Podcasts about architectural

Architect Ben Kasdan  and I explore the ethos of design, the importance of “innovation through experience,” and why architecture should be viewed as a living organism rather than a machine. Designer Resources Pacific Sales Kitchen and Home. Where excellence meets expertise. TimberTech – Real wood beauty without the upkeep Shelter Republic – Request your membership invitation Innovation vs. Practicality: The discussion begins with the idea of innovative design, citing Frank Gehry’s Walt Disney Concert Hall. While the building faced initial criticism for a “glare” issue from its steel facade, its true innovation lies in the acoustic experience and its purpose as a “living room for the city”. Architecture as an Organism: Challenging Le Corbusier's famous “machine for living” concept, Ben suggests that buildings are more like living organisms that must be nurtured, maintained, and allowed to evolve. The “Ideas” Lab: Ben's firm, KTGY, operates a dedicated R&D studio that explores “outside the lane” concepts—like 3D-printed modular housing and solutions for homelessness—without the immediate constraints of budgets or specific client demands. Designing for the Inhabitants: A significant portion of the work focuses on student and senior housing. Ben emphasizes that while these spaces are often transient, they must be designed to support the mental, physical, and intellectual well-being of the people living there. Architectural “Grafting”: Instead of the common practice of demolition, the conversation touches on the value of “grafting” or repurposing older structures, preserving their emotional and historical significance while adapting them for new use. KTGY Architecture + Planning: The firm where Ben Kasdan is a principal, known for its diverse housing typologies. KTGY Website Walt Disney Concert Hall: Referenced as a prime example of experience-driven innovation in Los Angeles. LA Phil – Walt Disney Concert Hall The Broad: Mentioned in the context of downtown LA’s architectural landscape and public perception. The Broad Museum Frank Lloyd Wright's Price Tower: Discussed as a structure that, while visually extraordinary, struggled with functional longevity. Price Tower Arts Center Marin County Civic Center: Cited as an early inspiration for Ben, showcasing how a building’s unique form can evoke a powerful emotional response. Marin County Civic Center

The journey of Developer Confidence Growth rarely follows a straight line. Most developers begin their careers believing technical knowledge alone determines success. Then reality arrives. A challenging project, a difficult mentor, an unfamiliar technology stack, or a room full of people who seem far more experienced can quickly reveal how much there is still to learn. That realization isn't failure. It's often the beginning of a successful career. In a recent conversation with Deloitte Software Solutions Specialist Samuel Otero, a recurring theme emerged: the developers who continue to grow are often the ones who recognize how much they don't know and use that awareness as fuel for improvement rather than as a reason to quit. About Samuel Otero Samuel Otero is a Software Solutions Specialist with Deloitte US and a technology consultant with nearly 14 years of experience spanning enterprise software development, government projects, commercial consulting, and large-scale digital transformation initiatives. His career began with an early Microsoft internship that shaped his approach to continuous learning and technical humility. Since then, he has worked across media, public-sector, and enterprise environments, helping organizations deliver complex software solutions while mentoring the next generation of developers. Based in Puerto Rico, Samuel is also an advocate for developer growth, career development, and practical AI adoption in modern software engineering. Links LinkedIn Developer Confidence Growth Starts with Humility Many developers can remember a moment when their confidence collided with reality. For Samuel, that moment came during an early Microsoft internship. As a young student entering a world filled with highly accomplished engineers and mentors, he quickly discovered that classroom success and industry expertise were very different things. This type of experience is surprisingly valuable. The industry often celebrates confidence, but sustainable confidence is built on understanding limitations. Developers who believe they already know everything stop learning. Developers who understand the size of the field continue improving year after year. The fastest-growing developers are often the ones who are most aware of what they still need to learn. Why Developer Confidence Growth Requires Discomfort Growth rarely feels comfortable. New developers frequently experience uncertainty when they enter professional environments. Meetings are filled with unfamiliar terminology. Business discussions happen faster than expected. Architectural decisions involve tradeoffs that aren't covered in tutorials. Samuel discussed how many interns sit quietly in meetings because they don't fully understand what's happening yet. Rather than seeing that as a weakness, he recognizes it as a natural stage of professional development. The challenge is learning to remain engaged despite uncertainty. Developers who avoid difficult situations often remain stuck. Developers who stay involved despite discomfort gradually build the context and experience necessary for long-term success. The goal isn't eliminating uncertainty. The goal is to become comfortable learning in uncertain environments. Developer Confidence Growth and the Reality of Imposter Syndrome Few topics resonate with developers more than imposter syndrome. At every stage of a career, new responsibilities create new doubts. Junior developers wonder whether they're qualified for their first role. Mid-level developers question their readiness for leadership opportunities. Senior engineers worry about keeping pace with rapidly evolving technologies. Samuel openly shared his own struggles with imposter syndrome and how those feelings followed him throughout multiple stages of his career. The important lesson is that imposter syndrome often appears during periods of growth. When responsibilities expand faster than confidence, uncertainty naturally follows. The mistake is assuming those feelings mean you don't belong. In many cases, they simply mean you're entering a new level of your career. Treating imposter syndrome as evidence of incompetence can stop career growth before it starts. How Mentorship Accelerates Developer Confidence Growth One of the most powerful themes from Samuel's story is the impact of mentorship. Strong mentors do more than answer technical questions. They provide perspective. Experienced professionals understand that beginners don't need perfection. They need guidance, encouragement, and opportunities to learn through real-world experiences. Because Samuel remembers what it felt like to be the quiet person in the room, he actively invests time helping students and junior developers build confidence. This highlights an important truth for organizations. Teams that create mentoring cultures develop stronger engineers over time. Teams that expect people to figure everything out alone often lose talented developers before they reach their potential. Find someone at least two years ahead of you professionally and schedule regular conversations about their experiences and lessons learned. Developer Confidence Growth Is a Continuous Process Technology never stands still. Frameworks evolve. Languages change. New platforms emerge. AI tools are transforming workflows across the industry. Developers sometimes believe confidence arrives when they finally know enough. The reality is different. The most successful engineers understand that learning never ends. Every major technological shift resets part of the playing field. Even highly experienced professionals must adapt, learn new tools, and develop new approaches. Samuel's career demonstrates that long-term success isn't about reaching a finish line. It's about building a mindset capable of navigating constant change. Confidence doesn't come from knowing everything. It comes from trusting your ability to learn what comes next. Conclusion Developer careers are built through repeated cycles of learning, uncertainty, growth, and adaptation. The experiences that challenge confidence often become the experiences that strengthen it. True Developer Confidence Growth happens when engineers stop measuring success by what they already know and start measuring success by their willingness to keep learning. The developers who thrive over decades aren't the ones who avoid discomfort. They're the ones who embrace it as part of the journey. Stay Connected: Join the Developreneur Community

After a spirited game of Anime or Not-ime, Tim review Capsulre Silence XXIV! Then, Cozy talks about Pokopia and Tim sells Cody on four indie rock albums!Bluesky - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@hardsellshow⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Email - hardsellshow@gmail.comTwitch - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@hardsellshow⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠(00:00:00) Intro: Anime or Not-ime(00:14:38) Review: Capsule Silence XXIV(00:59:16) Middle Segment: Pokopia(01:32:21) Pitch: Frightened Rabbit - Painting of a Panic Attack; Noah Kahan - The Great Divide, The National - Trouble Will Find Me (01:43:25) Outro

Tomas Stokke joins us from Haptic, an architectural firm bringing Scandinavian style to global projects. We also meet Dicle Guntas from Forefront, who aims to revive downtowns through art.See omnystudio.com/listener for privacy information.

Christele Harrouk is a French-Lebanese architect, urban designer, and Editor-in-Chief of ArchDaily. With over a decade of editorial experience, she explores architectural  and urban narratives and amplifies underrepresented voices and geographies, all while contributing to global architectural discourse. Her work focuses on making architectural knowledge more accessible, fostering broader conversations, and critically engaging with the future of the field. We talk about: - Christele's career journey and how feeling like she didn't quite fit within traditional practice led her to experiment with careers in architecture, writing, and even fashion and how those roles eventually led her to her impactful job at ArchDaily.- In regards to her career, we talk about being an “Architect who writes” rather than just a journalist and why careers in editing, curation, and research are just as much a part of the profession as those who build.- We discuss more about ArchDaily's content curation; how they sort through thousands of project submissions and what ultimately influences the people and projects they choose to highlight.- We also talk about content overload and social media, and why ArchDaily is focusing on value rather than short lived trends and algorithms. - We end by talking about Christele's perspective on emerging professionals, student competitions, and technology in the profession. >>> Connect with Christele:ArchDaily: https://www.archdaily.com/author/christele-harroukLinkedin: https://www.linkedin.com/in/christele-harrouk-1250a6a2/ Instagram: https://www.instagram.com/christeleharrouk/ >>>Thank you to our Sponsor:⁠⁠⁠Arcol ⁠⁠⁠is a collaborative building design tool built for modern teams. Arcol streamlines your design process by keeping your model, data, and presentations in sync- enabling your team to work together seamlessly. Learn more about Arcol on their ⁠⁠⁠Website⁠⁠⁠, ⁠⁠⁠Instagram⁠⁠⁠, ⁠⁠⁠YouTube⁠⁠⁠, ⁠⁠⁠X⁠⁠⁠, and ⁠⁠⁠LinkedIn⁠⁠⁠.>>>Connect with Architectette:- Website: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ www.architectette.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ (Learn more)- Instagram:⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ @architectette⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ (See more)- Newsletter:⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ www.architectette.com/newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ (Behind the Scenes Content)- LinkedIn:⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ The Architectette Podcast⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Page and/or⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Caitlin Brady⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠>>> Support Architectette:- Leave us a rating and review!>>>Music by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ AlexGrohl⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ from ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Pixabay⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.

Alex Horne - comedian, creator, and the middle of three boys from Chichester - joins Harry to talk about loving school, his hard-hitting Goldsmiths student documentary about urban foxes, and whether the word "meat" was meant as a pun in Harry's new ballad. We also hear about a 24 hour singing challenge that accidentally lasted 25 and three quarter hours, why Alex's wife Rachel is in charge of his private pension, and a highly questionable "life swap" idea based entirely on dishwasher ethics. Architectural historian and seaside culture expert Dr. Kathryn Ferry stops by to celebrate Scarborough's 400th anniversary and answer the questions that matter - did King George III actually say "bugger Bognor"? Why do pleasure piers have a habit of burning down? And would you buy the Brighton Palace Pier with Harry? Hit subscribe so you never miss an episode! Timestamps 00:00 – Welcome to the Hill Show! 00:36 – A Love Song for Ham 01:36 – Meet Alex Horne! 02:28 – Licky the Mascot 03:45 – The Cheshire United Pig Mascot 04:50 – The 25-and-Three-Quarter-Hour Sing-a-thon Error 06:15 – Granola Chaos Backstage at Battersea Power Station 07:18 – Dishwashing Debates & The Wife Swap Idea 10:45 – Sarah the AI Bot Claims She Felt Scammed 12:44 – Is Alex a Musician? (And the Son of a GP) 15:25 – Goldsmiths, Urban Foxes, and a Guaranteed Distinction 16:45 – Seeing Vic and Bob at the Albany Empire 18:45 – Sarah's Breakdown of Alex's Sky News Career 22:20 – Trying to Force "Honk" and "Pratt Digger" into the Dictionary 24:35 – Meeting Ken Dodd & Leaving the Show to Get a Coat 26:34 – Wafer-Thin Ham Product Recall Emergency 28:40 – Taskmaster in the Children's Ward 29:45 – The Traumatic Five-Foot Badger Story 31:04 – Wafer-Thin Ham Preventative Nose Cages 32:34 – The British Seaside ft. Dr. Catherine Ferry 35:05 – Scarborough's 400th Anniversary & The Mineral Spring 37:32 – Steamers, Trains, and Jane Austen Styles 38:45 – King George V and the Truth About "Bugger Bognor" 39:15 – Victorians, Bank Holidays, and the Invention of the Holiday 40:00 – The Very First Pleasure Pier on the Isle of Wight 42:50 – Buying Brighton Pier & The Fire Overheads 44:54 – Pebble Ridges, Mud, and Catherine's Postcard Book 47:45 – Name the Celebrity Seed! 52:30 – Gary's Joke Corner: Identity Politics 54:55 – Animals in Clothes Outro Song "Alex Horne" by Wikipedia contributors, used under CC BY-SA 4.0. Derived from the Wikipedia article on Alex Horne. / This work is licensed under CC BY-SA 4.0. Learn more about your ad choices. Visit podcastchoices.com/adchoices

 summaryThis episode features an engaging discussion on architectural process, design techniques, and the use of AI in creative workflows. Kurt and Jamie share insights on sketching, digital rendering, and the importance of process in architecture and design.Chapters00:00 Coffee Conversations and Personal Updates03:16 Exploring Kalamazoo and Local Lore08:28 Pronunciation Games and Cultural Anecdotes10:08 Exploring the Creative Process11:15 Midjourney and Image Generation Techniques13:17 Analyzing Artistic Styles and Techniques16:37 Iterative Design and Architectural Concepts18:35 Juxtaposition of Old and New in Architecture22:04 Inhabiting Spaces: The Role of Installation24:39 Reconstructing Historical Contexts in Design28:31 Balancing Old and New in Urban Design32:13 The Importance of Process in Design38:00 Teaching Techniques and the Value of Sketching resourcesMidjourneys AI Tool - https://www.midjourney.com/Charcoal Drawing Techniques - https://www.architecturaldigest.com/story/how-to-master-charcoal-drawingWatercolor Digital Effects - https://www.youtube.com/watch?v=exampleSecretary of the Interior Standards for Rehabilitation - https://www.nps.gov/tps/standards/rehabilitation.htmSend Feedback :) Support the showBuy some Coffee! Support the Show!https://ko-fi.com/coffeesketchpodcast/shopOur LinksFollow Jamie on Instagram  - https://www.instagram.com/falloutstudio/ Follow Kurt on Instagram - https://www.instagram.com/kurtneiswender/ Kurt's Practice - https://www.instagram.com/urbancolabarchitecture/ Coffee Sketch on Twitter - https://twitter.com/coffeesketch Jamie on Twitter - https://twitter.com/falloutstudio Kurt on Twitter - https://twitter.com/kurtneiswender 

Luxury residential properties feature complex architecture and premium materials that standard roofing companies are not equipped to handle. This article explores why high-end homes demand specialized architectural roofing expertise for roof installations, repairs, and long-term preservation. Salvo Architectural Roofing Contractors City: Naperville Address: 566 West 5th Avenue Website: https://salvoarchitecturalroofingcontractors.com/ Phone: +1 630 857 3631 Email: info@salvoarchitecturalroofingcontractors.com

Architectural restoration requires specialized knowledge, historical accuracy, and rare craftsmanship that general roofing companies cannot provide. This article examines why complex historical and architectural preservation projects demand an elite, experienced firm to protect structural integrity and heritage. Salvo Architectural Roofing Contractors City: Naperville Address: 566 West 5th Avenue Website: https://salvoarchitecturalroofingcontractors.com/ Phone: +1 630 857 3631 Email: info@salvoarchitecturalroofingcontractors.com

Moore's Law has been a cornerstone of the rapid advancement of digital technology over the past decades, although it is now confronting physical limits and diminishing economic returns.过去几十年，摩尔定律一直是数字技术快速进步的基石，尽管如今它正面临物理极限和边际收益递减的挑战。For an industry conditioned to equate progress with nanometers, the Tau Scaling Law disclosed by Huawei on Monday is a challenge to the organizing logic of the semiconductor ecosystem.对于一个习惯于用纳米衡量进步的行业而言，华为5月25日公布的“τ scaling law”（陶缩放定律）无疑是对半导体生态系统运行逻辑的一次挑战。Instead of continuing the increasingly expensive race to shrink transistors, Tau Scaling proposes that future chip performance gains can come from compressing the signal propagation time through architectural and timing innovations. Huawei has set a target of reaching a chip density equivalent to 1.4 nanometers by 2031.陶缩放定律提出，摒弃代价日益高昂的晶体管微缩竞赛，转而通过架构与时序创新压缩信号传播时间，驱动未来芯片性能提升。华为已设定目标，到2031年实现相当于1.4纳米制程的芯片密度。Washington's export restrictions have attempted to cut China off from advanced lithography equipment, leading-edge foundries and portions of the global event-driven architecture software stack. Such measures were designed to slow China's progress in advanced semiconductors.美国的出口限制试图将中国排除在先进光刻设备、前沿代工厂以及部分全球事件驱动架构软件栈之外。这些措施旨在减缓中国在先进半导体领域的进步。That is where Tau Scaling enters the picture. Instead of shrinking transistor dimensions from 3 nm to 2 nm and beyond, Huawei is extracting more performance from mature process nodes such as 5 nm and 7 nm by means of architectural optimization, timing compression, logic folding and system-level coordination.这正是陶缩放定律发挥作用的地方。华为不再追求从3纳米到2纳米及更小尺寸的晶体管微缩，而是通过架构优化、时序压缩、逻辑折叠和系统级协调等手段，从5纳米、7纳米等成熟工艺节点中挖掘更多性能。Much of the underlying research — including asynchronous computing concepts, wave pipelining, and timing optimization techniques — can be traced back decades. What Huawei has done, under conditions where the traditional scaling route became inaccessible, is to revisit those ideas, combine them, enhance them and industrialize them.许多基础性研究，包括异步计算概念、波流水线技术和时序优化技术等都可以追溯到几十年前。华为所做的，是在传统微缩路径受阻的情况下，重新审视这些想法，将它们加以融合、改进并产业化。In that sense, the emergence of Tau Scaling reflects a broader historical pattern in technology. Constraints often redirect innovation rather than stop it. So, if chip performance can be improved through architecture rather than lithography alone, then the balance of competition changes. The key question becomes not simply who owns the most advanced EUV machines, but who can design the most efficient systems using available manufacturing capabilities.从这个意义上说，陶缩放定律揭示了技术发展的一条普遍规律：限制往往促使创新转向，而非将其扼杀。若芯片性能可借架构而非单纯依赖光刻技术提升，竞争的格局便将随之改变。关键问题不再是“谁拥有最先进的极紫外光刻机”，而是“谁能利用现有制造能力设计出最高效的系统”。It would be premature, though, to declare that the arrival of Tau Scaling heralds the post-Moore era. Semiconductor history is filled with elegant concepts that struggled once they encountered manufacturing economics, ecosystem inertia, or commercial realities. Huawei's proposal faces several important ceilings.不过，现在就说陶缩放定律预示后摩尔时代已经开启，未免为时过早。半导体发展史上不乏精妙构想，但一旦遭遇制造经济学、生态系统惯性或商业现实，便会步履维艰。华为的方案目前仍面临若干关键瓶颈。Architecture cannot completely replace physics. Timing optimization can reduce inefficiencies, but signals still obey physical propagation limits. As chips become larger and workloads more complex, interconnect delays and synchronization overhead remain major bottlenecks.架构终究无法替代物理规律。时序优化虽能减少低效，信号却始终受制于物理传播的极限。随着芯片尺寸不断增大、工作负载日趋复杂，互连延迟与同步开销仍是绕不开的主要瓶颈。Logic folding and time-domain optimization introduce their own complexity penalties. The more aggressively a design compresses timing, the harder verification, debugging and manufacturing become. Commercialization will determine whether Tau Scaling becomes an industry framework. For Huawei's approach to become influential, other companies must adopt it, customers must validate it and developers must build around it. That process will take years, not conference announcements.逻辑折叠与时域优化本身也需付出复杂性代价。设计越激进地压缩时序，验证、调试与制造的难度便越大。陶缩放定律能否成为行业框架，最终取决于商业化落地。华为的方案要产生影响力，必须获得其他公司的采纳、客户的验证以及开发者的生态共建。这需要数年之功，而非一场发布会所能成就。Even so, the broader lesson already stands. The semiconductor industry is entering a phase where innovation no longer relies exclusively on brute-force scaling and trillion-dollar capital expenditures. Architectural intelligence, software-hardware codesign, advanced packaging and system optimization are becoming increasingly important.即便如此，一个更宏观的启示已然显现：半导体行业正步入新阶段——创新不再单纯依赖蛮力微缩与万亿美元级的资本投入。架构智能、软硬件协同设计、先进封装与系统优化，正变得日益关键。For China, that shift creates both an opportunity and a responsibility. The country still faces major gaps in lithography, materials, EDA tools and manufacturing equipment. But Tau Scaling demonstrates something equally important: when external pressure blocks one route, researchers will look for alternative routes and solutions can emerge through persistence, engineering discipline and targeted input.对中国而言，这一转变既是机遇，也是责任。尽管在光刻、材料、EDA工具及制造设备上差距显著，但陶缩放定律揭示了一个重要道理：外部压力堵住一条路，科研人员就会开辟另一条路。凭借坚韧、工程严谨和精准投入，解决方案终将破土而出。The semiconductor race is no longer just about making things smaller. Increasingly, it is about making systems smarter. The challenge now is for more Chinese companies and engineers to push beyond incremental imitation and focus on resolving genuine choke-point technologies with the tools they already possess.半导体竞赛，已从单纯追求“更小”转向致力实现“更智能”。当务之急，是更多中国企业与工程师超越渐进式模仿，立足现有工具，攻克真正的“卡脖子”技术。Moore's Law /mʊəz lɔː/摩尔定律diminishing economic returns /dɪˈmɪnɪʃɪŋ ˌiːkəˈnɒmɪk rɪˈtɜːnz/边际收益递减conditioned to /kənˈdɪʃənd tuː/习惯于Tau Scaling Law /taʊ ˈskeɪlɪŋ lɔː/ τ缩放定律（陶缩放定律）semiconductor ecosystem /ˌsemikənˈdʌktər ˈiːkəʊsɪstəm/半导体生态系统shrink transistors /ʃrɪŋk trænˈzɪstəz/微缩晶体管advanced lithography equipment /ədˈvɑːnst lɪˈθɒɡrəfi ɪˈkwɪpmənt/先进光刻设备leading-edge foundries /ˈliːdɪŋ edʒ ˈfaʊndriz/前沿代工厂event-driven architecture /ɪˈvent ˈdrɪvən ˈɑːkɪtektʃə/事件驱动架构asynchronous computing /eɪˈsɪŋkrənəs kəmˈpjuːtɪŋ/异步计算wave pipelining /weɪv ˈpaɪplaɪnɪŋ/波流水线EUV machines /ˌiː juː ˈviː məˈʃiːnz/极紫外光刻机post-Moore era /pəʊst mʊə ˈɪərə/后摩尔时代manufacturing economics /ˌmænjʊˈfæktʃərɪŋ ˌiːkəˈnɒmɪks/制造经济学ecosystem inertia /ˈiːkəʊsɪstəm ɪˈnɜːʃə/生态系统惯性software-hardware codesign /ˈsɒftweə ˈhɑːdweə ˌkəʊdɪˈzaɪn/软硬件协同设计advanced packaging /ədˈvɑːnst ˈpækɪdʒɪŋ/先进封装system optimization /ˈsɪstəm ˌɒptɪmaɪˈzeɪʃən/系统优化lithography /lɪˈθɒɡrəfi/光刻EDA tools /ˌiː diː ˈeɪ tuːlz/电子设计自动化工具

Betsy discusses her recent move and insights on real estate, answers Laurie's question about leather couches by explaining different types of leather, advises Kirsten on coordinating curtains in open concept spaces, and helps Monica with craftsman style door and window frames. Plus, check out the new YouTube channel. 0:00 Introduction and premium membership details 1:27 Welcoming listeners and encouraging questions 2:09 Betsy's personal update on moving and real estate 7:00 Listener question from Laurie about leather couches 9:25 Explanation of different types of leather 17:37 Listener question from Kirsten about coordinating curtains in open concept spaces 24:07 Listener question from Monica about craftsman style door and window frames 31:23 Announcement about the new YouTube channel and social media links 33:07 Closing remarks and credits Don't forget to subscribe for more design tips and inspiration! Links: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Uploft.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠AffordableInteriorDesign.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Submit your design questions⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to be featured on the show ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Become a Premium Member⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and access the bonus episodes Click ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to become an interior designer with Uploft's Interior Design Academy. Get Betsy's book: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠betsyhelmuth.com/book⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠For more about our residential interior design services, visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ModernInteriorDesign.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ For our commercial interior design services, visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠OfficeInteriorDesign.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Follow Us: Instagram: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@uploftinteriordesign⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Facebook: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠facebook.com/UploftIntDes⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ TikTok: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠tiktok.com/@uploftinteriordesign⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ LinkedIn: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠linkedin.com/company/uploft-interior-design⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ If you enjoy the show, please spread the word and leave a review on iTunes! Learn more about your ad choices. Visit podcastchoices.com/adchoices

Ep 118: And another one live from the ISA International Sign Expo 2026. This time, Tyler is joined by Josh Culverhouse and Tom Reece of Metamark to talk about the durability and transformative qualities of Metamark Interior Architectural Films.Check out the featured products:SIHL ProductsGFP ProductsArlon DPF V9500G2G Products"Your podcast is the best podcast in the business." - Jared Granberry, President, GSG (Graphic Solutions Group)The Slightly Serious Sign Podcast is now the #1 Most Fact Checked Podcast in the United States.Voted #1 by Signman (standing on a van on top of 18 pallets changing a lightbulb over a movie theater sign)https://www.wensco.com/company/slightly-serious-sign-podcast616.785.3333W.A.R. (Wensco Automotive Restyling)Slightly Serious Sign Podcast Theme Song Courtesy of Joe Morreale© 2025 Joe MorrealeThe views, thoughts, and opinions expressed are the speaker's own and do not represent the views, thoughts, and opinions of Wensco Sign Supply. The material and information presented here is for general information purposes only. The "Wensco Sign Supply" name and all forms and abbreviations are the property of its owner and its use does not imply endorsement of or opposition to any specific organization, product, or service. Things to...

Cindy Lee from Stratco Architectural  talks about the strategies needed to bridge the gap between design and delivery in her role at Stratco. In this recent interview, Cindy Lee shares insights on the company's evolution, the shifting challenges of practice, and how early collaboration with suppliers can help architects realise their vision.

Can the rigorous, systematic process of architectural design be the secret ingredient to disrupting the fashion industry?In this episode of Practice Disrupted, Evelyn Lee sits down with Aidan Turner, the founder of The Garment Architect. Aidan, who graduated from the Syracuse School of Architecture just one year ago, is challenging the standard "fast fashion" model by treating apparel design with the same technical precision and systemic discipline typically reserved for buildings.Aidan's journey began well before his first day of architecture school; he was running a clothing brand as an undergraduate, balancing studio critiques with supply chain management. He explains how he bridges these two worlds by viewing a "tech pack" (the documentation for a garment) as an architectural blueprint. By applying principles like site analysis (market research), structural integrity (fabric testing), and construction sequencing (production), Aidan has created a studio that prioritizes quality and longevity over the rapid-fire releases common in the apparel world.The conversation explores the "architectural mindset" as a transferable skill. Aidan argues that the value architects bring to any industry, whether it's real estate, manufacturing, or fashion, is the ability to see a project through a full, multi-phase lifecycle. They discuss the challenges of being an entrepreneur in a field that often demands 100% of your time, and why Aidan believes the "veil of mystery" surrounding the design process needs to be lifted to better communicate the true value of professional expertise to clients."We communicate through drawings, but our process is definitely not communicated through our deliverables. It's everything that goes on in our brains. I think if architecture can evolve in a way where our skills are valued as highly as they should be, then we would be able to be more entrepreneurial and more business-minded." - Aidan TurnerThis episode is a compelling case study on the versatility of an architectural education. Aidan highlights that when you understand how to design systems and manage complex production, the scale of the object, whether it's a skyscraper or a jacket, is secondary to the process itself.Guest:Aidan Turner is the founder of The Garment Architect, a Syracuse School of Architecture alumnus, and an entrepreneur who successfully merged his love for fashion and architecture. He is redefining apparel design by implementing professional architectural workflows, including rigorous blueprinting, sourcing, and project management, to create more sustainable and high-quality clothing.This episode is especially for you if:✅ You are curious about how architectural skills and workflows can be applied to fields entirely outside of the built environment.✅ You want to learn how to bridge the gap between "design-focused" creative work and "business-focused" operational work.✅ You are a student or recent graduate wondering how to leverage your education to start a business early in your career.✅ You believe the architecture profession needs to remove the "veil of mystery" and communicate our value more clearly to non-architect clients.✅ You are interested in the parallels between construction documents and technical apparel packs for streamlined production.What have you done to take action lately? Share your reflections with us on social and join the conversation.

Take the 2026 AI Engineering Survey and get >$2k in credits and AIE WF tickets!This was recorded before Railway suffered a major GCP outage on May 19, despite being a multi-AZ, multi-zone mesh ring, with HA fiber interconnects between their Metal GCP AWS, because workload discoverability was unintentionally still tied to GCP. All has been resolved with a post-mortem.Railway did not start as an AI infrastructure company.It was founded in 2020 years before agents became the default way people thought about deploying software. Jake Cooper, formerly at Bloomberg and Uber, started Railway with a simple obsession: the activation energy to ship something to production should be near zero. Push code, get a URL, iterate. No Docker files, no Kubernetes manifests, no Ansible scripts stacked on Ansible scripts.For years, this was a slow grind. Railway spent its first 18 months hand-acquiring its first 100 users with Jake personally greeting every Discord signup on a second monitor.Today, Railway has raised $124m and is growing very fast. A 35-person team supports 3 million users, adding roughly 100,000 signups a week. Their bare metal data centers have a 3-month payback period vs. renting in the cloud, with 70% margins funding aggressive cloud bursting when needed. The servers they own have actually appreciated in value as RAM prices have climbed basically meaning the value of their hardware now exceeds the capital they've raised.From rebuilding Railway's network overlay over a weekend to moving the vast majority of workloads onto its own bare metal data centers, Jake Cooper is trying to build a new cloud for an agent-native world. In this episode, Railway's founder and “conductor” joins swyx and Alessio to unpack why the next era of software infrastructure is not just “Heroku but newer,” what agents need that humans did not, and why the old deployment loop of Git, PRs, CI/CD, and static cloud resources may be heading for a rewrite.We go deep on Railway's infrastructure stack: own-metal data centers, three-month cloud payback periods, cloud bursting, data center debt, Railpack, Nixpacks, Temporal, feature flags, Central Station, content-addressable filesystems, agent-safe production forks, and why the CLI may become more important than the canvas in an agent world. Jake also shares the founder journey behind Railway, how the company survived losing $500K/month, why it now serves millions of users with only 35 people, and why he believes the pull request is dying.We discuss:* How Railway went from a slow six-year grind to adding 100,000 users a week* How Railway thinks about agents as the next dominant software species* Why agents need version control, observability, compute, storage, and orchestration at 1000x scale* The economics of Railway's own-metal data centers and three-month payback* How Railway uses cloud bursting while scaling its own infrastructure* Why data center debt can be a better tool than venture debt for infra startups* Central Station, Railway's internal system for clustering customer feedback and incidents* Why responsible disclosure and over-communication matter for platforms* Why feature flags, progressive rollouts, and shadow traffic are essential for agents* Temporal's strengths, pain points, and why workflows matter for agents* Railpack, Nixpacks, Nix, and lazy-loaded content-addressable filesystems* Why “cattle, not pets” may change if you can clone the pets* Why Railway is building a new cloud from scratch instead of copying hyperscalers* The solo founder path, focus, writing, and how Jake thinks about company buildingRailway:* Website: https://railway.com/* X: https://x.com/RailwayJake Cooper:* LinkedIn: https://www.linkedin.com/in/thejakecooper/* X: https://x.com/JustJakeTimestamps00:00:00 Introduction: What Is Railway?00:02:07 Jake's Path to Railway00:06:13 Railway's Six-Year Growth Story00:08:52 Rebuilding the Business After the Free Tier00:11:17 Agents as the Next Software Platform00:13:29 Railway's Infrastructure Philosophy00:15:42 Bare Metal, Cloud Economics, and the Compute Crunch00:17:22 Cloud Bursting and Five-Cloud Networking00:20:20 Data Center Debt and Infra Financing00:23:31 Data Centers in Space00:25:24 What Agents Need From Infrastructure00:28:24 CLIs, Canvas, and Agent-Native UX00:35:15 Central Station, Incidents, and Responsible Disclosure00:40:30 Safe Rollouts, SRE Agents, and Production Forks00:45:00 AI SRE, Specs, Code, and Tests00:48:24 Self-Replicating Infrastructure and the New Serverless00:53:18 Heroku, Temporal, and Workflow Engines01:04:07 Railpack, Nixpacks, and Lazy-Loaded Filesystems01:06:01 Coding Agents, Token Spend, and Roadmap Acceleration01:10:56 The Pull Request Is Dying01:12:28 Feature Flags and the Agent-Era SDLC01:16:15 Cattle, Pets, and Cloning Machines01:19:29 Solo Founder Lessons01:24:12 Focus, GPUs, and Building a New Cloud01:28:20 Closing ThoughtsTranscriptAlessio [00:00:00]: Hey, everyone. Welcome to the Latent Space Podcast. This is Alessio, founder of Kernel Labs, and I'm joined by Swyx, editor of Latent Space.Swyx [00:00:10]: Hey, hey, hey. Today we're in the studio with Jake Cooper of Railway.Alessio [00:00:14]: Conductor of Railway.Swyx [00:00:15]: Conductor at Railway. Yeah.Alessio [00:00:16]: Choo-choo.Swyx [00:00:17]: Do you actually have that anywhere, like on your business card?Jake [00:00:20]: We call some of our volunteer moderators conductors. I don't have a business card. We're not that big yet. At some point I will. I got handed a nice business card from the Supermicro folks, and I was like, “Damn, this is pretty official.”Swyx [00:00:30]: Business cards are coming back.Jake [00:00:32]: They're cool. They're hip. The conductor thing is good. We're trying to figure out what we want to call each other internally. Some people think it's super cringe and say, “You don't need a name for people internally.” Some people want to call each other something. We still don't have a really good one.Jake [00:00:55]: We've got New Railcrews, Trainiacs. Nothing has stuck yet.Swyx [00:01:00]: I like Trainiac. Trainiac sounds good. Railwayians. For those who don't know, what is Railway? Let's give people a crisp definition up front.Jake [00:01:09]: Railway is the easiest way to ship anything. You go to the canvas, or you talk with Claude, and you say, “Deploy a Postgres instance, deploy my GitHub repository, run this code,” and you're off to the races.Swyx [00:01:22]: You've got a nice animation on the landing page.Jake [00:01:24]: Thank you. None of my work, by the way. They don't let me touch the design stuff anymore.Jake [00:01:25]: We want to make it trivially easy not just to deploy things, but to evolve applications over time. Most tooling right now stacks entropy on top of entropy: Docker, Kubernetes, Ansible scripts, and all these other things. If we can version all of your software and keep track of all the changes, then we can make it trivial to clone environments, fork into a parallel universe, get copies of production data, get copies of any services, make changes, validate them, and collapse them back in without reproducing everything across a staging environment.The Railway Origin Story: From Uber Systems to a New CloudSwyx [00:02:07]: I was looking at your background: Bloomberg, Uber. Nothing immediately stands out as, “This guy is going to found the next great platform as a service.” What prepared you for Railway?Jake [00:02:21]: It was curiosity to keep going deeper. I started out on front-end stuff, working on Wolfram Mathematica and porting it over. Then I briefly moved to Bloomberg, then toward Uber and distributed systems, taking the Jump Bikes systems and moving them to a distributed system built on top of Cadence, the pre-Temporal Temporal.Swyx [00:02:44]: Which, by the way, I'm happy to talk about, pros and cons.Jake [00:02:48]: Totally.Swyx [00:02:51]: But let's do the Railway story.Jake [00:02:52]: It has been a continual step of wanting an experience. Whether it's walking up to a bike, unlocking it, and having it work frictionlessly, or something else, the depth required to make that happen follows from the experience. A lot of the work I do, and a lot of the team does, is in service of that experience. We fundamentally don't care how deep we have to go. We will swim to the bottom of the swimming pool to get the experience.Jake [00:03:17]: I don't have a physics PhD. I did an EECS degree. It has always been about figuring out the next step: how do we get there? That's what led to starting Railway for that experience and then moving all the way to bare metal data centers. I was adding patches to the kernel this week to get the experience there because I can see how much better it can be.Swyx [00:03:49]: Other patches to the Linux kernel this week?Jake [00:03:51]: Yeah. Not upstream. Our fork.Swyx [00:03:52]: That's a flex. Railpack? No, this is different. This is the OS on top of Railpack?Jake [00:03:57]: No, this is an actual kernel patch. It's always literally: what do we have to do to get that experience? Then figure it out. Anything is figureoutable.Swyx [00:04:10]: Would you send the patch upstream, or does it not fit other use cases?Jake [00:04:13]: Maybe. We have to work out the experience internally. It has to do with the storage layer we're building for some of the agentic stuff. Maybe it'll be useful upstream, but it's deeply useful for us internally.Open Source, Forks, and Non-Deterministic VersioningSwyx [00:04:29]: You mentioned open source before. How do you think about starting from open source, and then coding agents letting you do a lot more from forks of it?Jake [00:04:38]: GitHub's original sin is that it's almost a series of broken pointers. You have this thing, then you clone it, and now you've lost the whole upstream. How do we make it trivial for people to modify really small pieces of it?Jake [00:04:51]: We think of Git in a discrete sense: I've either made a change and merged upstream, or I haven't. What would it look like if it were percentage-based, a little more non-deterministic, or a stream of changes that users traverse as a percentage rolled out in general and then rolled all the way up?Jake [00:05:13]: We have the open-source kickback program and let you deploy templates because we want to make it trivial for people to version these shards over time. It solves a large problem around authentication, authorization, and security. NPM has a way to define, “Don't take any new packages.” The ideal end state is that you roll out progressively to users with the minimum impact zone and continue rolling up. JPMorgan should probably be the last one on the patch line, for all our sakes, because our money and livelihoods are there.Jake [00:05:53]: It's okay if Johnny Vibe Coder gets a broken patch because there's so much entropy in the system that the rubber has to meet the road at some point. You have to test at varying levels.The Long Grind: First Users, Free Tier, and Making the Business WorkSwyx [00:06:13]: I wanted to pull up this glorious chart, which is your usage or number of daily signups?Jake [00:06:22]: Daily signups, I think.Swyx [00:06:24]: You started six years ago. It was a slow grind, and now you're on a rocket ship. You say, “Don't doubt your fight and don't quit.” Maybe pick out certain points that were key inflections for the company.Jake [00:06:40]: At the start, it's about getting your first 100 users, hell or high water. We had a website and a support link. The support link was the Discord channel. I had notifications on with two monitors: the monitor I was working on and the other monitor with Discord. If anybody came in, I was immediately like, “Hey, how's it going?” It was rare, so getting those first 100 users to come back was the start.Jake [00:07:14]: Then you build a consultancy factory because users want all these things. You have to go back to the board and ask, “What is the actual product offering I want to build on top of this?”Jake [00:07:28]: VCs want charts that always go up and to the right, but in reality you don't necessarily want charts that look like that. For us, there have been periods of expansion where we add features to test use cases, and periods of compaction where we ask, “If the experience we have is good, how do we make it significantly better?” Maybe we strip out features that don't fit our ICP anymore.Jake [00:07:57]: The boom from 2022 to 2023 came from the free tier. Everybody under the sun was using it.Swyx [00:08:09]: A lot of Reddit bots and Discord bots.Jake [00:08:12]: And crypto miners. When you build an open product on the internet where anybody can sign up, the internet is a horrible place with so many things. You go through periods of asking, “How do I reach as many people as possible?” Then, “How do I fit the exact use case for the people who really matter and are really excited about this specific thing?”Jake [00:08:39]: Then there was a two-year period of making the actual business work. During the free-tier era, we were losing about half a million dollars a month.Swyx [00:08:59]: On a $20 million bank account.Jake [00:09:02]: On a $20 million bank account with maybe $50,000 a month in revenue. That's a horrible business. I don't know how anybody invested. But you have to go through it and say, “We have an experience people love, but the business has to work.”Jake [00:09:17]: There are two schools of thought. You can run the horrible business all the way up with bad margins, or you can go back and make it work. We've always wanted a super lean team. We're 35 people right now. It's very small.Swyx [00:09:36]: Supporting three million already?Jake [00:09:38]: Yeah. We're adding 100,000 users a week right now, so it's growing fast. We don't want to add headcount for the sake of headcount or throw bodies at problems. We want to build systems. It's hard to build systems during expansion because you're adding things to the system because people are asking for them or things are breaking.Jake [00:10:00]: We had to cut off the free users for a little while, rebuild the business, and make sure it worked. We want to reach as many people as possible because software is important. It's become difficult to create things in the physical world, so it's important to make it easy for people to build in the virtual world and have access to creation. But there are legs to that journey.Jake [00:10:30]: You can see divots in the charts. If you follow between 2025 and 2026, it's either summer or winter. People go on holiday with family.Swyx [00:10:50]: It affects that much?Jake [00:10:51]: Yeah. It's kind of B2C and kind of B2B. People are shipping constantly, then they stop. Our activation curve now shows more people activating on weekdays because we have more business users, so it smooths out over time.Agents as the New Interface to DeploymentSwyx [00:11:17]: Was there a point where you started prioritizing AI development or agent development?Jake [00:11:24]: We've prioritized agentic as a top-of-funnel thing. Over the last six months, we've deeply prioritized agentic as a mechanism to build and deploy things because we believe the curve is so steep and that is how people will build and deploy software.Jake [00:11:42]: It almost fundamentally doesn't matter whether this is dot-com or not because we're all on the internet anyway. If agents are going to deploy a bunch of things and we hit an inference wall at some point, we'll fix those problems. The dominant species over the next 10 years is that we've moved from assembly to C to C++ to JavaScript to words. You're going to need to close that loop.Swyx [00:12:13]: When you say this is dot-com, did you mean buying the domain, or the general case?Jake [00:12:17]: I mean the dot-com era, when companies had a huge run-up because people understood the internet was important. Then they hit bottlenecks, fundamental laws of physics, math didn't work, and everybody came back down to earth. But it didn't matter because the internet became so impactful. If you operate on a long enough time horizon, you should build these things anyway because you can see where it's going.Jake [00:12:45]: That's where I think a lot of agent stuff is. You get to a point where you're running thousands of agents in parallel. What is the inference cost? What is the compute cost? How do you make that efficient? How do you coordinate all this? We have issues coordinating humans; we don't even have good tooling for that. Now we have to figure out how to get agents to coordinate, safely version changes, and know when to raise their hand for someone to intervene. Otherwise it becomes an interrupt factory.Railway's Infrastructure Thesis: Network, Compute, Storage, and MetalSwyx [00:13:19]: Let's go right into the technical side. What are the core infrastructure or architectural beliefs of Railway that allow you to do what you do?Jake [00:13:29]: The primitives matter a lot for us. We need network, compute, storage, and orchestration around it. You need control over a lot of those things. We've talked a lot about how we don't really use Kubernetes because we want higher-order control to place workloads in very specific places.Jake [00:13:48]: The reason is that you have to be very efficient with agents: memory reuse and all these other things, or you're going to massively blow up your cost structure. Being able to rack and stack your own servers and build your own metal unlocks performance and cost. Experiences where you're running 1,000 agents in parallel are not massively cost prohibitive.Jake [00:14:13]: Token use and compute use are blowing up. Over time, those things have to get a lot more efficient. You can get a lot of margin to make those experiences solid by building your own metal. That's all in service of offering a differentiated experience to as many people as humanly possible.Swyx [00:14:51]: You have a data center in Singapore.Jake [00:14:53]: Yeah. We have two in every other region now. In Singapore, we're adding a second one in Q3.Swyx [00:14:58]: What's it like? I've never built a data center. Do you go to Equinix and say, “I want some slots?”Jake [00:15:05]: Yeah. Equinix. You basically go and say, “I want power and I want a cage.” They say, “Great, here's what it's going to be.” You rent the cage for a period of time, fill it with racks and servers, and hook up internet to it. That's all the pieces.Swyx [00:15:36]: Then you handle everything else.Jake [00:15:37]: You handle everything else.Swyx [00:15:39]: What's the math versus clouds doing it for you?Jake [00:15:43]: If we rented in the cloud, our payback period when we go to metal is about three months.Swyx [00:15:50]: Which is crazy.Jake [00:15:51]: It's nuts. That's four years of depreciated hardware. You're going to see a lot of this compute crunch because hyperscalers are buying up a lot of stuff. We're working directly with OEMs, resellers, and people building these machines: Supermicro, Dell, and others.Jake [00:16:11]: Upstream, there's a bunch of supply pressure. When we raised our last round, between deploying capital for servers and now, the amount of money we've raised is less than the amount of money we have in the bank plus the value of the servers because the servers have appreciated as RAM has gone up. It's nuts how valuable hardware has become.Jake [00:16:50]: If you look at hyperscalers, they deployed around $80 billion of capital expenditures this year, and next year will be more. That's a massive infrastructure build-out. You look at that and think it's crazy that they're spending way more than the Manhattan Project. But if every person is going to run dozens or hundreds of agents in parallel, you have no conceptual idea how much compute is required to make that experience happen, even if you're deeply efficient and sharing resources. And that doesn't even count inference.Swyx [00:17:22]: How do you plan the build-out? The growth chart is so vertical. Are you usually at 100% utilization as soon as racks are live? How far ahead are you planning?Jake [00:17:33]: We still maintain cloud presence for bursting. We work with AWS, GCP, and a few other clouds. We can rent, and then the moment we get space or power, we compact those workloads off the cloud. We started on the clouds, then built a system to migrate to our own metal. There's nothing that says you can't continually do that again, and that's exactly what we do. We never want to be compute constrained.Jake [00:18:09]: At the start of the year, we actually became compute constrained because one upstream provider wasn't able to give us quota at the rate we needed, and the hardware was slower. I spent a weekend rebuilding our entire network overlay so we could straddle five clouds: Oracle, AWS, ourselves, GCP, and one other one. We can do more than that now.Jake [00:18:38]: We got into a spot where we were trying to pack instances tight because we couldn't get enough compute. That led to a few reliability issues, which are now past us. I made a tweet pointing out that it's becoming harder and harder to acquire compute at the rate these models need to acquire compute. We got bit by it.Swyx [00:19:15]: How do you think about pricing knowing you might not have your own metal available at all times? Are you pricing assuming you need extra margin if you end up going into the cloud?Jake [00:19:26]: Because we've built out our metal data centers, our margins on metal are around 70%. We can deeply subsidize the cloud business if we want to scale at a reasonable rate. We have a few levers: metal, which makes the margins; cloud burst; debt to buy servers; and venture capital. It's an interesting operational problem: how much cash do we have, how much should we raise, how quickly can we deploy it, and can we scale revenue as quickly as we scale compute?Jake [00:20:05]: If we continue making it trivially easy for people to build and deploy, then the faster we close that loop and the more operationally excellent we are with capital, the faster the business can scale. It's almost a straight linear deployment rate.Financing Infrastructure: Hardware Debt, VC, and Operational LeverageSwyx [00:20:20]: I think infra startups raising debt is a tool people don't utilize enough or know enough about. What can you tell us about that? Is it secured against your CPUs?Jake [00:20:32]: It's secured against our hardware.Swyx [00:20:37]: What rates do you get? Who are the lenders?Jake [00:20:39]: We pay prime plus a spread, and we can refinance any of the debt as rates go down. The terms are pretty good. The unfortunate thing is that Twitter has no nuance, so people say, “Venture debt bad.” But as with all things, there are specific tools and areas where you can be deliberate instead of using one tool as a hammer. Venture capital is not the hammer for everything. You have to explore and figure out what works.Swyx [00:21:12]: VC is usually the most expensive financing you can get.Jake [00:21:15]: Yeah. I also think people think about VC incorrectly from a capital-raising perspective. Most people think, “How do I raise as much money as possible from whoever is probably the best I can get at that time?” That's close to right, but what we've tried to do is figure out what unfair advantage we can buy with that equity.Jake [00:21:34]: It's the most expensive equity you're going to give away at that point in time, assuming the company keeps getting better. How do you use it to work with someone stellar who complements you? In the seed stage, I had never started a company. Ray Tonsing had good advice, and I could text him all the time. He was really fast. Awesome.Jake [00:22:01]: Then with John and Erica at Unusual, they said, “You roughly know what you're doing building a product. We'll mostly leave you alone and be available for advice.” Amazing. Then we got to Series A and the business was an operational tire fire because we didn't know how to scale a business. Work with Erica, and Jordan is over at Redpoint, so bonus.Jake [00:22:28]: Now we've raised from TQ and FPV as we're moving into enterprises. Every step of the way, we've asked: who can we partner with at this specific time to unlock the next section of the journey? I don't know enterprise sales. As an engineer, I can eyeball what features we might need, and we have wonderful people internally who can help. But you want boardroom dynamics where everyone is aligned and asking, “How do we win this?” instead of bickering about strategy.Data Centers in Space and the Physics of ComputeSwyx [00:23:31]: You had a tweet about data centers in space. Why no data centers in space?Jake [00:23:37]: It's not “no data centers in space.” My hot take is that I think it is solvable. I've just never seen anybody solve it.Swyx [00:23:49]: You said, “How are you going to dissipate that much heat in a vacuum?” You're making a physics claim.Jake [00:23:55]: I haven't seen anybody prove how you're going to dissipate that much heat in a vacuum. It doesn't mean it's not possible. It just means nobody has brought it up yet.Swyx [00:24:05]: Astrophage.Jake [00:24:06]: I don't know what that is.Swyx [00:24:07]: The Martian thing. Okay, you're very logical.Jake [00:24:09]: It could work. A lot of people are putting the cart before the horse. They say, “We're going to put data centers in space.” Okay, but how? “We have time to figure it out.” It's like in The Martian where they ask how they're going to intercept something and say, “We'll figure it out.”Swyx [00:24:36]: Making a bet on human invention is weird because you blind trust that it can be solved. But with physics, there are first-principles bounds you can put on it. Maybe not. Maybe you're asking to travel time or break a fundamental thermodynamic law.Jake [00:24:57]: I don't know how VCs do this either. How do you know what's not possible and a grift versus what's possible but sounds completely insane? “We're going to put data centers in space.” Coin flip as to which it is, and I guess you'll know in 10 years. That's one cycle.What Agents Need: Versioning, Observability, and 1,000x ScaleSwyx [00:25:23]: Moving back to agents. The branching, fast spin-up, and orchestration you do feels like pre-work that happened to be exactly what agents want. What do agents want differently than humans?Jake [00:25:37]: They want the ability to version things. It's not that different; it materializes slightly differently. Agents want a way to test changes incrementally. Engineers have feature flags. Is there a reason agents can't use feature flags? I don't think so.Jake [00:25:54]: They want version control. Can we use Git or not Git? That one is up in the air. I think something outside Git will emerge for how we version these things over time. They need observability. You need to query what happened, when it happened, which steps failed, traces, logs, metrics, and all the rest. They need network, compute, and storage. They need to write files, save files, iterate on files, and snapshot file systems.Jake [00:26:25]: A lot of what humans needed is in line with what agents need. Branching and forking are not different; we're just moving 1,000 times quicker. It can look like you need something massively different, but what you need is something massively better than what existed. You need orchestration massively better than Kubernetes. You need networking probably better than Envoy. It goes all the way down the stack.Jake [00:26:55]: If the workload profile doesn't change so much as it gets massively compressed because you need thousands of these things, what assumptions change? etcd is going to melt. You need to replace it with something. You can go all the way down the stack and say, “That part has to change, that part has to change, and that part has to change.”Jake [00:27:19]: The interesting thing about the super-exponential curve is that you have to build systems where you can rip out those parts at any time because a new bottleneck might emerge. You get good at parallel agents, and a different part of the system breaks. So it's similar to what humans needed, but at 1,000x scale.Jake [00:27:55]: How do you do code review in the age of agents?Swyx [00:28:00]: You throw more agents at it.Jake [00:28:01]: You don't. But then who reviews for CVEs and all these other things?Swyx [00:28:07]: More agents.Jake [00:28:08]: And that's how we hit the inference wall. You can continually throw agents at the problem, but I think there's a limit to the number of agents you can throw at a problem.CLI, Agent Handles, and Closing the LoopSwyx [00:28:24]: You already had a CLI before it was cool. How is the shape of what you're exposing changing, if at all?Jake [00:28:28]: CLIs have always been cool. The CLI changes because we think about how to give Claude, Codex, ChatGPT, or any model a handhold.Jake [00:28:50]: A CLI is a single command: deploy, get logs, and so on. Things that were prohibitively annoying to humans are not annoying to agents. They're nice. If I handed you a CLI with 40 arguments and 600 flags, you'd think, “I'm never going to use all of this.” But if you hand it to an agent, it says, “This is excellent. I have so many handles to work with.”Jake [00:29:24]: If you're going to expose things to agents that way, you want as many handles as possible where they can get information, query dynamic information, and close the loop quickly. Most problems right now are about how to close the loop as quickly as possible. Where does the agent get stuck, and how can you remove that?Jake [00:29:49]: Telemetry is important. If you can tell where the agent gets stuck from the CLI and say, “12% of people deviate from the happy path because of this, and now I add this argument and drive it down to 2%,” you massively increase the rate of loop closure.Jake [00:30:03]: That's how we think about not just the CLI, but every point in the dashboard. It's a user journey: I hear about Railway. I get something deployed. I get my first green build or aha moment. I see an endpoint, logs, whatever. Then I iterate. The iteration loop is indefinite. The user wants to deploy a new thing, a Postgres instance, change code, and keep iterating.Jake [00:30:36]: If you focus on the iteration loops and what's blocking them from closing quickly, one thing we say internally is: you never want to be waiting on compute anymore. You always want to be waiting on intelligence. If you're waiting on compute, there's a bottleneck that needs to be destroyed because eventually that bottleneck becomes so large that another workflow emerges to change it.Jake [00:31:04]: We've built a product where you push code, build it, and so on. But I fundamentally believe the push-pull loop is going away. We'll get to a point where you make a small change in production, that change is versioned across your infrastructure, you're working alongside copy-on-write versions of your database and infrastructure, and then you merge it in and it's instantaneously live. That's the holy grail of loops. The push-pull-rebuild thing is a point of friction that we're removing entirely.Canvas as Output: Dashboards, Context Anchors, and HyperstructuresSwyx [00:31:43]: It's incredibly fast. If anyone hasn't tried it, that fast feedback is great. My hot take is that Railway was famous for its canvas, which visualizes your infrastructure and lets you manipulate it visually. But that was for humans. For the next phase of growth, Railway CLI is more important than canvas.Jake [00:32:05]: The canvas is funny because it's a mechanism to show changes over time. You're right that previously we used it a lot as an input. Moving forward, its goal is more like an output. You would go to the canvas, make changes, see them, and watch your infrastructure evolve. Now agents have access to the CLI and can make those changes. So the canvas becomes an output: what information does the human need at this moment to make suitable decisions about control requests? Do I approve this or not?Jake [00:32:57]: It also has to be an anchor for your context, a port in the storm. Think of it like layers in a file system. You start with a project, then drill down into services, then into a function or code, because you want to represent the entire thing not just in your head, but in the canvas. Other people can share that representation, think on the same wavelength, and move quickly.Jake [00:33:33]: A lot of organizations get in trouble as they scale because all the context lives in someone's head. “How does this microservice work?” “I have no idea; go ask this person.” Then you have whole categories of products built around context discovery. A lot of that melts away if you have a solid hierarchy and can infinitely nest services, code, context, and everything else all the way down. That's what lets you build these structures over time.Jake [00:34:18]: It's also what lets us build what I've called hyperstructures: things that are way bigger. You look at the Golden Gate Bridge and ask, “How did we build that?” There's a meme that we lost the technology. To some extent, yes, because the coordination that built those things evolved and changed. We lost some of the art of building structure as we jammed everything into Slack.Swyx [00:34:52]: But you jam everything in Discord.Jake [00:34:53]: Same point. It doesn't matter. It's message passing and interrupts, message passing and interrupts.Swyx [00:35:00]: So you're arguing there should be something better and more structured than Slack?Jake [00:35:04]: Yeah. For sure. I think Slack is awful, and Discord is awful too.Central Station: Context Routing, Support, and Incident ClustersSwyx [00:35:09]: This is the equivalent of my mom test. What have you done that has your solution to this?Jake [00:35:15]: Internally, we've built a tool called Central Station that aggregates all the context from our users. Every piece of feedback, every customer support item, everything gets aggregated into clusters. If an incident is brewing, we can determine how many users are affected and break off a discussion based on that.Jake [00:35:40]: That is more helpful than long-running channels where you're trying to decide which channel to put something in. If you can dynamically aggregate information and dynamically route it to the right person based on context, it works better. We know internally that these four people are close to networking. If we see a networking thing, we can drill it down to those four people. If it's with this part, we can look at the commits. This is no longer a manual process internally.Jake [00:36:13]: If you go to station or help.railway.com, that's why we built it. We wanted to scale with a massive amount of leverage by aggregating feedback.Swyx [00:36:27]: This is built in-house?Jake [00:36:28]: Yep.Swyx [00:36:29]: I remember helping out on this one with Angelo in 2023. You scale a lot with a very small team.Jake [00:36:38]: Yeah. We're about 10 times bigger now.Swyx [00:36:40]: You have your full developer code here? Very cool.Jake [00:36:44]: If you go to railway.com/stats, we expose this as a pub-sub-able thing. It's all real-time metrics. There's a way to get it as JSON somewhere if you care.Jake [00:37:01]: We're big on trying to build everything in public and talk about what we're working on. We've had issues in the past, and we'll say, “Here's how we're fixing these things.” We've gotten compliments and flak for incident reports. We're always trying to make them better and talk with people.Incidents, Disclosure, and Progressive RolloutsSwyx [00:37:20]: You had a big one recently. I liked that it was scoped to 3,000. You presumably used Central Station. Talk through what happened and how you address it internally as a team.Jake [00:37:38]: Internally, this one really sucked. It had to do with an upstream provider that didn't do the behavior it said it documented, which is unfortunate given they wrote the RFC for how the behavior should work. We rolled those things out, and Central Station caught it initially when a couple users said caches weren't invalidating. We turned it off immediately.Jake [00:38:03]: When you roll out to a large user base of three million people, you get a lot of disparate behaviors. We tested in staging and had tests, but we hit an edge case. We've hardened those systems, and now we can make that better. But it was a tough one.Swyx [00:38:39]: I always wonder how private disclosure is supposed to work if people find an issue. Are they supposed to contact you first? When you run a platform, these things will happen. What channels should people pursue to quietly resolve it before it becomes a bigger incident?Jake [00:38:59]: There's responsible disclosure. We err on the side of over-disclosing and letting you know something is wrong versus having your provider gaslight you. We've erred on sharing those things more publicly, even if they impact a small subset of users. That's a decision we've made internally. We have four values. One is honor. The honorable thing is to notify people to the widest degree at which they may have been affected or there was an issue, and then confront it head-on: why did it happen, what can we do better?Swyx [00:39:45]: Not the whole user base. That's because of incremental rollouts and other things?Jake [00:39:50]: Yeah. Progressive rollouts.Swyx [00:39:54]: That should be the norm at all large platforms.Jake [00:39:58]: It should. A variety of companies do this. There's the quote that Meta runs 10,000 different versions of Meta. To our earlier point about agents, they need the same thing. They need shadow traffic and all these other things. We've built so much ceremony around production being sacred that we need to make it trivially easy to test different behaviors in a safe environment. Then you can make mistakes in a safe environment.Safe AI SRE: Customer Agents, Forked Environments, and Production ParityAlessio [00:40:30]: Do you see a world where these things get automatically caught, not necessarily by your agent, but by your customer's agent? The cache invalidation issue seems easy to check if you know to look for it.Jake [00:40:44]: It's hard because to determine it, we almost need to hook into your observability infrastructure. That's why we have the template loop on the platform: so you can roll things out progressively. You can roll out to Johnny Vibe Coder initially, or push a shard that someone consumes at their own leisure. Or you can roll it out over weeks: 0.1% of people, 1% of people, early adopters, then all the way up. That's the non-deterministic version control we talked about earlier.Jake [00:41:30]: I believe that's where most things should go, because most companies end up building staged rollout systems in-house. It's the same thing built again and again at every company. There's a massive opportunity to consolidate developer debt.Alessio [00:41:45]: You should have a free tier. Model providers give free tokens if you let them use the data. You could give free compute if someone is the number-one shard that goes out and lets you plug into their observability.Jake [00:41:55]: We do that. That's why we talked about the impact on 3,000 people. We start with lower-impact people. Larger companies on the platform are last to receive those rollouts so they have a version of the platform that's deeply stable.Alessio [00:42:16]: I have three services, so I'm sure I get the first rollout. You can nuke my thing at any time. There are all these SRE agent companies. Observability people also want agents that fix upstream problems. You have your own agent in the canvas now. How do you see that playing out?Jake [00:42:39]: It's the stacking entropy problem. If you don't have primitives to make iteration in production safe, it becomes difficult. If you're an observability provider saying, “Here's the fix to this error,” assume 80% are good and make sense. But in the last 20% long tail of complex issues, if you let somebody stamp it, you create an opportunity for an incident.Jake [00:43:08]: That's why forked environments are important. People have staging, but it always drifts from production. You need primitives, workflows, and experience built first-party on the platform so you can fork any service at any point in time.Jake [00:43:33]: I think of the canvas as a sheet of transparency paper. The agent is a little guy you push up into the canvas. It should say, “I need to copy that service and that service so I can test these two things.” It gets a read-only copy of production. Anything that's PII gets marked as a transform when we clone the database, create a copy-on-write version, or read from it. Then the agent makes changes and asks, “Does this actually work?” as close to production as possible.Jake [00:44:22]: That's how close you have to be, or you get massive drift. The system becomes unstable. You see this with massive systems built on Docker for local, Kubernetes for production, and a specific thing for something else. That complexity slows developers and becomes unstable at scale, making it hard to iterate. We want to compress that way down and say, “As close to prod as possible is where we want to be.”From AISRE Skeptic to Agent BelieverSwyx [00:45:00]: I was texting Erica for questions, and she says you were originally not a believer in AISRE. Have you come around on it?Jake [00:45:10]: I flipped, but I'm still not a believer in AISRE if you don't have the primitives to make it safe. If you unleash AISRE on production infrastructure without safe primitives for copying volumes and making sure things are fine, it's going to nuke your production database. It's not a matter of if, but when. I'm a big believer in making those loops safe.Jake [00:45:33]: I was a deep AI skeptic until 2023. In 2024, I thought, “Maybe I can roughly make this thing do it.” In 2025, I thought, “Now I can hold this.” Over winter break, everybody came back saying, “It's almost impossible to hold this.”Swyx [00:46:01]: Did you see this on the Claude docs? CloudBot? OpenCloud?Jake [00:46:06]: It's gotten to a point where it's harder to hold it wrong than to hold it right. There's a scene in Avengers where Vision picks up Thor's hammer and says it's terribly well-balanced. It self-balances and works well. I'm a deep believer at this point that this will be the dominant species: assembly, C, C++, JavaScript, words.Swyx [00:46:35]: It feels like a big jump.Jake [00:46:37]: It is. But it's not like you abandon CPU-based discrete logic and move straight to fuzzy logic. You need both. Your skills should call code or applications or some static structure. You can use skills to distill what the procedure should be or how the code should act.Jake [00:47:02]: I'm coming to a thesis: you need three points. You need a clear spec defining the system, the code, and the tests. When you say it out loud, if you've been in engineering long enough, you're like, “Of course. That's an RFC, tests, and code.” But they all matter. Having them together lets them reinforce each other: the spec and tests match, but the code doesn't, so reconcile it. Or the tests and code match but the spec doesn't, so reconcile that. That's the iteration loop.Jake [00:47:41]: That's why you're seeing people talk about software factories, docs, and reconciliation. Some of that is architectural astronomy if you don't implement it, but that loop is where most things will end up.Swyx [00:48:07]: For listeners, we've been talking about this on the pod for three years: the holy trinity of specs and tests. Itamar Friedman from Qodo is the reference if people want to look it up.Self-Modifying Infrastructure and the End of Push-Pull-RebuildSwyx [00:48:18]: One thing I want to mention on the OpenCloud idea is self-modification. I don't know how Railway would support it, but I have my OpenClaw, and I just tell it it has the Railway CLI and can do whatever. In theory, whatever capabilities or new infra it needs, it can call the Railway CLI, provision it, and add it to itself. The agent can modify its own infra.Jake [00:48:45]: It's nuts. I have a loop set up where you put the Railway CLI on top of something that runs on Railway. You're authenticated as whatever the current box is, and you can make any changes to it. Then you call Railway deploy, and it deploys itself.Jake [00:49:04]: It's like: “I need to spin up this instance of this environment. I already exist in this environment. Excellent, I have access to a Postgres instance now.” That's where we want to go with agentic, self-replicating infrastructure. That's your loop: iterate in production. You continue making changes. If it works, merge it upstream. If it doesn't, throw it away.Jake [00:49:37]: How do you make throwaway copies trivial to spin up and super cheap? The era of “I have an AWS instance with four vCPU and 16 gigs of RAM” is going to get destroyed. If you do that for agents, you need a thousand of those machines. It's prohibitively expensive compared with what we've spent a ton of time figuring out: the atomic unit of deploy, whether you call it isolates, sandboxes, or something else. Only pay for what you use, spin up instantaneously, and close the loop as quickly as possible.Jake [00:50:15]: If the system can self-replicate safely and say, “This is my environment, I'm making these changes,” it can come back with, “Does this look good? This is a new state of infrastructure given this prompt. I think I've solved it.” Then you go back and say, “Actually, it looks different.” It does the loop again. Then you say, “Cool. Apply.”Swyx [00:50:38]: That's retroactively obvious, which is the most useful kind. Any other comments on agent deployment on Railway?Jake [00:50:51]: It's getting better every day. I'm on X or Twitter. You can always yell at me about the parts not working as well as they should, because plenty of things should work way better.The New Serverless: Stateful, Long-Running, Pay-for-What-You-Use LinuxSwyx [00:51:04]: At this stage, when people want massively or embarrassingly parallel compute, they usually talk serverless. I feel like there's a new serverless compared to the previous five years of serverless. You're in that new bucket. Do you have comparisons or philosophical differences you want to call out?Jake [00:51:31]: It's somewhere in between. It's the ability to run stateful, long-running workflows or executions.Swyx [00:51:42]: Vercel has Fluid Compute, Cloudflare has some container thing, Google has App Runner and others.Jake [00:51:55]: That's where everything is roughly going, and it's why we've been working on this for six years. We believe users need access to a computer: a box that speaks Linux. They need to deploy what they want. Other systems change the surface area of what you can build. For us, users need a computer and need to deploy anything they truly want. That's why we've focused on the primitives: network, compute, storage. If we give you those and expose them so you can run things indefinitely, that's where we believe it's going.Jake [00:52:43]: Twitter has no nuance, so everyone says “servers” or “serverless.” It's always somewhere in the middle: I want to run it for a long time, but I don't want to provision the resource statically or pay for things I'm not using. That's been our thesis from day one: pay only for what you use, run it indefinitely, and it is full Linux.Swyx [00:53:12]: That's why I like the naming of Fluid. It's fluid. Flexible.Heroku, Focus, and Carrying the Torch Without Becoming the PastSwyx [00:53:18]: Another milestone is the Heroku official deprecation. You're one of the presumptive new Herokus. “New Heroku” has been a category for as long as I've been in developer tooling. It's finally happening. What was that like? Any behind-the-scenes of, “This is the moment”?Jake [00:53:42]: You have people where you're like, “You were running stuff on here? You, as this company?” It's crazy that names you would know are running on it and now coming to us saying, “We want to move a lot of this off.”Swyx [00:54:00]: Any behind-the-scenes on why Salesforce let Heroku stagnate?Jake [00:54:05]: I can only guess. It's hard when it's not your business. Salesforce's business is to build a great CRM. That's their focus. Then you acquire a compute business as an offshoot. A lot of early Meta people talk about focus. Boz has a write-up about how in the early days of Meta they had no money, so they were forced to focus. Then they turned on the money tree and had no reason not to split their focus.Jake [00:54:52]: But that dilutes your product. You get offshoots where you ask, “Is this the focus of the business?” If it's not core, it languishes. A lot of companies get in trouble when they split focus because they're fighting a multi-front war, not just externally but internally for alignment. Where are we going? What are we doing? What is our purpose?Jake [00:55:24]: If you're Salesforce-built and mission-driven, you want to work on Salesforce. Heroku is off to the side. It's not core to the business. Getting resources, budget, focus, and alignment internally becomes hard. It was a matter of time.Swyx [00:56:06]: Kudos for them to call it out instead of leaving it unknown.Jake [00:56:12]: Their release was a little odd. They called it out, but they didn't say they were shutting it down. Behind the scenes, I think they issued messages to people saying they should close accounts and that they were going to deprecate and remove things over time.Jake [00:56:30]: It's crazy because some of my first deployment experiences were on Heroku. You start with dragging things into an FTP server, then you try to get a deploy working, and then it's Heroku. It was the on-ramp for us. But the wheel turns. New things emerge. We're happy to carry the torch for a lot of that. But we don't want to be the new Heroku. We want to be the way people build and deploy software, and ultimately the way people monetize software over time.Swyx [00:57:19]: It's still a big crown to be the new Heroku. There are 50 companies that fought for that.Jake [00:57:23]: Everybody is holding some portion of it. We're happy to support people and companies. The platform works differently. The game loop is similar, but we've been dogmatic about where these things are going: primitives, agents, fan-out. Some things fit; some workflows need to change. We have an approximation of Heroku pipelines with the environment system. It's exciting. We've got a ton of people we can support, and it's growing a lot.Temporal, Workflow Engines, and State MachinesSwyx [00:58:12]: I have one more technical question about Temporal. I've sold my shares. You're a power user and one of our earliest customers. I met you through Temporal. You built on Temporal. You have complaints. This may be the most neutral and informed conversation anyone will hear about Temporal without someone working at the company.Jake [00:58:39]: That's fair. I've used Temporal for almost 10 years because of Cadence at Uber.Swyx [00:58:52]: Give people a sense of what Cadence was at Uber.Jake [00:58:57]: Cadence was the precursor to Temporal. It powers trip actions, rides, when you rent a Jump bike or scooter or car. You're running workflows for a period of time and saying, “This ride will run indefinitely until it finishes.” You attach information: you paused in this zone, so add this charge to the bill. When you end the trip, the workflow is done. That experience was powered by Cadence at the time.Swyx [00:59:34]: I used to say it's like programming the entire user journey top-down as one function.Jake [00:59:39]: It's a powerful idea and important. It's also important for the next phase of the agentic journey. You want an agent to do a specific task, be complete or incomplete on that task, and move on to the next thing. You need a way to manage workflows dynamically.Jake [00:59:59]: Temporal was always great in theory, and great when you got it working the way you wanted in production. But it required you to model the entire journey in your head. If you didn't, you could cause issues where replaying the state of the workflow causes non-determinism.Swyx [01:00:25]: Because it works on deterministic workflow history.Jake [01:00:28]: Exactly. I describe it as a jet engine. If you know how to operate it and run it, it's great. But you can't hand it to people trying to build complicated things if they don't have the whole state in their head.Jake [01:00:48]: We run our whole deployment pipeline on top of it. That's a reasonably complicated workflow: pre-commit hooks, signaling, queuing, and all the rest. We ran into the same thing at Uber. As you express a large workflow, it gets more complicated, with more states in the state machine that you have to map back to the workflow.Swyx [01:01:15]: It's a lot of ifs.Jake [01:01:16]: Exactly. At Uber, we built a system for doing the state machine and testing it. We've started to build some of those things here because it's grown heavily. It's not quite love-hate. When it works well, it works super well. But if someone who doesn't have full context puts something into the system that invalidates state or causes non-determinism, or spins off a ton of activities, you have to keep track of underlying SRE knobs like activity slots. Those should scale with memory, vCPU, and so on. It becomes a bear to scale.Swyx [01:02:10]: You need a capable sysadmin running things behind the scenes. If you moved off, what would you do?Jake [01:02:19]: We'd build our own workflow engine. We have a few internally that we've worked on.Swyx [01:02:27]: This is one of those classes of things you typically wouldn't vibe code, but I'm wondering if you can.Jake [01:02:33]: I still don't think you should vibe code it. You still want to run decent tests to make sure it works.Swyx [01:02:39]: Timo didn't invent that from scratch either. There are libraries you can run. On top of that, it's just a state machine that you have to map out. Ultimately, you define the instructions you want and run them through a state machine.Jake [01:03:00]: It's very doable. Workflow stuff is interesting. Restate is doing neat stuff here.Swyx [01:03:10]: You're tied into JavaScript. Are you a JavaScript maxi?Jake [01:03:13]: Internally, we have TypeScript, Rust, and Go. We don't add more languages. Actually, we have a little C because we write BPF code and hooks. But those are the languages.Swyx [01:03:28]: Is this for sidecars?Jake [01:03:32]: No. It's for the networking stack, volumes, and things like that. We use TypeScript a lot because it powers the dashboard, but we're moving a lot of workflow stuff off the dashboard stack and into the infrastructure stack.Railpack, Nixpacks, and Content-Addressable FilesystemsSwyx [01:04:00]: Cool. Any other technical infrastructure stuff? Railpacks?Jake [01:04:07]: We built an engine for determining dependencies based on source code. It's called Railpack. We built the first version, Nixpacks, on top of Nix, and then we moved.Swyx [01:04:17]: People have been trying to get me to adopt Nix and NixOS for four years. Is it ever going to be a thing?Jake [01:04:23]: I don't know. We're excited about it, but it has pain points. Think of it as a stack of versioned binaries at specific slices in time. If you want version X and version Y, you bloat the package space, which blows up image size and makes real-world workloads difficult.Swyx [01:04:53]: But you content-address it and cache it. In theory, there are optimizations.Jake [01:05:00]: In theory, yes. But with a large enough user base and disparate enough machines, you run into a problem Meta described in the XFAAS paper, their internal serverless system. It becomes difficult at scale unless you break out specific runtimes.Jake [01:05:24]: We didn't want to do that because we wanted to truly allow you to deploy anything. That was our initial thing with Nix. But we've moved toward interesting work around content-addressable file systems that can lazy-load anything from any point and page it into memory.Swyx [01:05:48]: Amazing.Jake [01:05:49]: The future is very bright. It's crazy, and it's going to be nuts.Coding Agent Spend, Roadmaps, and Token ROISwyx [01:05:54]: Founder journey stuff?Alessio [01:05:56]: Your cloud usage: you tweeted you're going to spend $300K this month?Jake [01:06:01]: I think we got to $200K.Alessio [01:06:02]: Coding agents?Jake [01:06:03]: Yeah.Swyx [01:06:04]: Across the company?Alessio [01:06:05]: You only have 35 people, so I'm sure they're not all spending $10K a month. What's the distribution?Jake [01:06:10]: I think I'm at about $25K. We have power users all the way down. We came back from winter break, and I basically said, “If you're writing code by hand, you're doing this wrong.” The tools are good enough now that you can move extremely quickly. There are issues and pain points, but you should be reviewing the code you are writing instead of writing it by hand.Jake [01:06:40]: Architectural patterns matter more now than ever, but you shouldn't spend your time generating code you would write. If you know how to write it, ask the agent to write it and reconcile it until it looks like you would have written it yourself.Jake [01:06:58]: People misconstrue my propensity to push people toward agents as connected to our growth and some reliability bumps. They're not necessarily related. The tools are good enough to move extremely quickly and build things way larger than you could before.Jake [01:07:19]: To the earlier point about cooling data centers in space: I don't know. But with software, you can ask, “How would I build block storage from scratch? How would I do these things?” I have ideas because I have history and have read papers. Let me work them out and build massive test benches with thousands of tests, because those are now free to author. If you're not using AI systems to speed-run your roadmap and reconcile your existing system onto the future, you're missing a large point of what's happening.Alessio [01:08:12]: What's the path to spending $3 million a month? Is it bound by ideas and things customers can absorb?Jake [01:08:19]: For most companies, it's bound by deployment at this point. That's why we've seen a massive boom in users and companies, from Fortune 50s down, asking how to get developers to move faster. You'll probably hit your CFO before any technical limits because they'll look at the eye-watering amount of money spent on tokens. Inference costs have to come down, but we're inference constrained now. There will be price discovery around what makes sense for an org to adopt.Jake [01:09:06]: I think you'll end up with the F1 driver concept. If someone is really adept at these things, it makes sense to put them in a $3 million car. If they're not, it probably doesn't make sense. You'll take a few people and say, “You can drive the F1 car. We need to go in this direction. Figure out if it works and prototype it.”Jake [01:09:33]: We've done some of that and vastly accelerated our roadmap. We thought we'd ship something in a few years; now we can probably ship it in a few months because we validated it and don't have to build it incrementally. We can skip steps and move toward our vision.Alessio [01:09:58]: A lot of people are realizing the roadmap doesn't always have a business impact, so they say tokens are too expensive. But if your roadmap were built to make more money by the time you built it, you'd have token pricing for it, the same way you do with sales. You'd spend a billion dollars on sales if you knew you would get $2 billion of revenue.Jake [01:10:19]: Exactly. A naive way to measure this is the percentage of tokens that end up in production. If you can measure impact because those tokens end up in production, that's awesome. But the burden of proof will rise. Internally, we have a growing number of pull requests that haven't merged. The question becomes: how do you get this into production? It's about how quickly you can build and deploy software, which is exciting because that's our whole thing.The SDLC Shift: Prompt Requests, Feature Flags, and Safe RolloutsSwyx [01:10:56]: The SDLC is changing. One thesis is that the pull request is dying. It's going to be the prompt request. Beyond that, code review is also kind of dying if you have all the other systems in place. What else is changing about the SDLC?Jake [01:11:19]: The AISRE and the tools to make it happen. AISRE is pie-in-the-sky aspirational. What does it take to get an AISRE? What tools do you need to build?Swyx [01:11:32]: You should expose your tooling to customers at some point. The Central Station command center.Jake [01:11:39]: We have it for template maintainers. Template maintainers can deploy and maintain templates, and they get feedback. We're going to expose those things incrementally.Swyx [01:11:51]: Clustering around incidents. Everyone has a version of that, but I don't think anyone has solved it.Jake [01:11:56]: I won't say we've solved it internally, but it's gotten so good that we can see incidents forming pretty quickly. At some point, those will be things either someone else builds or we build. We've always built things purpose-built for us. If it makes sense to make it useful for users, monetize it, or turn that loop into a profit center instead of a cost center, we want to do that.Jake [01:12:28]: Pull request is definitely dying.Swyx [01:12:29]: Do you do first-party feature flagging and incremental rollout stuff?Jake [01:12:34]: We have a feature-flagging engine we built internally and will eventually roll out.Swyx [01:12:38]: I don't see it as a user. How come you didn't give us what you have?Jake [01:12:43]: We have to beta test it. We care a lot about the quality of the things. There's plenty we've used internally that doesn't make it all the way through the journey because it fails. It works for one service but not multiple services. We'd have to build it for multiple services and know that if we released it, we'd rebuild it again and again. Some things are worth that, but many inform the roadmap.Jake [01:13:18]: We don't want to dilute the experience by saying, “This works, but only for this service,” unless it's a core initiative. Over the next few months, we'll roll out things that work for a single service, then multiple services, then multiple services across the environment. You have to be deliberate. Otherwise you create broken disparate experiences and support load because people ask how to use the feature.Jake [01:13:52]: It's the earlier expansion and compaction pattern. You expand the company to get features, then compact and smooth them out so the experience is stellar. You told me in the hallway, “It's gotten so much better.” Internally we're saying, “This part really sucks. We need to make it significantly better.”Swyx [01:14:11]: I can attest to that over the last three years watching you build Railway. For listeners, feature flagging is a huge part of Uber culture. So much so that they have too many feature flags and another thing to remove feature flags. Facebook has Gatekeeper. Agents are going to need this. It's fundamental to incremental rollouts. OpenAI acquired Statsig. GPT-5 is routing and flagging through different models.Jake [01:14:56]: It's super important. If the software development lifecycle is going to change because we're doing things 1,000 times faster and 1,000 times more concurrently, what becomes important at scale?Jake [01:15:16]: Before I started Railway, I built a feature-flagging product and tried to sell it. It was an easier version of LaunchDarkly. I ran into a problem: anyone small enough to adopt your technology doesn't care about feature flags, and anyone large enough to need feature flags needs so much scale that you have to build out all the infrastructure. I scrapped it.Jake [01:15:42]: But what is old is new again. Companies are trying to move quickly, but you can't YOLO a vibe-coded thing straight into production. You need to say, “Here's my blast radius, my impact, and I want to shadow it for these users.” Feature flags. You're going to need the tools larger companies built to maintain their structures. Everything gets compressed by 1,000x so everybody can build those structures quickly.Jake [01:16:07]: That's exactly where we are: compressing the software development lifecycle, then expanding it and adding more new things.Cattle, Pets, and Clonable InfrastructureSwyx [01:16:15]: Another term that comes to mind for newer developers is “cattle, not pets.” People treat production like a pet. It has a name. You baby it and keep it alive. With cattle, you can mass farm, roll out, portion parts out, and kill them.Jake [01:16:37]: I think that might change. You can move toward having pets as long as you have a cloning machine for your pets.Swyx [01:16:52]: Yeah.Jake [01:16:52]: If you can snapshot every single thing at every frame, it doesn't matter if something gets obliterated because you have a snapshot of it. The things we've built right now are designed to block changes from the hermetically sealed DevOps line. You have to write a Dockerfile because you nee

Gates and Gardens of Victoria's past with Martin Segger, author and architectural historian.http://www.martinsegger.com/

Timothy Adams is renowned as a classical residential architect, and his practice spans vernaculars and centuries. Architectural inspiration and interpretations include the Cotswolds; a French chateau; a Moroccan retreat; and a Federal farmhouse, with each specifically created for that client and place, and featured in his new monograph, “Tradition Made New.” Learn more about your ad choices. Visit megaphone.fm/adchoices

Susan Weiss's career is a masterclass in how early environments shape creative destinies. Growing up the daughter of Harold Bailey—an architect, avid collector, and adventurer—Susan was immersed in a world where design was not just a profession, but a lifestyle. She describes this early exposure as "intravenous," suggesting that while she didn't realize she was being shaped at the time, the appreciation for craftsmanship and the stories behind objects became part of her DNA.Her father's approach to collecting was never about the mere possession of "things"; it was about the journey, the people met along the way, and the process of refurbishing and sharing those pieces. This foundational philosophy led Susan into the world of luxury curation, eventually leading her to play a pivotal role in the development of Net-a-Porter's furniture and home divisions. She learned early on that a piece of furniture is a living history, carrying the fingerprints of those who created it and those who lived with it before.Today, Susan reflects on her journey from a curious child watching her father refurbish antiques to becoming a leading voice in high-end curation. She discusses how her background in art history and her inherent "processor" personality allowed her to bridge the gap between architectural structure and the fluid beauty of interior objects. Her story is a testament to the power of observation and the importance of honoring one's creative lineage while forging a unique professional path.

FACT OR FICTION?IS ARCHI-PORN A REAL THING? John Gollings is far and away Australia's most celebrated architectural photographer. But he has never limited himself to architecture, nor hidden the fact that his images are artworks in themselves. What is the job? To tell the truth? Sell architecture? Or reveal something new about both? JOHN GOLLINGS [...]Read More... from John Gollings, Architectural Photographer

In this episode, Jonathan and Gary welcome architect Paul Steelman, founder/CEO of Steelman Partners, to discuss his career shaping casino resorts worldwide. Steelman recounts starting in Atlantic City after casino gambling was approved in 1976, meeting Joel Bergman and Steve Wynn, and working on Golden Nugget Atlantic City and The Mirage. He shares major international projects such as Sands Macao, Solaire (Philippines), Ho Tram (Vietnam), and casinos across Europe, plus design myths about casinos. The conversation covers Circa's design choices, Resorts World's long development and scaled-back vision, and Steelman's view that Las Vegas is losing magic through generic LED "boxes" and monetized "obstacle courses," while praising the Sphere and anticipating the Mirage guitar redevelopment.

In the latest Amber Muse Radio episode, Taran & Lomov deliver two hours of deep techno, acid, and hypnotic electronics. The first hour features fresh cuts from Delsin Records, R&S, !K7, Kompakt, and The Bunker New York, alongside music by Architectural, Batu & Donato Dozzy, Fantastic Twins, Silat Beksi, and more. In the second hour, Kaņepes Kultūras centrs crew member Kirha joins the show with a deep and hypnotic guest mix.. Full tracklisting: https://ambermuse.com/amber-muse-radio-424-taran-lomov-kirha-guest-mix-08-may-2026/

When most nonprofit leaders hear "capital campaign," they picture a new building. A groundbreaking ceremony. Architectural renderings. But what if the most transformative investment your organization could make isn't a building at all — it's the people who do the work?In this episode of All About Capital Campaigns, Andrea Kihlstedt spoke with Esther Landau, Senior Director of Advancement Services at the Arc San Francisco, about a $3.3 million capital campaign that had nothing to do with bricks and mortar. Instead, the campaign funded staff pay increases to reduce crippling turnover and shrank a waitlist that was keeping adults with developmental disabilities from accessing services they needed.The Arc San Francisco, now celebrating its 75th anniversary, serves roughly 800 adults across three Bay Area counties. When their strategic planning process surfaced the root problem — staff wages were not sustainable, which meant they couldn't hire enough people, which meant the waitlist grew — the campaign became the solution. Of the $3.3 million goal, $2.5 million went directly to increasing staff compensation, and $800,000 funded program growth including a new internship program with San Francisco Rec and Park.With one month left in the campaign and only $150,000 to go, Esther reflected on the surprises along the way. One donor she'd prepared to ask for $7,500 immediately responded with $25,000. Clients of the Arc — people the organization serves — asked to donate to the campaign themselves, raising important questions about ethical fundraising and the universal desire to contribute to something meaningful. For organizations considering whether they have the internal capacity to run a campaign, Capital Campaign Pro's campaign resources offer a practical starting point.Not every moment was easy. Esther described stretches that felt like dragging a bag of rocks — donors who answered every email except the one about making a gift, months of cheerful persistence before a single meeting materialized. Her advice: the campaign moves at the speed of your donors, not the timeline your board wants. And if you haven't gotten a no, the answer isn't yet no.Some of the most creative work happened in cultivation. For the public phase launch, Esther's team built an immersive experience where attendees assumed the identity of someone trying to access disability services and navigated real-world barriers — bureaucracy, transportation, waitlists — with outcomes determined by a roll of the dice. Some didn't make it through. The ten-minute exercise gave donors a visceral understanding of the problem the campaign was solving.Esther also championed low-tech, high-touch donor outreach. When emails went unanswered, she recorded short personal video messages — casual, unpolished, like popping into someone's office to say hello. Donors watched them. And they responded. As she put it: people feel it when you've made the personal effort to do something just for them.The takeaway from the Arc's campaign is simple but powerful: capital campaigns don't have to be about buildings. They can be about building capacity, building wages, and building the ability to serve more people. And sometimes that's the most important building you can do.Considering a capital campaign for your organization? Download Capital Campaign Pro's free campaign resources to explore your options and plan your path forward: https://capitalcampaignpro.com/campaign-resources

Canada is known for its vibrant culture and diversity, but you wouldn't know that from our architecture. It's no surprise that the bottom line plays a role into materials and design decisions of commercial, residential and cultural buildings, but is there a way Canada can balance creativity, budget and authenticity to have the best looking country? Host Maria Kestane speaks to Alex Josephson, founder of Toronto-based architecture firm, Partisans, to dig into the investment Canada needs to make into its up-and-coming creatives, and just how important building aesthetics are to our country's ethos. We love feedback at The Big Story, as well as suggestions for future episodes. You can find us:Through email at hello@thebigstorypodcast.ca Or @thebigstory.bsky.social on Bluesky

Become a member of AIAP to participate in these discussions: https://forms.aiap.net/forms/createaccount Is social media really the best place to find your next big architecture client? In this episode of A Photographer's Life, members of the Association of Independent Architectural Photographers (AIAP) pull back the curtain on their most effective business tool: Email Marketing. While everyone else is chasing "likes," top-tier pros are seeing 30%+ open rates and landing consistent contracts through curated, high-value email campaigns. In this episode, we dive into: • The "Social Media Trap": Why awareness doesn't always equal hires. • Lead Generation Secrets: How to use LinkedIn, SMPS rosters, and tools like Hunter.io and LeadLeaper to find the right decision-makers. •Targeting the Right Hierarchy: Should you be emailing Marketing Directors, Partners, or Project Architects? •Technical Success: Why you must use a reputable service (like Mailchimp or Benchmark) to avoid the dreaded spam folder. •The Long Game: How one campaign can fuel your business for months. Whether you're a seasoned pro or just starting to build your firm's contact list, this discussion offers a roadmap to making your marketing as precise as your photography. This podcast is Copyright 2026, The Association of Independent Architectural Photographers™, All Rights Reserved. This content may not be used in full or in part without the written consent of the AIAP. Don't forget to like the video and subscribe to the channel. #ArchitecturalPhotography #PhotographyBusiness #EmailMarketing #AIAP #PhotographyTips #CreativeEntrepreneur #MarketingForPhotographers

X: @simonedegale @americasrt1776 @ileaderssummit @NatashaSrdoc @JoelAnandUSA @supertalk @JTitMVirginia Join America's Roundtable radio co-hosts Natasha Srdoc and Joel Anand Samy with a guest from London, Great Britain - Simone de Gale, a Chartered Architect who qualified at the Architectural Association in Bedford Square, London. She has served on the Royal Institute of British Architects board as Honorary Treasurer and board trustee. Simone also engages with the Britain's Royal Family as her affiliation with organizations in the field of urban planning and architecture are connected to Kensington Palace, a royal residence situated within Kensington Gardens in the Royal Borough of Kensington and Chelsea in London, England. She is the driving force behind SGA's Westminster based organization, an Award Winning Architecture Practice which operates in UK and internationally. Simone is shaping innovative architecture throughout London and Internationally. She has won many awards and accolades including the Winner 'Architect of the Year' Women in Construction. The conversation is focused on America and Britain's challenges and opportunities in the housing sector as a new generation and first home buyers face skyrocketing prices and fewer choices. We are also looking for solutions and best practices in the areas of urban planning, infrastructure and long-term growth. In April 2026 via AP: WASHINGTON (AP) — White House economists estimate the United States has a shortage of 10 million houses, according to a new report — and say regulatory cuts could lead to more construction to stabilize prices, increase home ownership and fuel faster economic growth. From a UK think tank: New analysis by the Centre for Policy Studies reveals that the UK has a shortage of 6.5 million homes when compared to similar European countries. Britain has just 446 homes per 1,000 people, the second worst rate in Europe. This compares to 560 in France, 516 in Germany, and a European average of 542. americasrt.com https://ileaderssummit.org/ | https://jerusalemleaderssummit.com/ America's Roundtable on Apple Podcasts: https://podcasts.apple.com/us/podcast/americas-roundtable/id1518878472 X: @simonedegale @ileaderssummit @americasrt1776 @NatashaSrdoc @JoelAnandUSA @supertalk @JTitMVirginia America's Roundtable is co-hosted by Natasha Srdoc and Joel Anand Samy, co-founders of International Leaders Summit and the Jerusalem Leaders Summit. America's Roundtable radio program focuses on America's economy, healthcare reform, rule of law, security and trade, and its strategic partnership with rule of law nations around the world. The radio program features high-ranking US administration officials, cabinet members, members of Congress, state government officials, distinguished diplomats, business and media leaders and influential thinkers from around the world. Tune into America's Roundtable Radio program from Washington, DC via live streaming on Saturday mornings via 68 radio stations at 7:30 A.M. (ET) on Lanser Broadcasting Corporation covering the Michigan and the Midwest market, and at 7:30 A.M. (CT) on SuperTalk Mississippi — SuperTalk.FM reaching listeners in every county within the State of Mississippi, and neighboring states in the South including Alabama, Arkansas, Louisiana and Tennessee. Tune into WTON in Central Virginia on Sunday mornings at 9:30 A.M. (ET). Listen to America's Roundtable on digital platforms including Apple Podcasts, Spotify, Amazon, Google and other key online platforms. Listen live, Saturdays at 7:30 A.M. (CT) on SuperTalk | https://www.supertalk.fm

By Doug Green “The question is no longer whether an attacker gets in—it's how far they can go.” In a recent Technology Reseller News podcast, I spoke with Doug Merritt, CEO of Aviatrix, about the company's latest platform launch and a broader shift in cybersecurity strategy he calls the “Containment Era.” Aviatrix operates at the architectural layer of cloud environments, focusing on how systems, applications, and workloads communicate—where security outcomes are ultimately determined. As Merritt explains, the industry is moving beyond the assumption that breaches can always be prevented. Instead, the focus must shift to controlling what happens after a breach by defining exactly what each workload is allowed to reach and enforcing those boundaries consistently. The result is a model where lateral movement is restricted and risk is managed by reducing blast radius rather than relying solely on detection. A major driver behind this shift is the rapid rise of AI. According to Merritt, AI has dramatically accelerated both vulnerability discovery and exploitation, shrinking the window between exposure and attack and making traditional response models less effective. At the same time, attackers are increasingly using legitimate credentials, trusted code, and authorized pathways, blending malicious activity into normal operations and making detection far more difficult. Compounding the issue, autonomous AI agents can now operate across systems, increasing both scale and risk. This combination defines the Containment Era—a model where the key question is not whether an attack gets in, but how far it can spread. The Containment Era represents a shift from detection-first security to containment-first architecture. When threats are indistinguishable from legitimate activity, the defining variable becomes lateral movement—how far a compromised workload, identity, or AI agent can reach. Containment addresses this by enforcing strict communication controls so that systems can only access what they are explicitly permitted to reach. Even if a breach occurs, its impact is limited by design, requiring enforcement to move into the network and infrastructure layer rather than relying solely on edge or endpoint tools. To support this shift, Aviatrix has introduced new capabilities within its Cloud Native Security Fabric. The platform delivers workload-level containment by enforcing precise communication policies across cloud environments without requiring agents or code changes. Key capabilities include consistent enforcement across clouds, regions, and compute environments; Zero Trust controls for AI workloads; default-deny policies to eliminate shadow AI and unauthorized connections; AgentGuard visibility into AI workloads; and integration with partners to secure both AI behavior and access. The goal is to reduce blast radius while maintaining flexibility for modern, distributed applications. For enterprise and service provider leaders, the takeaway is clear: AI has fundamentally changed the threat landscape. The first step is understanding exposure—specifically, how far a compromise could spread—followed by measuring and managing blast radius as a core security metric. Architectural controls that limit workload communication need to become standard in cloud design, and security and infrastructure teams must align around containment as a shared responsibility. As AI adoption accelerates, governing how systems connect and interact will become increasingly critical, and the organizations that move early will be best positioned to harness AI while keeping risk contained. Learn more: https://aviatrix.ai/  

On this episode of Inside the Firm, home remodeling profit margins hit highest rates since 2006, then we are short 10 million homes, and finally Ai workflows for architectural visualizations. Join us as we go back Inside the Firm!

Learn how custom copper finials transform rooflines into landmarks, evolving from bright penny to verdigris green. Understand their dual role as architectural signatures and functional protectors—lightning rods, weathervane mounts, and more. The crowning jewel of your renovation awaits. Salvo Metal Works City: Naperville Address: 566 W 15th Ave Website: https://salvometalworks.com/

What happens when you sit down with an interior designer who's spent years shaping the energy of some of the country's most ambitious sports venues—and ask her how light transforms hospitality into emotion? In this episode of LytePOD, host Sam Koerbel travels to Snapdragon Stadium in San Diego to sit down with Edith Ponciano, an elite interior designer whose work has redefined what it means to experience a sports venue. From Collegiat to NFL and multi-use stadiums nationwide - she talks about how the gameday experience is being redefined. It's a deep dive into the philosophy, process, and creative tension that transforms a stadium from a place to watch a game into a destination where people feel something the moment they walk in. Recorded on location at Snapdragon Stadium in San Diego, CA, this conversation reveals why lighting isn't just an element of design—it's the emotional foundation that makes hospitality work. Edith reveals why sports venues should feel like hotels, why lighting creates energy, not just illumination, and why the most successful spaces blur the line between architecture, interiors, and atmosphere. This conversation goes deeper. It's about the tension between creating beauty and creating energy, the challenge of selling something people feel but don't see, and why the most rewarding moment isn't the rendering or the approval—it's walking into the space on opening day and watching 35,000 people experience something you helped create. Edith shares why she loves working on sports venues despite not being a sports fan, why collaboration matters more than ownership, and why lighting designers need stronger advocacy from the design community if the profession is going to grow.

What happens when you sit down with an interior designer who's spent years shaping the energy of some of the country's most ambitious sports venues—and ask her how light transforms hospitality into emotion?In this episode of LytePOD, host Sam Koerbel travels to Snapdragon Stadium in San Diego to sit down with Edith Ponciano, an elite interior designer whose work has redefined what it means to experience a sports venue. From Collegiat to NFL and multi-use stadiums nationwide - she talks about how the gameday experience is being redefined. It's a deep dive into the philosophy, process, and creative tension that transforms a stadium from a place to watch a game into a destination where people feel something the moment they walk in. Recorded on location at Snapdragon Stadium in San Diego, CA, this conversation reveals why lighting isn't just an element of design—it's the emotional foundation that makes hospitality work.Edith reveals why sports venues should feel like hotels, why lighting creates energy, not just illumination, and why the most successful spaces blur the line between architecture, interiors, and atmosphere. This conversation goes deeper. It's about the tension between creating beauty and creating energy, the challenge of selling something people feel but don't see, and why the most rewarding moment isn't the rendering or the approval—it's walking into the space on opening day and watching 35,000 people experience something you helped create. Edith shares why she loves working on sports venues despite not being a sports fan, why collaboration matters more than ownership, and why lighting designers need stronger advocacy from the design community if the profession is going to grow.

Everybody knows that secrets and intrigue are the building blocks of any great mystery, but what about when the building blocks themselves are the real mystery at hand? From secret chambers inside famous monuments to an ancient mega-pyramid that no one can find, grab your chisels as we chip away at some of the most curious architectural mysteries that have baffled even the smartest historians.Our Sponsors:* Check out BetterHelp: https://www.betterhelp.comAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Architectural decision‑making in large enterprises can break down when system knowledge is fragmented, slowing delivery and creating inconsistent outcomes across teams. In this episode, Amar Akshat, Senior Vice President of Architecture at PaySafe, examines how codified organizational memory and deterministic guardrails enable intelligent systems to accelerate development without sacrificing control. He highlights the shift toward machine‑readable decision records, intent‑driven interfaces, and standardized design patterns that help enterprises reduce drift, strengthen compliance, and move faster with greater confidence. Learn how brands work with Emerj and other Emerj Media options at http://go.emerj.com/partner

Erin and Alyssa catch up on Pete Hegseth's bizarre intervention into service members' promotions, new congressional efforts to regulate prediction markets, and what the f– is going on with Kristi Noem's husband. Then they give an Architectural Digest-style tour of Trump's absolutely bonkers plans for his ballroom. The show wraps up in the Sanity Corner.For a closed-captioned version of this episode, click here. For a transcript of this episode, please email transcripts@crooked.com and include the name of the podcast.Defense Secretary Hegseth intervened to stop promotions of Black and female officers (NPR 3/27)Lawmakers Press to Limit Prediction Bets by Policymakers (NYT 3/26)US abortion rate holds steady largely due to travel and telehealth availability – report (The Guardian 3/29)Trump's Ballroom Design Has Barely Been Scrutinized (NYT 3/29)Secret double life of Kristi Noem's cross-dressing husband Bryon: The pouting 'busty bimbo' photos and trove of explicit messages (Daily Mail 3/31)

For episode 705 of the BlockHash Podcast, host Brandon Zemp is joined by Wael Rajab, Co-founder of DEXTools, Director of DEXT Ventures & CMO of PERPTools.PERPTools is a decentralized finance (DeFi) trading platform designed for trading perpetual futures (perps), which often acts as part of the broader DEXTools ecosystem. It provides users with tools for high-leverage trading, including features such as AI-driven trading agents and high-speed execution. 

summaryJoin Kurt and Jamie as they explore architectural critique, the significance of Dallas City Hall, and the influence of Banksy's art on urban spaces. They also share insights on preservation debates, their recent sketches, and upcoming trips to Columbus, Indiana. keywordsarchitecture, Dallas City Hall, Banksy, urban critique, preservation, Columbus Indiana, sketching, city planning, brutalist buildings, architectural education key  topicsDallas City Hall's history and controversyBanksy's influence on urban art and critiqueThe debate over preservation vs demolition of iconic buildingsSketching as a form of architectural critiqueTrip to Columbus, Indiana, and its architectural significance guest  nameJamie and Kurt key  frameworksPreservation vs Demolition DebateBanksy's Street Art as CritiqueArchitectural Sketching as CritiqueTitlesBanksy and Dallas City Hall: Art, Architecture, and Urban CritiqueThe Future of Dallas City Hall: Preservation or Demolition? sound bites"Episode is raw and unfiltered""Banksy's art provokes urban critique""Art and architecture shape city identity"Chapters00:00 Technical Difficulties and AI Critique06:29 Coffee Conversations and Personal Updates14:03 Art and Architecture: Dallas City Hall Discussion24:07 Exploring Columbus, Indiana and Architectural Education resourcesBanksy: Collected Works - https://www.amazon.com/Banksy-Collected-Works/dp/XXXXXXDallas City Hall - https://dallascityhall.comColumbus Indiana Architecture - https://columbus.in.usBanksy on Instagram - https://www.instagram.com/banksy/ guest linksTwitter - https://twitter.com/JamieTwitter - https://twitter.com/KurtSend Feedback :) Support the showBuy some Coffee! Support the Show!https://ko-fi.com/coffeesketchpodcast/shopOur LinksFollow Jamie on Instagram  - https://www.instagram.com/falloutstudio/ Follow Kurt on Instagram - https://www.instagram.com/kurtneiswender/ Kurt's Practice - https://www.instagram.com/urbancolabarchitecture/ Coffee Sketch on Twitter - https://twitter.com/coffeesketch Jamie on Twitter - https://twitter.com/falloutstudio Kurt on Twitter - https://twitter.com/kurtneiswender 

Become a member of AIAP to participate in these discussions: https://forms.aiap.net/forms/createaccount. This discussion delves into essential file management and metadata practices for architectural photographers, offering practical advice for organizing, protecting, and retrieving your work: CAMERA SETTINGS: The Foundation of File Management • Ensure your camera is configured for optimal file management from the start. • Copyright Information: Set up your camera's menu to embed copyright details. This is crucial as used camera bodies often lack this information. • Annual Updates: Remember to update copyright information annually, particularly the year.   CONTINUOUS FILE NUMBERING: Utilize continuous file numbering in your camera to avoid duplicate numbers, which can cause significant issues, especially for copyright registration. • File Naming Conventions: Structure and Clarity • Establishing a clear file naming system is vital for easy retrieval and client clarity. • Project-Based Naming: Incorporate project names, dates, and client information into your file names for efficient searching. • Date Format: Use a consistent date format (e.g., YYYY-MM-DD) for chronological organization. • Personal Suffix: Add your last name as a suffix to file names to clearly identify ownership.   METADATA: Embedding Essential Information • Metadata is crucial for protecting your work and providing essential details. • Lightroom Presets: Utilize Lightroom presets to automatically populate metadata fields, saving significant time. • Key Metadata Fields: Include your name, contact information (phone, email, website), and copyright notice. • IPTC Standards: Adhere to IPTC metadata standards, which are widely supported by professional photo software.   METADATA RESOURCES and TOOLS • Leverage available resources to deepen your understanding and implementation of metadata. • "The Damned Book" by Peter Crow: Recommended for comprehensive information on metadata. • Lightroom Queen Guides: Valuable resources for Lightroom users. • Michael Clark's Resources: Useful content from an adventure and sports photographer.   FILE DELIVERY and COLOR MANAGEMENT • Understand the importance of delivering files in appropriate formats. • Dual Format Delivery: Provide both high-resolution JPEGs (300 PPI for print) and sRGB JPEGs for web use. • CMYK for Specific Needs: While generally not recommended unless requested by a printer, be prepared to provide CMYK files if specifically asked for by ad agencies. • Color Management: Understand basic color management principles for accurate representation across different platforms.   COPYRIGHT PROTECTION and INFRINGEMENT DETECTION • Proactively protect your work and monitor its usage. • Google Lens for Image Search: Use Google Lens for reverse image searches to identify where your photos are being used online. • "Exact Matches" Tab: Focus on the "exact matches" tab in Google Lens for precise identification of your images. • Demand Letters and Legal Action: If infringements are found, sending demand letters or pursuing legal action can be necessary.   NAVIGATING ONLINE PLATFORMS and AI • Be aware of the complexities surrounding online platforms and the rise of AI. • Platform Policies: Understand the terms of service for platforms like Houzz, which may grant broad usage rights to uploaded images. • AI-Generated Content: Be mindful of contracts that prohibit the use of AI in your deliverables, as AI can embed copyrighted material. • AI Detection: While early, European regulations are beginning to address AI's use of copyrighted material, with potential for licensing fees.   FOLDER STRUCTURE and WORKFLOW EFFICIENCY • Maintain a clear and logical folder structure for seamless file management. • Simple, Consistent Structure: Organize files by broad categories (e.g., architecture, landscape, commercial) and then by project. • Lightroom Integration: Lightroom can mirror your existing folder structures, aiding organization. • Batch Processing: While debated, batch processing can be efficient for certain tasks, but individual review is often preferred.   This podcast is Copyright 2026, The Association of Independent Architectural Photographers™, All Rights Reserved. This content may not be used in full or in part without the written consent of the AIAP. ➤➤Don't forget to like the podcast and subscribe to the channel .... Click the bell icon to get our regular videos. Share the video with your friends if you like it, and stay tuned to our channel.

Discover how custom metal fabrication transforms architectural challenges into stunning, functional solutions. From tailored roof vents and high-strength snow guards to hand-soldered copper elements, learn how old-world craftsmanship meets modern precision to bring architectural visions to life. Salvo Metal Works City: Naperville Address: 566 W 15th Ave Website: https://salvometalworks.com/

“The center of any change that we’re doing in the fourth industrial revolution is always the human being, because humans have an ability to adopt, adapt to skills, and adjust to an environment.” –Henrik von Scheel About Henrik von Scheel Henrik von Scheel is Co-Founder of advisory firm Strategic Intelligence, Chairman of the Climate Asset Trust, Vice Chairman of Regulatory Intelligence Committee, and Professor of Strategy, Arthur Lok Jack School of Business, among other roles. He is best known as originator of Industry 4.0, with many awards and extensive global recognition of his work. Webiste: von-scheel.com LinkedIn Profile: Henrik von Scheel What you will learn Why human-centered AI is crucial for widespread societal prosperity The impact of AI hype cycles, media narratives, and the realities of technology adoption How equitable wealth distribution and capital allocation in AI can shape economic outcomes Risks around data ownership, privacy, and the importance of controlling your own data in the AI era Divergent approaches to AI regulation in the US, EU, and China, and the implications for global AI leadership The importance of trust calibration and intentional human-AI collaboration in practical applications How education and lifelong learning can be reshaped by AI to support individualized growth and mistake-enabled reasoning Opportunities for AI to amplify individual talents, address educational gaps, and enable more specialized and innovative skills Episode Resources Transcript Ross Dawson: Henrik, it is wonderful to have you on the show. Henrik von Scheel: Thank you very much for having me, Ross. Ross Dawson: So I think we’re pretty aligned in believing that we need to approach AI from a human-centered perspective and how it can bring us prosperity. So I’d just love to start with, how do you think about how we should be thinking about AI? Henrik von Scheel: Well, I think, like every technology that comes into play, it brings a lot of changes to us. But I think the center of any change that we’re doing in the fourth industrial revolution is always the human being, because humans have an ability to adapt, adapt to skills, and adjust to an environment. So technology is something that we apply, but it’s the strategy on how we adapt with it that makes a difference. It’s never the technology itself. So I’m excited. It’s one of the most exciting periods for the industry and for us as people. Ross Dawson: There’s a phrase which I’ve heard you say more than once around AI should make us smarter, healthier, and wealthier. So if that’s the case, how do we frame it? How do we start to get on that journey? Henrik von Scheel: So I think what people experience today in AI is that they experience a lot of media hype—large language models, ChatGPT, and all of this—and they consume it from the media. So there’s a big hype around it, and I believe that AI is about to crash fundamentally, but crashing in technology is not bad, right? There are a lot of promises and then an inability to deliver, and then it crashes. What you hear in the media today is very much driven by a story of them raising funds because it’s so expensive, and so they are promising the world of everything and nothing, and the reality looks a little bit better. The world that they are presenting is that you will be replaced, and you will be happy, and you’ll be served by everything else. And somehow it will work out. We don’t know how, but it will work out. And that’s not a future that is really a real future. The future must include that everybody gets smarter, wealthier, and healthier. And when I say everybody, I mean not only the guys that have money, that they become more rich, or the middle class. It’s like everybody in society should get smarter from AI. That means part of the things that they need to learn or how human evolution works should be better, and it should make us healthier people and wealthier people. So it should not only be that we sacrifice our convenience with our freedom, with our privacy, with our environment, or any other things that we put on the table to get convenience back. That exchange we have done a couple of times, and it’s not working really well for humans, and it’s not a good trade for us, right? Ross Dawson: Yeah, I love that. And since it’s quite simple, you know, you can say it, it’s clear, it sounds good, and it is a really clear direction. But you’re actually pointing in a couple of ways there to capital allocation. So obviously, if you’re looking at the AI economic story, this is around this diversion of capital from other places to AI model development, data centers, deployment, and so on. But also, when you’re saying wealth here, this is around the distribution of wealth—where we’re allocating capital to AI development, but also from the way in which AI is developed, there will be creation of wealth. There is the real potential for productivity improvement. But then it’s about finding, how do we have the mechanisms for allocation of wealth or capital from that which is allocated? Let’s call it equitably. Henrik von Scheel: I’m a firm believer that this year, 35 to 45% of the money invested in AI will evaporate. Companies that have invested—they’re the early adopters—they have this format, so they’re rushing to it. From a company perspective, you always adapt the best practices. When it goes beyond the hype, and the performance curve and adoption curve is low. For example, for AI, the simple version is there. You heard that Deloitte and McKinsey talked 10 years ago about robotic process automation like God’s gift to mankind in AI. Today, you don’t hear them talking about it, because you can download it for free—for HR, for forecasting, planning, budgeting, and so on, you can save 20 or 30%, and as an organization, you can do it yourself. You download two, three models, you test it, and you run it. Good, okay, so that’s when you apply best practices. Then you have industry practices, like AI agents. So when you have AI agents for manufacturing, for industrial sectors, for energy sectors, they are nothing else than workflow optimization. You use robotic process optimization, you do a visualization on it, so it’s far more practical at a level, because you use the data they already have in the organizations under a simple line on the process flow, on the safety, security—it’s very much down at the level where they can apply it and use it. So this version of large language models, where you have this magic powder you spread over the organization and it’s totally working—it’s not really there. And then there’s the third leg that companies are quite aware of. It’s called Shadow AI, right? Shadow AI is because AI is the biggest infringement on intellectual capital within organizations. The reason why normal people are not allowed to look at pornography at their work is because of cybersecurity. It’s not that your boss doesn’t like you to look at pornography; it’s because of cybersecurity. It’s the same reason with AI—you should not be allowed to use Copilot latest version or large language models as a CFO or as a worker, because you’re exporting your own information outside. Copilot takes, every five seconds, a screenshot for the large language models’ learning. So as a corporate point of view, that’s the first thing—you should actually protect your own data so you can monetize your data in the future. From an economic point of view, if you go two, three steps behind this, you ask, okay, what is it that makes sense in this? There’s something really, really strange in this. Australia was built by building railways—they take 100 years to build, they also last 100 years. The infrastructure that lasts. So there’s a return on investment. You build streets, you build education systems—everything we build as humans, as society, has a lasting element to it. Now, we build data centers that last three months until the chips need to be returned, or six months. So there’s no sense in that we are building data centers around the world where we capture all data. It has a volume of hundreds of trillions of dollars, and we need to exchange them at a rate between three to six months to maintain the data. And then you say, wow. And you do that via license models of large language models—the data can never, in its entire life cycle, be that much worth. So there’s a very strange element, because most of the entrepreneurs that go to large language models and use their solutions on Gemini and ChatGPT and so on, you say, okay, you are building your solution on large language models, but you don’t own the model. You don’t own the data. You don’t own your own data. So what are you doing? Ross Dawson: You have architectural choices, to a point, as to— Henrik von Scheel: That’s Architectural choices, but you are limiting yourself. So the first element you always say, if my value is customizing a solution, your value is actually the data. So you must have a way to keep and maintain the data yourself. We can take another call to say how you apply AI and what the future of AI looks like, because AI today is very much focused on language models, and language models are the most limited version of AI science of all. It has the least data, but it’s the one we’re most excited about, because it resembles something we do—our wording, our formation of words. It’s a recognition. Recognitions are what we do. I wanted to come back to this about the economy, right? The US economy puts all chips on this. It’s highly energy sensitive, and it’s working all railroads. However, the US dollar is on a really, really bad track record. Three and a half years ago, there was a president in the US—he was sleeping—and meanwhile, he was sleeping, Saudi Arabia’s King MBS went in and he did a divorce, which is called the divorce of the petrodollar. So the gold linked with US dollar linked with oil—that was the solution. The US had that anybody, they could print as much money as they wanted, and the rest of the world was paying the dividend for it. It was the only country that could just print money. That brought the US into a mode, and when the new president came into his office, it’s very rare that in the US, you are writing an accord. An accord is only written when the Federal Reserve goes into the president’s office saying, guys, we’re hitting the wall. We need to do something. And they wrote five plans, what they wanted to do. And here’s the funny thing—when I mention them, you will recognize them very much. Number one, bring back manufacturing. Number two, implement tariffs so they can pull back US dollars. Number three, then they wanted to implement stable coins to pull back US dollars. I forgot number three, actually. Number four, and number five was actually they want to go to war. Now they go to war, right? So they are going to war, not because of any reasons besides their economy is based on a war machine, and the economy is becoming unstable. So that’s one of the main reasons. The US has put all cards on AI—all their economy cards are on AI. And that’s, from a country perspective, a very dangerous thing to do because you need energy and you need data, and AI from the US perspective has become a defense mechanism. When you look at the regulatory aspect of AI, Europe is very much put into human and center, and that the human owns the data, protects teenagers up to 16 years old, and that you can work as an entrepreneur with data, but you have to coordinate how you protect and manage the data. You have to be transparent on how you use the data and how much data you use. The US is very different—red tape off, no regulations at all, full-blown power to the market, and you are seen as a consumer, Ross, so all power to the guys who earn money to make more money. So no protections of anything, of your data—that’s the US version and literally, no regulations, no redtape regulations. Ross Dawson: In a moment, I want to move on to the human-AI collaboration. But just to round this out, you said before about your prediction that 35 to 40% of the investment in AI is gone, which I think is very, very fair. So back when we both were speakers at the Future of Sex Summit in Dubai last year, I was on a panel where I was asked, is it boom or bust? And basically both, in the sense of 35–40%—that’s bust. But at the same time, there are other parts of the market which can prosper. Of course, consolidation of the market means that there’s massive investments and in some cases massive losses, but there still are sectors where high value can be created. But this goes back to your point where still a lot of the center is in the US. We are starting to see sovereign AI initiatives and other initiatives around the world, but those are often open source foundation models. And obviously the regulation, particularly around the EU, provides a still very differentiated AI landscape with US, China, EU, and then some other players as well, where if we see boom and bust, that could be very much focused on the US, with potential for other parts of the world to see more growth in AI. Henrik von Scheel: So Ross, you’re using large language models, right? Ross Dawson: Yes. Henrik von Scheel: Do you have the feeling that they, since last year, are getting stronger or weaker? they’re getting weaker? Ross Dawson: They’re getting better. Henrik von Scheel: My feeling is the opposite. My feeling is that they’re getting weaker and weaker, and that’s because part of the data — Ross Dawson: In which content? Henrik von Scheel: They’re using old, old content. They’ve already used old content. So now you need to go to specialized, you need to go to public sources, to go for research data, you know. But from a content-wise perspective, it becomes extremely weak. I mean, last year, I’m extremely disappointed by large language models—very, very disappointed in terms of what they can deliver and what they do. Ask it whatever—ask it about futurism prediction, or ask about Industry 5.0, 5.6, whatever answer you give it, you can get an answer. You know, 110%—like CPAM, there are 19 regulations on CPAM, and you ask, how many regulations are there? They will give you sometimes 19, sometimes 17, sometimes 23—they just make up stuff. It just gets worse and worse. So if the valid data is not strong enough, it becomes actually a very, very weak tool after all, right? Ross Dawson: So are these using the top models from the frontier labs, because they are very good. Henrik von Scheel: Yeah, but then you have to have the paid model. But it’s not like I’m really, really impressed by it. It’s not kicking my bum where it says, holy smokes. In the beginning, the first two years, you were surprised, right? So I have a little bit of the feeling that AI today is a little bit where emails were in the beginning, and then digitalization came. With emails, we were all excited, but emails just created not less workload, but more workload for us—it decreased our productivity. There are really good signs of this. Then you look at digitalization, right? We were all excited because we can connect, we can talk to our friends, all of this. But what ended up with WhatsApp Business? WhatsApp Business is no business, right? We are using it, but it decreases our productivity level far more. So today, with digitalization, we are becoming generalists—quick information, we know something, but we don’t know anything, right? It’s not that you would put the finger on it and say, well, it has really increased our innovation level. No. Has it really increased our research level? No. Has it really made us better human beings? No. So I’m not negative against it. I’m just saying we have to be careful, because we have a knife or a hammer—we shouldn’t use the hammer for everything. And you mentioned that really well, right? AI’s hype cycle is, with any technology, there’s a hype, and then it goes down and matures, and then the application of this is different than what you thought in the beginning, of course, but that’s AI—it’s very much relevant. But you know, the big message today in AI is AI physical, right? What is AI physical? Ross Dawson: Well, just going back to the point—a lot of what I’m working on at the moment is the idea of appropriate trust. So you trust the models enough, but not too much, so that if they are going to give you bad results, you’re not relying on them. But if they are useful, you can use them. So we have to continue to calibrate for any particular model, which is different in every particular context. This is both essentially a skill or a capability, where we need to know when and how to use models at any particular time, because they’re changing in whatever way. So that becomes a foundation of how we can trust them to the right degree—not too much, but enough that we can actually use them if they are useful. Which comes back to this frame of the human-AI collaboration, which you’ve been doing a lot of work on. So if AI can be useful in some contexts, how is it that we can best build effective human-AI collaboration? Henrik von Scheel: I like this. Let’s play a little bit, right? So if human evolution is evolving with the birth certificate, we go to kindergarten, we go to school, and we learn differently. Everybody’s individual—we learn differently, right? It takes humans a long time to learn, to sense, to do all of this. And then you have AI, which is a supporting learning model for you to store information. But today you learn, and the model learns on you. You log in, and every time you learn, the model learns from you. That means that all your information is captured there, right? So the next evolution of a model should be that the privacy of Ross is throughout your last five years with large language models—you’ve studied Porter’s models, you’ve studied this and this. Well, if I ask you next day about Porter’s model, you still forget it, but the machine should be able to help you to learn, to adopt the skills in your daily life. So it cannot be a machine knowledge learning that is owned somewhere else by a big company—it must be something that is attached to Ross throughout your life, that you go from where you are now, and in five years, you’re somewhere else. So the knowledge that you have searched and gained and adopted, it follows your life, right? This is, for me, AI—the real AI revolution happens in the bio revolution in 2030, because the biggest amount of data we have is biophysical data. So the interconnection between our body, the modules, the biosystem modules, the biophysical systems, how we eat food, how material, with their level, is coming all in there, and part of this is the knowledge center of you, Ross. So if you learn something, how does it follow your evolution? Do you learn the same way today you learned 10 years ago? Ross Dawson: And it’s a wonderful thing that we continue to learn and forget and evolve. We are the same person, sort of, but, you know, we are a different person at the same time. Henrik von Scheel: I was talking yesterday to a psychiatrist who’s studying human evolution, and she’s called Trina Gondo, and I had this interesting discussion with her, because she says humans’ learning capacity changes throughout their life. So if we have learning modules that can support us throughout our life—to go through how conscious, how focused we are on things, how much stress level we can take, because stress levels are also different, how much breadth are you covering in terms of your work, your private life, how are you in terms of setup, in terms of your spiritual life—all of this has something to do with your learning, because it’s your perspective you drive. It’s your values you drive. I actually developed with her a model in terms of how the six aggregates of the brain work to understand our human evolution. For the last eight months, I’m trying to map human evolution, to map it to what AI—how it affects it, what we should regulate and how we should protect it, and how the human can monetize its own data, right? So just look at— Ross Dawson: The initiative by Doc Searls. So there’s a couple of really interesting initiatives. This is one where he worked originally on VRM, the vendor relationship management—you own your own data and trade that as effective—and is now building, or being instrumental in setting up, an AI initiative where it is around your personal AI, so you own the data, you own the systems, and you’re able to evolve with it. There are some other interesting initiatives like this, but these are obviously very tiny compared with the ways in which most people are using—essentially giving off their data to other people. But this is certainly part of the potential, to build the structures and architectures where we do own our data and our models and how they are used and what comes from them. Henrik von Scheel: So let’s go back into one element, right? Originally, Ross, you and everybody else of us who live in a society, we made an agreement with the government—a social agreement. And the social agreement is, I’m using, you’re protecting me, and I’m willing to pay tax somehow, right? So in reality, the government you made an agreement with should have the ability to protect you. However, in an AI model today, it’s not possible, because if they should protect you from the very beginning and keep the store of your data and maintain your data, the amount of money they need just to maintain your data is immense. So we need to define and find a model with governments where governments and the human being can, in co-ownership, hold the data structure—like in a blockchain, that you have a public and a private key, and both can hold the data, but the data is only unlocked both ways. Why? Because there’s a monetization model on your own data throughout your life. And when you die, your data goes on to your children, because that’s your DNA data, that’s your history life data, that’s all of it. So there should be an ability to monetize it. The challenge we face with this is the amount it will cost to maintain your data throughout your life, and we need to find—in the fourth industrial revolution, we’re going through the bio revolution, then we’re going to the consumer revolution, and then we go to the fusion revolution. And in the fusion revolution, the objective and the hope is that we are finding mechanisms to have cheap energy, because the amount of energy we use today in terms of data is literally crazy. It’s utterly, utterly crazy. We should be ashamed of ourselves if we see that, and that’s just for the amount of convenience. So if we find a model for our government to do this, we should actually work on this. This is what I’m trying to look at. I want to alert you to one interesting thing. My key field of study is patternicity with probabilities. So when you look at trends that are coming, you look at probabilities—not ChatGPT stuff, right? When you look at this, there’s one trend that emerged last week that hasn’t been emerging before—the trend of anarchy in Europe. Anarchy is an interesting aspect, because anarchy is your distrust in the government. And when anarchy comes, it’s just an equation of 25%. If 25% in a country like Germany or UK or France will take it, 25% is a flipping chart for everybody, because the petrol prices are too high, expenses for food are too high, they get too many promises they never—and then take the power in their own hand. When you look at it a little bit, you say, but anarchy—is that something new? No, the US is living in anarchy today. Trump is the true version of anarchy. They distrust the government, and they choose him, and he, from all aspects, says, okay, I’m doing something very different. I give all the power to the market. There’s been no time in history where all the power is residing within the market—Elon Musk and Amazon, Apple, all of them have literally all the power. It’s totally, utterly crazy. This is the highest version of anarchy you can see in a country. And if we’re not careful, it’s spreading. Why am I discussing this in an AI human element? Because if the human is the centerpiece, what is the core element of human development? It’s that we have safety, security, and trust. If trust is broken, anarchy emerges. So if anarchy emerges, AI can take on very different versions that we don’t want in a scenario thinking, but AI can also take on the version that it can support us in our evolution. Ross Dawson: Well, just going to that—education. You are a professor. You are an educator. You look at the future of education, and you alluded to that before. So in this world where AI is already and is becoming more significant, how do we reinvent education? How do we educate ourselves as individuals, as educational institutions, or society? How do we shape the education that we need for the exciting coming times? Henrik von Scheel: I think one of our challenges with education is that we as people, when we go beyond eight years old, the key element we’re learning is reasoning, and our reasoning skills are learned by doing mistakes, unfortunately. We never learn by getting an answer. If you study Porter’s model on ChatGPT, and you get all the answers from Porter’s model, and I ask you the next day, if you haven’t applied it, you haven’t learned it. If I would ask you, you will learn it. You do mistakes, and it’s by doing the mistakes, by putting yourself into the content, working with the content, and doing mistakes, you learn. Unfortunately, most of the stuff we learn today—now, human evolution in reasoning is by doing mistakes. So we need to find a very smart way how AI can support us in this mistake learning phase, because it’s the way that we are built to learn, right? Ross Dawson: And I think that’s a critical thing—where as individuals, we need to understand that if we delegate our thinking to AI, it’s not going to work; you’re going to be dumber rather than smarter. But if we can have the intent of using it to hone our thinking and helping us to make mistakes or be a Socratic dialog or whatever, we can do that, but that requires the individual intent. So again, we also need to frame as educators and also in organizations—which should be educational institutions in their own right, because they are learning organizations—it’s this framing of the use of AI as a cognitive foil for us, as opposed to something where we delegate our work, which is never going to get us anywhere good. Henrik von Scheel: And where do you think we can use it in education? Ross Dawson: The good thing is, you know, personalized education, where I think that there is definitely this ability to address where individuals are and their understanding, the metaphors that will be relevant to them, the frames for that. But it never has to be in a form of giving the answer. So there’s always this complement of human—as in, the educator needs to be inspiring. They need to help the person to find themselves. They have that relationship with them. So it’s this complement with the AI, which can guide to specific lessons or frames or examples that people resonate with, which can assist them. And so again, it needs to be very much—individuals need to understand, they have to shape it for themselves. I think we can present things in the right way. And there’s very much a human plus AI educational frame. Henrik von Scheel: I think you’re spot on with this. When you look at the five aggregates that we have in human evolution and in education phases, our sensory—our forming of ourselves to the outside world—is shaped quite early on, until we are maybe 12 years old, but quite early, the first two years. That means our sight, our smell, how we hear, how we taste, how we feel, and how our balance works—we learn quite fast. This is what AI is focusing on in AI physical today. They’re trying to come from a language model point of view outside to the physical world. Then we have this cognitive version of us, which is the intellect version. It’s very different. The intellect version of us is a version of awareness, a version of how we comprehend things, how we understand things, how our knowledge is conceived and given out. So it’s both communications, it’s storytelling, it’s our comprehension, it’s our perspective, it’s our reasoning, it’s our awareness. These four things are never the same for the same person. I can have a room of 200 students, I can talk about the same element on Adam Smith’s first principle, and they will all understand it differently because of their different backgrounds. So this part of cognitive understanding, the intellect, is far more complex. Then you go to the versions of who we are as a person. Our memories—our memories are a whole element of our emotions, which is a hugely important part of our learning, because memories have nothing to do with truth. Large language models always look for the truth, but in our own memories, we are lying to ourselves to keep our sanity. We are partly, not consciously but unconsciously, lying to ourselves because we view it only from one perspective. So our reflection of our memories or our impulses are related to our memories or our conceptual things. All these elements are our emotional elements, in terms of how strongly we can link to knowledge, how strongly we can see the future, how we can see ourselves in the future—all of this. When you look at the crisis now, the memory is on how resilient we are as people, how resilient we are in our learning phase, how comfortable we are with the unknown, how comfortable we are to learning. Then you have the next two ones. The other one is our mental formation or our identity. This is the element we’re trying to protect in digitalization—how we form our opinions, our insight, our resolution, our understanding, ourselves, and our retentiveness, who we are. All of these things are being shaped as teenagers. We don’t want this to be in a social aspect. We want this to be a safe, secure element. So this is the identity you form. Then you have the consciousness. The consciousness is a strange thing. You have two layers running in your education. You have the layers that are running long term and the unconsciousness that actually takes the decision—the analytical versions and the underlying elements. For example, why are you doing something? So you come with purposes, you come with energy, you come with desire, or you come with willpower. Then you say, well, they’re more etheric. No, they’re not. Because, Ross, you wake up every morning with that much amount of energy. You can use this the next eight hours you work. You can use it on emails the first four hours, but then you’re using your most precious willpower and energy right then. You have your willpower to train, for example, if you want to do training. When you want to train in the evening, when your willpower is lower, you want to train early in the morning. So this willpower and the energy is what we as humans in our consciousness—how we are aware of things, what we focus on, we magnify. So these are the five aggregates you’re using from the learning perspective. If we apply these, you and I, Ross, we would go into an initiative to say, how can we apply this to understand human evolution when we evolve this? Because I’m nearly 60 years old now, and that means, for me, my concept of life, experience of life, is different than when I was 30, than when I was 20. You cannot go to a young person that is 15 years old and say, let me tell you about love—there are four different phases of love. They need to experience them themselves, because it’s not my job to take that away from them. And it’s not my job to tell a young man, now you want to conquer and do, you want to have freedom, Generation X and all of this. And then you realize, easy, easy, easy. I’ll let you know. When you fall in love and you become a father, it changes you. Why does it change you? Because accountability moves into a man’s focus area, as before he was conquering. And then accountability—a man wants to be a caretaker of something, and it fulfills and magnifies a man. And then you say, well, this is not part of the five aggregates—very much so, right? Because it’s part of human evolution. Ross, you have experienced that in your life. So then you say, how do we connect that with our evolution and learning? Ross Dawson: Yeah, no, I think that’s a really important point around accountability for ourselves, for those around us, directly in the broader community. And I think that’s kind of this big humans plus AI frame. So we’re obviously just touching the surface of what we could dig into now. But how can people find out more about your work Henrik? Henrik von Scheel: I’m a public figure. I’m doing a lot of research projects with universities. I have a lot of PhD students and coaching and supporting governments on policy initiatives. Currently, I’m focusing a lot in the Gulf regions on strategic briefings, on crisis management, in terms of doing scenarios for strategic, tactical, operational, for short term and long term. But my passion is actually teaching, and this is far more a personal story on teaching. People see me always as the Industry 4.0 originator on everything I have accomplished. But my true story is actually quite different. When I was young, I was dyslexic. I’m actually double dyslexic, and I was stuttering. I had a very, very difficult time in school. That’s why I am a little bit passive aggressive, because I’m always on the defensive, because many years I went through life just being some sort of an outcast. So within that phase, I had a very strong teacher that actually supported me and used time and effort to see my skills, and he helped me to overcome my dyslexia—which is not really true. You never overcome your dyslexia. You are just getting tools to work with it. So that means I’ve written today nine books, and five of them are bestsellers, but I cannot even read my own books aloud. So what is the message I’m giving? Everybody of us is made different, and because we’re made different, it’s not that—because society is often built on, if you don’t fit that frame, then you’re not part of that frame. But I think AI opens up something for us—that the breadth of who we are as people is a beautiful thing. And because I cannot speak the same way, like I have a good friend Tarek, who is also your friend—he’s a gifted storyteller. My gift is that I can see patterns. So I believe that every human being should be able to see their superpower. Your gift, Ross, is a very different gift. You can gather communities, you can convey difficult things in a simple thing, you have an ability to put the human in the future, where everybody sits today and they freak the hell out because they don’t see them part of the future. So I think everybody has a future in that. To answer your question, I’m a quite reachable person. I believe the future looks like a good future for us, Ross. I believe this is the time for our educators to wake up out of their long-term sleep. We need to evolve our teaching material. We need to evolve the way that we learn and teach. We have terrible lessons in terms of how boys and girls evolve in their learnings, and we’re not doing anything about it. This is our chance with AI to change the learning mechanisms for boys and girls, our learning mechanisms if you’re one like me that doesn’t fit these templates, if you have special needs. We have the ability with AI to specialize ourselves far more in detail. One of the challenges we have with education today—when you go from primary school to higher education, and then go beyond higher education—our challenge with higher education is we have become generalists, and our generalism is actually inhibiting us to innovate, so we’re not meeting some of the core challenges that we have in science today, and we need to push the boundaries on where we go to research to really become innovative. We need to push our boundaries in terms of manufacturing, energy sector, and so on, to specialize in special fields. When you look at engineering schools, engineering schools have become more and more generalist in six fields, and they should become specialists in fields. So I think that’s where we need to really push the boundaries. Ross Dawson: Yeah, no, I think, to your point, what I see as one of the ultimate possibilities from AI is that it amplifies our individuality. And so that’s an extraordinary possibility. So thank you so much for your time and your insights, Henrik. You’re sharing some great work, and we’ll share in the show notes links to one of your research papers and the work you do. Thank you. Henrik von Scheel: Okay, thanks a lot. Good. Goodbye. The post Henrik von Scheel on making people smarter, wealthier and healthier, biophysical data, resilient learning, and human evolution (AC Ep37) appeared first on Humans + AI.

Ezequiel Paniagua LinkedIn Education: CoD-Pre- Architecture University of Wisconsin-Milwaukee-BA & MA of Architecture 

Architectural photographer Patrick Rogers joins Trent and Tim in the studio for a wide-ranging conversation about composition, client relationships, lighting, editing, pricing, publications, and the challenge of building a sustainable creative career. This episode is full of honest insight on the craft and business of architectural photography. About Patrick: Patrick Rogers is a Massachusetts-based architectural and portrait photographer focused on capturing the relationship between people, place, and design. His work highlights not just the finished structure, but the intention, craftsmanship, and human stories behind it—often with an emphasis on sustainable and biophilic architecture.  Through ongoing collaborations with architects, builders, and designers, Patrick creates imagery that supports both marketing and storytelling, helping firms consistently share their work and process. He also runs a studio in Maynard, where he photographs headshots and personal projects centered on craft and community.  At the heart of his work is a simple idea: that good design—and good photography—can help people feel something lasting. More from Patrick: Website: https://www.patrickrphoto.com  Instagram: https://www.instagram.com/patrickrphotos  LinkedIn: https://www.linkedin.com/in/patrick-rogers-8378265/  More from us: Website: www.adppodcast.com  Instagram: http://instagram.com/adppod_  Apple Podcast: https://podcasts.apple.com/us/podcast/architecture-design-photography/id1447381737  Spotify: https://open.spotify.com/show/5qTtT0lpXkVGyksEkN57VS  Thanks for watching!

This week, we're digging into Rotterdam's competition for a €240M new "climate landmark" — and the architectural competition for it is wild.This episode is sponsored by Trimble. Learn more about Trimble's ProjectSight here

6. Cline explores the decline of the Minoans on Crete and the Mycenaeanson mainland Greece. Both civilizations are categorized as failures that were internally fragile despite impressive architectural achievements like the Lion Gate. Overextension through massive construction projects and internal uprisings during periods of drought likely contributed to their demise. By the 11th century BC, these societies had vanished, though some cultural elements persisted through a permeable membrane into the Iron Age. Cline also discusses how Homer's epics, written centuries later, cautiously reflect this transition from the Bronze Age "Wanax" kings to the Iron Age "Basileus" leaders. (6)

Is your website a high-performing storefront or just a digital paperweight? In this session of the AIAP (Association of Independent Architectural Photographers), we take a deep dive into the "behind-the-scenes" mechanics that separate a pretty portfolio from a profitable business. Led by Alan Blakely and featuring insights from AIAP industry pros, we break down exactly how clients find you—and why they hire you. In this episode, we cover: • The SEO Myth: Why Google Analytics and Business Profiles are non-negotiable for 2026. • Portfolio Curation: Why 15-25 elite images beat an "endless scroll" every time. • Mobile-First or Mobile-Last? Analyzing the data on how many clients are actually viewing your work on their phones. • The AI Audit: How to use tools like Gemini and ChatGPT to get an objective, brutal review of your website's UX. • Pricing Transparency: Should you list your rates or keep them hidden? The group debates the pros and cons of vetting clients early. • Platform Wars: A look at Squarespace, PhotoFolio, Pixieset, and why "easy to update" beats "complex design." Whether you're a seasoned architectural shooter or a real estate photographer looking to level up to commercial work, this discussion provides the blueprint for a website that actually works while you're out shooting. This podcast is Copyright 2026, The Association of Independent Architectural Photographers™, All Rights Reserved. This content may not be used in full or in part without the written consent of the AIAP. ➤➤Don't forget to like the video and subscribe to the channel.

Artist and designer Dennis Maher has spent decades exploring the life cycles of buildings. After studying architecture at Cornell, he moved to Buffalo, New York—where a job in demolition introduced him to the visceral reality of the built environment constantly breaking down and rebuilding itself.That experience sparked a practice rooted in salvaged materials, forgotten objects, and the imaginative transformation of ordinary spaces. Maher's work now spans sculptural installations, living environments, and his most ambitious project: The Assembly House, an evolving artwork housed inside a historic church that also serves as a training ground for the building arts.Part immersive artwork, part cultural attraction, part educational engine, The Assembly House teaches people to build while reconnecting them to the tactile, communal experience of craft. Through what he calls “architectural dream worlds,” Maher explores how memory, materials, and imagination reshape the way we understand the spaces we inhabit—and the role we play in building them. Images and more from Dennis Maher on our website!Special thanks to our sponsor! Wix Studio is a platform built for all web creators to design, develop, and manage exceptional web projects at scale.Clever is hosted & produced by Amy Devers, with editing by Mark Zurawinski, production assistance from Ilana Nevins and Anouchka Stephan, and music by El Ten Eleven.SUBSCRIBE - listen to Clever on any podcast app!SIGN UP - for our Substack for news, bonus content, new episode alertsVISIT - cleverpodcast.com for transcripts, images, and 200+ more episodesSAY HI! - on Instagram & LinkedIn @cleverpodcast @amydeversApply to participate in Emerging Designers Spotlight LIVESpecial thanks to our sponsors!Wix Studio is a platform built for all web creators to design, develop, and manage exceptional web projects at scale. Hosted on Acast. See acast.com/privacy for more information.

On this episode of Inside the Firm, AIA says billings are down, then BLOK and Jack lead the way on Ai driven layoffs, and finally what Ai software you need to be implementing NOW at your firm to stay ahead of the curve. Join us as we go back Inside the Firm!

At Davos this year, some of the biggest names in tech sent a clear signal. AI is no longer a novelty. It is no longer a proof-of-concept exercise. As Demis Hassabis of Google DeepMind suggested, AI will shape more meaningful work. And Satya Nadella of Microsoft was even more direct. AI only matters if it improves real outcomes for people. So what does that look like inside the enterprise? In this episode of Tech Talks Daily, I'm joined by Andrew Boyagi, Customer CTO at Atlassian, to unpack how the conversation has shifted from experimentation to execution. Developers, in many ways, are the perfect lens for understanding this moment. Over the last two decades, their role has expanded far beyond writing code. They now own products, infrastructure, operations, and business outcomes. AI is simply the next chapter in that evolution. Andrew argues that AI will not replace engineers. It will raise expectations. As intelligent tools absorb repetitive work, the real value moves up the stack. System design. Architectural thinking. Reviewing and refining AI-generated output and orchestrating solutions that solve genuine business problems. And through it all, humans remain firmly in the loop. We also explore what this means for leadership, why mindset is starting to matter more than technical skill alone, how organizations can avoid layering AI on top of broken processes. And why the companies pulling ahead are treating AI as a strategic discipline, not a feature upgrade. This is a conversation grounded in reality. It speaks to product leaders, CTOs, CIOs, and anyone asking a simple but powerful question. If we are investing in AI, what are we actually getting back? And before we close, we look ahead to Team '26 and the themes Andrew and his team are already working on.  If this year has been about proving value, what will the next chapter demand from enterprise leaders? As always, I'd love to hear your thoughts. Are you seeing proof of value in your organization yet, or are you still working through the pilot phase?

Emily is an Architectural and Landscape Lighting Designer with over 20 years in the industry and 13 years running her own solo practice. Specializing in high-end residential and hospitality projects, her work blends interior and landscape lighting to create intentional, award-winning spaces. A two-time AIA awardee, USGBC award winner, educator, and ILLI board member, Emily is passionate about advancing lighting design excellence through education and real-world experience.

Modern art has always been a battleground — and the highly influential Museum of Modern Art has been partisan since its inception. Architectural historian Patricio Del Real discusses two differing political visions of modernism and modern architecture: one rooted in the left, and associated with figures such as Communist muralist Diego Rivera, and the other on the right, represented by the architect and fascist sympathizer Philip Johnson. He weighs in on the role of MoMa in promoting a view of modernism in Latin America, stripped of its radical politics and racial fusions, and radiating American power and hegemony. (Encore presentation.) Patricio del Real, Constructing Latin America: Architecture, Politics, and Race at the Museum of Modern Art Yale University Press, 2022 The post MoMa and Cultural Imperialism in Latin America appeared first on KPFA.

Kick off 2026 with a special edition of the Global DJ Broadcast: New Year's Rehab. Markus Schulz takes you on a journey through the sultry, sexy and euphoric moods of the afterhours, blending indie dance, Italian disco-inspired sounds and hypnotic late-night grooves. This standalone mix captures the essence of the early morning hours where music turns introspective, playful, and irresistibly addictive. Perfect for winding down after the celebrations or for embracing the start of a brand-new year.   Tracklist:   01. Hellmuth - Can't Resist 02. The Organism vs. John Summit, HAYLA & Millero - Serotonin Where You Are (Markus Schulz Mashup) 03. John Lord Fonda & Damon Jee vs. Tall Paul - Les Dunes d'Altair de Voodoo Ray (Markus Schulz Mashup) 04. Monococ - Pressure 05. Frankey & Sandrino - Acamar 06. Hellmuth - Stockholm Syndrome 07. Rex the Dog - Change This Pain for Ecstasy 08. David Tort & Kurt Caesar - Clear All Patterns 09. Alessa Khin - Hanami 10. GENESI, Wave Wave & Roland Clarke - Phones Down (Hellmuth Rework) 11. Damon Jee & Demian - Memories 12. Architectural vs. Stylo & Space Motion - Never Be Yours Again, Boy (Markus Schulz Mashup) 13. Ed Ed - The Ellcrys 14. Laurent Garnier - Man with the Red Face 15. Infektion vs. MODEON - Disco Crazy Armor (Markus Schulz Mashup) 16. Kollektiv &Turmstrasse - Stalker: Cold Love 17. Frankie Knuckles presents Director's Cut - Your Love (Director's Cut Signature Mix) 18. Luka Cikic - Floating in Desert 19. Dave Brody - Eclipse (Guy J Remix) 20. Ame, Trikk & Jens Kuross - Don't Waste My Time 21. Empire of the Sun - We Are the People (Adam Sellouk Remix) 22. Eagles & Butterflies - The Trip (Jennifer Cardini & Damon Jee Remix) 23. Deep Dish x Eynka featuring Wrabel - Midnight  

  ECONOMIC SLOWDOWN AND CONSUMER SPENDING Colleague Gene Marks, The Guardian. Gene Marksreports on a US economic slowdown, citing contracting architectural billings and falling hotel occupancy. He notes that while the wealthy continue spending, the middle class is cutting back on dining out. Marks attributes inflation to government money circulation and discusses proposals for mandated retirement contributions. NUMBER 15