme, mold, AIDS, Crohn's, herpes, and the diagnostic loopholes that keep people cycling through tests until they find one that sticks. Along the way: why antibiotics appear to work, what helminth therapy reveals about deworming, and why translocation gets mistaken for transformation.Underneath it all is a thread about faith, coherence, and what changes when you stop trying to fix yourself.You'll Learn:[0:00] Introduction[7:53] The Jesus message that arrived mid-podcast[14:38] My daughter throwing up coagulated blood through a German new medicine lens[23:53] The Mandela effect, the black raven, and why the Bible keeps changing[40:09] The cat with four white paws and what suffering actually means[47:24] Praying with the cop who pulled me over for going 74 in a 55[55:03] How Liev tried to disprove Kaufman and ended up unleashed by his professors[1:08:31] Why boiling toxic water works, and what Pasteur got fundamentally wrong[1:26:52] Why chronic Lyme is a made-up diagnosis, and mold only heals in the forest[2:10:38] What herpes, AIDS, and STDs actually are, and why the cover story held[2:33:54] Why removing parasites causes disease, and what fenbendazole really doesRelated The Way Forward Episodes:Rethinking DNA: Examining the Evidence featuring Dr. Tom Cowan | YouTubeResources Mentioned:Dissolving Illusions by Suzanne Humphries | BookBitten by Kris Newby | BookThe Emperor's New Virus | DocumentaryFind more from Jacob and Liev:Jacob Diaz, Terrain U.V. | WebsiteLiev Dalton, Beyond Terrain | Website | YouTubeFind more from Alec:Alec Zeck | Instagram | XThe Way Forward | InstagramDonate to The Way Forward here.The Way Forward is Sponsored By:PaleoValley: 100% Grass-Fed Bone Broth Protein is a nutrient-dense, easy-to-digest source of collagen and essential amino acids. Sourced from grass-fed cows, this protein powder provides the building blocks for healthy joints, skin, and gut function—without fillers or artificial ingredients. Support the show and claim 15% off your PaleoValley order!Reconnect with the earth's natural charge and move naturally by using code FWRD10 for 10% off at Earth Runners.New Biology Clinic: Redefine Health from the Ground UpExperience tailored terrain-based health services with consults, livestreams, movement classes, and more. Use code THEWAYFORWARD (case sensitive) for $50 off activation.The Way Forward members get the $150 fee waived.

What does AI transformation actually look like inside one of the world's largest engineering organizations? At Team '26 in Anaheim, I recently sat down with Jason Andrews to unpack how Cisco transformed decades of fragmented tooling, disconnected workflows, and spreadsheet-driven operations into a unified system of work built around Jira, Confluence, Jira Service Management, automation, and AI-ready workflows. And honestly, this conversation felt refreshingly practical. Jason oversees engineering operations across Cisco Networking, a business unit with around 22,000 engineers and product managers representing roughly $40 billion in annual revenue. So when he talks about transformation, this isn't theory. This is operational change happening at enterprise scale. We discuss how Cisco consolidated more than 85 Jira instances, reduced tooling spend by 54%, and accelerated reporting by 40x while creating a far more scalable engineering organization. But as Jason explains throughout the conversation, the real challenge was never the technology itself. It was getting teams to rethink how they wanted to work moving forward rather than simply migrating years of technical debt into modern systems. One of the strongest themes in this episode is the difference between transformation and migration. Jason explains why organizations often fail when they focus only on moving systems rather than changing workflows, behaviors, and operational culture at the same time. We also dive deep into AI adoption inside engineering organizations. Jason shares how Cisco is already seeing significant productivity gains from AI-assisted development, why organizational context matters so much for enterprise AI success, and why he believes the industry is still massively underestimating how much structured data and workflow consistency AI systems actually require. Along the way, we unpack scenario planning in the AI era, why annual planning cycles are becoming increasingly fragile, and how leaders can move from rigid long-term roadmaps toward more agile operational playbooks capable of adapting to constant disruption. There's also a fascinating discussion around the so-called "SaaS apocalypse," the limits of AI-generated software, and why Jason believes humans will remain central to enterprise operations for years to come, especially in organizations managing millions of lines of legacy code and decades of accumulated institutional knowledge. If your organization is currently navigating modernization, operational complexity, AI adoption, or large-scale systems transformation, this episode is packed with lessons learned from the front lines of enterprise change. And perhaps most importantly, Jason offers a reminder that AI alone is not the strategy. The real opportunity comes from reducing friction, improving context, and helping teams spend more time solving meaningful problems instead of manually stitching systems together.

Steve Nison shares how he discovered Japanese candlestick charting techniques in the 1980s, translated Japanese literature, and successfully applied these methods in trading. He explains candlestick construction, the importance of context, and combining patterns with other technical indicators for better signals. Steve also emphasizes strict risk management through protective stop losses. Despite market evolution and the rise of AI, he affirms that candlestick principles remain relevant, as human emotions like fear and greed continue driving markets. https://tradingnut.com/steve-nison/ - Steve's Links

In this episode, Confluence reviews the Asset Allocation rebalance for the second quarter of 2026, featuring a brief economic analysis and insights on asset class and security selection for the firm's Asset Allocation portfolios. Joining the podcast to recap the rationale for this quarter's changes is Kaisa Stucke, analyst and chair of the Asset Allocation Committee's quarterly investment meetings.

What happens when AI stops being a feature and starts reshaping the very craft of design itself? Live from, I sat down with Charlie Sutton for a conversation that went far beyond product interfaces and pixels. As Atlassian unveiled its latest AI ambitions around agents, context, and the Teamwork Graph, Charlie offered a fascinating look at the human side of that transformation and why design may become even more important as AI becomes embedded into the way we work. Charlie shared how Atlassian approaches design at scale across products like Jira, Confluence, Loom, and Rovo, explaining why every interaction should feel intentional and cohesive, even when built by hundreds of people across dozens of teams. But this conversation quickly moved into much bigger territory. We explored how AI is changing the relationship between designers, developers, and business teams, and why the traditional barriers between idea and execution are rapidly disappearing. One of the most thought-provoking parts of the discussion centered around democratization. Charlie argued that while AI tools have dramatically lowered the floor for creativity, they have also raised the ceiling for what users now expect from software experiences. Anyone can prototype an app today, but expectations around quality, coherence, trust, and usability are climbing just as quickly. We also unpacked the growing shift from prompting AI to delegating work to AI agents. Charlie explained why assigning work to agents increasingly resembles managing human teammates, from defining goals and success criteria to understanding strengths, limitations, and context. That naturally led us into a deeper conversation about trust, transparency, and why users must always feel they can "pop the bonnet" and understand what AI systems are doing on their behalf. Another major theme throughout the episode was context. Charlie shared why Atlassian sees organizational context as one of the defining challenges of the AI era and how the Teamwork Graph is helping connect people, projects, conversations, and knowledge across the company. He compared this moment to the first time many of us used Google search and suddenly realized the scale of what was possible. We also discussed how AI adoption is unfolding differently from previous technology waves. Instead of adoption trickling down from hardcore technical users, Charlie is seeing rapid experimentation from marketing, HR, and design teams looking to reduce repetitive work and communicate ideas more effectively. Even his own mother, he joked, has become an AI power user before he has. From AltaVista nostalgia and Ask Jeeves memories to serious conversations about the future of human creativity, this episode captures a rare and honest perspective on where design, collaboration, and AI may be heading next. How will organizations balance personalization with shared experiences as AI becomes embedded into every workflow, and what role will human creativity play when everyone suddenly has access to the same powerful tools? Please check the partners of the Tech Tech Talks Network Learn more about the NordLayer Browser Visit Denodo.com

What happens when one of the most iconic teams in Formula One decides to rethink how work gets done behind the scenes completely? Last year, Atlassian Williams Racing made headlines when Atlassian entered Formula One as both title partner and technology partner. At the time, many people saw the partnership as another high-profile sponsorship deal. But over the last twelve months, something much bigger has been unfolding inside the Williams organization. At Team '26 in Anaheim, I sat down with Andrew Boyagi and Matt Harman to unpack how AI, data, workflows, and organizational transformation are reshaping life both at the factory and on the grid. This conversation goes far beyond racing. Matt explains how Williams is reducing the time between "idea to track," compressing development cycles so upgrades arrive at race weekends weeks earlier than before. One striking example involves reducing front wing lead times by a factor of three through parallel workflows and better collaboration, allowing performance gains to reach the circuit three race weekends sooner. Andrew shares how Atlassian's system-of-work philosophy is being applied in one of the most data-intensive environments on earth. We explore how tools like Jira, Confluence, Loom, Rovo, and Teamwork Graph are helping engineers, strategists, operations teams, and factory staff make faster decisions with less operational friction. We also discuss how AI is changing engineers' roles, why organizational context matters more than raw intelligence, and how Formula One teams balance human instinct with AI-driven precision in race strategy decisions. Matt offers fascinating insight into how AI helps teams process decades of historical race data in real time while still relying on human judgment in critical moments. Along the way, we explore the cultural transformation underway at Williams, including the shift away from endless meetings toward faster, outcome-focused collaboration. Matt explains how tools like Loom and Confluence are helping teams make decisions more efficiently while spreading knowledge more effectively across specialist departments. Andrew also reveals some eye-opening metrics from the partnership so far. Since rolling out Atlassian's Teamwork Collection, teams have reportedly increased throughput by 83%, while low-value meetings have been reduced by 863 hours in a single month across 200 people. Perhaps the biggest takeaway from this episode is that Formula One may actually be a perfect reflection of the challenges facing every modern business. As Andrew puts it during our conversation, Formula One is ultimately "an enterprise performance problem," just operating at 300 kilometers an hour with millions of people watching every weekend. If you've ever wondered what enterprise transformation looks like when milliseconds matter, this episode offers a fascinating look inside one of the most ambitious AI and workflow transformation journeys happening anywhere in business today   Please check the partners of the Tech Tech Talks Network Learn more about the NordLayer Browser Visit Denodo.com

For several years in my forties, I swam in the ocean each morning. The water was cold when we dove into the Bay and often times it would take a while before my strokes would find the rhythm of the waves in order that I wouldn't swallow too much water whenever I turned my thermal cap covered head to take a breath as I watched the city lights in the dawn of early morning.This past week has been full. We went to our daughter's and son's gathering in Texas, where over 1000 people gathered for Confluence, and yesterday I sat with my sister through her 4-plus hour appointment for her first chemotherapy infusion.Listen in as we explore just how our job is to ride the waves of life.Thank you for being here; you matter.I am offering sessions on Tuesday mornings. If you want an elder to hold space for you and reflect on your amazingness, sign up on my website. I am always happy to hear from you.You can reach me at terces@tercesengelhart.com, and I will reply. Additionally, if you would like to order my book directly from me, I am happy to send you a signed copy. Please email me, and I'll send it to you. ($15 plus shipping)If you know of anyone who might benefit from listening in, share a link to an episode with them; in other words, be an invitation to join us. Get full access to Terces's Substack at engelhart.substack.com/subscribe

Boris Berenberg bootstrapped Atlas Authority, an Atlassian partner that resold Jira and Confluence to mid-market companies and built apps on top of the platform, to high seven figures in revenue with 18% net margins, then sold to private equity in May 2022.  A year later he wrote a blog post titled "I regret selling my startup" that went viral inside the exited founder community. 

Mareko & Geoff answer your questions an horse around. Thanks again to Evenheat, Damasteel, Brodbeck Ironworks, Texas Farrier Supply, Indasa, Tormek, Indasa, Maritime Knife Supply and Tormek for the support.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy