Podcasts about Observable

Sponsor Link:To grab our special money saving NordVPN deal - Click HereIn today's episode, Anna and Avery cover a blue whale-sized asteroid making a close pass of Earth today, the imminent debut of SpaceX's most powerful rocket yet, NASA's Psyche spacecraft successfully completing its Mars gravity assist, fresh science arriving at the ISS, a new physics paper challenging the simulation hypothesis at its foundations, and Congress pushing back hard against proposed cuts to NASA's science budget.   Story 1 — Asteroid 2026 JH2 Newly discovered asteroid 2026 JH2 (first spotted 10 May 2026) makes a close Earth flyby today at ~90,000 km — within the orbital radius of many satellites. Estimated size: up to ~35 metres (blue whale-sized). Zero impact risk confirmed. Observable with binoculars at peak magnitude ~11.5. Live stream available via the Virtual Telescope Project. Orbital period: 3.7 years between Earth and Jupiter.   Story 2 — Starship V3 / Flight 12 SpaceX targets May 19, 2026 for the debut of Starship Version 3 (Flight 12) from Pad 2 at Starbase, Texas. Launch window opens 6:30 PM EDT. Key upgrades: Raptor 3 engines (250 tf SL thrust, up from 230 tf), three larger grid fins, new integrated hot-stage design, updated propellant systems. No tower catch on this flight; booster splashes in Gulf of Mexico. Upper stage (Ship 39) targets Indian Ocean after 65 minutes. Payload: 22 Starlink simulator satellites. Critical step toward Artemis lunar landings.   Story 3 — NASA Psyche Mars Flyby On 15 May 2026 at 3:28 PM EDT, Psyche completed its Mars gravity assist at 4,500 km altitude travelling at 12,333 mph. Passed inside the orbits of both Martian moons. Confirmed by Doppler shift monitoring. Mission: en route to metal-rich asteroid 16 Psyche (arrival July 2029). Thousands of Mars observations gathered for science calibration.   Story 4 — SpaceX CRS-34 SpaceX's 34th Dragon cargo mission docked at ISS at 6:37 AM EDT on 17 May 2026, delivering ~6,500 lb of cargo for Expedition 74. Science payloads include: microgravity simulator validation study, wood-based bone scaffold (osteoporosis research), red blood cell/spleen spaceflight study. Dragon will return to Earth mid-June splashing down off California coast.   Story 5 — Simulation Hypothesis Paper Paper: ‘Non-algorithmic physics and the limits of the simulation hypothesis', published in the Journal of Holography Applications in Physics. Authors: Mir Faizal (UBC Okanagan), Lawrence Krauss, Arshid Shabir, Francesco Marino. Core argument: using Gödel's incompleteness theorems, the team argues any theory of quantum gravity would be non-algorithmic — containing truths no computation can capture. Since any simulation requires algorithms, reality cannot be fully simulated. Note: this is a theoretical paper, not an experimental result. The authors acknowledge no complete quantum gravity theory currently exists.   Story 6 — NASA FY2027 Budget House Appropriations Committee approved $24.438 billion for NASA in FY2027 — matching FY2026 and rejecting the White House's proposed $18.8 billion (a 23% cut). The proposal would have cut the Science Mission Directorate by 46%, terminating 50+ missions. Committee protects science, Habitable Worlds Observatory, and STEM education funding. Bill still needs Senate passage and reconciliation.   Skywatching TONIGHT — Moon-Venus conjunction: look west after sunset for the crescent Moon close to brilliant Venus. Earthshine visible on dark lunar limb. Southern Hemisphere: look west-northwest, best in first hour after sunset. Blue Moon on 31 May (second full Moon of the month).  Become a supporter of this podcast: https://www.spreaker.com/podcast/astronomy-daily-space-news-updates--5648921/support.Sponsor Details:Ensure your online privacy by using NordVPN. To get our special listener deal and save a lot of money, visit www.bitesz.com/nordvpn. You'll be glad you did!Become a supporter of Astronomy Daily by joining our Supporters Club. Commercial free episodes daily are only a click way... Click HereThis episode includes AI-generated content.

"Hee hee. Ow!" Those are the noises you make when a laser from an alien spacecraft shoots you in 1967 Manitoba. Or when a diamond-shaped craft in rural Texas bathes you in radiation on a cold December night in 1980. Or when you're just trying to sleep on a Brazilian island and something called "Chupa Chupa" decides to use you as a snack. Those incidents -and hundreds like them = add up to something even stranger than the aliens, cryptids, or apparitions themselves. A pattern. A map. A theory that explains all of it. You're going to find out what that is in this episode. By the time you finish listening to this episode, perhaps by the time you've finished reading this sentence, this week's guest will have finished writing yet another fact-supported, heavily detailed, richly sourced book about ancient archaeology. Or alien sightings. Or religious apparitions. Or cryptids. Or climate shifts across the millennia. Yes, any of those topics. And yes, a full book. If Substack tried to contain the output of George Mitrovic, returning champion, it would crash like a saucer in '47. (Seriously, the Greys don't use Waymo?!) He's the HARDEST WORKING MAN IN FRINGE RESEARCH. Prolific, wise, witty, honest, and the unquestionable KING OF P.O.P. (Paranormal Observable Phenomena, i.e., a bunch of people have seen it and it's left physical traces. Saucers with souvenirs, Bigfoot leaving skidmarks, you get the picture). With over 150 books, one of the highest measured IQs on his side of the world, and a lifetime of research, scholarship, data mapping, pattern recognition, and scientific analysis, George brings something unique to the world of paranormal research: a grand unifying framework for where and why paranormal events happen. Fully mapped, explained, and unlimited in its potential. In this episode, Greg sits down with George to get to the bottom of why this may be the most important scholarship on the unexplained that nobody is talking about. If you've ever wanted to traverse the multiverse, George's Sine Wave Theory is your ticket to other dimensions. You ARE the cryptid. We all are. George's Links:

Matt and Ben explore the intersection of testing, metrics, and observability in performance-critical code. They debate push vs pull metric systems, share war stories from financial trading systems, and ponder what to do when your program can't tell anyone it's in trouble.

A right relationship with God has a way of turning things upside down. Consider the evidence: Daniel remained at ease the night he spent in a den of hungry lions, while the king whose law put Daniel there lay tossing on his bed in torment of soul. What a difference a clean conscience makes! "My God sent His angel and shut the lions' mouths, and they have not harmed me, inasmuch as I was found innocent before Him," exclaimed Daniel the next morning. "... and also toward you, O king, I have done no harm." Last week, we saw the character God formed in Daniel before the crisis. This week, we'll see what that relationship with God produces during the crisis. To believe we're kept by God's sovereign hand gives us boldness as His exiles. And to know He favors His covenant people, that our sins have been blotted out, gives us confidence even when we face our own death. Observable boldness and quiet confidence are the fruit of a right relationship with God—and a display case for His power to deliver. Even the wicked, like Babylon's King Darius, see God's power at work among His people. "... men are to fear and be in dread before the God of Daniel," Daniel 6:26 (LSB). "... for He is the living God and enduring forever, and His kingdom is one which will not be destroyed, and His dominion will be unto the end." This Lord's Day, we'll finish our look at Daniel 6, concluding the first half of the book of Daniel. I hope you'll join us as we consider, "God's People in Exile: Conscience Before Confidence." Prepare for Sunday: Read and meditate on Daniel 6, focusing on verses 18-28. What contrasts do you see between Daniel and Darius? Why was Daniel delivered

https://teachhoops.com/ Communicating your vision is the most important "Pre-Game" activity you will ever perform. A vision isn't just a list of goals; it is a vivid picture of a future that hasn't happened yet. If you can't describe exactly what your program will look like, sound like, and feel like in three years, you can't expect your players or community to buy in. To be effective, your vision must move from "Abstract" to "Observable." Instead of saying "We want to be a tough program," say "We will be the team that is first to the floor for every loose ball and the loudest team in the hallway before every tip-off." When you make the vision "visible," you give your athletes a specific standard to measure themselves against every single day. The second pillar of communication is "The Power of Repetition." A vision is not a "One-and-Done" speech at the parent meeting in November; it is a daily "drip." You must be the "Chief Reminding Officer" of your program. Every drill, every post-game talk, and every social media post should be filtered through your vision. If your vision is "Unselfish Excellence," then you must publicly celebrate the "Extra Pass" more than the "Crossover Layup." In the mid-season January grind, when fatigue sets in, the vision is the "Why" that keeps your players pushing through the "How." Use your TeachHoops member calls to "audit" your messaging: if you asked your 12th man what the program's vision is, could they answer you in ten seconds? Finally, you must master "The Art of the Individual Connection." While you cast a broad vision for the team, you must also communicate a "Micro-Vision" for every individual. Every player needs to know exactly how their unique "Role" contributes to the "Master Plan." When a player understands that their "bench energy" or their "defensive rebounding" is a vital organ in the body of the program, they find "Purpose in the Process." Utilize "Vision One-on-Ones"—short, 5-minute meetings where you paint a picture of who that player can become by the end of the season. By connecting their personal growth to the program's success, you create an unbreakable bond of "Shared Ownership" that lasts long after the final buzzer. Basketball vision, coaching leadership, program building, team culture, athletic leadership, high school basketball, youth basketball, basketball IQ, coach development, championship habits, "Trust Equity" in sports, coaching philosophy, character development, coach unplugged, teach hoops, basketball success, mental toughness, leadership standards, communication skills for coaches, organizational vision. SEO Keywords Learn more about your ad choices. Visit podcastchoices.com/adchoices

Send a textMost people have looked to the skies and wondered if the universe has a boundary, or maybe it goes on for ever. The universe might be finite, with and end somewhere. Or, it might be infinite, with an infinite amount of space and matter. Both of thos throw up some mind bending questions, and maybe even real life duplicates of ourselves. Problem is, we would never be able to observe them, or even test for their presence, or even know if they exist. So does it matter?Follow Cosmic Coffee Time on X for some special contentX.com/CosmicCoffTimeEmail us! cosmiccoffeetime@gmail.comYou can request a topic for the show! Or even just say hi!We'd love to hear from you.

View This Week's Show NotesStart Your 7-Day Trial to Mobility CoachJoin Our Free Weekly Newsletter: The AmbushIn a world obsessed with “optimal” routines, Dr. Rachel Pojednic cuts through the noise with a grounded, evidence-based approach to longevity and performance. This conversation is a reset for anyone overwhelmed by conflicting health advice, anxious about wearable scores, or stuck chasing perfect protocols that collapse under real life stress.You'll learn what the science actually supports, what's still uncertain, and how to build a simple, sustainable health strategy using the biggest levers first—movement, nutrition, sleep, stress, and relationships—before you bother with the “fun stuff.” Dr. Pojednic also shares what she's learned studying wellness therapies in industry and academia, why most people misunderstand Zone 2, and what to track if you want a clearer picture of your health over time.What You'll Learn in This EpisodeWhy “protocol life” is making people more confused (and often less healthy)The difference between big levers (high impact) and little levers (fine-tuning) for longevityWhat to track that's actually useful: A1C trends, fasting glucose, lipids, resting heart rateWhy wearable metrics can conflict—and how that can create anxiety and false certaintyA clearer, non-hype explanation of HRV and why “low” isn't always “bad”What Zone 2 is really for (and why it isn't a magical mitochondrial hack)How to think about supplement safety, including third-party testing and the “lead in protein powder” scareA simple 7–30 day “one change” experiment to build habits that survive real lifeIf you've ever felt like you're “failing” health because you can't follow a perfect routine—or you've been pulled in six directions by influencers, devices, and contradictory advice—this episode gives you something rare: a sane framework. You'll walk away with fewer rules, better priorities, and a practical way to measure progress that doesn't depend on hype, fear, or the latest trend.Chapters(00:00) - Intro(01:39) - The Problem with Protocols(05:29) - Rachele's Backstory and Research Journey(13:06) - Rachele's Research Focus(18:45) - Sponsor: Vitality Blueprint(20:40) - Science Communication and Social Media(23:24) - Getting Started in Science Communication(25:10) - Bridging Research and Real-World Applications(29:35) - New Lane for Performance Therapy(31:05) - Key Metrics to Track(32:07) - Importance of Observable, Measurable Data(34:34) - Need for Common Diagnostic Suite(40:19) - Current State of Healthcare and EHRs(42:32) - Momentous: Protein Powder Insights(44:44) - Subscribe to This Podcast(46:30) - Basics We Can All Agree On(47:10) - Regular Tracking Essentials(53:10) - Heart Rate Variability (HRV)(54:42) - Wearables and Big Games(57:06) - Desire to Train(59:28) - Big Opportunity and Challenges(1:00:30) - Rapid Fire: Zone 2(1:03:02) - LMNT: Try a Personal Experiment(1:06:58) - Your Micro-Experiment(1:10:34) - Rachele's “Infinite Shelf” Recommendation(1:14:55) - Join The Starrett SystemWebsite | Instagram | Facebook | YouTubeCheck our Dr. Rachele's courses at Strong ProcessHuge thanks to our sponsors, Vitality, Momentous, and LMNT.

Show Highlights: External forces that challenge co-ops in today's ag world. [00:36] The myth of co-op member alignment vs. diverging needs. [02:18] Explore the key drivers of co-op member misalignment. [07:07] Observable signals and costs of misalignment in co-ops. [11:06] Why co-ops must segment members like a business, not a club. [13:31] Successful explicit segmentation criteria for co-ops. [14:32] Leaning into the discomfort of strategic segmentation. [17:00] The mechanics of segmentation and pitfalls to avoid. [18:58] Embracing tough inevitable trade-offs to let clarity win. [22:18] Discover clear signs of effective member segmentation. [26:36] If you are interested in connecting with Joe, go to LinkedIn: https://www.linkedin.com/in/joemosher/, or schedule a call at www.moshercg.com.

Join the Free Kickstart ChallengeSummaryIn this episode of the AI in Football podcast, hosts Tom Butterfield and David Bromley delve into the significance of defining a game model in football recruitment. They discuss how a clear identity can streamline recruitment decisions, emphasizing the importance of observable player behaviors and the integration of AI in enhancing scouting processes. The conversation covers the various phases of a game, the implications for recruitment, and the necessity of proof behaviors to measure team performance effectively. The episode concludes with a look ahead to future discussions on formations and role archetypes.TakeawaysRecruitment decisions should align with a club's identity.Defining a game model helps clarify recruitment needs.Observable behaviors are essential for effective coaching.Simplicity in defining player roles aids understanding.Proof behaviors provide measurable standards for performance.AI can enhance the recruitment process by standardizing evaluations.Clarity in communication between coaches and scouts is crucial.Identifying specific behaviours aids in player scouting.Game phases must be understood for effective strategy implementation.A concise game model fosters better team cohesion.Useful LinksJoin the Free Kickstart ChallengeSupport The Show - Buy David and Tom a bag of peanut M&M's.InstagramYoutube Channel

In this episode of The Product Experience, host Lily Smith speaks with veteran product leader Sean Flaherty about a question at the heart of modern product management: how do you influence without authority? Drawing from behavioural science and decades of experience building products and teams, Sean outlines a framework based on self‑determination theory — the modern science of intrinsic motivation.Through the lens of autonomy, competence and relatedness, Sean explains why traditional command‑and‑control leadership undermines creativity and accountability. He shows how true autonomy is structured freedom, how competence is demonstrated through behaviour, and how relatedness builds trust and advocacy among teams and users. Along the way he reframes accountability as something teams hold themselves to, not something enforced by fear, and discusses how leaders can help teams grow, adapt and thrive in a world of constant change.Chapters00:00 — Introduction & central question01:30 — Guest background04:45 — State of leadership today06:10 — Intro to intrinsic motivation08:40 — The “code” of motivation12:28 — Autonomy in teams17:11 — Competence and product work20:30 — Observable behaviour and growth paths23:10 — Adaptability and learning culture24:25 — Accountability misunderstood27:04 — Accountability spectrum31:21 — Addressing negative behaviour36:19 — AI and leadership change38:01 — Leadership trends todayKey Takeaways— Motivation is scientific, not abstract— Product leaders need to understand the science of intrinsic motivation — not just processes or tools — to influence without authority and achieve sustainable outcomes.— Three core motivators drive behaviourAutonomy: people need meaningful choice, not chaos or micro‑managementCompetence: motivation increases when people feel capable and are supported to growRelatedness: connection and shared purpose power trust, loyalty and advocacy— Autonomy is structured freedom: Autonomy is not “do whatever you want”. It's about balancing freedom with guidance so teams can be creative but not lost.— Competence is observed in behaviour, not checklists: Real competence shows up in behaviour — what people do — not just knowledge or titles.— Accountability emerges, not enforced: Traditional accountability relies on fear and external control. In contrast, self‑accountability arises when goals are meaningful and environments allow peopleOur HostsLily Smith enjoys working as a consultant product manager with early-stage and growing startups and as a mentor to other product managers. She's currently Chief Product Officer at BBC Maestro, and has spent 13 years in the tech industry working with startups in the SaaS and mobile space. She's worked on a diverse range of products – leading the product teams through discovery, prototyping, testing and delivery. Lily also founded ProductTank Bristol and runs ProductCamp in Bristol and Bath. Randy Silver is a Leadership & Product Coach and Consultant. He gets teams unstuck, helping you to supercharge your results. Randy's held interim CPO and Leadership roles at scale-ups and SMEs, advised start-ups, and been Head of Product at HSBC and Sainsbury's. He participated in Silicon Valley Product Group's Coaching the Coaches forum, and speaks frequently at conferences and events. You can join one of communities he runs for CPOs (CPO Circles), Product Managers (Product In the {A}ether) and Product Coaches. He's the author of What Do We Do Now? A Product Manager's Guide to Strategy in the Time of COVID-19. A recovering music journalist and editor, Randy also launched Amazon's music stores in the US & UK.

In this second part of my three-part series (catch Part I via episode 182), I dig deeper into the key idea that sales in commercial data products can be accelerated by designing for actual user workflows—vs. going wide with a “many-purpose” AI and analytics solution that “does more,” but is misaligned with how users' most important work actually gets done.   To explain this, I will explain the concept of user experience (UX) outcomes, and how building your solution to enable these outcomes may be a dependency for you to get sales traction, and for your customer to see the value of your solution. I also share practical steps to improve UX outcomes in commercial data products, from establishing a baseline definition of UX quality to mapping out users' current workflows (and future ones, when agentic AI changes their job). Finally, I talk about how approaching product development as small “bets” helps you build small, and learn fast so you can accelerate value creation.    Highlights/ Skip to: Continuing the journey: designing for users, workflows, and tasks (00:32) How UX impacts sales—not just usage and  adoption(02:16) Understanding how you can leverage users' frustrations and perceived risks as fuel for building an indispensable data product (04:11)  Definition of a UX outcome (7:30) Establishing a baseline definition of product (UX) quality, so you know how to observe and measure improvement (11:04 ) Spotting friction and solving the right customer problems first (15:34) Collecting actionable user feedback (20:02) Moving users along the scale from frustration to satisfaction to delight (23:04) Unique challenges of designing B2B AI and analytics products used for decision intelligence (25:04) Quotes from Today's Episode One of the hardest parts of building anything meaningful, especially in B2B or data-heavy spaces, is pausing long enough to ask what the actual ‘it' is that we're trying to solve. People rush into building the fix, pitching the feature, or drafting the roadmap before they've taken even a moment to define what the user keeps tripping over in their day-to-day environment.   And until you slow down and articulate that shared, observable frustration, you're basically operating on vibes and assumptions instead of behavior and reality.   What you want is not a generic problem statement but an agreed-upon description of the two or three most painful frictions that are obvious to everyone involved, frictions the user experiences visibly and repeatedly in the flow of work.   Once you have that grounding, everything else prioritization, design decisions, sequencing, even organizational alignment suddenly becomes much easier because you're no longer debating abstractions, you're working against the same measurable anchor.   And the irony is, the faster you try to skip this step, the longer the project drags on, because every downstream conversation becomes a debate about interpretive language rather than a conversation about a shared, observable experience. __ Want people to pay for your product? Solve an *observable* problem—not a vague information or data problem. What do I mean? “When you're trying to solve a problem for users, especially in analytical or AI-driven products, one of the biggest traps is relying on interpretive statements instead of observable ones.   Interpretive phrasing like ‘they're overwhelmed' or ‘they don't trust the data' feels descriptive, but it hides the important question of what, exactly, we can see them doing that signals the problem.   If you can't film it happening, if you can't watch the behavior occur in real time, then you don't actually have a problem definition you can design around.   Observable frustration might be the user jumping between four screens, copying and pasting the same value into different systems, or re-running a query five times because something feels off even though they can't articulate why.   Those concrete behaviors are what allow teams to converge and say, ‘Yes, that's the thing, that is the friction we agree must change,' and that shift from interpretation to observation becomes the foundation for better design, better decision-making, and far less wasted effort.   And once you anchor the conversation in visible behavior, you eliminate so many circular debates and give everyone, from engineering to leadership, a shared starting point that's grounded in reality instead of theory." __ One of the reasons that measuring the usability/utility/satisfaction of your product's UX might seem hard is that you don't have a baseline definition of how satisfactory (or not) the product is right now. As such, it's very hard to tell if you're just making product *changes*—or you're making *improvements* that might make the product worth paying for at all, worth paying more for, or easier to buy. "It's surprisingly common for teams to claim they're improving something when they've never taken the time to document what the current state even looks like. If you want to create a meaningful improvement, something a user actually feels, you need to understand the baseline level of friction they tolerate today, not what you imagine that friction might be. Establishing a baseline is not glamorous work, but it's the work that prevents you from building changes that make sense on paper but do nothing to the real flow of work. When you diagram the existing workflow, when you map the sequence of steps the user actually takes, the mismatches between your mental model and their lived experience become crystal clear, and the design direction becomes far less ambiguous. That act of grounding yourself in the current state allows every subsequent decision, prioritizing fixes, determining scope, measuring progress, to be aligned with reality rather than assumptions. And without that baseline, you risk designing solutions that float in conceptual space, disconnected from the very pains you claim to be addressing." __ Prototypes are a great way to learn—if you're actually treating them as a means to learn, and not a product you intend to deliver regardless of the feedback customers give you.  "People often think prototyping is about validating whether their solution works, but the deeper purpose is to refine the problem itself. Once you put even a rough prototype in front of someone and watch what they do with it, you discover the edges of the problem more accurately than any conversation or meeting can reveal. Users will click in surprising places, ignore the part you thought mattered most, or reveal entirely different frictions just by trying to interact with the thing you placed in front of them. That process doesn't just improve the design, it improves the team's understanding of which parts of the problem are real and which parts were just guesses. Prototyping becomes a kind of externalization of assumptions, forcing you to confront whether you're solving the friction that actually holds back the flow of work or a friction you merely predicted. And every iteration becomes less about perfecting the interface and more about sharpening the clarity of the underlying problem, which is why the teams that prototype early tend to build faster, with better alignment, and far fewer detours." __ Most founders and data people tend to measure UX quality by “counting usage” of their solution. Tracking usage stats, analytics on sessions, etc. The problem with this is that it tells you nothing useful about whether people are satisfied (“meets spec”) or delighted (“a product they can't live without”). These are product metrics—but they don't reflect how people feel. There are better measurements to use for evaluating users' experience that go beyond “willingness to pay.”  Payment is great, but in B2B products, buyers aren't always users—and we've all bought something based on the promise of what it would do for us, but the promise fell short. "In B2B analytics and AI products, the biggest challenge isn't complexity, it's ambiguity around what outcome the product is actually responsible for changing.   Teams often define success in terms of internal goals like ‘adoption,' ‘usage,' or ‘efficiency,' but those metrics don't tell you what the user's experience is supposed to look like once the product is working well.   A product tied to vague business outcomes tends to drift because no one agrees on what the improvement should feel like in the user's real workflow.   What you want are visible, measurable, user-centric outcomes, outcomes that describe how the user's behavior or experience will change once the solution is in place, down to the concrete actions they'll no longer need to take.   When you articulate outcomes at that level, it forces the entire organization to align around a shared target, reduces the scope bloat that normally plagues enterprise products, and gives you a way to evaluate whether you're actually removing friction rather than just adding more layers of tooling.   And ironically, the clearer the user outcome is, the easier it becomes to achieve the business outcome, because the product is no longer floating in abstraction, it's anchored in the lived reality of the people who use it."   Links Listen to part one: Episode 182  Schedule a Design-Eyes Assessment with me and get clarity, now.

How do you monitor distributed systems that span dozens of microservices, multiple languages, and different databases? The old approach of gathering logs from different machines and recompiling apps with profiling flags doesn't scale when you're running thousands of servers. You need a unified strategy that works everywhere, on every component, in every language—and that means tackling the problem from the kernel level up.Mohammed Aboullaite is a backend engineer at Spotify, and he joins us to explore the latest in continuous profiling and observability using eBPF. We dive into how eBPF lets you programmatically peek into the Linux kernel without recompiling it, why companies like Google and Meta run profiling across their entire infrastructure, and how to manage the massive data volumes that continuous profiling generates. Mohammed walks through specific tools like Pyroscope, Pixie, and Parca, explains the security model of loading code into the kernel, and shares practical advice on overhead thresholds, storage strategies, and getting organizational buy-in for continuous profiling.Whether you're debugging performance issues, optimizing for scale, or just want to see what your code is really doing in production, this episode covers everything from packet filters to cultural changes in service of getting a clear view of your software when it hits production.---Support Developer Voices on Patreon: https://patreon.com/DeveloperVoicesSupport Developer Voices on YouTube: https://www.youtube.com/@DeveloperVoices/joineBPF: https://ebpf.io/Google-Wide Profiling Paper (2010): https://research.google.com/pubs/archive/36575.pdfGoogle pprof: https://github.com/google/pprofContinuous Profiling Tools:Pyroscope (Grafana): https://grafana.com/oss/pyroscope/Pixie (CNCF): https://px.dev/Parca: https://www.parca.dev/Datadog Continuous Profiler: https://www.datadoghq.com/product/code-profiling/Supporting Technologies:OpenTelemetry: https://opentelemetry.io/Grafana: https://grafana.com/New Relic: https://newrelic.com/Envoy Proxy: https://www.envoyproxy.io/Spring Cloud Sleuth: https://spring.io/projects/spring-cloud-sleuthMohammed Aboullaite:LinkedIn: https://www.linkedin.com/in/aboullaite/GitHub: https://github.com/aboullaiteWebsite: http://aboullaite.meTwitter/X: https://twitter.com/laytounKris on Bluesky: https://bsky.app/profile/krisajenkins.bsky.socialKris on Mastodon: http://mastodon.social/@krisajenkinsKris on LinkedIn: https://www.linkedin.com/in/krisjenkins/

Send us a textIn this episode of the Deep Dive, the hosts explore the principles behind explosive large-scale discipleship movements, focusing on the work of Aychi. They emphasize the importance of prioritizing relationship over religion, discussing how this approach leads to observable lifestyle changes in new disciples. The conversation highlights the role of divine encounters in transforming individuals and the practical outreach strategies that avoid religious debates. Cultural sensitivity is also addressed, emphasizing the need for a relationship with Jesus to guide necessary changes within local contexts. The episode concludes with a reflection on the power of relationship in driving these movements.TakeawaysThe core idea is to prioritize relationship, not religion.Hope without assurance leads to constant striving.Obedience should flow from love, not duty.Observable lifestyle changes are key in discipleship.Divine encounters can break through resistance.Outreach should avoid religious debates.Building trust is essential in conversations.Cultural elements can be redeemed, not discarded.The focus should be on internal transformation.The distinction between religion and relationship drives movements. Support the show

In this episode of the storytelling with data podcast, Simon chats with Allison Horst—developer advocate at Observable, educator, and beloved data illustrator—to explore the difference between dashboards that get used and those that don't.They dig into why so many data products go to waste, the importance of co-creating with your audience, and the overlooked power of early feedback. Allison reflects on her experiences helping people go from "I built this thing" to "This actually gets used"—and how teams can better collaborate to avoid dashboard graveyards.Along the way, they talk about environmental storytelling, visual metaphors, teaching the “gray areas” of data viz, and why curiosity (not perfection) is the key to lasting impact.Related Links:Check out Allison's work at: https://allisonhorst.com/Connect with and follow her on LNKD: https://www.linkedin.com/in/allison-horst/Order SWD's latest book, Before & After https://www.storytellingwithdata.com/books

Observable phenomena that precede changes in larger markets are found everywhere…hence why I believe a trio of trending nutraceutical ingredients could be a powerful leading indicator for the next generation of energy drinks. And I want to set the stage by providing my basic mental model surrounding the market evolution of energy drinks. Firstly, energy drinks are no longer just sugar-filled flavored caffeinated carbonated waters. In fact, more than half of all energy drinks sold in the United States are sugar free. Secondly, energy drinks are no longer marketed primarily to thrill-seeking young males. In fact, energy drink consumers have evolved greatly…with the current market largely gender-balanced, age-balanced, and lifestyle-oriented. Lastly, energy drinks are no longer a niche beverage category. In fact, the categorical mainstreaming effect catapulted three energy drink brands onto the top ten list of largest liquid refreshment beverages. Additionally, every multibillion-dollar functional beverage category (such as energy drinks) is in the early innings of a remarkable transformation…as consumers move closer towards this four-way intersection of taste, convenience, nutrition, and (not only) functionality (but) multifunctional benefits that contribute to overall wellbeing. And I'm not debating against plain ole great tasting sugar free energy drinks remaining a consumption evergreen…but an evolving arbitrage will continue existing due to individuals not wanting totally different consumption habits (just more beneficial ones). So, amidst this booming desire for packing more functionality within energy drinks…savvy ingredient companies have found a catalyst to mainstream awareness and mass acceptance. Currently, almost all energy drink consumers understand the category as stimulation (delivered through caffeine). Yet, even against the backdrop of likely the highest consumer interest level in caffeine ever…why then do I think Cognizin citicoline, goBHB ketones, and Enfinity paraxanthine, will play an outsized role in the next generation of energy drinks? For the evolving RTD energy category, that increasingly serves as a euphemism for other benefits like alertness, focus, reduced fatigue, and improved endurance…consumers concentrating around a handful of clear outcomes will play an important role in how these nutraceutical ingredients (beyond caffeine) deliver relevant products that tap into broader market opportunities. Also, over the last handful of years…work-life balance has gotten redefined (and adjusted bi-directionally), as the typical 9-to-5 work schedule intermixes with other segments of personal time. Additionally, consider the widening range of applications and “physical versus mental energy” need states this functional beverage category can serve like active nutrition, cognitive performance, and healthy aging…suggesting consumers (more than ever) are looking for solutions that help energize them throughout the day (even into the night) and help recovery for the next day. But then why does caffeine still dominate as the primary ingredient solution? Caffeine is universally lauded for its ability to kickstart the day, with effects felt almost immediately, but the ingredient does have its limitations. So, taking into consideration those well-known limiting factors…how about I briefly describe some of the underlying drivers of demand that support my non-consensus (and early) conviction around escalating importance of (Cognizin, goBHB, and Enfinity paraxanthine) within the next generation of energy drinks.

Burnout isn't always about “too much work.” In this Healthy Mind, Healthy Life episode, leadership advisor and former Nike executive Nick Montalbine breaks down three overlooked forms of burnout—overload, under-challenged, and neglect—and explains why misalignment and weak feedback loops quietly drain teams. We dig into early signals (withdrawal, sharper tone, Sunday dread), how continuous listening beats annual surveys, and a practical 90-day challenge any company can run to rebuild trust and retention. Direct, useful, and built for leaders and contributors who want healthier performance without the hustle myth. Guest: Nick Montalbine. About the Guest   Nick Montalbine is a leadership advisor, former Nike executive, and founder of Inner Voice Analytics. He helps organizations detect cultural cracks early through behavioral signals, ongoing listening, and actionable data—so people stay energized, seen, and productive. Key Takeaways   Burnout has three types: overload (too much), under-challenged (bored/misaligned), and neglect (helplessness). A “dream job” can still burn you out if it doesn't light you up or fit your strengths. Observable leader cues: withdrawal from collaboration, sharper tone, reduced stretch-taking, rising irritability. Self-signals: concentration slips, short-term memory lapses, insomnia (e.g., waking at the same time nightly), and Sunday dread. Culture accelerators of burnout: infrequent surveys, slow action on feedback, and failure to reach team-level issues. Move from annual/pulse surveys to continuous listening mapped to the employee lifecycle (apply → onboard → grow → exit). Use people data (e.g., turnover patterns) to find “smoke” and intervene before fires start. If you have one lever, pull trust through action: run focused listening sessions, ship quick wins, and communicate progress. 90-day challenge: ask 7–10 sharp questions (value, career mobility, meaning/strategy link), separate short- vs. long-term fixes, and show weekly momentum. Personal alignment isn't fluffy; it's a performance driver and a retention moat.   How to Connect with the Guest   Nick Montalbine — Founder, Inner Voice Analytics - https://www.innervoiceanalytics.com/ Best avenues: LinkedIn (Nick Montalbine) and search “Inner Voice Analytics” for contact options. Want to be a guest on Healthy Mind, Healthy Life? DM on PM - Send me a message on PodMatch DM Me Here: https://www.podmatch.com/hostdetailpreview/avik Disclaimer: This video is for educational and informational purposes only. The views expressed are the personal opinions of the guest and do not reflect the views of the host or Healthy Mind By Avik™️. We do not intend to harm, defame, or discredit any person, organization, brand, product, country, or profession mentioned. All third-party media used remain the property of their respective owners and are used under fair use for informational purposes. By watching, you acknowledge and accept this disclaimer. Healthy Mind By Avik™️ is a global platform redefining mental health as a necessity, not a luxury. Born during the pandemic, it's become a sanctuary for healing, growth, and mindful living. Hosted by Avik Chakraborty—storyteller, survivor, wellness advocate—this channel shares powerful podcasts and soul-nurturing conversations on: • Mental Health & Emotional Well-being• Mindfulness & Spiritual Growth• Holistic Healing & Conscious Living• Trauma Recovery & Self-Empowerment With over 4,400+ episodes and 168.4K+ global listeners, join us as we unite voices, break stigma, and build a world where every story matters.

Data visualization is increasingly important as organizations prioritize data-driven decision-making. Tools that transform complex datasets into intuitive, interpretable visualizations are arguably just as critical as the data itself. Robert Kosara is a Data Visualization Developer at Observable which is a platform for creating interactive data visualizations, and which makes extensive use of the popular D3 The post Modern Data Visualization with Robert Kosara appeared first on Software Engineering Daily.

Data visualization is increasingly important as organizations prioritize data-driven decision-making. Tools that transform complex datasets into intuitive, interpretable visualizations are arguably just as critical as the data itself. Robert Kosara is a Data Visualization Developer at Observable which is a platform for creating interactive data visualizations, and which makes extensive use of the popular D3 The post Modern Data Visualization with Robert Kosara appeared first on Software Engineering Daily.

God's Majesty is Vast, Observable, Bestowed on Mankind and Revealed in Jesus Christ

Bridging the Gap Between AI and Business Data // MLOps Podcast #325 with Deepti Srivastava, Founder and CEO at Snow Leopard.Join the Community: https://go.mlops.community/YTJoinInGet the newsletter: https://go.mlops.community/YTNewsletter// AbstractI'm sure the MLOps community is probably aware – it's tough to make AI work in enterprises for many reasons, from data silos, data privacy and security concerns, to going from POCs to production applications. But one of the biggest challenges facing businesses today, that I particularly care about, is how to unlock the true potential of AI by leveraging a company's operational business data. At Snow Leopard, we aim to bridge the gap between AI systems and critical business data that is locked away in databases, data warehouses, and other API-based systems, so enterprises can use live business data from any data source – whether it's database, warehouse, or APIs – in real time and on demand, natively. In this interview, I'd like to cover Snow Leopard's intelligent data retrieval approach that can leverage business data directly and on-demand to make AI work.// BioDeepti is the founder and CEO of Snow Leopard AI, a platform that helps teams build AI apps using their live business data, on-demand. She has nearly 2 decades of experience in data platforms and infrastructure.As Head of Product at Observable, Deepti led the 0→1 product and GTM strategy in the crowded data analytics market. Before that, Deepti was the founding PM for Google Spanner, growing it to thousands of internal customers (Ads, PlayStore, Gmail, etc.), before launching it externally as a seminal cloud database service. Deepti started her career as a distributed systems engineer in the RAC database kernel at Oracle.// Related LinksWebsite: https://www.snowleopard.ai/AI SQL Data Analyst // Donné Stevenson - https://youtu.be/hwgoNmyCGhQ~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our Slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Deepti on LinkedIn: /thedeepti/Timestamps:[00:00] Deepti's preferred coffee[00:49] MLflow vs Kubeflow Debate[04:58] GenAI Data Integration Challenges[09:02] GenAI Sidecar Spicy Takes[14:07] Troubleshooting LLM Hallucinations[19:03] AI Overengineering and Hype[25:06] Self-Serve Analytics Governance[33:29] Dashboards vs Data Quality[37:06] Agent Database Context Control[43:00] LLM as Orchestrator[47:34] Tool Call Ownership Clarification[51:45] MCP Server Challenges[56:52] Wrap up

One Another: Observable Love with Pastor Jason Eddy www.betheljanesville.org

Tous les matins à 8H10, Salomé nous donne des infos aléatoires du monde.

John 2:23 Now when He was in Jerusalem at the Passover, during the feast, many believed in His name, observing His signs which He was doing. The things Jesus did in the temple took place during the Passover, which means His coming death and resurrection were on top of mind. Surely He could not observe the Passover Sabbath week without thinking that He was the substance of the events. He was the lamb slain. His was the blood to be spilled and would mark the doors of hearts over which the death angel would pass. So the cleansing of the temple was a sign among many signs, apparently, done during the feast. John testifies in this verse that there was a faith of some sort generated by the signs. At first glance, this seems like a good thing. However, we are going to learn in the following verses that faith that comes from undeniable facts isn't the same as faith generated by the Holy Spirit. We'll talk more about that in the days to come. The point I want to make for our encouragement is what I have been saying in the last few days. We, the church, are a sign that God has placed before the world. As we live to love with Jesus, many will observe our love and believe in His name. But that doesn't mean they are born again or have new lives. Not everyone who says they believe has eternal life. They may believe it because they cannot deny the facts. Many people have grown up in Christian homes who are like the believers spoken of in this and the following verses. They cannot deny what they have seen, heard, and experienced. They have once been enlightened, have tasted of the heavenly gift, have been made partakers of the Holy Spirit, and have tasted of the good word of God and the powers of the age to come, as it says in Hebrews 6:4-5. Yet, they fall away in unbelief. Their salvation is not our responsibility. Our responsibility is to be an observable sign that Jesus is God living in bodies of flesh—our bodies. His love in us is the sign of new life and the power of God. Let us live to love with Jesus for His purposes and His glory, leaving all who cross our paths in His hands. We may trust the Holy Spirit to do the miraculous work of imparting new life as He wills. I invite you to become a partner in our ministry. Would you pray about becoming a regular supporter of Elijah Ministries and the Live to Love with Jesus ministry? I hope you will receive the joy and benefit of “giving it forward,” so others may receive encouragement to turn their hearts to God and to live to love with Jesus. You may give online or send a check to the address listed at www.spiritofelijah.com/donate.

In this episode of R Weekly Highlights: We have a six-month follow-up perspective from an early Positron user, how the current landscape of AI tools perform when learning the ropes with the Tidyverse, and how you can create your first Observable plot while using R for data munging.Episode LinksThis week's curator: Jon Carroll - @jonocarroll@fosstodon.org (Mastodon) & @jonocarroll.fosstodon.org.ap.brid.gy (Bluesky) & @carroll_jono (X/Twitter)Positron: current joys and painsLearning the tidyverse with the help of AI toolsObservable for R usersEntire issue available at rweekly.org/2025-W15Supplement ResourcesPositron +1e https://open-vsx.org/extension/grrrck/positron-plus-1-eVanishing Gradients episode 47 (The Great Pacific Garbage Patch of Code Slop with Joe Reis) https://vanishinggradients.fireside.fm/47Observable color palette viewer https://observablehq.com/plot/features/scales#color-scalesObservable Plots (R/Pharma 2024 Workshop Series) https://www.youtube.com/watch?v=M6fP68XnacMSupporting the showUse the contact page at https://serve.podhome.fm/custompage/r-weekly-highlights/contact to send us your feedbackR-Weekly Highlights on the Podcastindex.org - You can send a boost into the show directly in the Podcast Index. First, top-up with Alby, and then head over to the R-Weekly Highlights podcast entry on the index.A new way to think about value: https://value4value.infoGet in touch with us on social mediaEric Nantz: @rpodcast@podcastindex.social (Mastodon), @rpodcast.bsky.social (BlueSky) and @theRcast (X/Twitter)Mike Thomas: @mike_thomas@fosstodon.org (Mastodon), @mike-thomas.bsky.social (BlueSky), and @mike_ketchbrook (X/Twitter) Music credits powered by OCRemixSunny Side Up - Yoshi's Island DS - ZackParrish - https://ocremix.org/remix/OCR04558Costa Del Sol DANCE - Final Fantasy VII - Posu Yan - https://ocremix.org/remix/OCR00095

User research is an underappreciated art - we in tech are so used to being immersed in an ocean of quantitative data that we can forget that on the other side of the screen are real humans who want to solve very specific problems. And often times, their problems are extremely hard to put a number on. Why did they abandon their cart right before checkout? What made them start creating a new newsletter but then abandon it but come back a month later? Not everything can be answered with a SQL query against the telemetry database. Marisa Morby, a Principal Researcher at Observable, sat down with me to help me better understand what it means to be great (not just good) at user research, and how that can help produce a whole new range of unexpected product insights. And Marisa definitely knows what the impact of great user research can be on the product - she previously worked at such notable companies like Netlify, Gatsby, and Accenture Song, where she honed her skills and UX instincts.

Today's episode is with Paul Klein, founder of Browserbase. We talked about building browser infrastructure for AI agents, the future of agent authentication, and their open source framework Stagehand.* [00:00:00] Introductions* [00:04:46] AI-specific challenges in browser infrastructure* [00:07:05] Multimodality in AI-Powered Browsing* [00:12:26] Running headless browsers at scale* [00:18:46] Geolocation when proxying* [00:21:25] CAPTCHAs and Agent Auth* [00:28:21] Building “User take over” functionality* [00:33:43] Stagehand: AI web browsing framework* [00:38:58] OpenAI's Operator and computer use agents* [00:44:44] Surprising use cases of Browserbase* [00:47:18] Future of browser automation and market competition* [00:53:11] Being a solo founderTranscriptAlessio [00:00:04]: Hey everyone, welcome to the Latent Space podcast. This is Alessio, partner and CTO at Decibel Partners, and I'm joined by my co-host Swyx, founder of Smol.ai.swyx [00:00:12]: Hey, and today we are very blessed to have our friends, Paul Klein, for the fourth, the fourth, CEO of Browserbase. Welcome.Paul [00:00:21]: Thanks guys. Yeah, I'm happy to be here. I've been lucky to know both of you for like a couple of years now, I think. So it's just like we're hanging out, you know, with three ginormous microphones in front of our face. It's totally normal hangout.swyx [00:00:34]: Yeah. We've actually mentioned you on the podcast, I think, more often than any other Solaris tenant. Just because like you're one of the, you know, best performing, I think, LLM tool companies that have started up in the last couple of years.Paul [00:00:50]: Yeah, I mean, it's been a whirlwind of a year, like Browserbase is actually pretty close to our first birthday. So we are one years old. And going from, you know, starting a company as a solo founder to... To, you know, having a team of 20 people, you know, a series A, but also being able to support hundreds of AI companies that are building AI applications that go out and automate the web. It's just been like, really cool. It's been happening a little too fast. I think like collectively as an AI industry, let's just take a week off together. I took my first vacation actually two weeks ago, and Operator came out on the first day, and then a week later, DeepSeat came out. And I'm like on vacation trying to chill. I'm like, we got to build with this stuff, right? So it's been a breakneck year. But I'm super happy to be here and like talk more about all the stuff we're seeing. And I'd love to hear kind of what you guys are excited about too, and share with it, you know?swyx [00:01:39]: Where to start? So people, you've done a bunch of podcasts. I think I strongly recommend Jack Bridger's Scaling DevTools, as well as Turner Novak's The Peel. And, you know, I'm sure there's others. So you covered your Twilio story in the past, talked about StreamClub, you got acquired to Mux, and then you left to start Browserbase. So maybe we just start with what is Browserbase? Yeah.Paul [00:02:02]: Browserbase is the web browser for your AI. We're building headless browser infrastructure, which are browsers that run in a server environment that's accessible to developers via APIs and SDKs. It's really hard to run a web browser in the cloud. You guys are probably running Chrome on your computers, and that's using a lot of resources, right? So if you want to run a web browser or thousands of web browsers, you can't just spin up a bunch of lambdas. You actually need to use a secure containerized environment. You have to scale it up and down. It's a stateful system. And that infrastructure is, like, super painful. And I know that firsthand, because at my last company, StreamClub, I was CTO, and I was building our own internal headless browser infrastructure. That's actually why we sold the company, is because Mux really wanted to buy our headless browser infrastructure that we'd built. And it's just a super hard problem. And I actually told my co-founders, I would never start another company unless it was a browser infrastructure company. And it turns out that's really necessary in the age of AI, when AI can actually go out and interact with websites, click on buttons, fill in forms. You need AI to do all of that work in an actual browser running somewhere on a server. And BrowserBase powers that.swyx [00:03:08]: While you're talking about it, it occurred to me, not that you're going to be acquired or anything, but it occurred to me that it would be really funny if you became the Nikita Beer of headless browser companies. You just have one trick, and you make browser companies that get acquired.Paul [00:03:23]: I truly do only have one trick. I'm screwed if it's not for headless browsers. I'm not a Go programmer. You know, I'm in AI grant. You know, browsers is an AI grant. But we were the only company in that AI grant batch that used zero dollars on AI spend. You know, we're purely an infrastructure company. So as much as people want to ask me about reinforcement learning, I might not be the best guy to talk about that. But if you want to ask about headless browser infrastructure at scale, I can talk your ear off. So that's really my area of expertise. And it's a pretty niche thing. Like, nobody has done what we're doing at scale before. So we're happy to be the experts.swyx [00:03:59]: You do have an AI thing, stagehand. We can talk about the sort of core of browser-based first, and then maybe stagehand. Yeah, stagehand is kind of the web browsing framework. Yeah.What is Browserbase? Headless Browser Infrastructure ExplainedAlessio [00:04:10]: Yeah. Yeah. And maybe how you got to browser-based and what problems you saw. So one of the first things I worked on as a software engineer was integration testing. Sauce Labs was kind of like the main thing at the time. And then we had Selenium, we had Playbrite, we had all these different browser things. But it's always been super hard to do. So obviously you've worked on this before. When you started browser-based, what were the challenges? What were the AI-specific challenges that you saw versus, there's kind of like all the usual running browser at scale in the cloud, which has been a problem for years. What are like the AI unique things that you saw that like traditional purchase just didn't cover? Yeah.AI-specific challenges in browser infrastructurePaul [00:04:46]: First and foremost, I think back to like the first thing I did as a developer, like as a kid when I was writing code, I wanted to write code that did stuff for me. You know, I wanted to write code to automate my life. And I do that probably by using curl or beautiful soup to fetch data from a web browser. And I think I still do that now that I'm in the cloud. And the other thing that I think is a huge challenge for me is that you can't just create a web site and parse that data. And we all know that now like, you know, taking HTML and plugging that into an LLM, you can extract insights, you can summarize. So it was very clear that now like dynamic web scraping became very possible with the rise of large language models or a lot easier. And that was like a clear reason why there's been more usage of headless browsers, which are necessary because a lot of modern websites don't expose all of their page content via a simple HTTP request. You know, they actually do require you to run this type of code for a specific time. JavaScript on the page to hydrate this. Airbnb is a great example. You go to airbnb.com. A lot of that content on the page isn't there until after they run the initial hydration. So you can't just scrape it with a curl. You need to have some JavaScript run. And a browser is that JavaScript engine that's going to actually run all those requests on the page. So web data retrieval was definitely one driver of starting BrowserBase and the rise of being able to summarize that within LLM. Also, I was familiar with if I wanted to automate a website, I could write one script and that would work for one website. It was very static and deterministic. But the web is non-deterministic. The web is always changing. And until we had LLMs, there was no way to write scripts that you could write once that would run on any website. That would change with the structure of the website. Click the login button. It could mean something different on many different websites. And LLMs allow us to generate code on the fly to actually control that. So I think that rise of writing the generic automation scripts that can work on many different websites, to me, made it clear that browsers are going to be a lot more useful because now you can automate a lot more things without writing. If you wanted to write a script to book a demo call on 100 websites, previously, you had to write 100 scripts. Now you write one script that uses LLMs to generate that script. That's why we built our web browsing framework, StageHand, which does a lot of that work for you. But those two things, web data collection and then enhanced automation of many different websites, it just felt like big drivers for more browser infrastructure that would be required to power these kinds of features.Alessio [00:07:05]: And was multimodality also a big thing?Paul [00:07:08]: Now you can use the LLMs to look, even though the text in the dome might not be as friendly. Maybe my hot take is I was always kind of like, I didn't think vision would be as big of a driver. For UI automation, I felt like, you know, HTML is structured text and large language models are good with structured text. But it's clear that these computer use models are often vision driven, and they've been really pushing things forward. So definitely being multimodal, like rendering the page is required to take a screenshot to give that to a computer use model to take actions on a website. And it's just another win for browser. But I'll be honest, that wasn't what I was thinking early on. I didn't even think that we'd get here so fast with multimodality. I think we're going to have to get back to multimodal and vision models.swyx [00:07:50]: This is one of those things where I forgot to mention in my intro that I'm an investor in Browserbase. And I remember that when you pitched to me, like a lot of the stuff that we have today, we like wasn't on the original conversation. But I did have my original thesis was something that we've talked about on the podcast before, which is take the GPT store, the custom GPT store, all the every single checkbox and plugin is effectively a startup. And this was the browser one. I think the main hesitation, I think I actually took a while to get back to you. The main hesitation was that there were others. Like you're not the first hit list browser startup. It's not even your first hit list browser startup. There's always a question of like, will you be the category winner in a place where there's a bunch of incumbents, to be honest, that are bigger than you? They're just not targeted at the AI space. They don't have the backing of Nat Friedman. And there's a bunch of like, you're here in Silicon Valley. They're not. I don't know.Paul [00:08:47]: I don't know if that's, that was it, but like, there was a, yeah, I mean, like, I think I tried all the other ones and I was like, really disappointed. Like my background is from working at great developer tools, companies, and nothing had like the Vercel like experience. Um, like our biggest competitor actually is partly owned by private equity and they just jacked up their prices quite a bit. And the dashboard hasn't changed in five years. And I actually used them at my last company and tried them and I was like, oh man, like there really just needs to be something that's like the experience of these great infrastructure companies, like Stripe, like clerk, like Vercel that I use in love, but oriented towards this kind of like more specific category, which is browser infrastructure, which is really technically complex. Like a lot of stuff can go wrong on the internet when you're running a browser. The internet is very vast. There's a lot of different configurations. Like there's still websites that only work with internet explorer out there. How do you handle that when you're running your own browser infrastructure? These are the problems that we have to think about and solve at BrowserBase. And it's, it's certainly a labor of love, but I built this for me, first and foremost, I know it's super cheesy and everyone says that for like their startups, but it really, truly was for me. If you look at like the talks I've done even before BrowserBase, and I'm just like really excited to try and build a category defining infrastructure company. And it's, it's rare to have a new category of infrastructure exists. We're here in the Chroma offices and like, you know, vector databases is a new category of infrastructure. Is it, is it, I mean, we can, we're in their office, so, you know, we can, we can debate that one later. That is one.Multimodality in AI-Powered Browsingswyx [00:10:16]: That's one of the industry debates.Paul [00:10:17]: I guess we go back to the LLMOS talk that Karpathy gave way long ago. And like the browser box was very clearly there and it seemed like the people who were building in this space also agreed that browsers are a core primitive of infrastructure for the LLMOS that's going to exist in the future. And nobody was building something there that I wanted to use. So I had to go build it myself.swyx [00:10:38]: Yeah. I mean, exactly that talk that, that honestly, that diagram, every box is a startup and there's the code box and then there's the. The browser box. I think at some point they will start clashing there. There's always the question of the, are you a point solution or are you the sort of all in one? And I think the point solutions tend to win quickly, but then the only ones have a very tight cohesive experience. Yeah. Let's talk about just the hard problems of browser base you have on your website, which is beautiful. Thank you. Was there an agency that you used for that? Yeah. Herb.paris.Paul [00:11:11]: They're amazing. Herb.paris. Yeah. It's H-E-R-V-E. I highly recommend for developers. Developer tools, founders to work with consumer agencies because they end up building beautiful things and the Parisians know how to build beautiful interfaces. So I got to give prep.swyx [00:11:24]: And chat apps, apparently are, they are very fast. Oh yeah. The Mistral chat. Yeah. Mistral. Yeah.Paul [00:11:31]: Late chat.swyx [00:11:31]: Late chat. And then your videos as well, it was professionally shot, right? The series A video. Yeah.Alessio [00:11:36]: Nico did the videos. He's amazing. Not the initial video that you shot at the new one. First one was Austin.Paul [00:11:41]: Another, another video pretty surprised. But yeah, I mean, like, I think when you think about how you talk about your company. You have to think about the way you present yourself. It's, you know, as a developer, you think you evaluate a company based on like the API reliability and the P 95, but a lot of developers say, is the website good? Is the message clear? Do I like trust this founder? I'm building my whole feature on. So I've tried to nail that as well as like the reliability of the infrastructure. You're right. It's very hard. And there's a lot of kind of foot guns that you run into when running headless browsers at scale. Right.Competing with Existing Headless Browser Solutionsswyx [00:12:10]: So let's pick one. You have eight features here. Seamless integration. Scalability. Fast or speed. Secure. Observable. Stealth. That's interesting. Extensible and developer first. What comes to your mind as like the top two, three hardest ones? Yeah.Running headless browsers at scalePaul [00:12:26]: I think just running headless browsers at scale is like the hardest one. And maybe can I nerd out for a second? Is that okay? I heard this is a technical audience, so I'll talk to the other nerds. Whoa. They were listening. Yeah. They're upset. They're ready. The AGI is angry. Okay. So. So how do you run a browser in the cloud? Let's start with that, right? So let's say you're using a popular browser automation framework like Puppeteer, Playwright, and Selenium. Maybe you've written a code, some code locally on your computer that opens up Google. It finds the search bar and then types in, you know, search for Latent Space and hits the search button. That script works great locally. You can see the little browser open up. You want to take that to production. You want to run the script in a cloud environment. So when your laptop is closed, your browser is doing something. The browser is doing something. Well, I, we use Amazon. You can see the little browser open up. You know, the first thing I'd reach for is probably like some sort of serverless infrastructure. I would probably try and deploy on a Lambda. But Chrome itself is too big to run on a Lambda. It's over 250 megabytes. So you can't easily start it on a Lambda. So you maybe have to use something like Lambda layers to squeeze it in there. Maybe use a different Chromium build that's lighter. And you get it on the Lambda. Great. It works. But it runs super slowly. It's because Lambdas are very like resource limited. They only run like with one vCPU. You can run one process at a time. Remember, Chromium is super beefy. It's barely running on my MacBook Air. I'm still downloading it from a pre-run. Yeah, from the test earlier, right? I'm joking. But it's big, you know? So like Lambda, it just won't work really well. Maybe it'll work, but you need something faster. Your users want something faster. Okay. Well, let's put it on a beefier instance. Let's get an EC2 server running. Let's throw Chromium on there. Great. Okay. I can, that works well with one user. But what if I want to run like 10 Chromium instances, one for each of my users? Okay. Well, I might need two EC2 instances. Maybe 10. All of a sudden, you have multiple EC2 instances. This sounds like a problem for Kubernetes and Docker, right? Now, all of a sudden, you're using ECS or EKS, the Kubernetes or container solutions by Amazon. You're spending up and down containers, and you're spending a whole engineer's time on kind of maintaining this stateful distributed system. Those are some of the worst systems to run because when it's a stateful distributed system, it means that you are bound by the connections to that thing. You have to keep the browser open while someone is working with it, right? That's just a painful architecture to run. And there's all this other little gotchas with Chromium, like Chromium, which is the open source version of Chrome, by the way. You have to install all these fonts. You want emojis working in your browsers because your vision model is looking for the emoji. You need to make sure you have the emoji fonts. You need to make sure you have all the right extensions configured, like, oh, do you want ad blocking? How do you configure that? How do you actually record all these browser sessions? Like it's a headless browser. You can't look at it. So you need to have some sort of observability. Maybe you're recording videos and storing those somewhere. It all kind of adds up to be this just giant monster piece of your project when all you wanted to do was run a lot of browsers in production for this little script to go to google.com and search. And when I see a complex distributed system, I see an opportunity to build a great infrastructure company. And we really abstract that away with Browserbase where our customers can use these existing frameworks, Playwright, Publisher, Selenium, or our own stagehand and connect to our browsers in a serverless-like way. And control them, and then just disconnect when they're done. And they don't have to think about the complex distributed system behind all of that. They just get a browser running anywhere, anytime. Really easy to connect to.swyx [00:15:55]: I'm sure you have questions. My standard question with anything, so essentially you're a serverless browser company, and there's been other serverless things that I'm familiar with in the past, serverless GPUs, serverless website hosting. That's where I come from with Netlify. One question is just like, you promised to spin up thousands of servers. You promised to spin up thousands of browsers in milliseconds. I feel like there's no real solution that does that yet. And I'm just kind of curious how. The only solution I know, which is to kind of keep a kind of warm pool of servers around, which is expensive, but maybe not so expensive because it's just CPUs. So I'm just like, you know. Yeah.Browsers as a Core Primitive in AI InfrastructurePaul [00:16:36]: You nailed it, right? I mean, how do you offer a serverless-like experience with something that is clearly not serverless, right? And the answer is, you need to be able to run... We run many browsers on single nodes. We use Kubernetes at browser base. So we have many pods that are being scheduled. We have to predictably schedule them up or down. Yes, thousands of browsers in milliseconds is the best case scenario. If you hit us with 10,000 requests, you may hit a slower cold start, right? So we've done a lot of work on predictive scaling and being able to kind of route stuff to different regions where we have multiple regions of browser base where we have different pools available. You can also pick the region you want to go to based on like lower latency, round trip, time latency. It's very important with these types of things. There's a lot of requests going over the wire. So for us, like having a VM like Firecracker powering everything under the hood allows us to be super nimble and spin things up or down really quickly with strong multi-tenancy. But in the end, this is like the complex infrastructural challenges that we have to kind of deal with at browser base. And we have a lot more stuff on our roadmap to allow customers to have more levers to pull to exchange, do you want really fast browser startup times or do you want really low costs? And if you're willing to be more flexible on that, we may be able to kind of like work better for your use cases.swyx [00:17:44]: Since you used Firecracker, shouldn't Fargate do that for you or did you have to go lower level than that? We had to go lower level than that.Paul [00:17:51]: I find this a lot with Fargate customers, which is alarming for Fargate. We used to be a giant Fargate customer. Actually, the first version of browser base was ECS and Fargate. And unfortunately, it's a great product. I think we were actually the largest Fargate customer in our region for a little while. No, what? Yeah, seriously. And unfortunately, it's a great product, but I think if you're an infrastructure company, you actually have to have a deeper level of control over these primitives. I think it's the same thing is true with databases. We've used other database providers and I think-swyx [00:18:21]: Yeah, serverless Postgres.Paul [00:18:23]: Shocker. When you're an infrastructure company, you're on the hook if any provider has an outage. And I can't tell my customers like, hey, we went down because so-and-so went down. That's not acceptable. So for us, we've really moved to bringing things internally. It's kind of opposite of what we preach. We tell our customers, don't build this in-house, but then we're like, we build a lot of stuff in-house. But I think it just really depends on what is in the critical path. We try and have deep ownership of that.Alessio [00:18:46]: On the distributed location side, how does that work for the web where you might get sort of different content in different locations, but the customer is expecting, you know, if you're in the US, I'm expecting the US version. But if you're spinning up my browser in France, I might get the French version. Yeah.Paul [00:19:02]: Yeah. That's a good question. Well, generally, like on the localization, there is a thing called locale in the browser. You can set like what your locale is. If you're like in the ENUS browser or not, but some things do IP, IP based routing. And in that case, you may want to have a proxy. Like let's say you're running something in the, in Europe, but you want to make sure you're showing up from the US. You may want to use one of our proxy features so you can turn on proxies to say like, make sure these connections always come from the United States, which is necessary too, because when you're browsing the web, you're coming from like a, you know, data center IP, and that can make things a lot harder to browse web. So we do have kind of like this proxy super network. Yeah. We have a proxy for you based on where you're going, so you can reliably automate the web. But if you get scheduled in Europe, that doesn't happen as much. We try and schedule you as close to, you know, your origin that you're trying to go to. But generally you have control over the regions you can put your browsers in. So you can specify West one or East one or Europe. We only have one region of Europe right now, actually. Yeah.Alessio [00:19:55]: What's harder, the browser or the proxy? I feel like to me, it feels like actually proxying reliably at scale. It's much harder than spending up browsers at scale. I'm curious. It's all hard.Paul [00:20:06]: It's layers of hard, right? Yeah. I think it's different levels of hard. I think the thing with the proxy infrastructure is that we work with many different web proxy providers and some are better than others. Some have good days, some have bad days. And our customers who've built browser infrastructure on their own, they have to go and deal with sketchy actors. Like first they figure out their own browser infrastructure and then they got to go buy a proxy. And it's like you can pay in Bitcoin and it just kind of feels a little sus, right? It's like you're buying drugs when you're trying to get a proxy online. We have like deep relationships with these counterparties. We're able to audit them and say, is this proxy being sourced ethically? Like it's not running on someone's TV somewhere. Is it free range? Yeah. Free range organic proxies, right? Right. We do a level of diligence. We're SOC 2. So we have to understand what is going on here. But then we're able to make sure that like we route around proxy providers not working. There's proxy providers who will just, the proxy will stop working all of a sudden. And then if you don't have redundant proxying on your own browsers, that's hard down for you or you may get some serious impacts there. With us, like we intelligently know, hey, this proxy is not working. Let's go to this one. And you can kind of build a network of multiple providers to really guarantee the best uptime for our customers. Yeah. So you don't own any proxies? We don't own any proxies. You're right. The team has been saying who wants to like take home a little proxy server, but not yet. We're not there yet. You know?swyx [00:21:25]: It's a very mature market. I don't think you should build that yourself. Like you should just be a super customer of them. Yeah. Scraping, I think, is the main use case for that. I guess. Well, that leads us into CAPTCHAs and also off, but let's talk about CAPTCHAs. You had a little spiel that you wanted to talk about CAPTCHA stuff.Challenges of Scaling Browser InfrastructurePaul [00:21:43]: Oh, yeah. I was just, I think a lot of people ask, if you're thinking about proxies, you're thinking about CAPTCHAs too. I think it's the same thing. You can go buy CAPTCHA solvers online, but it's the same buying experience. It's some sketchy website, you have to integrate it. It's not fun to buy these things and you can't really trust that the docs are bad. What Browserbase does is we integrate a bunch of different CAPTCHAs. We do some stuff in-house, but generally we just integrate with a bunch of known vendors and continually monitor and maintain these things and say, is this working or not? Can we route around it or not? These are CAPTCHA solvers. CAPTCHA solvers, yeah. Not CAPTCHA providers, CAPTCHA solvers. Yeah, sorry. CAPTCHA solvers. We really try and make sure all of that works for you. I think as a dev, if I'm buying infrastructure, I want it all to work all the time and it's important for us to provide that experience by making sure everything does work and monitoring it on our own. Yeah. Right now, the world of CAPTCHAs is tricky. I think AI agents in particular are very much ahead of the internet infrastructure. CAPTCHAs are designed to block all types of bots, but there are now good bots and bad bots. I think in the future, CAPTCHAs will be able to identify who a good bot is, hopefully via some sort of KYC. For us, we've been very lucky. We have very little to no known abuse of Browserbase because we really look into who we work with. And for certain types of CAPTCHA solving, we only allow them on certain types of plans because we want to make sure that we can know what people are doing, what their use cases are. And that's really allowed us to try and be an arbiter of good bots, which is our long term goal. I want to build great relationships with people like Cloudflare so we can agree, hey, here are these acceptable bots. We'll identify them for you and make sure we flag when they come to your website. This is a good bot, you know?Alessio [00:23:23]: I see. And Cloudflare said they want to do more of this. So they're going to set by default, if they think you're an AI bot, they're going to reject. I'm curious if you think this is something that is going to be at the browser level or I mean, the DNS level with Cloudflare seems more where it should belong. But I'm curious how you think about it.Paul [00:23:40]: I think the web's going to change. You know, I think that the Internet as we have it right now is going to change. And we all need to just accept that the cat is out of the bag. And instead of kind of like wishing the Internet was like it was in the 2000s, we can have free content line that wouldn't be scraped. It's just it's not going to happen. And instead, we should think about like, one, how can we change? How can we change the models of, you know, information being published online so people can adequately commercialize it? But two, how do we rebuild applications that expect that AI agents are going to log in on their behalf? Those are the things that are going to allow us to kind of like identify good and bad bots. And I think the team at Clerk has been doing a really good job with this on the authentication side. I actually think that auth is the biggest thing that will prevent agents from accessing stuff, not captchas. And I think there will be agent auth in the future. I don't know if it's going to happen from an individual company, but actually authentication providers that have a, you know, hidden login as agent feature, which will then you put in your email, you'll get a push notification, say like, hey, your browser-based agent wants to log into your Airbnb. You can approve that and then the agent can proceed. That really circumvents the need for captchas or logging in as you and sharing your password. I think agent auth is going to be one way we identify good bots going forward. And I think a lot of this captcha solving stuff is really short-term problems as the internet kind of reorients itself around how it's going to work with agents browsing the web, just like people do. Yeah.Managing Distributed Browser Locations and Proxiesswyx [00:24:59]: Stitch recently was on Hacker News for talking about agent experience, AX, which is a thing that Netlify is also trying to clone and coin and talk about. And we've talked about this on our previous episodes before in a sense that I actually think that's like maybe the only part of the tech stack that needs to be kind of reinvented for agents. Everything else can stay the same, CLIs, APIs, whatever. But auth, yeah, we need agent auth. And it's mostly like short-lived, like it should not, it should be a distinct, identity from the human, but paired. I almost think like in the same way that every social network should have your main profile and then your alt accounts or your Finsta, it's almost like, you know, every, every human token should be paired with the agent token and the agent token can go and do stuff on behalf of the human token, but not be presumed to be the human. Yeah.Paul [00:25:48]: It's like, it's, it's actually very similar to OAuth is what I'm thinking. And, you know, Thread from Stitch is an investor, Colin from Clerk, Octaventures, all investors in browser-based because like, I hope they solve this because they'll make browser-based submission more possible. So we don't have to overcome all these hurdles, but I think it will be an OAuth-like flow where an agent will ask to log in as you, you'll approve the scopes. Like it can book an apartment on Airbnb, but it can't like message anybody. And then, you know, the agent will have some sort of like role-based access control within an application. Yeah. I'm excited for that.swyx [00:26:16]: The tricky part is just, there's one, one layer of delegation here, which is like, you're authoring my user's user or something like that. I don't know if that's tricky or not. Does that make sense? Yeah.Paul [00:26:25]: You know, actually at Twilio, I worked on the login identity and access. Management teams, right? So like I built Twilio's login page.swyx [00:26:31]: You were an intern on that team and then you became the lead in two years? Yeah.Paul [00:26:34]: Yeah. I started as an intern in 2016 and then I was the tech lead of that team. How? That's not normal. I didn't have a life. He's not normal. Look at this guy. I didn't have a girlfriend. I just loved my job. I don't know. I applied to 500 internships for my first job and I got rejected from every single one of them except for Twilio and then eventually Amazon. And they took a shot on me and like, I was getting paid money to write code, which was my dream. Yeah. Yeah. I'm very lucky that like this coding thing worked out because I was going to be doing it regardless. And yeah, I was able to kind of spend a lot of time on a team that was growing at a company that was growing. So it informed a lot of this stuff here. I think these are problems that have been solved with like the SAML protocol with SSO. I think it's a really interesting stuff with like WebAuthn, like these different types of authentication, like schemes that you can use to authenticate people. The tooling is all there. It just needs to be tweaked a little bit to work for agents. And I think the fact that there are companies that are already. Providing authentication as a service really sets it up. Well, the thing that's hard is like reinventing the internet for agents. We don't want to rebuild the internet. That's an impossible task. And I think people often say like, well, we'll have this second layer of APIs built for agents. I'm like, we will for the top use cases, but instead of we can just tweak the internet as is, which is on the authentication side, I think we're going to be the dumb ones going forward. Unfortunately, I think AI is going to be able to do a lot of the tasks that we do online, which means that it will be able to go to websites, click buttons on our behalf and log in on our behalf too. So with this kind of like web agent future happening, I think with some small structural changes, like you said, it feels like it could all slot in really nicely with the existing internet.Handling CAPTCHAs and Agent Authenticationswyx [00:28:08]: There's one more thing, which is the, your live view iframe, which lets you take, take control. Yeah. Obviously very key for operator now, but like, was, is there anything interesting technically there or that the people like, well, people always want this.Paul [00:28:21]: It was really hard to build, you know, like, so, okay. Headless browsers, you don't see them, right. They're running. They're running in a cloud somewhere. You can't like look at them. And I just want to really make, it's a weird name. I wish we came up with a better name for this thing, but you can't see them. Right. But customers don't trust AI agents, right. At least the first pass. So what we do with our live view is that, you know, when you use browser base, you can actually embed a live view of the browser running in the cloud for your customer to see it working. And that's what the first reason is the build trust, like, okay, so I have this script. That's going to go automate a website. I can embed it into my web application via an iframe and my customer can watch. I think. And then we added two way communication. So now not only can you watch the browser kind of being operated by AI, if you want to pause and actually click around type within this iframe that's controlling a browser, that's also possible. And this is all thanks to some of the lower level protocol, which is called the Chrome DevTools protocol. It has a API called start screencast, and you can also send mouse clicks and button clicks to a remote browser. And this is all embeddable within iframes. You have a browser within a browser, yo. And then you simulate the screen, the click on the other side. Exactly. And this is really nice often for, like, let's say, a capture that can't be solved. You saw this with Operator, you know, Operator actually uses a different approach. They use VNC. So, you know, you're able to see, like, you're seeing the whole window here. What we're doing is something a little lower level with the Chrome DevTools protocol. It's just PNGs being streamed over the wire. But the same thing is true, right? Like, hey, I'm running a window. Pause. Can you do something in this window? Human. Okay, great. Resume. Like sometimes 2FA tokens. Like if you get that text message, you might need a person to type that in. Web agents need human-in-the-loop type workflows still. You still need a person to interact with the browser. And building a UI to proxy that is kind of hard. You may as well just show them the whole browser and say, hey, can you finish this up for me? And then let the AI proceed on afterwards. Is there a future where I stream my current desktop to browser base? I don't think so. I think we're very much cloud infrastructure. Yeah. You know, but I think a lot of the stuff we're doing, we do want to, like, build tools. Like, you know, we'll talk about the stage and, you know, web agent framework in a second. But, like, there's a case where a lot of people are going desktop first for, you know, consumer use. And I think cloud is doing a lot of this, where I expect to see, you know, MCPs really oriented around the cloud desktop app for a reason, right? Like, I think a lot of these tools are going to run on your computer because it makes... I think it's breaking out. People are putting it on a server. Oh, really? Okay. Well, sweet. We'll see. We'll see that. I was surprised, though, wasn't I? I think that the browser company, too, with Dia Browser, it runs on your machine. You know, it's going to be...swyx [00:30:50]: What is it?Paul [00:30:51]: So, Dia Browser, as far as I understand... I used to use Arc. Yeah. I haven't used Arc. But I'm a big fan of the browser company. I think they're doing a lot of cool stuff in consumer. As far as I understand, it's a browser where you have a sidebar where you can, like, chat with it and it can control the local browser on your machine. So, if you imagine, like, what a consumer web agent is, which it lives alongside your browser, I think Google Chrome has Project Marina, I think. I almost call it Project Marinara for some reason. I don't know why. It's...swyx [00:31:17]: No, I think it's someone really likes the Waterworld. Oh, I see. The classic Kevin Costner. Yeah.Paul [00:31:22]: Okay. Project Marinara is a similar thing to the Dia Browser, in my mind, as far as I understand it. You have a browser that has an AI interface that will take over your mouse and keyboard and control the browser for you. Great for consumer use cases. But if you're building applications that rely on a browser and it's more part of a greater, like, AI app experience, you probably need something that's more like infrastructure, not a consumer app.swyx [00:31:44]: Just because I have explored a little bit in this area, do people want branching? So, I have the state. Of whatever my browser's in. And then I want, like, 100 clones of this state. Do people do that? Or...Paul [00:31:56]: People don't do it currently. Yeah. But it's definitely something we're thinking about. I think the idea of forking a browser is really cool. Technically, kind of hard. We're starting to see this in code execution, where people are, like, forking some, like, code execution, like, processes or forking some tool calls or branching tool calls. Haven't seen it at the browser level yet. But it makes sense. Like, if an AI agent is, like, using a website and it's not sure what path it wants to take to crawl this website. To find the information it's looking for. It would make sense for it to explore both paths in parallel. And that'd be a very, like... A road not taken. Yeah. And hopefully find the right answer. And then say, okay, this was actually the right one. And memorize that. And go there in the future. On the roadmap. For sure. Don't make my roadmap, please. You know?Alessio [00:32:37]: How do you actually do that? Yeah. How do you fork? I feel like the browser is so stateful for so many things.swyx [00:32:42]: Serialize the state. Restore the state. I don't know.Paul [00:32:44]: So, it's one of the reasons why we haven't done it yet. It's hard. You know? Like, to truly fork, it's actually quite difficult. The naive way is to open the same page in a new tab and then, like, hope that it's at the same thing. But if you have a form halfway filled, you may have to, like, take the whole, you know, container. Pause it. All the memory. Duplicate it. Restart it from there. It could be very slow. So, we haven't found a thing. Like, the easy thing to fork is just, like, copy the page object. You know? But I think there needs to be something a little bit more robust there. Yeah.swyx [00:33:12]: So, MorphLabs has this infinite branch thing. Like, wrote a custom fork of Linux or something that let them save the system state and clone it. MorphLabs, hit me up. I'll be a customer. Yeah. That's the only. I think that's the only way to do it. Yeah. Like, unless Chrome has some special API for you. Yeah.Paul [00:33:29]: There's probably something we'll reverse engineer one day. I don't know. Yeah.Alessio [00:33:32]: Let's talk about StageHand, the AI web browsing framework. You have three core components, Observe, Extract, and Act. Pretty clean landing page. What was the idea behind making a framework? Yeah.Stagehand: AI web browsing frameworkPaul [00:33:43]: So, there's three frameworks that are very popular or already exist, right? Puppeteer, Playwright, Selenium. Those are for building hard-coded scripts to control websites. And as soon as I started to play with LLMs plus browsing, I caught myself, you know, code-genning Playwright code to control a website. I would, like, take the DOM. I'd pass it to an LLM. I'd say, can you generate the Playwright code to click the appropriate button here? And it would do that. And I was like, this really should be part of the frameworks themselves. And I became really obsessed with SDKs that take natural language as part of, like, the API input. And that's what StageHand is. StageHand exposes three APIs, and it's a super set of Playwright. So, if you go to a page, you may want to take an action, click on the button, fill in the form, etc. That's what the act command is for. You may want to extract some data. This one takes a natural language, like, extract the winner of the Super Bowl from this page. You can give it a Zod schema, so it returns a structured output. And then maybe you're building an API. You can do an agent loop, and you want to kind of see what actions are possible on this page before taking one. You can do observe. So, you can observe the actions on the page, and it will generate a list of actions. You can guide it, like, give me actions on this page related to buying an item. And you can, like, buy it now, add to cart, view shipping options, and pass that to an LLM, an agent loop, to say, what's the appropriate action given this high-level goal? So, StageHand isn't a web agent. It's a framework for building web agents. And we think that agent loops are actually pretty close to the application layer because every application probably has different goals or different ways it wants to take steps. I don't think I've seen a generic. Maybe you guys are the experts here. I haven't seen, like, a really good AI agent framework here. Everyone kind of has their own special sauce, right? I see a lot of developers building their own agent loops, and they're using tools. And I view StageHand as the browser tool. So, we expose act, extract, observe. Your agent can call these tools. And from that, you don't have to worry about it. You don't have to worry about generating playwright code performantly. You don't have to worry about running it. You can kind of just integrate these three tool calls into your agent loop and reliably automate the web.swyx [00:35:48]: A special shout-out to Anirudh, who I met at your dinner, who I think listens to the pod. Yeah. Hey, Anirudh.Paul [00:35:54]: Anirudh's a man. He's a StageHand guy.swyx [00:35:56]: I mean, the interesting thing about each of these APIs is they're kind of each startup. Like, specifically extract, you know, Firecrawler is extract. There's, like, Expand AI. There's a whole bunch of, like, extract companies. They just focus on extract. I'm curious. Like, I feel like you guys are going to collide at some point. Like, right now, it's friendly. Everyone's in a blue ocean. At some point, it's going to be valuable enough that there's some turf battle here. I don't think you have a dog in a fight. I think you can mock extract to use an external service if they're better at it than you. But it's just an observation that, like, in the same way that I see each option, each checkbox in the side of custom GBTs becoming a startup or each box in the Karpathy chart being a startup. Like, this is also becoming a thing. Yeah.Paul [00:36:41]: I mean, like, so the way StageHand works is that it's MIT-licensed, completely open source. You bring your own API key to your LLM of choice. You could choose your LLM. We don't make any money off of the extract or really. We only really make money if you choose to run it with our browser. You don't have to. You can actually use your own browser, a local browser. You know, StageHand is completely open source for that reason. And, yeah, like, I think if you're building really complex web scraping workflows, I don't know if StageHand is the tool for you. I think it's really more if you're building an AI agent that needs a few general tools or if it's doing a lot of, like, web automation-intensive work. But if you're building a scraping company, StageHand is not your thing. You probably want something that's going to, like, get HTML content, you know, convert that to Markdown, query it. That's not what StageHand does. StageHand is more about reliability. I think we focus a lot on reliability and less so on cost optimization and speed at this point.swyx [00:37:33]: I actually feel like StageHand, so the way that StageHand works, it's like, you know, page.act, click on the quick start. Yeah. It's kind of the integration test for the code that you would have to write anyway, like the Puppeteer code that you have to write anyway. And when the page structure changes, because it always does, then this is still the test. This is still the test that I would have to write. Yeah. So it's kind of like a testing framework that doesn't need implementation detail.Paul [00:37:56]: Well, yeah. I mean, Puppeteer, Playwright, and Slenderman were all designed as testing frameworks, right? Yeah. And now people are, like, hacking them together to automate the web. I would say, and, like, maybe this is, like, me being too specific. But, like, when I write tests, if the page structure changes. Without me knowing, I want that test to fail. So I don't know if, like, AI, like, regenerating that. Like, people are using StageHand for testing. But it's more for, like, usability testing, not, like, testing of, like, does the front end, like, has it changed or not. Okay. But generally where we've seen people, like, really, like, take off is, like, if they're using, you know, something. If they want to build a feature in their application that's kind of like Operator or Deep Research, they're using StageHand to kind of power that tool calling in their own agent loop. Okay. Cool.swyx [00:38:37]: So let's go into Operator, the first big agent launch of the year from OpenAI. Seems like they have a whole bunch scheduled. You were on break and your phone blew up. What's your just general view of computer use agents is what they're calling it. The overall category before we go into Open Operator, just the overall promise of Operator. I will observe that I tried it once. It was okay. And I never tried it again.OpenAI's Operator and computer use agentsPaul [00:38:58]: That tracks with my experience, too. Like, I'm a huge fan of the OpenAI team. Like, I think that I do not view Operator as the company. I'm not a company killer for browser base at all. I think it actually shows people what's possible. I think, like, computer use models make a lot of sense. And I'm actually most excited about computer use models is, like, their ability to, like, really take screenshots and reasoning and output steps. I think that using mouse click or mouse coordinates, I've seen that proved to be less reliable than I would like. And I just wonder if that's the right form factor. What we've done with our framework is anchor it to the DOM itself, anchor it to the actual item. So, like, if it's clicking on something, it's clicking on that thing, you know? Like, it's more accurate. No matter where it is. Yeah, exactly. Because it really ties in nicely. And it can handle, like, the whole viewport in one go, whereas, like, Operator can only handle what it sees. Can you hover? Is hovering a thing that you can do? I don't know if we expose it as a tool directly, but I'm sure there's, like, an API for hovering. Like, move mouse to this position. Yeah, yeah, yeah. I think you can trigger hover, like, via, like, the JavaScript on the DOM itself. But, no, I think, like, when we saw computer use, everyone's eyes lit up because they realized, like, wow, like, AI is going to actually automate work for people. And I think seeing that kind of happen from both of the labs, and I'm sure we're going to see more labs launch computer use models, I'm excited to see all the stuff that people build with it. I think that I'd love to see computer use power, like, controlling a browser on browser base. And I think, like, Open Operator, which was, like, our open source version of OpenAI's Operator, was our first take on, like, how can we integrate these models into browser base? And we handle the infrastructure and let the labs do the models. I don't have a sense that Operator will be released as an API. I don't know. Maybe it will. I'm curious to see how well that works because I think it's going to be really hard for a company like OpenAI to do things like support CAPTCHA solving or, like, have proxies. Like, I think it's hard for them structurally. Imagine this New York Times headline, OpenAI CAPTCHA solving. Like, that would be a pretty bad headline, this New York Times headline. Browser base solves CAPTCHAs. No one cares. No one cares. And, like, our investors are bored. Like, we're all okay with this, you know? We're building this company knowing that the CAPTCHA solving is short-lived until we figure out how to authenticate good bots. I think it's really hard for a company like OpenAI, who has this brand that's so, so good, to balance with, like, the icky parts of web automation, which it can be kind of complex to solve. I'm sure OpenAI knows who to call whenever they need you. Yeah, right. I'm sure they'll have a great partnership.Alessio [00:41:23]: And is Open Operator just, like, a marketing thing for you? Like, how do you think about resource allocation? So, you can spin this up very quickly. And now there's all this, like, open deep research, just open all these things that people are building. We started it, you know. You're the original Open. We're the original Open operator, you know? Is it just, hey, look, this is a demo, but, like, we'll help you build out an actual product for yourself? Like, are you interested in going more of a product route? That's kind of the OpenAI way, right? They started as a model provider and then…Paul [00:41:53]: Yeah, we're not interested in going the product route yet. I view Open Operator as a model provider. It's a reference project, you know? Let's show people how to build these things using the infrastructure and models that are out there. And that's what it is. It's, like, Open Operator is very simple. It's an agent loop. It says, like, take a high-level goal, break it down into steps, use tool calling to accomplish those steps. It takes screenshots and feeds those screenshots into an LLM with the step to generate the right action. It uses stagehand under the hood to actually execute this action. It doesn't use a computer use model. And it, like, has a nice interface using the live view that we talked about, the iframe, to embed that into an application. So I felt like people on launch day wanted to figure out how to build their own version of this. And we turned that around really quickly to show them. And I hope we do that with other things like deep research. We don't have a deep research launch yet. I think David from AOMNI actually has an amazing open deep research that he launched. It has, like, 10K GitHub stars now. So he's crushing that. But I think if people want to build these features natively into their application, they need good reference projects. And I think Open Operator is a good example of that.swyx [00:42:52]: I don't know. Actually, I'm actually pretty bullish on API-driven operator. Because that's the only way that you can sort of, like, once it's reliable enough, obviously. And now we're nowhere near. But, like, give it five years. It'll happen, you know. And then you can sort of spin this up and browsers are working in the background and you don't necessarily have to know. And it just is booking restaurants for you, whatever. I can definitely see that future happening. I had this on the landing page here. This might be a slightly out of order. But, you know, you have, like, sort of three use cases for browser base. Open Operator. Or this is the operator sort of use case. It's kind of like the workflow automation use case. And it completes with UiPath in the sort of RPA category. Would you agree with that? Yeah, I would agree with that. And then there's Agents we talked about already. And web scraping, which I imagine would be the bulk of your workload right now, right?Paul [00:43:40]: No, not at all. I'd say actually, like, the majority is browser automation. We're kind of expensive for web scraping. Like, I think that if you're building a web scraping product, if you need to do occasional web scraping or you have to do web scraping that works every single time, you want to use browser automation. Yeah. You want to use browser-based. But if you're building web scraping workflows, what you should do is have a waterfall. You should have the first request is a curl to the website. See if you can get it without even using a browser. And then the second request may be, like, a scraping-specific API. There's, like, a thousand scraping APIs out there that you can use to try and get data. Scraping B. Scraping B is a great example, right? Yeah. And then, like, if those two don't work, bring out the heavy hitter. Like, browser-based will 100% work, right? It will load the page in a real browser, hydrate it. I see.swyx [00:44:21]: Because a lot of people don't render to JS.swyx [00:44:25]: Yeah, exactly.Paul [00:44:26]: So, I mean, the three big use cases, right? Like, you know, automation, web data collection, and then, you know, if you're building anything agentic that needs, like, a browser tool, you want to use browser-based.Alessio [00:44:35]: Is there any use case that, like, you were super surprised by that people might not even think about? Oh, yeah. Or is it, yeah, anything that you can share? The long tail is crazy. Yeah.Surprising use cases of BrowserbasePaul [00:44:44]: One of the case studies on our website that I think is the most interesting is this company called Benny. So, the way that it works is if you're on food stamps in the United States, you can actually get rebates if you buy certain things. Yeah. You buy some vegetables. You submit your receipt to the government. They'll give you a little rebate back. Say, hey, thanks for buying vegetables. It's good for you. That process of submitting that receipt is very painful. And the way Benny works is you use their app to take a photo of your receipt, and then Benny will go submit that receipt for you and then deposit the money into your account. That's actually using no AI at all. It's all, like, hard-coded scripts. They maintain the scripts. They've been doing a great job. And they build this amazing consumer app. But it's an example of, like, all these, like, tedious workflows that people have to do to kind of go about their business. And they're doing it for the sake of their day-to-day lives. And I had never known about, like, food stamp rebates or the complex forms you have to do to fill them. But the world is powered by millions and millions of tedious forms, visas. You know, Emirate Lighthouse is a customer, right? You know, they do the O1 visa. Millions and millions of forms are taking away humans' time. And I hope that Browserbase can help power software that automates away the web forms that we don't need anymore. Yeah.swyx [00:45:49]: I mean, I'm very supportive of that. I mean, forms. I do think, like, government itself is a big part of it. I think the government itself should embrace AI more to do more sort of human-friendly form filling. Mm-hmm. But I'm not optimistic. I'm not holding my breath. Yeah. We'll see. Okay. I think I'm about to zoom out. I have a little brief thing on computer use, and then we can talk about founder stuff, which is, I tend to think of developer tooling markets in impossible triangles, where everyone starts in a niche, and then they start to branch out. So I already hinted at a little bit of this, right? We mentioned more. We mentioned E2B. We mentioned Firecrawl. And then there's Browserbase. So there's, like, all this stuff of, like, have serverless virtual computer that you give to an agent and let them do stuff with it. And there's various ways of connecting it to the internet. You can just connect to a search API, like SERP API, whatever other, like, EXA is another one. That's what you're searching. You can also have a JSON markdown extractor, which is Firecrawl. Or you can have a virtual browser like Browserbase, or you can have a virtual machine like Morph. And then there's also maybe, like, a virtual sort of code environment, like Code Interpreter. So, like, there's just, like, a bunch of different ways to tackle the problem of give a computer to an agent. And I'm just kind of wondering if you see, like, everyone's just, like, happily coexisting in their respective niches. And as a developer, I just go and pick, like, a shopping basket of one of each. Or do you think that you eventually, people will collide?Future of browser automation and market competitionPaul [00:47:18]: I think that currently it's not a zero-sum market. Like, I think we're talking about... I think we're talking about all of knowledge work that people do that can be automated online. All of these, like, trillions of hours that happen online where people are working. And I think that there's so much software to be built that, like, I tend not to think about how these companies will collide. I just try to solve the problem as best as I can and make this specific piece of infrastructure, which I think is an important primitive, the best I possibly can. And yeah. I think there's players that are actually going to like it. I think there's players that are going to launch, like, over-the-top, you know, platforms, like agent platforms that have all these tools built in, right? Like, who's building the rippling for agent tools that has the search tool, the browser tool, the operating system tool, right? There are some. There are some. There are some, right? And I think in the end, what I have seen as my time as a developer, and I look at all the favorite tools that I have, is that, like, for tools and primitives with sufficient levels of complexity, you need to have a solution that's really bespoke to that primitive, you know? And I am sufficiently convinced that the browser is complex enough to deserve a primitive. Obviously, I have to. I'm the founder of BrowserBase, right? I'm talking my book. But, like, I think maybe I can give you one spicy take against, like, maybe just whole OS running. I think that when I look at computer use when it first came out, I saw that the majority of use cases for computer use were controlling a browser. And do we really need to run an entire operating system just to control a browser? I don't think so. I don't think that's necessary. You know, BrowserBase can run browsers for way cheaper than you can if you're running a full-fledged OS with a GUI, you know, operating system. And I think that's just an advantage of the browser. It is, like, browsers are little OSs, and you can run them very efficiently if you orchestrate it well. And I think that allows us to offer 90% of the, you know, functionality in the platform needed at 10% of the cost of running a full OS. Yeah.Open Operator: Browserbase's Open-Source Alternativeswyx [00:49:16]: I definitely see the logic in that. There's a Mark Andreessen quote. I don't know if you know this one. Where he basically observed that the browser is turning the operating system into a poorly debugged set of device drivers, because most of the apps are moved from the OS to the browser. So you can just run browsers.Paul [00:49:31]: There's a place for OSs, too. Like, I think that there are some applications that only run on Windows operating systems. And Eric from pig.dev in this upcoming YC batch, or last YC batch, like, he's building all run tons of Windows operating systems for you to control with your agent. And like, there's some legacy EHR systems that only run on Internet-controlled systems. Yeah.Paul [00:49:54]: I think that's it. I think, like, there are use cases for specific operating systems for specific legacy software. And like, I'm excited to see what he does with that. I just wanted to give a shout out to the pig.dev website.swyx [00:50:06]: The pigs jump when you click on them. Yeah. That's great.Paul [00:50:08]: Eric, he's the former co-founder of banana.dev, too.swyx [00:50:11]: Oh, that Eric. Yeah. That Eric. Okay. Well, he abandoned bananas for pigs. I hope he doesn't start going around with pigs now.Alessio [00:50:18]: Like he was going around with bananas. A little toy pig. Yeah. Yeah. I love that. What else are we missing? I think we covered a lot of, like, the browser-based product history, but. What do you wish people asked you? Yeah.Paul [00:50:29]: I wish people asked me more about, like, what will the future of software look like? Because I think that's really where I've spent a lot of time about why do browser-based. Like, for me, starting a company is like a means of last resort. Like, you shouldn't start a company unless you absolutely have to. And I remain convinced that the future of software is software that you're going to click a button and it's going to do stuff on your behalf. Right now, software. You click a button and it maybe, like, calls it back an API and, like, computes some numbers. It, like, modifies some text, whatever. But the future of software is software using software. So, I may log into my accounting website for my business, click a button, and it's going to go load up my Gmail, search my emails, find the thing, upload the receipt, and then comment it for me. Right? And it may use it using APIs, maybe a browser. I don't know. I think it's a little bit of both. But that's completely different from how we've built software so far. And that's. I think that future of software has different infrastructure requirements. It's going to require different UIs. It's going to require different pieces of infrastructure. I think the browser infrastructure is one piece that fits into that, along with all the other categories you mentioned. So, I think that it's going to require developers to think differently about how they've built software for, you know

ABOUT MELODY MECKFESSELMelody Meckfessel is the Chief Technology Officer (CTO) at Jasper.ai, the world's leading AI marketing platform. In her role, Melody shapes the technical vision of the company, oversees product delivery, and spearheads AI research to develop new capabilities that accelerate business outcomes for enterprise marketers.Before joining Jasper.ai, Melody co-founded and served as CEO of Observable, a data visualization platform that empowers teams to understand their businesses through data. She also spent over a decade at Google as Vice President of Engineering, where she led core infrastructure, Search, and DevOps teams for Google and Google Cloud Platform, impacting millions of users worldwide.Melody is recognized for her hands-on approach to engineering leadership and her expertise in building large-scale distributed systems. Her work is crucial in solving complex problems at scale for enterprise companies. She is passionate about defining the future of work with AI, where humans come first.This episode is brought to you by Clipboard HealthClipboard Health is looking for the next generation of exceptional software engineering leaders, not just managers. They're a profitable unicorn, backed by top-tier investors, and they take the craft of engineering management seriously.Clipboard Health matches highly qualified healthcare workers with nearby facilities to fulfill millions of shifts a year - revolutionizing healthcare staffing with a fast, flexible, and user-friendly platform.Learn more & browse their open roles at clipboardhealth.com/engineeringSHOW NOTES:Melody's perspective on the tech industry's rapid rate of change right now (2:53)Critical questions to guide investment decisions on “what to build & how“ in a rapidly evolving market (5:57)Strategies for navigating rapid change internally within eng teams (10:07)What it means to be an AI-first engineering organization (12:30)Changes in goals, metrics, and processes to shape your org and guide you through rapid change (15:33)Developing agile communication processes (18:39)Navigating ambiguity as a learned skill - practical ways to strengthen your ability to navigate uncertainty (20:09)Implementing a framework of curiosity & openness within eng teams (22:40)Why great things can't be planned (26:21)Becoming dynamic and resilient - how to thrive amid uncertainty and constant industry shifts (28:57)How to shift from prescriptive to inspirational - using illustrated inspiration to empower teams (32:00)Breaking through self-imposed limitations - understanding where eng leaders may limit themselves (33:48)Melody's perspective on fostering a culture of creativity within eng teams (35:06)Rapid fire questions (37:13)LINKS AND RESOURCESThe Qualified Sales Leader: Proven Lessons from a Five Time CRO - John McMahon shares valuable lessons for sales leaders and sales reps selling enterprise software solutions. In a conversational and easy to read narrative style, this must-read book provides learnings on how sales leaders can help their reps sell more for higher average deal sizes to executive level buyers.This episode wouldn't have been possible without the help of our incredible production team:Patrick Gallagher - Producer & Co-HostJerry Li - Co-HostNoah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/

For episode 196 of De Facto Leaders, I share a Q & A session where I talk through how to write language therapy goals that are both trackable and functional.This is just one of many Q & A sessions I'm planning on sharing where I talk through how to find the balance between focusing on external behaviors that allow us to document progress and internal cognitive processes.I also talk about when to focus on “observable” language skills vs. strategy-based goals; especially when addressing both language and executive functioning skills. Throughout the session, you'll hear examples related to working on skills like syntax, semantic feature study, vocabulary, and cognitive processes that support language comprehension. This Q & A session was done in the member's group for Language Therapy Advance Foundations, my program that helps SLPs build a system for language therapy. You can learn more about Language Therapy Advance Foundations here : https://drkarenspeech.com/languagetherapy We're thrilled to be sponsored by IXL. IXL's comprehensive teaching and learning platform for math, language arts, science, and social studies is accelerating achievement in 95 of the top 100 U.S. school districts. Loved by teachers and backed by independent research from Johns Hopkins University, IXL can help you do the following and more:Simplify and streamline technologySave teachers' timeReliably meet Tier 1 standardsImprove student performance on state assessments

The Observer and Trapper swap stories. On the origins of Christmas Traditions. You'll never bake anything good again. The mouldering remains of last year.The First Supplemental Frequency from Observable Radio, a found footage podcast from Cameron Suey. Phil van Hest, and Purpurina.Content Warnings: Explicitly Depicted Violence/SquelchingWritten by Purpurina, Cameron Suey, and Wendy HectorProduced by Cameron Suey, Phil van Hest, and PurpurinaEdited by Cameron SueyThe EnsemblePhil van HestJason SmithKatie SkovholtPurpurinaArt by Karrin FletcherPsychology Consultant - Elisa Leal, Psy.D (CA PSY28330)Our Theme Music is: The Backrooms - MyuuAdditional Music provided by Tim Kulig, Katie Skovholt, and the artists at Epidemic SoundAncient Lands - FlouwDiabolic Gaze - Luella GrenCold Nights - KikoruStrangled by Piano Strings Part 1 - Ludvig MoulinBlue Spaces - Oakwood StationAbyssal Hibernation (Delta Drone L144Hz R147Hz) - OokeanGoth Christmas - parA Cradle Song - Mary RiddleSilent Night (Ambient Version) (Instrumental Version) - Ingrid WittAdditional Sound Design by PurpurinaSFX provided by Epidemic Sound and the artists at Freesound.orgAdditional SFX and Music covered under the following licenses:creativecommons.org/licenses/by/3.0/creativecommons.org/licenses/by/4.0/Special Thanks to Cathleen, Jon, Tid, Russ, Kalasin, Rick, Brianna, Zach and all our patrons and listeners.Thank you for listening, and stay tuned.

At Redeemer Presbyterian Church in Charleston, SC, our senior pastor Rev. Craig Bailey preached for the second Sunday of Advent.

At Redeemer Presbyterian Church in Charleston, SC, our senior pastor Rev. Craig Bailey preached for the second Sunday of Advent.

If we need to fully understand space we need more time - lots of it. Beyond the hubblesphere things gets lumpy. drkarl.com

Alan is joined by Lou Elizondo, former military intelligence officer and author of Imminent: Inside the Pentagon's Hunt for UFOs. Lou shares his journey from joining JROTC to his work in the Pentagon's classified UFO program. He describes Unidentified Aerial Phenomena (UAP) with extraordinary capabilities like hypersonic speeds and movement without visible propulsion, raising national security concerns. Lou explains that UAP sightings date back to the 1950s, and the government once stigmatized discussions to avoid panic. Now, bipartisan efforts push for transparency, supported by emerging legislation and international cooperation on UAP research.     Guest Bio Lou Elizondo is a former military intelligence officer who served in various classified roles, including a key position in the Pentagon's UFO program. After his resignation in 2017, Lou became an advocate for transparency about Unidentified Aerial Phenomena (UAPs), revealing shocking insights into advanced aerospace technologies observed by military pilots. His New York Times bestselling book, Imminent: Inside the Pentagon's Hunt for UFOs, uncovers the hidden world of UAP investigations and challenges our understanding of reality. Lou's work has sparked global conversations about science, security, and the future of human knowledge.     Show Highlights (1:29) What led to Luis' career in military and intelligence services (5:26) What remote sensing is (11:03) How Luis' became in involved with UAPs from a military perspective (25:09) How Luis' deals with the lack of acceptance of the data (29:42) What led Louis to resign from the Pentagon (34:04) Observable traits of UAPs based on famous filmed cases (40:48) Why the government's attitude toward public transparency is changing (46:03) Next steps for people as UAPs are more openly discussed (52:56) The importance of keeping an open mind moving forward     Links Referenced Imminent: Inside the Pentagon's Hunt for UFO's https://www.amazon.com/Imminent-Pentagons-Investigating-UAPs_Featured-Experience/dp/0063235560

10.6.24 - Acts 11:19-30, 12:25-13:3 - “Observable Signs of God's Grace” - Alex Gailey

Ben Scheirman is back for part 2 of our interview on SwiftUI Migration. In this episode we focus on navigation, data handling and Swift packages.GuestBen Scheirman | Ben is an experienced software engineer from Houston, TX. Currently focused on Swift, iOS, Ruby, and Rust.Ben Scheirman (@bens@mastodon.xyz) - Mastodonsubdigital (Ben Scheirman)NSScreencast: Bite-sized Screencasts for iOS DevelopmentCombine SwiftAnnouncementsNeed help with your projects this year? BrightDigit has openings.Join Bushel BetaJoin our Brand New Patreon Page!LinksEpisode #288: Modern UIKit: Stack Navigation, Part 2pointfreeco/swift-perception: Observable tools, backported.brightdigit/Sublimation: Enable automatic discovery of your local development server on the fly. Turn your Server-Side Swift app from a mysterious vapor to a tangible solid server.krzysztofzablocki/LifetimeTracker: Find retain cycles / memory leaks sooner.siteline/swiftui-introspect: Introspect underlying UIKit/AppKit components from SwiftUIPresenting Coordinators - Soroush Khanlou on VimeoRelated EpisodesThe Great SwiftUI Migration - Part 1 with Ben ScheirmanSwiftUI Field Guide with Chris EidhofSOTU 2024 with Peter WithamSwiftUI Tips and Tricks with Craig ClaytonSwiftly Tooling with Pol Piella AbadiaIt Depends with Brandon WilliamsMy Taylor Deep Dish Swift Heroes World TourMobile System Design with Tjeerd in 't VeenThe Composable Architecture with Zev EisenbergBehind the Scenes of SwiftUI with Aviel GrossWWDC 2022 - SwiftUI and UIKit with Evan StoneSocial MediaEmailleo@brightdigit.comGitHub - @brightdigitTwitter BrightDigit - @brightdigitLeo - @leogdionLinkedInBrightDigitLeoPatreon - brightdigitCreditsMusic from https://filmmusic.io"Blippy Trance" by Kevin MacLeod (https://incompetech.com)License: CC BY (http://creativecommons.org/licenses/by/4.0/) (00:00) - Discussing Data Handling in Swift UI (01:22) - Observable Objects and View Models (04:20) - The Power of Previews in Swift UI (06:36) - Combining Combine and Async/Await (10:29) - Interfacing Between UIKit and Swift UI (17:12) - Challenges with Swift Package Manager Thanks to our monthly supporters Bertram Eber Edward Sanchez Satoshi Mitsumori Danielle Lewis Steven Lipton ★ Support this podcast on Patreon ★

Ben Scheirman of NSScreenCast comes on to talk about migrating apps such as a Nike's Sneakers app from UIKit to SwiftUI and all the little things you don't think about. This is part 1 of a 2 part interview.GuestBen Scheirman | Ben is an experienced software engineer from Houston, TX. Currently focused on Swift, iOS, Ruby, and Rust.Ben Scheirman (@bens@mastodon.xyz) - Mastodonsubdigital (Ben Scheirman)NSScreencast: Bite-sized Screencasts for iOS DevelopmentCombine SwiftAnnouncementsNeed help with your projects this year? BrightDigit has openings.Join Bushel BetaJoin our Brand New Patreon Page!LinksEpisode #288: Modern UIKit: Stack Navigation, Part 2pointfreeco/swift-perception: Observable tools, backported.brightdigit/Sublimation: Enable automatic discovery of your local development server on the fly. Turn your Server-Side Swift app from a mysterious vapor to a tangible solid server.krzysztofzablocki/LifetimeTracker: Find retain cycles / memory leaks sooner.siteline/swiftui-introspect: Introspect underlying UIKit/AppKit components from SwiftUIPresenting Coordinators - Soroush Khanlou on VimeoRelated EpisodesSwiftUI Field Guide with Chris EidhofSOTU 2024 with Peter WithamSwiftUI Tips and Tricks with Craig ClaytonSwiftly Tooling with Pol Piella AbadiaIt Depends with Brandon WilliamsMy Taylor Deep Dish Swift Heroes World TourMobile System Design with Tjeerd in 't VeenThe Composable Architecture with Zev EisenbergBehind the Scenes of SwiftUI with Aviel GrossWWDC 2022 - SwiftUI and UIKit with Evan StoneSocial MediaEmailleo@brightdigit.comGitHub - @brightdigitTwitter BrightDigit - @brightdigitLeo - @leogdionLinkedInBrightDigitLeoPatreon - brightdigitCreditsMusic from https://filmmusic.io"Blippy Trance" by Kevin MacLeod (https://incompetech.com)License: CC BY (http://creativecommons.org/licenses/by/4.0/) (00:00) - Who is Ben Scherman (02:38) - Migrating Apps to Swift UI (07:03) - Challenges with Swift UI and iOS Versions (10:24) - Using Introspect for Swift UI (16:44) - Implementing Collection View in Swift UI (25:05) - Exploring iOS 18 Scroll View API (25:30) - SwiftUI vs UIKit: Productivity and Constraints (26:38) - Design and Engineering Collaboration (29:43) - Stages of Migrating to SwiftUI (34:14) - SwiftUI Navigation and Environment Bindings (39:44) - Retain Cycles and Memory Management Thanks to our monthly supporters Bertram Eber Edward Sanchez Satoshi Mitsumori Danielle Lewis Steven Lipton ★ Support this podcast on Patreon ★

COVID Vax Sperm and Egg Disaster, a Weapon of Mass Depopulation? BREAKING: Naonostructures in COVID-19 Injectables ALERT: The mRNA Vaccines Contained A Secret Weapon of Mass Depopulation For Globalists To Trigger At Will - Top Scientists Warn Christiane Northrup: Infertility clinics are reporting that The sperm of inoculated men does not swim and the eggs of inoculated women won't grow into embryos. Vaccine Nanobots: The Conspiracy That Could Be True BREAKING: New peer reviewed paper confirms presence of nanostructures in COVID-19 injectables   Post Alex Jones @RealAlexJones ALERT: The mRNA Vaccines Contained A Secret Weapon of Mass Depopulation For Globalists To Trigger At Will - Top Scientists Warn 17:17 / 19:16 6:43 PM · Sep 7, 2024 6M Views   Post Blue Sky    @Anpo_Star Dr. Christiane Northrup: Infertility clinics are reporting that The sperm of inoculated men does not swim and the eggs of inoculated women won't grow into embryos. 3:31 PM · Sep 7, 2024 16.4K Views   Vaccine Nanobots: The Conspiracy That Could Be True Watch this video at- https://www.youtube.com/live/o4IU71zHnCQ?si=vxqGsTnw1RCrGQsm Vejon Health 141K subscribers 59,866 views Streamed live on Sep 7, 2024 #covid #medicine #research In this incredible video, we dive deep into the controversial topic of vaccine nanobots. Are they a ground-breaking scientific advancement or just a conspiracy theory? ******************************************************************************************** Join Vejon Health to get access to Members Only videos and posts:    / @vejonhealth   ******************************************************************************************** Join us as we explore a recent paper on the presence of nanotechnology in vaccines. ========================================================== Composition and Potential Cause of Embalmers' Clots Webinar - Thursday 12th September at 7PM UK time https://www.eventbrite.ca/e/101120607... ========================================================== We'll separate fact from fiction and uncover the shocking truths that will change your perspective on vaccines forever. Don't miss out on this critical discussion that affects you and your health! Remember to like, subscribe, and hit the notification bell for more insightful content! ========================================================== Disease X: Are you prepared? A Comprehensive Guide to Pandemic Preparedness Join our Kickstarter here: https://www.kickstarter.com/projects/... ========================================================== Advanced Covid 360 Course Register for Pre-launch DISCOUNTED Course Here! Limited Time! https://vejonhealth.learnworlds.com/c... ========================================================== Help "Humming Heroes" get to Number ONE on Amazon! Preorder with a reduced price here: https://mcmillanresearch.com/humming_... ======================================================== Alternative Links Here: Substack - COVID-19: https://philipmcmillan.substack.com/ Patreon:   / vejonhealth   Videos: https://mcmillanresearch.com/media/ Courses: https://mcmillanresearch.com/mr-educa... Rumble: https://rumble.com/user/vejonhealth Substack - Long Covid: https://drphilipmcmillan.substack.com/ More info: https://vejonhealth.com/ Twitter - Vejon Health:   / vejon_health   Twitter - Dr Philip A McMillan:   / philamillan   #covid #medicine #research   Post BREAKING: New peer reviewed paper confirms presence of nanostructures in COVID-19 injectables Shaun Rickard @ShaunRickard67   Watch this video on Rumble at- https://rumble.com/v5e07d1-breaking-new-peer-reviewed-paper-confirms-presence-of-nanostructures-in-cov.html ***WARNING - Those who have been injected with the experimental mRNA Gene Therapies may to want to sit down before watching this video Dr. John Campbell presents new peer reviewed papers which confirm the presence of mRNA nanostructures in the COVID-19 injectables NOTE: I have screen recorded this video because YouTube will very likely censor it and take it down shortly. I have also uploaded it to my censorship free Rumble channel for those who wish to share it on other SM platforms, or with friends and family who are not on X: https://rumble.com/v5e07d1-breaking-new-peer-reviewed-paper-confirms-presence-of-nanostructures-in-cov.html… For those wishing to conduct their own research, and for all the sceptics out there, I have listed all of Dr. Campbell's notes, research and source links below... "Real-Time Self-Assembly of Stereomicroscopically Visible Artificial Constructions in Incubated Specimens of mRNA Products Mainly from Pfizer and Moderna: A Comprehensive Longitudinal Study https://ijvtpr.com/index.php/IJVTPR/article/view/102… Our observations suggest the presence of some kind of nanotechnology in the COVID-19 injectables. International Journal of Vaccine Theory, Practice, and Research https://ijvtpr.com/index.php/IJVTPR/index… Full version of the journal Vol. 3 No. 2 (2024): Injuries, Causes, and Treatments, Part 2 https://ijvtpr.com/index.php/IJVTPR/issue/view/6… Creative Commons link https://creativecommons.org/licenses/by-nc-nd/4.0/… Observable real-time injuries at the cellular level in recipients of the “safe and effective” COVID-19 injectables are documented here for the first time, with the presentation of a comprehensive description and analysis of observed phenomena. The global administration of these often-mandated products from late 2020 triggered a plethora of independent research studies of the modified RNA injectable gene therapies, most notably those manufactured by Pfizer and Moderna. Analyses reported here consist of precise laboratory “bench science” aiming to understand why serious debilitating, prolonged injuries (and many deaths) occurred increasingly without any measurable protective effect The contents of COVID-19 injectables were examined under a stereomicroscope at up to 400X magnification. Carefully preserved specimens were cultured in a range of distinct media to observe immediate and long-term cause-and-effect relationships between the injectables and living cells under carefully controlled conditions. From such research, reasonable inferences can be drawn about observed injuries worldwide that have occurred since the injectables were pressed upon billions of individuals. In addition to cellular toxicity, our findings reveal numerous — on the order of 3~4 x 106 per milliliter of the injectable — visible artificial self-assembling entities ranging from about 1 to 100 µm, or greater, of many different shapes. There were animated worm-like entities, discs, chains, spirals, tubes, right-angle structures containing other artificial entities within them All these are exceedingly beyond any expected and acceptable levels of contamination of the COVID-19 injectables, and incubation studies revealed the progressive self-assembly of many artifactual structures. As time progressed during incubation, simple one- and two-dimensional structures over two or three weeks became more complex in shape and size developing into stereoscopically visible entities in three-dimensions. They resembled carbon nanotube filaments, ribbons, and tapes, some appearing as transparent, thin, flat membranes, and others as three-dimensional spirals, and beaded chains. Some of these seemed to appear and then disappear over time. Our observations suggest the presence of some kind of nanotechnology in the COVID-19 injectables. Dr. Young Mi Lee, Jeju, Jejudo, 63098, Republic of Korea (South Korea)" @TuckerCarlson @natalimorris @ReginaWatteel @KarlDHarrison @jordanbpeterson @elonmusk @WoodReporting @NChartierET @Inquiry_Canada @PierrePoilievre @CPC_HQ @ColinCarrieCPC @DrJBhattacharya @DavidKrayden @brianlilley @rupasubramanya @rustyrockets @therationalpost @ryangerritsen @TheRedactedInc @dbongino @bennyjohnson @charliekirk11 @realDonaldTrump 8:44 AM · Sep 7, 2024 1.2M Views

In this episode, Jimmy shares valuable examples of Culturize Checkpoints to help bring clarity to what being a Champion for Students truly looks like in our classrooms, and more importantly, what it leads to when it comes to observable impact. 

Known for co-creating Django and Datasette, as well as his thoughtful writing on LLMs, Simon Willison joins the show to chat about blogging as an accountability mechanism, how to build intuition with LLMs, building a startup with his partner on their honeymoon, and more.   Segments: (00:00:00) The weird intern (00:01:50) The early days of LLMs (00:04:59) Blogging as an accountability mechanism (00:09:24) The low-pressure approach to blogging (00:11:47) GitHub issues as a system of records (00:16:15) Temporal documentation and design docs (00:18:19) GitHub issues for team collaboration (00:21:53) Copy-paste as an API (00:26:54) Observable notebooks (00:28:50) pip install LLM (00:32:26) The evolution of using LLMs daily (00:34:47) Building intuition with LLMs (00:43:24) Democratizing access to automation (00:47:45) Alternative interfaces for language models (00:53:39) Is prompt engineering really engineering? (00:58:39) The frustrations of working with LLMs (01:01:59) Structured data extraction with LLMs (01:06:08) How Simon would go about building a LLM app (01:09:49) LLMs making developers more ambitious (01:13:32) Typical workflow with LLMs (01:19:58) Vibes-based evaluation (01:23:25) Staying up-to-date with LLMs (01:27:49) The impact of LLMs on new programmers (01:29:37) The rise of 'Goop' and the future of software development (01:40:20) Being an independent developer (01:42:26) Staying focused and accountable (01:47:30) Building a startup with your partner on the honeymoon (01:51:30) The responsibility of AI practitioners (01:53:07) The hidden dangers of prompt injection (01:53:44) “Artificial intelligence” is really “imitation intelligence”   Show Notes: Simon's blog: https://simonwillison.net/ Natalie's post on them building a startup together: https://blog.natbat.net/post/61658401806/lanyrd-from-idea-to-exit Simon's talk from DjangoCon: https://www.youtube.com/watch?v=GLkRK2rJGB0 Simon on twitter: https://x.com/simonw Datasette: https://github.com/simonw/datasette   Stay in touch:

Fear of death often stems from the unknown, yet this very uncertainty can be a source of comfort rather than dread. Since we lack concrete knowledge about what lies beyond life, it's worth considering that our fear might be misplaced. Death is a universal experience, and its mystery can remind us to embrace the present, […]

We've hoped you enjoyed this episode of the Morbid Forest Spotlight series. On today's episode, you've listened to our neighbors- Observable Radio.    Observable Radio is a found footage anthology retro sci fi analogy podcast. Follow the Observe as he and his colleague decipher mysterious signals from other worlds.  https://www.observableradio.com/ https://twitter.com/observableradio https://www.youtube.com/@observableradio https://www.instagram.com/observableradio See you very soon, Dear Travelers!!  

Join Hugh Ross in this breaking News of the Day episode of Stars, Cells, and God. Hugh describes a discovery that may resolve a long-standing mystery about dark matter. Primordial Black Holes Resolve Dark Matter Mystery? Dark matter is matter that doesn't interact with light or interacts at an extremely weak level. The quantity of dark matter that exists and its locations in the universe are not mysteries. Dark matter's composition is a mystery that has stymied astronomers and physicists for 5 decades. Leading candidates for dark matter's composition are axions and sterile neutrinos, but neither of these particles has been detected. Physicists Elba Alonso-Monsalve and David Kaiser propose that primordial black holes (PBHs) could make up all or a large fraction of dark matter if they formed previous to a tenth of a quadrillionth of a second after the cosmic creation event. These PBHs would take two forms: atom-sized bodies with masses equal to that Deimos and Phobos; bodies a ten thousandth the diameter of a proton with masses equal to a ton, with only the first form possibly existing to the present time. Observable tests for these PBHs include the degree to which they would 1) shift the balance between protons and neutrons, 2) cause ripples in the cosmic spacetime fabric, and 3) affect the amount of helium produced during the universe's first 3 minutes. Resources:  Primordial Black Holes with QCD Color Change Quantum Gravity Constraints Affirm Cosmic Creator

Scott and Wes serve up top tools and tricks for rapid idea execution, from JavaScript services like Valtown and Observable to database solutions including LowDB and Google Sheets integration. Get ready to streamline your development ideation process with these tasty insights! Show Notes 00:00 Welcome to Syntax! 02:16 Brought to you by Sentry.io. 03:14 JavaScript Services. 03:43 Valtown. 05:44 Observable. 06:35 Notebooks. 08:23 Deno Juypter Notebooks. 09:51 Svelte Repl. 10:32 Playgrounds: TypeScript, Tailwind, etc… 11:05 CSS Services. 11:10 CodePen. 13:14 Full stack services. 13:47 Your own stack. Hot Tips & Cool Treats. Wes's Hot Tips. Scott's Cool Treats. 21:01 Bun file routing. 24:25 Tooling and tips. 26:30 Database. 26:51 Write to a file. 27:40 LowDB. 29:00 SQLite + Drizzle. 29:40 Google Sheets. 30:06 Sheet DB. Hit us up on Socials! Syntax: X Instagram Tiktok LinkedIn Threads Wes: X Instagram Tiktok LinkedIn Threads Scott:X Instagram Tiktok LinkedIn Threads Randy: X Instagram YouTube Threads

The Observer catalogues his first signal. A mysterious curfew. An annual celebration. The pursuit of stasis.   This program is intended for mature audiences only. Content Warnings Mention of Suicide Implied harm of a Child   Performed by The Ensemble Phil van Hest Katie Skovholt Orion Kellogg Jason Smith Xalavier Nelson Jr. Kris Straub Purpurina

Welcome to the latest edition of Talking Data. Our Talking Data series seeks to offer timely insights into macro market themes along with macro data and its impact on the economy and markets. I am your host Kristen Radosh of Arbor Research and Trading. Our commentator is Jim Bianco of Bianco Research. Today Jim discusses managing fixed income in a world with yield. • What is going on with interest rates? • What is your outlook? • How hard is it to beat a benchmark? • How has the Index done? • What is the current positioning? Thank you for joining us today. We are client driven, if you have any questions or feedback on future topics, please let us know. For further information on Arbor Research, Bianco Research and Arbor Data Science, please contact Gus Handler at gus.handler@arborresearch.com.

Preached by Nathan Bayly; Acts 4:13-17

This is a recap of the top 10 posts on Hacker News on February 15th, 2024.This podcast was generated by wondercraft.ai(00:37): Sora: Creating video from textOriginal post: https://news.ycombinator.com/item?id=39386156&utm_source=wondercraft_ai(02:25): Our next-generation model: Gemini 1.5Original post: https://news.ycombinator.com/item?id=39383446&utm_source=wondercraft_ai(04:07): OpenAI – Application for US trademark “GPT” has failedOriginal post: https://news.ycombinator.com/item?id=39380165&utm_source=wondercraft_ai(05:35): Apple confirms it's breaking iPhone web apps in the EU on purposeOriginal post: https://news.ycombinator.com/item?id=39388218&utm_source=wondercraft_ai(07:36): Observable 2.0, a static site generator for data appsOriginal post: https://news.ycombinator.com/item?id=39383386&utm_source=wondercraft_ai(09:19): Uv: Python packaging in RustOriginal post: https://news.ycombinator.com/item?id=39387641&utm_source=wondercraft_ai(11:02): Every default macOS wallpaperOriginal post: https://news.ycombinator.com/item?id=39384731&utm_source=wondercraft_ai(12:57): Asahi Linux project's OpenGL support on Apple Silicon officially surpasses AppleOriginal post: https://news.ycombinator.com/item?id=39383798&utm_source=wondercraft_ai(14:46): Goodbye Auth0Original post: https://news.ycombinator.com/item?id=39380790&utm_source=wondercraft_ai(16:35): Feds want to ban the Flipper Zero – Experts say it's a scapegoatOriginal post: https://news.ycombinator.com/item?id=39385301&utm_source=wondercraft_aiThis is a third-party project, independent from HN and YC. Text and audio generated using AI, by wondercraft.ai. Create your own studio quality podcast with text as the only input in seconds at app.wondercraft.ai. Issues or feedback? We'd love to hear from you: team@wondercraft.ai

Cale Birk is a former teacher, high school principal, and District Head of Innovation from British Columbia, Canada. In 2015, one of his schools was named one of the first Model PLC Schools in Canada. Feeling like he was only scratching the surface with collaboration, Cale wrote the book PLC 2.0 – Collaborating for Observable […]