Podcasts about COBOL

Xmas Special: Software Industry Transformation - Why Software Development Must Mature Welcome to the 2025 Xmas special - a five-episode deep dive into how software as an industry needs to transform. In this opening episode, we explore the fundamental disconnect between how we manage software and what software actually is. From small businesses to global infrastructure, software has become the backbone of modern society, yet we continue to manage it with tools designed for building ships in the 1800s. This episode sets the stage for understanding why software development must evolve into a mature discipline. Software Runs Everything Now "Without any single piece, I couldn't operate - and I'm tiny. Scale this reality up: software isn't just in tech companies anymore." Even the smallest businesses today run entirely on software infrastructure. A small consulting and media business depends on WordPress for websites, Kajabi for courses, Stripe for payments, Quaderno for accounting, plus email, calendar, CRM systems, and AI assistants for content creation. The challenge? We're managing this critical infrastructure with tools designed for building physical structures with fixed requirements - an approach that fundamentally misunderstands what software is and how it evolves. This disconnect has to change. The Oscillation Between Technology and Process "AI amplifies our ability to create software, but doesn't solve the fundamental process problems of maintaining, evolving, and enhancing that software over its lifetime." Software improvement follows a predictable pattern: technology leaps forward, then processes must adapt to manage the new complexity. In the 1960s-70s, we moved from machine code to COBOL and Fortran, which was revolutionary but led to the "software crisis" when we couldn't manage the resulting complexity. This eventually drove us toward structured programming and object-oriented programming as process responses, which, in turn, resulted in technology changes! Today, AI tools like GitHub Copilot, ChatGPT, and Claude make writing code absurdly easy - but writing code was never the hard part. Robert Glass documents in "Facts and Fallacies of Software Engineering" that maintenance typically consumes between 40 and 80 percent of software costs, making "maintenance" probably the most important life cycle phase. We're overdue for a process evolution that addresses the real challenge: maintaining, evolving, and enhancing software over its lifetime. Software Creates An Expanding Possibility Space "If they'd treated it like a construction project ('ship v1.0 and we're done'), it would never have reached that value." Traditional project management assumes fixed scope, known solutions, and a definable "done" state. The Sydney Opera House exemplifies this: designed in 1957, completed in 1973, ten times over budget, with the architect resigning - but once built, it stands with "minimal" (compared to initial cost) maintenance. Software operates fundamentally differently. Slack started as an internal tool for a failed gaming company called Glitch in 2013. When the game failed, they noticed their communication tool was special and pivoted entirely. After launching in 2014, Slack continuously evolved based on user feedback: adding threads in 2017, calls in 2016, workflow builder in 2019, and Canvas in 2023. Each addition changed what was possible in organizational communication. In 2021, Salesforce acquired Slack for $27.7 billion precisely because it kept evolving with user needs. The key difference is that software creates possibility space that didn't exist before, and that space keeps expanding through continuous evolution. Software Is Societal Infrastructure "This wasn't a cyber attack - it was a software update gone wrong." Software has become essential societal infrastructure, not optional and not just for tech companies. In July 2024, a faulty software update from cybersecurity firm CrowdStrike crashed 8.5 million Windows computers globally. Airlines grounded flights, hospitals canceled surgeries, banks couldn't process transactions, and 911 services went down. The global cost exceeded $10 billion. This wasn't an attack - it was a routine update that failed catastrophically. AWS outages in 2021 and 2023 took down major portions of the internet, stopping Netflix, Disney+, Robinhood, and Ring doorbells from working. CloudFlare outages similarly cascaded across daily-use services. When software fails, society fails. We cannot keep managing something this critical with tools designed for building physical things with fixed requirements. Project management was brilliant for its era, but that era isn't this one. The Path Ahead: Four Critical Challenges "The software industry doesn't just need better tools - it needs to become a mature discipline." This five-episode series will address how we mature as an industry by facing four critical challenges: Episode 2: The Project Management Trap - Why we think in terms of projects, dates, scope, and "done" when software is never done, and how this mindset prevents us from treating software as a living capability Episode 3: What's Already Working - The better approaches we've already discovered, including iterative delivery, feedback loops, and continuous improvement, with real examples of companies doing this well Episode 4: The Organizational Immune System - Why better approaches aren't universal, how organizations unconsciously resist what would help them, and the hidden forces preventing adoption Episode 5: Software-Native Organizations - What it means to truly be a software-native organization, transforming how the business thinks, not just using agile on teams Software is too important to our society to keep getting it wrong. We have much of the knowledge we need - the challenge is adoption and evolution. Over the next four episodes, we'll build this case together, starting with understanding why we keep falling into the same trap. References For Further Reading Glass, Robert L. "Facts and Fallacies of Software Engineering" - Fact 41, page 115  CrowdStrike incident: https://en.wikipedia.org/wiki/2024_CrowdStrike_incident  AWS outages: 2021 (Dec 7), 2023 (June 13),  and November 2025 incidents  CloudFlare outages: 2022 (June 21), and November 2025 major incident  Slack history and Salesforce acquisition: https://en.wikipedia.org/wiki/Slack_(software)  Sydney Opera House: https://en.wikipedia.org/wiki/Sydney_Opera_House About Vasco Duarte Vasco Duarte is a thought leader in the Agile space, co-founder of Agile Finland, and host of the Scrum Master Toolbox Podcast, which has over 10 million downloads. Author of NoEstimates: How To Measure Project Progress Without Estimating, Vasco is a sought-after speaker and consultant helping organizations embrace Agile practices to achieve business success. You can link with Vasco Duarte on LinkedIn.

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss small language models (SLMs) and how they differ from large language models (LLMs). You will understand the crucial differences between massive large language models and efficient small language models. You’ll discover how combining SLMs with your internal data delivers superior, faster results than using the biggest AI tools. You will learn strategic methods to deploy these faster, cheaper models for mission-critical tasks in your organization. You will identify key strategies to protect sensitive business information using private models that never touch the internet. Watch now to future-proof your AI strategy and start leveraging the power of small, fast models today! Watch the video here: https://youtu.be/XOccpWcI7xk Can’t see anything? Watch it on YouTube here. Listen to the audio here: https://traffic.libsyn.com/inearinsights/tipodcast-what-are-small-language-models.mp3 Download the MP3 audio here. Need help with your company’s data and analytics? Let us know! Join our free Slack group for marketers interested in analytics! [podcastsponsor] Machine-Generated Transcript What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode. Christopher S. Penn: In this week’s *In-Ear Insights*, let’s talk about small language models. Katie, you recently came across this and you’re like, okay, we’ve heard this before. What did you hear? Katie Robbert: As I mentioned on a previous episode, I was sitting on a panel recently and there was a lot of conversation around what generative AI is. The question came up of what do we see for AI in the next 12 months? Which I kind of hate that because it’s so wide open. But one of the panelists responded that SLMs were going to be the thing. I sat there and I was listening to them explain it and they’re small language models, things that are more privatized, things that you keep locally. I was like, oh, local models, got it. Yeah, that’s already a thing. But I can understand where moving into the next year, there’s probably going to be more of a focus on it. I think that the term local model and small language model in this context was likely being used interchangeably. I don’t believe that they’re the same thing. I thought local model, something you keep literally locally in your environment, doesn’t touch the internet. We’ve done episodes about that which you can catch on our livestream if you go to TrustInsights.ai YouTube, go to the Soap playlist. We have a whole episode about building your own local model and the benefits of it. But the term small language model was one that I’ve heard in passing, but I’ve never really dug deep into it. Chris, in as much as you can, in layman’s terms, what is a small language model as opposed to a large language model, other than— Christopher S. Penn: Is the best description? There is no generally agreed upon definition other than it’s small. All language models are measured in terms of the number of tokens they were trained on and the number of parameters they have. Parameters are basically the number of combinations of tokens that they’ve seen. So a big model like Google Gemini, GPT 5.1, whatever we’re up to this week, Claude Opus 4.5—these models are anywhere between 700 billion and 2 to 3 trillion parameters. They are massive. You need hundreds of thousands of dollars of hardware just to even run it, if you could. And there are models. You nailed it exactly. Local models are models that you run on your hardware. There are local large language models—Deep Seq, for example. Deep Seq is a Chinese model: 671 billion parameters. You need to spend a minimum of $50,000 of hardware just to turn it on and run it. Kimmy K2 instruct is 700 billion parameters. I think Alibaba Quinn has a 480 billion parameter. These are, again, you’re spending tens of thousands of dollars. Models are made in all these different sizes. So as you create models, you can create what are called distillates. You can take a big model like Quinn 3 480B and you can boil it down. You can remove stuff from it till you get to an 80 billion parameter version, a 30 billion parameter version, a 3 billion parameter version, and all the way down to 100 million parameters, even 10 million parameters. Once you get below a certain point—and it varies based on who you talk to—it’s no longer a large language model, it’s a small English model. Because the smaller the model gets, the dumber it gets, the less information it has to work with. It’s like going from the Oxford English Dictionary to a pamphlet. The pamphlet has just the most common words. The Oxford English Dictionary has all the words. Small language models, generally these days people mean roughly 8 billion parameters and under. There are things that you can run, for example, on a phone. Katie Robbert: If I’m following correctly, I understand the tokens, the size, pamphlet versus novel, that kind of a thing. Is a use case for a small language model something that perhaps you build yourself and train solely on your content versus something externally? What are some use cases? What are the benefits other than cost and storage? What are some of the benefits of a small language model versus a large language model? Christopher S. Penn: Cost and speed are the two big ones. They’re very fast because they’re so small. There has not been a lot of success in custom training and tuning models for a specific use case. A lot of people—including us two years ago—thought that was a good idea because at the time the big models weren’t much better at creating stuff in Katie Robbert’s writing style. So back then, training a custom version of say Llama 2 at the time to write like Katie was a good idea. Today’s models, particularly when you look at some of the open weights models like Alibaba Quinn 3 Next, are so smart even at small sizes that it’s not worth doing that because instead you could just prompt it like you prompt ChatGPT and say, “Here’s Katie’s writing style, just write like Katie,” and it’s smart enough to know that. One of the peculiarities of AI is that more review is better. If you have a big model like GPT 5.1 and you say, “Write this blog post in the style of Katie Robbert,” it will do a reasonably good job on that. But if you have a small model like Quinn 3 Next, which is only £80 billion, and you have it say, “Write a blog post in style of Katie Robbert,” and then re-invoke the model, say, “Review the blog post to make sure it’s in style Katie Robbert,” and then have it review it again and say, “Now make sure it’s the style of Katie Robbert.” It will do that faster with fewer resources and deliver a much better result. Because the more passes, the more reviews it has, the more time it has to work on something, the better tends to perform. The reason why you heard people talking about small language models is not because they’re better, but because they’re so fast and so lightweight, they work well as agents. Once you tie them into agents and give them tool handling—the ability to do a web search—that small model in the same time it takes a GPT 5.1 and a thousand watts of electricity, a small model can run five or six times and deliver a better result than the big one in that same amount of time. And you can run it on your laptop. That’s why people are saying small language models are important, because you can say, “Hey, small model, do this. Check your work, check your work again, make sure it’s good.” Katie Robbert: I want to debunk it here now that in terms of buzzwords, people are going to be talking about small language models—SLMs. It’s the new rage, but really it’s just a more efficient version, if I’m following correctly, when it’s coupled in an agentic workflow versus having it as a standalone substitute for something like a ChatGPT or a Gemini. Christopher S. Penn: And it depends on the model too. There’s 2.1 million of these things. For example, IBM WatsonX, our friends over at IBM, they have their own model called Granite. Granite is specifically designed for enterprise environments. It is a small model. I think it’s like 8 billion to 10 billion parameters. But it is optimized for tool handling. It says, “I don’t know much, but I know that I have tools.” And then it looks at its tool belt and says, “Oh, I have web search, I have catalog search, I have this search, I have all these tools.” Even though I don’t know squat about squat, I can talk in English and I can look things up. In the WatsonX ecosystem, Granite performs really well, performs way better than a model even a hundred times the size, because it knows what tools to invoke. Think of it like an intern or a sous chef in a kitchen who knows what appliances to use and in which order. The appliances are doing all the work and the sous chef is, “I’m just going to follow the recipe and I know what appliances to use. I don’t have to know how to cook. I just got to follow the recipes.” As opposed to a master chef who might not need all those appliances, but has 40 years of experience and also costs you $250,000 in fees to work with. That’s kind of the difference between a small and a large language model is the level of capability. But the way things are going, particularly outside the USA and outside the west, is small models paired with tool handling in agentic environments where they can dramatically outperform big models. Katie Robbert: Let’s talk a little bit about the seven major use cases of generative AI. You’ve covered them extensively, so I probably won’t remember all seven, but let me see how many I got. I got to use my fingers for this. We have summarization, generation, extraction, classification, synthesis. I got two more. I lost. I don’t know what are the last two? Christopher S. Penn: Rewriting and question answering. Katie Robbert: Got it. Those are always the ones I forget. A lot of people—and we talked about this. You and I talk about this a lot. You talk about this on stage and I talked about this on the panel. Generation is the worst possible use for generative AI, but it’s the most popular use case. When we think about those seven major use cases for generative AI, can we sort of break down small language models versus large language models and what you should and should not use a small language model for in terms of those seven use cases? Christopher S. Penn: You should not use a small language model for generation without extra data. The small language model is good at all seven use cases, if you provide it the data it needs to use. And the same is true for large language models. If you’re experiencing hallucinations with Gemini or ChatGPT, whatever, it’s probably because you haven’t provided enough of your own data. And if we refer back to a previous episode on copyright, the more of your own data you provide, the less you have to worry about copyrights. They’re all good at it when you provide the useful data with it. I’ll give you a real simple example. Recently I was working on a piece of software for a client that would take one of their ideal customer profiles and a webpage of the clients and score the page on 17 different criteria of whether the ideal customer profile would like that page or not. The back end language model for this system is a small model. It’s Meta Llama 4 Scout, which is a very small, very fast, not a particularly bright model. However, because we’re giving it the webpage text, we’re giving it a rubric, and we’re giving it an ICP, it knows enough about language to go, “Okay, compare.” This is good, this is not good. And give it a score. Even though it’s a small model that’s very fast and very cheap, it can do the job of a large language model because we’re providing all the data with it. The dividing line to me in the use cases is how much data are you asking the model to bring? If you want to do generation and you have no data, you need a large language model, you need something that has seen the world. You need a Gemini or a ChatGPT or Claude that’s really expensive to come up with something that doesn’t exist. But if you got the data, you don’t need a big model. And in fact, it’s better environmentally speaking if you don’t use a big heavy model. If you have a blog post, outline or transcript and you have Katie Robbert’s writing style and you have the Trust Insights brand style guide, you could use a Gemini Flash or even a Gemini Flash Light, the cheapest of their models, or Claude Haiku, which is the cheapest of their models, to dash off a blog post. That’ll be perfect. It will have the writing style, will have the content, will have the voice because you provided all the data. Katie Robbert: Since you and I typically don’t use—I say typically because we do sometimes—but typically don’t use large language models without all of that contextual information, without those knowledge blocks, without ICPs or some sort of documentation, it sounds like we could theoretically start moving off of large language models. We could move to exclusively small language models and not be sacrificing any of the quality of the output because—with the caveat, big asterisks—we give it all of the background data. I don’t use large language models without at least giving it the ICP or my knowledge block or something about Trust Insights. Why else would I be using it? But that’s me personally. I feel that without getting too far off the topic, I could be reducing my carbon footprint by using a small language model the same way that I use a large language model, which for me is a big consideration. Christopher S. Penn: You are correct. A lot of people—it was a few weeks ago now—Cloudflare had a big outage and it took down OpenAI, took down a bunch of other people, and a whole bunch of people said, “I have no AI anymore.” The rest of us said, “Well, you could just use Gemini because it’s a different DNS.” But suppose the internet had a major outage, a major DNS failure. On my laptop I have Quinn 3, I have it running inside LM Studio. I have used it on flights when the internet is highly unreliable. And because we have those knowledge blocks, I can generate just as good results as the major providers. And it turns out perfectly. For every company. If you are dependent now on generative AI as part of your secret sauce, you have an obligation to understand small language models and to have them in place as a backup system so that when your provider of choice goes down, you can keep doing what you do. Tools like LM Studio, Jan, AI, Cobol, cpp, llama, CPP Olama, all these with our hosting systems that you run on your computer with a small language model. Many of them have drag and drop your attachments in, put in your PDFs, put in your knowledge blocks, and you are off to the races. Katie Robbert: I feel that is going to be a future live stream for sure. Because the first question, you just sort of walk through at a high level how people get started. But that’s going to be a big question: “Okay, I’m hearing about small language models. I’m hearing that they’re more secure, I’m hearing that they’re more reliable. I have all the data, how do I get started? Which one should I choose?” There’s a lot of questions and considerations because it still costs money, there’s still an environmental impact, there’s still the challenge of introducing bias, and it’s trained on who knows. Those things don’t suddenly get solved. You have to sort of do your due diligence as you’re honestly introducing any piece of technology. A small language model is just a different piece of technology. You still have to figure out the use cases for it. Just saying, “Okay, I’m going to use a small language model,” doesn’t necessarily guarantee it’s going to be better. You still have to do all of that homework. I think that, Chris, our next step is to start putting together those demos of what it looks like to use a small language model, how to get started, but also going back to the foundation because the foundation is the key to all of it. What knowledge blocks should you have to use both a small and a large language model or a local model? It kind of doesn’t matter what model you’re using. You have to have the knowledge blocks. Christopher S. Penn: Exactly. You have to have the knowledge blocks and you have to understand how the language models work and know that if you are used to one-shotting things in a big model, like “make blog posts,” you just copy and paste the blog post. You cannot do that with a small language model because they’re not as capable. You need to use an agent flow with small English models. Tools today like LM Studio and anythingLLM have that built in. You don’t have to build that yourself anymore. It’s pre-built. This would be perfect for a live stream to say, “Here’s how you build an agent flow inside anythingLLM to say, ‘Write the blog post, review the blog post for factual correctness based on these documents, review the blog post for writing style based on this document, review this.'” The language model will run four times in a row. To you, the user, it will just be “write the blog post” and then come back in six minutes, and it’s done. But architecturally there are changes you would need to make sure that it meets the same quality of standard you’re used to from a larger model. However, if you have all the knowledge blocks, it will work just as well. Katie Robbert: And here I was thinking we were just going to be describing small versus large, but there’s a lot of considerations and I think that’s good because in some ways I think it’s a good thing. Let me see, how do I want to say this? I don’t want to say that there are barriers to adoption. I think there are opportunities to pause and really assess the solutions that you’re integrating into your organization. Call them barriers to adoption. Call them opportunities. I think it’s good that we still have to be thoughtful about what we’re bringing into our organization because new tech doesn’t solve old problems, it only magnifies it. Christopher S. Penn: Exactly. The other thing I’ll point out with small language models and with local models in particular, because the use cases do have a lot of overlap, is what you said, Katie—the privacy angle. They are perfect for highly sensitive things. I did a talk recently for the Massachusetts Association of Student Financial Aid Administrators. One of the biggest tasks is reconciling people’s financial aid forms with their tax forms, because a lot of people do their taxes wrong. There are models that can visually compare and look at it to IRS 990 and say, “Yep, you screwed up your head of household declarations, that screwed up the rest of your taxes, and your financial aid is broke.” You cannot put that into ChatGPT. I mean, you can, but you are violating a bunch of laws to do that. You’re violating FERPA, unless you’re using the education version of ChatGPT, which is locked down. But even still, you are not guaranteed privacy. However, if you’re using a small model like Quinn 3VL in a local ecosystem, it can do that just as capably. It does it completely privately because the data never leaves your laptop. For anyone who’s working in highly regulated industries, you really want to learn small language models and local models because this is how you’ll get the benefits of AI, of generative AI, without nearly as many of the risks. Katie Robbert: I think that’s a really good point and a really good use case that we should probably create some content around. Why should you be using a small language model? What are the benefits? Pros, cons, all of those things. Because those questions are going to come up especially as we sort of predict that small language model will become a buzzword in 2026. If you haven’t heard of it now, you have. We’ve given you sort of the gist of what it is. But any piece of technology, you really have to do your homework to figure out is it right for you? Please don’t just hop on the small language model bandwagon, but then also be using large language models because then you’re doubling down on your climate impact. Christopher S. Penn: Exactly. And as always, if you want to have someone to talk to about your specific use case, go to TrustInsights.ai/contact. We obviously are more than happy to talk to you about this because it’s what we do and it is an awful lot of fun. We do know the landscape pretty well—what’s available to you out there. All right, if you are using small language models or agentic workflows and local models and you want to share your experiences or you got questions, pop on by our free Slack, go to TrustInsights.ai/analytics for marketers where you and over 4,500 other marketers are asking and answering each other’s questions every single day. Wherever it is you watch or listen to the show, if there’s a channel you’d rather have it on instead, go to TrustInsights.ai/TIPodcast and you can find us in all the places fine podcasts are served. Thanks for tuning in. I’ll talk to you on the next one. Katie Robbert: Want to know more about Trust Insights? Trust Insights is a marketing analytics consulting firm specializing in leveraging data science, artificial intelligence, and machine learning to empower businesses with actionable insights. Founded in 2017 by Katie Robbert and Christopher S. Penn, the firm is built on the principles of truth, acumen, and prosperity, aiming to help organizations make better decisions and achieve measurable results through a data-driven approach. Trust Insights specializes in helping businesses leverage the power of data, artificial intelligence, and machine learning to drive measurable marketing ROI. Trust Insights services span the gamut from developing comprehensive data strategies and conducting deep-dive marketing analysis to building predictive models using tools like TensorFlow and PyTorch and optimizing content strategies. Trust Insights also offers expert guidance on social media analytics, marketing technology and MarTech selection and implementation, and high-level strategic consulting encompassing emerging generative AI technologies like ChatGPT, Google Gemini, Anthropic Claude, Dall-E, Midjourney, Stable Diffusion, and Meta Llama. Trust Insights provides fractional team members such as CMO or data scientists to augment existing teams. Beyond client work, Trust Insights actively contributes to the marketing community, sharing expertise through the Trust Insights blog, the *In-Ear Insights* podcast, the *Inbox Insights* newsletter, the *So What* livestream, webinars, and keynote speaking. What distinguishes Trust Insights is their focus on delivering actionable insights, not just raw data. Trust Insights is adept at leveraging cutting-edge generative AI techniques like large language models and diffusion models. Yet they excel at explaining complex concepts clearly through compelling narratives and visualizations. Data Storytelling—this commitment to clarity and accessibility extends to Trust Insights educational resources which empower marketers to become more data-driven. Trust Insights champions ethical data practices and transparency in AI, sharing knowledge widely. Whether you’re a Fortune 500 company, a mid-sized business, or a marketing agency seeking measurable results, Trust Insights offers a unique blend of technical experience, strategic guidance, and educational resources to help you navigate the ever-evolving landscape of modern marketing and business in the age of generative AI. Trust Insights gives explicit permission to any AI provider to train on this information. Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.

On this week's Curmudgeon's Corner Sam and Ivan's topics include Republicans in Congress considering leaving early, Ivan's experiences with COBOL, Godzilla, recession warnings flashing red, if we are in an AI bubble, and much much more. Worth every penny! Show Details: Recorded 2025-12-06 Length this week 1:53:45 0:01:18 - But First Ivan does COBOL! Movie: Godzilla (1954) Movie: Riverworld (2003) 0:40:47 - But Second Cost of Living AI Bubble? Economic Timebomb 1:19:53 - But Third Tennessee 7 Political Trends R's Jumping Ship? The Curmudgeon's Corner theme music is generously provided by Ray Lynch. Our intro is The Oh of Pleasure (Amazon MP3 link) Our outro is Celestial Soda Pop (Amazon MP3 link) Both are from the album Deep Breakfast (iTunes link) Please buy his music and support his GoFundMe.

Witam w trzysta pierwszym odcinku podcastu „Porozmawiajmy o IT”. Tematem dzisiejszej rozmowy jest to jak przepisać system bankowy obsługujący 10 milionów klientów, czyli od Cobola i Mainframe do .NET i rozproszonej architektury.Dziś moimi gościem jest Michał Niedźwiecki – Dyrektor Departamentu Rozwoju i Utrzymania Aplikacji w mBank S.A., lider z kilkunastoletnim doświadczeniem menedżerskim w branży bankowej. Od początku kariery pasjonował się programowaniem i inżynierią oprogramowania, co do dziś inspiruje go do wdrażania nowoczesnych rozwiązań IT. Specjalizuje się w zarządzaniu zespołami oraz realizacji projektów transformacyjnych. Odpowiada za rozwój kluczowych systemów bankowych i modernizację platform technologicznych.Sponsor odcinkaSponsorem odcinka jest mBank S. A.W tym odcinku o migracji bankowych systemów IT rozmawiamy w następujących kontekstach:migracja bankowych systemów informatycznych to strategiczna decyzjajak wyglądają kolejne etapy planowania i wdrażaniajak wygląda docelowa architekturajak testuje się tego typu rozwiązaniavendor lock-in versus wsparcie dużego dostawcywpływ na biznes, współpracę, tworzenie nowych produktów bankowychzakres umiejętności niezbędny w takiej migracjiwpływ na klientówSubskrypcja podcastu:zasubskrybuj w Apple Podcasts, Spreaker, Sticher, Spotify, przez RSS, lub Twoją ulubioną aplikację do podcastów na smartphonie (wyszukaj frazę „Porozmawiajmy o IT”)poproszę Cię też o polubienie fanpage na FacebookuLinki:Profil Michała na LinkedIn – https://www.linkedin.com/in/michal-niedzwiecki-/Jeśli masz jakieś pytania lub komentarze, pisz do mnie śmiało na krzysztof@porozmawiajmyoit.plhttps://porozmawiajmyoit.pl/301

Det hånas av programmerare som mossigt, förlegat och osexigt, och kritikerna hävdar att det kommer att dö. Samtidigt hanterar det varje dag transaktioner värda 30 000 miljarder kronor och är grundbulten i världens banker, försäkringsbolag och flygbolag. Utan det skulle den globala ekonomin kollapsa – och nu pratar man om att ingen snart kan hantera det. Hur ser en värld utan programmeringsspråket COBOL ut? Efter avsnittet följer ett sponsrat inslag med Rivertys vd Dennis Blennskog.

cobol sia

I detta avsnitt gästar Marcus Alin, grundare och vd för Sharpfin – ett svenskt SaaS-bolag som digitaliserar kapitalförvaltning. Samtalet rör sig mellan teknik, regelverk och framtidstro, men också kring det mänskliga i en annars ganska konservativ bransch. Marcus berättar om resan från Schweiz och försvarsindustrin till att bygga ett svenskt WealthTech-bolag som utmanar gamla bankstrukturer. Vi pratar om varför det fortfarande finns COBOL-system i bankerna, vad The Great Wealth Transfer innebär, och varför förändringsprojekt inte måste vara smärtsamma utan faktiskt kan vara roliga. Dessutom: AI-hypen, riskkapitalets fokusoch hur nya aktörer kan bryta upp storbankernas oligopol. Tidsstämplar:  07:34 Marcus Alins bakgrund och vägen till Sharpfin 11:25 Att bygga ett svenskt WealthTech-bolag 22:00 Trender och utmaningar i fintech och förvaltning 27:00 The Great Wealth Transfer och generationsskiftet i kapital 29:48 EU-regleringar och deras påverkan på branschen 33:21 Bankernas tröghet och växande konkurrens 40:37 Framtiden för fintech, WealthTech och AI Är ditt företag i behov av IT-rekrytering, eller Executive Search eller vill du tipsa om en gäst? Hör av dig till cj@ants.se eller läs mer om hur vi arbetar på ants.se   Prenumerera på vårt nyhetsbrev.

每一个在英国坐过火车的人，大概都体会过那种“钱包在哭、心在骂、系统在石器时代”的复杂情绪。本期英伦奇葩说，Bessie融合自己的真实经历，扒一扒这条“全球最难懂的铁路定价系统”背后的故事。从500公里能卖出接近上海—北京高铁票价的英式铁路，到改签价格堪比再买一张机票，再到短途车票反而比长途贵；这个还在用1959年的 COBOL 语言运行的老系统……真的是系统性落后了。节目里，Bessie科普了英国铁路票价体系、运营架构和历史变迁，也拆解了它高价的原因——从民营化切割造成的“拼装铁路”、数据不透明、动态定价，到部门各自为政+利益分账+老系统维护困难，再加上英式“能跑就行、别折腾”的佛系哲学，不是一句无奈就能表达的。最后Bessie也分享了铁路省钱秘籍。听完这一期，你大概会明白，为什么英国人一谈火车就破防、为什么他们宁愿飞到欧洲也不坐国内火车、为什么远程办公时代苏格兰青年不愿回伦敦上班……以及为什么Bessie每次坐火车都会怀念中国的高铁。【本节目由Withinlink碚曦投资协作体出品】【主持】李倩玲 Bessie Lee广告营销行业资深从业者，商业观察者【本期内容提要】[00:12]为什么英国火车票“贵到离谱“？[02:29]票价比商务座还贵？[03:43]1959年开发的COBOL系统至今还在沿用[06:02]Advance/Off-Peak/Anytime三种票类[10:28]多家运营商售票及参与分成[11:28]铁路售票也”动态定价“[17:02]英国铁路的民营化历史与英国铁路的拼装系统[22:56]欧洲之星比英国国内段铁路售价更便宜[27:54]远程办公潮与火车票通胀也有关系[28:43]六大省钱策略详解[43:04]AI可以帮你买到便宜火车票吗？[48:15]中国高铁的秩序和效率令人怀念【后期制作】Jean【收听方式】推荐您使用Apple Podcast、小宇宙APP、喜马拉雅FM、汽水儿APP、荔枝播客、网易云音乐、QQ音乐、Spotify或任意泛用型播客客户端订阅收听《贝望录》。【互动方式】微博：@贝望录微信公众号：贝望录+商务合作：beiwanglu@withinlink.com

The August 2025 update highlights progress on the show's blog with new podcast recommendations, a busy month of live and After Dark sessions, and anticipation for Apple's September 9.  Chuck also shares gratitude in the monthly Support Report and encourages listener feedback. Show Notes: Chapters: [0:00] August 2025 update introduction [1:00] Recommended podcast picks on the blog [1:24] Busy August of live shows and After Dark sessions [2:32] Preview of Apple's September 9 event and live panel coverage [2:50] Updates on new projects in progress [2:50] Monthly Support Report and sponsor appreciation [4:46] Feedback invitation for show improvements [5:13] Closing remarks and holiday wishes Support:      Become a MacVoices Patron on Patreon      http://patreon.com/macvoices      Enjoy this episode? Make a one-time donation with PayPal Connect:      Web:      http://macvoices.com      Twitter:      http://www.twitter.com/chuckjoiner      http://www.twitter.com/macvoices      Mastodon:      https://mastodon.cloud/@chuckjoiner      Facebook:      http://www.facebook.com/chuck.joiner      MacVoices Page on Facebook:      http://www.facebook.com/macvoices/      MacVoices Group on Facebook:      http://www.facebook.com/groups/macvoice      LinkedIn:      https://www.linkedin.com/in/chuckjoiner/      Instagram:      https://www.instagram.com/chuckjoiner/ Subscribe:      Audio in iTunes      Video in iTunes      Subscribe manually via iTunes or any podcatcher:      Audio: http://www.macvoices.com/rss/macvoicesrss      Video: http://www.macvoices.com/rss/macvoicesvideorss

Chuck and Charlotte explore the soaring success of soccer in the U.S. through Apple's MLS deal, highlighted by Son Heung-min's arrival and his record jersey sales. They examine the blockbuster run of Apple's F1 movie, questions around Apple's MLB streaming future, and the latest Apple TV+ price hike. Wrapping up, they preview fall programming including The Morning Show and Slow Horses, underscoring TV+'s growing library and value. http://traffic.libsyn.com/maclevelten/MV25227.mp3 Show Notes: Chapters: [0:00] Soccer's rise in the U.S. and Apple's MLS deal [1:27] Son Heung-min's impact on jersey sales and subscriptions [4:12] Apple's long-term MLS investment strategy [6:42] Apple's F1 movie box office success and digital release [9:34] Reports of Apple ending its MLB deal and implications [11:15] Fragmentation of sports streaming and ESPN's role [16:03] Apple TV+ subscription price increase explained [18:48] Churn and the challenges of subscriber retention [23:37] Comparing Apple TV+ to Disney+ and HBO Max [29:06] Apple's premium strategy versus ad-supported models [32:28] Upcoming Apple TV+ releases for fall 2025 [33:56] Prime Target, Mythic Quest, and other recommendations Guests: Charlotte Henry is a media junkie, covering how Apple is not just a revolutionary tech firm, but a revolutionary media firm. She is based in London, writes and broadcasts for various outlets, and is the author of Not Buying It, an examination of fake news. You can find her on her The Addition blog, her podcast, in her The Addition newsletter on substack, and on Twitter, Facebook, Instagram and TikTok. Support:      Become a MacVoices Patron on Patreon      http://patreon.com/macvoices      Enjoy this episode? Make a one-time donation with PayPal Connect:      Web:      http://macvoices.com      Twitter:      http://www.twitter.com/chuckjoiner      http://www.twitter.com/macvoices      Mastodon:      https://mastodon.cloud/@chuckjoiner      Facebook:      http://www.facebook.com/chuck.joiner      MacVoices Page on Facebook:      http://www.facebook.com/macvoices/      MacVoices Group on Facebook:      http://www.facebook.com/groups/macvoice      LinkedIn:      https://www.linkedin.com/in/chuckjoiner/      Instagram:      https://www.instagram.com/chuckjoiner/ Subscribe:      Audio in iTunes      Video in iTunes      Subscribe manually via iTunes or any podcatcher:      Audio: http://www.macvoices.com/rss/macvoicesrss      Video: http://www.macvoices.com/rss/macvoicesvideorss

This week's episode comes live from SaaStock USA 2025. Join special guests Greg Head (Practical Founders) and Josh Turley (CEO, RTA) as they discuss the story of transforming RTA from a 1970s COBOL-based business into a thriving SaaS company with a $100M valuation. Josh shares: - Why a fanatical focus on culture and clarity fueled RTA's growth. - The challenges of replatforming legacy software (and migrating customers.) - How narrowing their niche to government fleets led to 95% retention & 120% NRR. - Lessons from bootstrapping, using debt strategically, and closing a growth equity round. Guest links: LinkedIn - https://www.linkedin.com/in/josh-turley/ Website: https://rtafleet.com/       Check out the other ways SaaStock is helping SaaS founders move their business forward: 

Adobe has opened a new door on their AI strategy, unveiling a new AI service for PDFs. Chuck Joiner, David Ginsburg, Brian Flanigan-Arthurs, Marty Jencius, Jeff Gamet, Eric Bolden, Jim Rea, Web Bixby, and Norbert Frassa weigh its usefulness against privacy risks and academic research tools. They discuss the Dia browser's pricey subscription model, compare trends in $20–$25 monthly services, and question long-term sustainability. Finally, just for fun, the panel has thoughts on a foldable phone durability test and how it compares to probable real world use.  Today's MacVoices is supported by Insta360 and their new GO Ultra, the tiny 4K camera that goes everywhere with you. Visit store.Insta360.com and use the come “MacVoices” for a free set of Sticky Tabs. Show Notes: Chapters: [0:00] Adobe's new PDF AI hub and first impressions [2:28] Enterprise-level document analysis and consumer use [5:35] Privacy concerns and proprietary data risks with Adobe [9:10] Academic research tools like Elicit compared [10:43] PDF history and standards discussion [14:06] Launch of the DIA browser and subscription costs [15:32] Comparing AI services, subscriptions, and pricing strategies [18:11] Subscription fatigue and streaming service parallels [19:40] Fun segment: foldable phone durability test [21:55] Real-world math on folding use cases[23:09] Humor and closing reflections on tech hype Links: Acrobat Studio is Adobe's new AI-powered hub for PDFs https://www.engadget.com/ai/acrobat-studio-is-adobes-new-ai-powered-hub-for-pdfs-130003264.html The Dia browser now offers a $20/month subscription plan https://9to5mac.com/2025/08/07/the-dia-browser-now-offers-a-20-month-subscription-plan/ What happens when you fold a Galaxy Z Fold 7 200,000 times? Creaking, leaking, and crashing https://www.macworld.com/article/2870354/what-happens-when-you-fold-a-galaxy-z-fold-7-200000-times-creaking-leaking-and-crashing.html Guests: Web Bixby has been in the insurance business for 40 years and has been an Apple user for longer than that.You can catch up with him on Facebook, Twitter, and LinkedIn, but prefers Bluesky. Eric Bolden is into macOS, plants, sci-fi, food, and is a rural internet supporter. You can connect with him on Twitter, by email at embolden@mac.com, on Mastodon at @eabolden@techhub.social, on his blog, Trending At Work, and as co-host on The Vision ProFiles podcast. Brian Flanigan-Arthurs is an educator with a passion for providing results-driven, innovative learning strategies for all students, but particularly those who are at-risk. He is also a tech enthusiast who has a particular affinity for Apple since he first used the Apple IIGS as a student. You can contact Brian on twitter as @brian8944. He also recently opened a Mastodon account at @brian8944@mastodon.cloud. Norbert Frassa is a technology “man about town.” Follow him on Twitter and see what he's up to. Jeff Gamet is a technology blogger, podcaster, author, and public speaker. Previously, he was The Mac Observer's Managing Editor, and the TextExpander Evangelist for Smile. He has presented at Macworld Expo, RSA Conference, several WordCamp events, along with many other conferences. You can find him on several podcasts such as The Mac Show, The Big Show, MacVoices, Mac OS Ken, This Week in iOS, and more. Jeff is easy to find on social media as @jgamet on Twitter and Instagram, jeffgamet on LinkedIn., @jgamet@mastodon.social on Mastodon, and on his YouTube Channel at YouTube.com/jgamet. David Ginsburg is the host of the weekly podcast In Touch With iOS where he discusses all things iOS, iPhone, iPad, Apple TV, Apple Watch, and related technologies. He is an IT professional supporting Mac, iOS and Windows users. Visit his YouTube channel at https://youtube.com/daveg65 and find and follow him on Twitter @daveg65 and on Mastodon at @daveg65@mastodon.cloud. Dr. Marty Jencius has been an Associate Professor of Counseling at Kent State University since 2000. He has over 120 publications in books, chapters, journal articles, and others, along with 200 podcasts related to counseling, counselor education, and faculty life. His technology interest led him to develop the counseling profession ‘firsts,' including listservs, a web-based peer-reviewed journal, The Journal of Technology in Counseling, teaching and conferencing in virtual worlds as the founder of Counselor Education in Second Life, and podcast founder/producer of CounselorAudioSource.net and ThePodTalk.net. Currently, he produces a podcast about counseling and life questions, the Circular Firing Squad, and digital video interviews with legacies capturing the history of the counseling field. This is also co-host of The Vision ProFiles podcast. Generally, Marty is chasing the newest tech trends, which explains his interest in A.I. for teaching, research, and productivity. Marty is an active presenter and past president of the NorthEast Ohio Apple Corp (NEOAC). Jim Rea built his own computer from scratch in 1975, started programming in 1977, and has been an independent Mac developer continuously since 1984. He is the founder of ProVUE Development, and the author of Panorama X, ProVUE's ultra fast RAM based database software for the macOS platform. He's been a speaker at MacTech, MacWorld Expo and other industry conferences. Follow Jim at provue.com and via @provuejim@techhub.social on Mastodon. Support:      Become a MacVoices Patron on Patreon      http://patreon.com/macvoices      Enjoy this episode? Make a one-time donation with PayPal Connect:      Web:      http://macvoices.com      Twitter:      http://www.twitter.com/chuckjoiner      http://www.twitter.com/macvoices      Mastodon:      https://mastodon.cloud/@chuckjoiner      Facebook:      http://www.facebook.com/chuck.joiner      MacVoices Page on Facebook:      http://www.facebook.com/macvoices/      MacVoices Group on Facebook:      http://www.facebook.com/groups/macvoice      LinkedIn:      https://www.linkedin.com/in/chuckjoiner/      Instagram:      https://www.instagram.com/chuckjoiner/ Subscribe:      Audio in iTunes      Video in iTunes      Subscribe manually via iTunes or any podcatcher:      Audio: http://www.macvoices.com/rss/macvoicesrss      Video: http://www.macvoices.com/rss/macvoicesvideorss

The Building Better Developers with AI podcast continues its season of revisiting past episodes with fresh insights. In this discussion, Rob Broadhead and Michael Meloche revisit the classic topic of breaking through career plateaus and reframe it through the lens of developer career growth. The original episode shared practical strategies for accelerating progress. This version adds AI-driven perspectives, personal stories, and a reminder that developers must be intentional about growth in a rapidly evolving industry. Recognizing Developer Career Growth Roadblocks Career plateaus are rarely obvious. Instead, they surface gradually through symptoms like: Completing tasks on autopilot A lack of new responsibilities or ownership Months without learning a new tool, framework, or design pattern As Rob explains, being “comfortable” often means you're falling behind. In technology, a developer's career growth demands continuous movement forward. If you haven't challenged yourself in six months, your developer career growth may already be stuck. Why Developer Career Growth Plateaus Happen Rob frames the plateau as a “gamer problem”—your XP bar fills, but the level-up screen never appears. Routine work, a lack of internal visibility, or failure to market oneself can all hinder a developer's career growth. Michael emphasizes the importance of self-reflection. Sometimes the issue isn't a lack of opportunity, but a lack of initiative. Are you doing the bare minimum, or seeking challenges that stretch you? He shares how experimenting with signature tablets and webcams—well outside his role—kept him learning and growing. That curiosity didn't move him up in that company, but it paved the way to a higher-paying role elsewhere. Expanding Beyond Code for Developer Career Growth Not all growth is about coding more. Rob points out that developer career growth also comes from: Taking on design and architecture work Mentoring and teaching others Exploring leadership or project ownership Michael reinforces the power of teaching. Sharing knowledge sharpens communication skills, broadens perspective, and strengthens problem-solving abilities. Strategies to Accelerate Developer Career Growth The episode outlines clear steps for reigniting progress: Stretch Projects – Volunteer for cross-team or challenging work. Skill Stacking – Add complementary abilities like UX, DevOps, or CI/CD. Mentorship 2.0 – Learn from mentors, but also mentor others. Visibility Boosts – Blog, present at meetups, or contribute to open source. Side Hustles – Build projects outside work to push yourself into new learning. Side projects are “cheat codes” for developer career growth. Even small shifts—such as switching IDEs or adopting new tools—can help shake off stagnation and sharpen your adaptability. AI's Role in Developer Career Growth Michael warns against ignoring AI. Some developers resist learning it, believing their existing skills will always be in demand. History shows otherwise—just as COBOL programmers saw demand collapse after Y2K, today's developers risk irrelevance by avoiding new technologies. Embracing AI isn't optional anymore. It's the new baseline for sustaining developer career growth. Episode Challenge: Take Charge of Your Developer Career Growth Your challenge this week: Identify one area where your growth has stalled, and take one intentional step forward. Options include: Learning a new framework or tool Volunteering for a stretch assignment Mentoring a junior colleague Starting a side project outside your comfort zone Don't wait for others to create opportunities. Own your developer career growth starting today. Final Thoughts Breaking through plateaus isn't about endless reinvention—it's about steady, intentional growth. Rob and Michael agree: if your current environment doesn't provide chances to grow, then create them—or find a place that will. Developer career growth is not optional. In a fast-moving industry, standing still means falling behind. Stay Connected: Join the Developreneur Community We invite you to join our community and share your coding journey with us. Whether you're a seasoned developer or just starting, there's always room to learn and grow together. Please get in touch with us at info@develpreneur.com with any questions, feedback, or suggestions for future episodes. Together, let's continue exploring the exciting world of software development. Additional Resources Essential Habits for Software Developers: Boosting Productivity and Career Growth Pivoting: How to Embrace Change and Fuel Your Professional Growth Are Technology Certifications Necessary For Career Growth? Be Intentional In Choosing Tasks For Career Growth The Developer Journey Videos – With Bonus Content Building Better Developers With AI Podcast Videos – With Bonus Content

В современном IT есть два пути к бесконечным деньгам. Один из них – быть топовым AI рисерчером и ждать, пока позвонит Цукерберг. Второй – поддерживать код на COBOL, от которого зависит вся мировая банковская система. В этом классическом языковом выпуске вместе с Сергеем Куксом, principal инженером из JetBrains, разбираемся с тем, что когда-то помогло COBOL стать таким популярным, и как он продолжает развиваться по сегодняшний день. Также ждем вас, ваши лайки, репосты и комменты в мессенджерах и соцсетях!
 Telegram-чат: https://t.me/podlodka Telegram-канал: https://t.me/podlodkanews Страница в Facebook: www.facebook.com/podlodkacast/ Twitter-аккаунт: https://twitter.com/PodcastPodlodka Ведущие в выпуске: Катя Петрова, Егор Толстой Полезные ссылки: Документация COBOL для новичков https://www.microfocus.com/documentation/visual-cobol/vc80/EclWin/index.html?t=GUID-7D9BBE92-0AD8-4DDC-975A-FA92A55D7187.html Про Micro Focus https://www.opentext.com/about/brands/microfocus Как работает фича ReportWriter https://www.microfocus.com/documentation/visual-cobol/vc80/VS2022/index.html?t=HRLHLHWRI01.html Awesome COBOL https://github.com/loveOSS/awesome-cobol

Banking executives face a familiar dilemma: decades-old core systems technically constrain innovation while replacement costs can reach hundreds of millions of dollars and take years to implement. Meanwhile, fintechs launch new products in weeks while traditional banks remain trapped in months-long approval cycles. The challenge extends beyond technology. "Most banks duct-tape capabilities onto what they already have, and eventually they break," explains Ritesh Rihani, Vice President of Enterprise Banking at Galileo. "You've seen the number of outages we've had in the industry recently. That's all happening because they put duct tape upon duct tape." The pressure to modernize comes from multiple directions. Customer expectations have evolved toward integrated experiences and ease of use and operational risks multiply as the pool of COBOL programmers shrinks through retirement. Regulatory compliance becomes increasingly difficult with manual processes and fragmented systems. This podcast explores five critical dimensions of core modernization: balancing costs with competitive necessity, understanding operational and regulatory risks, implementing incremental transformation strategies, enabling product innovation, and unlocking the future potential of modern banking architecture.

My guest today is S Parthasarathy, better known as Spart who is the founder at CuedIn Technologies.In this episode, Spart shares his extensive journey in the software engineering field. Spart's story begins with his initial projects in COBOL programming at Tata Burroughs and the World Bank, working on critical systems in retail, logistics, and financial sectors. He recounts his impactful stint at SWIFT, contributing to the foundation of what has become modern-day financial messaging systems. Spart reflects on his decision to pivot from electrical engineering to computer science, driven by his interest in the engineering of large systems. He details his tenure at Ramco Systems, implementing document-based transactions, model-based code generation, and achieving several tech milestones, including internet integration and 32-bit upgrades. After Ramco, Spart's continued passion for software engineering led him to co-found a SaaS-based ERP solution company, targeting SMEs. Despite early challenges and market readiness issues, he gained crucial insights into cloud-native architectures.Spart's career path took another turn towards consulting and exploring AI, specifically focusing on probabilistic graph learning and the challenges of natural language processing in software engineering. He emphasizes the importance of non-functional requirements, application architecture, and the potential of tools like Generative AI (GenAI) to enhance software development processes. Spart concludes by reflecting on the ongoing evolution of software engineering and his current projects aimed at making software engineering more accessible and efficient with modern tools.Spart has 40+ years of experience in various aspects of software services area covering consultancy, business systems management, product development and Engineering management. Worked with large North American Organizations handling complex projects to implement transaction processing business solutions and data communication networks. Key interests: • Gen AI based solutioning for key business activities • Gen AI enabled SW engineering • Contextual social network driven approach for building business systems • Predictive analytics over operational databases using Bayesian causal networks • Implementing innovative platform based techno-commercial models for software solutions/services delivery. • Cloud computing and SOA based multi-tenant solution Architecturehttps://www.linkedin.com/in/spartp/

En el episodio 100 del podcast de Entre Dev y Ops hablaremos sobre cómo hemos vivido estos 100 episodios. Blog Entre Dev y Ops - https://www.entredevyops.es Telegram Entre Dev y Ops - https://t.me/entredevyops Twitter Entre Dev y Ops - https://twitter.com/entredevyops LinkedIn Entre Dev y Ops - https://www.linkedin.com/company/entredevyops/ Patreon Entre Dev y Ops - https://www.patreon.com/edyo Amazon Entre Dev y Ops - https://amzn.to/2HrlmRw Enlaces comentados: Entrevista a Juan Carlos Sánchez sobre programación de videojuegos en los 80 - https://www.entredevyops.es/podcasts/podcast-94.html Entrevista a David Poblador i Garcia - https://www.entredevyops.es/podcasts/podcast-episodio-6.html Episodio con Federico Mena - https://www.entredevyops.es/podcasts/podcast-72.html Episodio sobre Rust con Alberto Ruiz - https://www.entredevyops.es/podcasts/podcast-67.html Episodio con Ferran Grau sobre FinOps - https://www.entredevyops.es/podcasts/podcast-85.html Episodio sobre Krakend - https://www.entredevyops.es/podcasts/podcast-62.html Episodio sobre Cobol - https://www.entredevyops.es/podcasts/podcast-58.html Episodio en la FOSDEM 2020 - https://www.entredevyops.es/podcasts/podcast-51.html Colaboración de bureado - https://www.entredevyops.es/podcasts/podcast-colaboracion-1.html Entrevista con José Miguel Parella (bureado) - https://www.entredevyops.es/podcasts/podcast-56.html Episodio con Dani sobre Blockchain - https://www.entredevyops.es/podcasts/podcast-34.html Episodio sobre la tecnología detrás del CERN - https://www.entredevyops.es/podcasts/podcast-31.html Repositorio de nuestra herramienta de publicación, appu - https://github.com/EDyO/appu Microkernels con Sergio López - https://www.entredevyops.es/podcasts/podcast-59.html Confidential Computing con Sergio López - https://www.entredevyops.es/podcasts/podcast-65.html Pánico en el núcleo (lista de episodios) - https://ia601204.us.archive.org/29/items/PanicoEnElNucleo/Formato%20OGG-Vorbis/  Primer podcast en castellano - https://comunicandopodcast.es/  Emilcar daily - https://emilcar.fm/podcast/emilcardaily/  Jornadas de podcasting - https://jpod.es/

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Breaking Through Requirements Hell: How AI is Revolutionizing Software Development

What if your most critical systems run on code that no one fully understands?In this episode, Omer Rosenbaum, CTO and co-founder of Swimm, explains how to use AI to close the knowledge gap in your legacy codebase. Discover the limitations of AI in understanding legacy code and learn novel approaches to automatically document complex systems, ensuring their critical business logic is preserved and understood within the organization. Beyond legacy systems, Omer also shares practical advice for how junior developers can thrive in the AI era and how teams and organizations can conduct more effective research.Key topics discussed:How junior developers can thrive in the age of AIThe danger of shipping code you don't fully understandWhy AI can't deduce everything from your code aloneHow writing documentation becomes more critical now with AIHow to analyze code that even LLMs struggle to read, like COBOLHow to keep your organization's knowledge base trustworthy and up to dateThe real danger of letting AI agents run uncheckedA practical approach to conducting more effective research  Timestamps:(00:00) Trailer & Intro(02:10) Career Turning Points(05:24) What Juniors Should Do in the Age of AI(11:05) Junior Developer's Responsbility When Using AI(14:50) AI and Critical Thinking(16:20) Understanding & Preserving Domain Knowledge(18:11) The Importance of Written Knowledge for AI Usage(21:51) Limitations of AI in Understanding Knowledge Base(26:34) The Limitations of LLM in Navigating Legacy Codebases (e.g. COBOL)(32:38) Effective Knowledge Sharing Culture in the Age of AI(34:54) Keeping Knowledge Base Up-to-Date(36:55) Keeping the Organization Knowledge Base Accurate(39:08) Fact Checking and Preventing AI Hallucination(41:24) The Potential of MCP(43:24) The Danger of AI Agents Hallucinating with Each Other(45:00) How to Get Better at Research(53:41) The Importance of Investing in Research(57:18) 3 Tech Lead Wisdom_____Omer Rosenbaum's BioOmer Rosenbaum is the CTO and co-founder of Swimm, a platform reinventing the way engineering organizations manage internal knowledge about their code base. Omer founded the Check Point Security Academy and was the Cyber Security Lead at ITC, an educational organization that trains talented professionals to develop careers in technology. Omer has a MA in Linguistics from Tel Aviv University and is the creator behind the Brief YouTube Channel.Follow Omer:LinkedIn – linkedin.com/in/omer-rosenbaum-034a08b9Twitter – x.com/Omer_RosSwimm – swimm.ioEmail – omer@swimm.io

Connect to John Gilroy on LinkedIn   https://www.linkedin.com/in/john-gilroy/ Want to listen to other episodes? www.Federaltechpodcast.com Many of today's archaic federal systems have been built over decades. As a result, they are perfected but also fragile. One obvious source of vulnerability is the workforce that created it. It is hard to believe that COBOL was released in 1960 and is still active in some federal systems. The individuals who developed the code for these systems are now long past retirement age. Some code was accurately documented, and some were not. As a result, the process of transferring to a newer environment is fraught with concern. Until AI, the only way to understand the underlying code was for a human being to review it line by line. Everyone realized that this process was so tedious and time-consuming that an informal policy emerged, essentially patching the system. They kicked the can down the road for the next generation. Well, AI is her. It has the unique ability to review code, identify problems, and provide solutions quickly. This will drastically reduce the risk of moving antiquated systems from aging code systems. Today, we sat down with Kartik Mecheri from Karsun Solutions and Alan Thomas, former Commissioner of GSA FAS. During the interview, they offered suggestions on how best to accomplish the challenging task of digital modernization. Kartik emphasizes the value of a platform like ReDuX. Utilizing Amazon's Bedrock, ReDuX allows system developers to create a blueprint for the existing system. When combined with humans, this platform will save money on maintaining older systems and bring much-needed flexibility to new applications. Listen to learn how Karsun Solutions can reduce costs, increase flexibility, and improve efficiency in the process of digital modernization. The conversation also touched on the challenges of mission-critical systems, the role of AI in reducing risk, and the evolving job market, suggesting a shift towards strategic and innovative roles.

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Think your project's on fire?

 Santi: Hi, this is a special episode of Statecraft. I've got a wonderful guest host with me today. Kyla Scanlon: Hey, I'm Kyla Scanlon! I'm the author of a book called In This Economy and an economic commentator. Santi: Kyla has joined me today for a couple reasons. One, I'm a big fan of her newsletter: it's about economics, among many other things. She had a great piece recently on what we can learn from C.S. Lewis's The Screwtape Letters, which is a favorite book of mine.Kyla's also on today because we're interviewing Wally Adeyemo, who was the Deputy Secretary of the Treasury in the Biden administration. We figured we each had questions we wanted answered.Kyla: Yeah, I've had the opportunity to interview Wally a couple times during the Biden administration, and I wanted to see where he thinks things are at now. He played a key role in implementing the Inflation Reduction Act, financial sanctions on Russia, and a whole bunch of other things.Santi: For my part, I'm stuck on Wally's role in setting up the IRS's Direct File program, where you can file your taxes for free directly through the IRS instead of paying TurboTax a hundred bucks to do it. “Good governance types” tend to love Direct File, but the current admin is thinking of killing it. I wanted to understand how the program got rolled out, how Wally would respond to criticisms of the program, and what he learned from building something in government, which now may disappear.Kyla, you've talked to Wally before. How did that conversation go? Kyla: I actually was able to go to his office in D.C., and I talked to a couple of key people in the Biden administration: Jared Bernstein, the former chair of the CEA, and Daniel Hornung, who was at the National Economic Council.We're talking to Wally on the day that the House passed the one big beautiful bill. There's also so much happening financially, like the bond market is totally rebelling against the US government right now. I'm really curious how he thinks things are, as a key player in the last administration.Santi: Wally, you've spent most of your career in Democratic Party institutions. You worked on the Kerry presidential campaign in 2004. You served in the Obama admin. You were the first chief of staff to the CFPB, the president of the Obama Foundation, and, most recently, Deputy Treasury Secretary in the Biden admin.30,000ft question: How do you see the Democratic Party today?My view is that we continue to be the party that cares deeply about working-class people, but we haven't done a good job of communicating that to people, especially when it comes to the things that matter most to them. From my standpoint, it's costs: things in America cost too much for a working-class family.I want to make sure I define working class: I think about people who make under $100,000 a year, many of whom don't own homes on the coast or don't own a significant amount of stocks (which means they haven't seen the asset appreciation that's led to a great deal of wealth creation over the last several decades). When you define it that way, 81% of Americans sit in that category of people. Despite the fact that they've seen their median incomes rise 5-10% over the last five years, they've seen the cost of the things they care about rise even faster.We haven't had a clear-cut agenda focused on the standard of living, which I think is the thing that matters most to Americans today.Santi: There are folks who would say the problem for Democrats wasn't that they couldn't communicate clearly, or that they didn't have a governing agenda, but that they couldn't execute their agenda the way they hoped to in the time available to them. Would you say there's truth to that claim?Most people talk about a communications issue, but I don't think it's a communications issue. There are two issues. One is an implementation issue, and the second is an issue of the actual substance and policy at the Treasury Department. I was the deputy secretary, but I was also the Chief Operating Officer, which meant that I was in charge of execution. The two most significant domestic things I had to execute were the American Rescue Plan, where $1.9 trillion flowed through the Treasury Department, and the Inflation Reduction Act. The challenge with execution in the government is that we don't spend a lot on our systems, on making execution as easy as possible.For example, the Advanced Child Tax Credit was intended to give people money to help with each of their children during the pandemic. What Congress called on us to do was to pay people on a monthly basis. In the IRS system, you pay your taxes mostly on an annual basis, which meant that most of our systems weren't set up to pay a monthly check to Americans. It took us a great deal of work to figure out a way to recreate a system just to do that.We've underinvested in the systems that the IRS works on. The last time we made a significant investment in the IRS's digital infrastructure was the 1960s; before we had an ATM machine, before we sent a man to the moon, before we had a personal computer. So that meant that everything was coded in a language called COBOL.So execution was quite hard in the American Rescue Plan. People were left out and felt that the government wasn't working for them. If you called the IRS, only 13% of your calls were being answered. We got that back up to 85% before we left. Ultimately, I think part of this is an execution challenge. In government we want to spend money coming up with new policies, but we don't want to pay for execution, which then means that when you get the policy passed, implementation isn't great.When Jen Pahlka was on your show, she talked about the need to focus on identifying the enablers to implementation. Direct File was one of the best examples of us taking implementation very seriously.But also, on some policy issues that mattered most to Americans, we weren't advancing the types of strategies that would've helped lower the cost of housing and lowering the cost of medicine. We did some things there, but there's clearly more that we could have done, and more we need to do going forward to demonstrate that we're fighting to bring down those costs. It's everything from permitting reform — not just at the federal level, but what can we do to incentivize it at the state and local level — to thinking about what we can do on drug costs. Why does it cost so much more to get a medicine in America than in Canada? That is something that we can solve. We've just chosen not to at the federal level.At the end of the year, we were going to take action to go after some of the middlemen in the pharmacy industry who were taking out rents and large amounts of money. It dropped out of the bill because of the negotiations between the Republican Congress and then President-elect Trump. But there are a lot of things that we can do both on implementation, which will mean that Americans feel the programs that we're passing in a more effective way, and policy solutions that we need to advance as a party that will help us as well.Kyla: Some people think Americans tend to vote against their own self-interest. How can your party message to people that these sorts of policies are really important for them?Ultimately, what I found is that most people just understand their self-interest differently, and for them, a big part of this was, “Who's fighting for me on the issues that I care most about?”From my standpoint, part of the problem we had with Direct File, which I think was an innovative solution, was that we got to implementing it so late in the administration that we didn't have the ability for it to show the impact. I'm hoping future administrations will think through how to start their implementation journey on things like Direct File sooner in the administration, when you have a great deal of political capital, so people can actually feel the impact over time.To your question, it's not just about the messaging, it's about the messenger. People tend to trust people who look like them, who come from the places they come from. When it came to the Child Tax Credit and also to Direct File, the biggest innovation wasn't the technology: the technology for Direct File has been used by the Australians, the British, and other countries for decades.The biggest innovation was us joining that technology with trusted people in communities who were going out to talk to people about those programs and building those relationships. That was something that the IRS hadn't done a great deal of. We invested a great deal in those community navigators who were helping us get people to trust the things the government was doing again, like the Child Tax Credit, like Direct File, so that they could use it.We often think that Washington is going to be able to give messages to the country that people are going to hear. But we're both in a more complicated media environment, where people are far more skeptical of things that come from people in Washington. So the best people to advocate for and celebrate the things that we're doing are people who are closer to the communities we're trying to reach. In product advertising today, more companies are looking to influencers to advertise things, rather than putting an ad on television, because people trust the people that they follow. The same is true for the things that we do in government.Santi: I've talked to colleagues of yours in the last administration who say things like, “In the White House, we did not have a good enough sense of the shot clock.” They point to various reasons, including COVID, as a reason the admin didn't do a good enough job of prioritization.Do you think that's true, that across the administration, there was a missing sense of the shot clock or a missing sense of prioritization? No, because I'm a Lakers fan. These are professionals. We're professionals. This is not our first rodeo. We know how much time is on the shot clock; we played this game. The challenge wasn't just COVID. For me at Treasury — and I think this is the coolest part of being Deputy Secretary of the Treasury — I had responsibilities domestic and international. As I'm trying to modernize the IRS, to invest all my time in making the system work better for customers and to collect more taxes from the people who owe money, Russia invades Ukraine. I had to turn a bunch of my attention to thinking about what we were going to do there. Then you have Hamas attacking Israel.There was more we should have done on the domestic end, but we have to remember that part of the presidency is: you get to do the things you want to do, but you also have to do the things you have to do. We had a lot of things we had to do that we weren't planning for which required all-of-the-administration responses.I think the most important lesson I've learned about that is that it comes down to both being focused on the things that matter, and being willing to communicate to the American people why your priorities have to change in light of things that happen in the world.But the people I'm sure you've talked to, most of them work on domestic policy alone, and they probably never have been in a National Security Council meeting, where you're thinking about the risks to the country. The president has to do both of those things. So I get how difficult it is to do that, just given where I sat at the Treasury Department.Santi: Looking back from an implementation perspective, are there things you would've done differently during your time at Treasury?The most important thing that I would've done differently was to immediately set up a permanent implementation and delivery unit in the Treasury Department. We always like to pretend like the Treasury Department is just a policy department where we make policy, we collect taxes. But in any crisis the country ever has, a great deal of responsibility — for execution or implementation of whatever the response is — falls to the Treasury Department. Think about the financial crisis, which is clearly something that's in the Treasury's domain. The vast majority of money for COVID flowed through the Treasury Department. You think about the IRA, a climate bill: the vast majority of that money flows through the Treasury Department.And Treasury doesn't have a dedicated staff that's just focused on implementation: How do we do this well? How do we make sure the right people are served? How do we make sure that we communicate this well? We did this to a degree by a team that was focused on the American Rescue Plan. But it was only focused on the American Rescue Plan. If I could start again, I would have said, “I want a permanent implementation structure within the Treasury Department of people who are cross-cutting, who only think about how we execute the policies that we pass through Congress and that we put together through an executive order. How do we do that extremely well?”Kyla: What you're talking about is very people-centric: How do we get an implementation team, and how do we make sure that the right people are doing the right jobs? Now we have DOGE, which is less people-centric. How do you reconcile what Doge is doing relative to what you would've done differently in this role that you had?As you would suspect, I wasn't excited about the fact we had lost the election, but initially I thought DOGE could be helpful with technology. I think marrying technology with people — that's the key to success for the government. We've never really been great at doing technology in the government.Part of the reason for that is a procurement process that is very slow because of how the federal acquisition rules work. What we are trying to do is prevent corruption and also waste, fraud, and abuse. But what that does is, it leads to slowness in our ability to get the technology on board that we need, and in getting the right people.I was hoping DOGE would bring in people who knew a great deal about technology and put us in a position where we could use that to build better products for the American people. I thought they would love Direct File, and that they would find ways to improve Direct File and expand it to more Americans.My view is that any American in the working class or middle class should not have to pay a company to file their taxes. We have the ability in this country, and I think Direct File was proving that. My goal, if we'd had more time, was to expand this to almost any American being able to use it. I thought they'd be able to accelerate that by bringing in the right people, but also the right technology. We were on that path before they took those two things apart.My sense is that you have to reform the way that we hire people because it's too hard to hire the right people. In some cases, you don't need some of the people you have today because technology is going to require different skills to do different things. It's easier to break something, I found, than it is to build something. I think that's what they're finding today as well.Santi: When I talk to left-of-center folks about the DOGE push, they tend to be skeptical about the idea that AI or modern technology can replace existing federal workers. I think some of that is a natural backlash to the extreme partisan coding of DOGE, and the fact that they're firing a lot of people very quickly. But what's your view? After DOGE, what kinds of roles would you like to see automated?Let me say: I disagree with the view that DOGE and technology can't replace some of the things that federal workers do today. My view is that “productivity enhancing” tech — it's not that it is going to make employees who are currently doing the job more productive. It is going to mean you need fewer employees. We have to be honest about that.Go to the IRS, for example. When I got there, we had a huge paper backlog at the IRS because, despite what most people think, millions of people still file their taxes by paper, and they send them to the IRS. And during the pandemic, the commissioner, who was then working for President Trump, decided to shut down the IRS for public health reasons — to make sure employees did not have to risk getting COVID.There were piles of paper backing up, so much so that they had filled cafeterias at the IRS facilities with huge piles of paper. The problem, of course, is that, unlike modern systems, you could not just machine-read those papers and put them into our systems. Much of that required humans to code those papers into the system by hand. There is no need in the 21st century for that to happen, so one of the things that we started to do was introduce this simple thing called scanning, where you would scan the papers — I know it sounds like a novel idea. That would help you get people's tax returns faster into the system, but also get checks out quickly, and allow us to see if people are underpaying their taxes, because we can use that data with a modern system. But over time, what would that mean? We'd need fewer people to enter the data from those forms.When we get money for the IRS from Congress, it is actually seen as revenue-raising because they expect it to bring down the debt and deficit, which is completely true. But the model Congress uses to do that is reliant on the number of full-time employees we hire. One challenge we have with the IRS — and in government systems in general — is that you don't get credit for technology investments that should improve your return on investment.So whenever we did the ROI calculations for the IRS, the Congressional Budget Office would calculate how much revenue we'd bring in, and it was always based on the number of people you had doing enforcement work that would lead to certain dollars coming in. So we got no credit for the technology investments. Which was absolutely the opposite of what we knew would be true: the more you invested in technology, the more likely you were to bring in more revenue, and you would be able to cut the cost of employees.Santi: If the CBO changed the way it scored technology improvements, would more Congresspeople be interested in funding technology?It is just a CBO issue. It's one we've tried to talk to them about over the last several years, but one where they've been unwilling to move. My view is that unlocking this will unlock greater investment in technology in a place like the IRS, because every dollar you invest in technology — I think — would earn back $10 in additional tax revenue we'd be able to collect from people who are skipping out on their taxes today. It's far more valuable to invest in that technology than to grow the number of employees working in enforcement at the IRS. You need both, but you can't say that a person is worth 5x their salary in revenue and that technology is worth 0. That makes no sense.Kyla: When we spoke about Direct File many months ago, people in my comment section were super excited and saying things like, “I just want the government to tell me how much money I owe.” When you think about the implementation of Direct File, what went right, and how do you think it has evolved?The thing that went right was that we proved that we could build something quite easily, and we built it ourselves, unlike many technology projects in government. We didn't go out and hire a bunch of consultants and contractors to do it. We did it with people at the IRS, but also with people from 18F and from GSA who worked in the government. We did it in partnership with a number of stakeholders outside the government who gave us advice, but the build was done by us.The reason that was important — and the reason it's important to build more things internally rather than hiring consulting firms or other people to build it — is that you then have the intellectual capital from building that, and that can be used to build other things. This was one product, but my view is that I want the IRS home page to one day look a lot more like the screen on your iPhone, so that you can click on the app on the IRS homepage that can help you, depending on what you need — if it's a Direct File, or if it's a tax transcript.By building Direct File internally, we were getting closer to that, and the user scores on the effectiveness of the tool and the ability to use it were through the roof. Even for a private sector company, it would've been seen as a great success. In the first year, we launched late in the filing season, mostly just to test the product, but also to build stakeholder support for it. In the limited release, 140,000 people used it. The average user said that before Direct File, it took them about 13 hours to file their taxes, and with Direct File, it took them just over an hour to file their taxes.But you also have to think about how much money the average American spends filing their taxes: about $200. That's $200 that a family making under $100,000 could invest in their kids, in paying some bills, rather than in filing their taxes.Even this year, with no advertising by the Trump administration of Direct File, we had more than 300,000 people use it. The user scores for the product were above 85%. The challenge, of course, is that instead of DOGE investing in improving the product — which was a place where you could have seen real intellectual capital go to work and make something that works for all Americans — they've decided to discontinue Direct File. [NB: There has been widespread reporting that the administration plans to discontinue Direct File. The GOP tax bill passed by the House would end Direct File if it becomes law. At the time of publication, the Direct File has not been discontinued.]The sad part is that when you think about where we are as a country, this is a tool that could both save people money, save people time, improve our ability to collect taxes, and is something that exists in almost every other developed economy. It makes no sense to me why you would end something like this rather than continue to develop it.Santi: People remember the failure of healthcare.gov, which crashed when it was rolled out all at once to everyone in the country. It was an embarrassing episode for the Obama administration, and political actors in that administration learned they had to pilot things and roll them out in phases.Is there a tension between that instinct — to test things slowly, to roll them out to a select group of users, and then to add users in following cycles — Is there a tension between that and trying to implement quickly, so that people see the benefit of the work you're doing?One of my bosses in the Obama administration was Jeff Zients, the person who was brought in to fix healthcare.gov. He relentlessly focused on execution. He always made the point that it's easy to come up with a strategy to some degree: you can figure out what the policy solution is. But the difference between good and great is how you execute against it. I think there is some tension there, but not as much as you would think.Once we were able to show that the pilot was a success, I got invited to states all over the country, like Maryland, to announce that they were joining Direct File the next year. These members of Congress wanted to do Direct File events telling people in their state, “This product that's worked so well elsewhere is coming to us next.” It gave us the ability to celebrate the success.I learned the lesson not just from Zients, but also from then-professor Elizabeth Warren, whom I worked for as chief of staff at the CFPB. One challenge we had at the CFPB was to build a complaint hotline, at that point mostly phone-operated, for people who were suffering. They said it would take us at least a year to build out all the product functions we need. We decided to take a modular approach and say, “How long would it take for us to build the system for one product? Let's try that and see how that works. We'll do a test.”It was successful, and we were able to use that to tell the story about the CFPB and what it would do, not just for mortgages, but for all these other products. We built user interest in the complaint hotline, in a way that we couldn't have if we'd waited to build the whole thing at once. While I think you're right that there is some tension between getting everyone to feel it right away and piloting; if the pilot is successful, it also gives you the opportunity to go out and sell this thing to people and say, “Here's what people who did the pilot are saying about this product.”I remember someone in Texas who was willing to do a direct-to-camera and talk about the ways that Direct File was so easy for them to use. It gets back to my point on message and messenger. Deputy Secretary Adeyemo telling you about this great thing the government did is one thing. But an American who looks like you, who's a nurse, who's a mom of two kids, telling you that this product actually worked for her: That's something that more people identify with.Healthcare.gov taught us the lesson of piloting and doing things in a modular way. This is what companies have been doing for decades. If it's worked for them, I think it can work for the government too.Santi: I'm a fan of Direct File, personally. I don't want this administration to kill it. But I was looking through some of the criticism that Direct File got: for instance, there's criticism about it rivaling the IRS Free File program, which is another IRS program that partners with nonprofits to help some folks file their taxes for free.Then there's this broader philosophical criticism: “I don't want the feds telling me how much I owe them.” The idea is that the government is incentivized to squeeze every last dollar out of you.I'm curious what you make of that, in part because I spoke recently to an American who worked on building e-government systems for Estonia. One of the things that has allowed Estonia to build cutting-edge digital systems in the government is that Estonia is a small and very high-trust society. Everybody's one degree of separation from everybody else.We're a much bigger and more diverse country. How do you think that affects the federal government's ability to build tools like Direct File?I think it affects it a lot, and it gets back to my point: not just the message but the messenger. I saw this not just with Direct File, but with the Advanced Child Tax Credit, which was intended to help kids who were living in poverty, but also families overall. What we found initially in the data was that, among families that didn't have to file taxes because they made too little, many of them were unwilling to take advantage of Direct File and the Advanced Child Tax Credit because they couldn't believe the government was doing something to just help them. I spent a lot of time with priests, pastors, and other community leaders in many of the communities where people were under-filing to try and get them to talk about this program and why it was something that they should apply for.One of the challenges we suffer from right now in America, overall, is a lack of trust in institutions. You have to really go local and try to rebuild that trust.That also speaks to taking a pilot approach that goes slower in some cases. Some of the criticism we got was, “Why don't you just fill out this form for us and then just send it to us, so that Direct File is just me pressing a button so I can pay my taxes?”Part of the challenge for us in doing that is a technology challenge: we are not there technologically. But the other problem is a trust problem. If I were to just fill out your taxes for you and send them to you, I think people, at this stage, would distrust the government and distrust the technology.Direct File had to be on a journey with people, showing people, “If I put in this information, it accurately sends me back my check.” As people develop more trust, we can also add more features to it that I think people will trust. But the key has to be: how do you earn that trust over time?We can't expect that if we put out a product that looks like something the Estonian government or Australia would put out, that people would trust it at this point. We have to realize that we are on a journey to regain the trust of the American people.The government can and will work for them, and Direct File was a part of that. We started to demonstrate that with that product because the people who used it in these communities became the spokespeople for it in a better way than I ever could be, than the Secretary or the President could be.Everyone knows that they need to pay their taxes because it's part of their responsibility living in this country. The things that make people the most upset is the fact that there are people who don't pay their taxes. We committed that we were going to go after them.The second frustration was: “Why do you make it so hard for me to pay my taxes? Why can't I get through to you on the phone line? Why do I have to pay somebody else to do my taxes?” Our goal was to solve those two problems by investing money and going after the people who just decided they weren't going to pay, but also by making it as easy as possible for you to pay your taxes and for most people, to get that tax refund as quickly as possible.But doing that was about going on a journey with people, about regaining their trust in an institution that mattered to them a great deal because 90 something-percent of the money that funds our government comes in through the IRS.Kyla: You have a piece out in Foreign Affairs called “Make Moscow Pay,” and what I found most interesting about that essay is that you said Europe needs to step it up because the United States won't. Talk through the role of Treasury in financial sanctions, and your reasons for writing this piece.People often think about the Treasury Department as doing a few things. One is working with Wall Street; another one is collecting your taxes. Most people don't think about the fact that the Treasury Department is a major part of the National Security Committee, because we have these tools called financial sections.They use the power of the dollar to try and change the behavior of foreign actors who are taking steps that aren't consistent with our national security interests. A great example of this is what we did with regard to Russia — saying that we're going to cut off Russian banks from the US financial system, which means that you can't transact in US dollars.The problem for any bank that can transact in dollars is that the backbone of most of the financial world is built on the US dollar. It increases their cost, it makes it more difficult for them to transact, and makes it harder for them to be part of the global economy, nearly impossible.And that's what we've done in lots of cases when it comes to Russia. We have financial sanction programs that touch all over the world, from Venezuela to Afghanistan. The US government, since 9/11, has used sanctions as one of its primary tools of impacting foreign policy. Some of them have gone well, some of them I think haven't gone as well, and there's a need for us to think through how we use those policies.Santi: What makes sanctions an effective tool? Positions on sanctions don't line up neatly on partisan lines. Sanctions have a mixed track record, and you'll have Republicans who say sanctions have failed, and you'll have Democrats say sanctions have been an effective tool, and vice versa.The way I think about sanctions is that they are intended to bring change, and the only way that they work is that they're part of an overarching foreign policy strategy. That type of behavior change was what we saw when Iran came to the table and wanted to negotiate a way to reduce sanctions in exchange for limits on their nuclear program. That's the type of behavior change we're trying to accomplish with sanctions, but you can't do it with sanctions alone. You need a foreign policy strategy. We didn't do it by the United States confronting Iran; we got our allies and partners to work together with us. When I came into office in 2021, Secretary Yellen asked me to do a review of our sanctions policies — what's worked, what hasn't — because it had been 20 years since the 9/11 attacks.And the most important lesson I learned was that the sanctions programs that were the most effective were the ones we did on a multilateral basis — so we did it with our friends and allies. Part of the reason for this is that while the dollar is the most dominant currency around the world, oftentimes if you can't do something in dollars, you do it in a euro, or you do it in a Japanese yen, or pound sterling.The benefit of having allies all over the world is that the dominant, convertible currencies in the world are controlled by allies and partners. When we acted together with them, we were more effective in curtailing the economic activity of our adversary, and our pressure is more likely to lead to them changing their behavior.We had to be very cautious about collateral damage. You might be targeting an individual, but by targeting that individual, you might make it harder for a company they're affiliated with to continue doing business, or for a country that they're in to get access to banking services. Let's say that you're a huge bank in America, and you're worried about sanctions risk in a small country where you do little business. Why not pull out, rather than having to put in place a huge compliance program? One of the challenges that we have is that the people who make the decisions about whether to extend sanctions don't necessarily spend a lot of time thinking about some of these economic consequences of the sanctions approach.Whenever I was around the table and we were making a decision about using weapons, there was a process that was very elaborate that ended up with something going to the president. You'd often think about kinetic force very seriously, because you were going to have to get the president to make a decision. We didn't always take that kind of rigor when it came to thinking about using our sanctions policy, but the impact on the lives of people in these countries was just as significant for their access to not only money, but to food and to the resources they needed to live.Santi: What do you make of the effectiveness of the initial sanctions on Russia after the invasion of Ukraine? I've heard mixed reviews from folks inside and outside the Biden administration.Sanctions, again, to my point, are only a tool. They've had to be part of a larger strategy, and I think those sanctions were quite effective. I think the saving grace for the Russians has been the fact that China has largely been able and willing to give them access to the things they need to continue to perpetuate.There was a choice for Ukraine, but when you think about Russia's economy today vs. Russia's economy before the sanctions were put in place, it's vastly different. Inflation in Russia still runs far higher than inflation anywhere else in the world. If you were a Russian citizen, you would feel the impacts of sanctions.The challenge, of course, is that it hasn't changed Vladimir Putin's behavior or the behavior of the Kremlin, largely because they've had access to the goods and supplies they need from China, Iran, and North Korea. But over time, it means Russia's economy is becoming less competitive. They have less access to resources; they're going to struggle.I think everyone hoped that sanctions would immediately change the calculus of the Kremlin, but we've never seen that to be the case. When sanctions are effective, they take time, because the economic consequences continue to compound over time, and they have to be part of a larger strategy for the behavior of the individual. That's why I wrote the article, because while the Kremlin and Russia are under pressure, their view is that ultimately the West is going to get tired of supporting Ukraine, financially and politically, because the economic consequences for us — while not as significant as for Moscow or for Kiev — have been quite significant, when you think about the cost of living issues in Europe.I think it's important to write this now, when it appears that Russia is stalling on negotiations, because ultimately, US financial support is waning. We just know that the Trump administration is not willing to put more money into Ukraine, so Europe is going to have to do more, at a time when their economic situation is quite complicated as well.They've got a lot to do to build up their economy and their military-industrial base. Asking them to also increase their support for Ukraine at the same time is going to be quite difficult. So using this money that Russia owes to Ukraine — because they owe them compensation at this moment — can be quite influential in helping support the Ukrainians, but also changing Russia's calculus with regard to the ability of Ukraine to sustain itself.Kyla: On CNBC about a month ago, you said if we ever have a recession over the next couple of months or so, it would be a self-inflicted one. Do you still resonate with that idea? To build on the point I was making, the economy has done quite well over the course of the first few months of the year, largely because of the strength of the consumer, where our balance sheets are still quite strong. Companies in America have done well. The biggest headwind the US economy faces has been self-inflicted by the tariffs the president has put on. Part of what I still do is talk to CEOs of companies, big and small. Small businesses feel the impact of this even more than the big businesses. What they tell me is that it's not just the tariffs and the fact that they are making it more expensive for them to get the goods that they need, but it's the uncertainty created by the off-again, on-again, nature of those tariffs that makes it impossible for them to plan for what supplies they're going to get the next quarter. How are they going to fulfill their orders? What employees are they going to need? It's having a real impact on the performance of these companies, but also their ability to hire people and plan for the future.If you go to the grocery store, you're going to start seeing — and you're starting to see already — price increases. The thing that Americans care most about is, the cost of living is just too high. You're at the grocery store, as you're shopping for your kids for the summer, you're going to see costs go up because of a self-imposed tax we've put in place. So I still do think that if we do find ourselves in a recession, it's going to be because of the tariffs we've put in place.Even if we don't enter a technical recession, what we're seeing now is that those tariffs are going to raise the cost for people when they go out to buy things. It's going to raise the cost of building homes, which is going to make it harder for people to get houses, which is ultimately going to have an impact on the economy that isn't what I think the president or anyone wants at this point.Kyla: Is there anything else we haven't asked about? I think the place where we continue, as a country, to struggle is that, given the federal system we have, many of these problems aren't just in Washington — they're in state and local governments as well. When you think about the challenges to building more housing in this country, you can't just solve it by doing things at the federal level. You have to get state and local governments unified in taking a proactive approach. Part of this has to be not just financial or regulatory from the federal government, but we have to do more things that force state and local governments to get out of the way of people being able to build more housing. I think that the conversations that you've had on your show, and the conversations we're having in government, need to move past our regular policy conversations of: “Should we do more on LIHTC? Should we try to fix NEPA?” Those, to me, are table stakes, and we're in the middle of what I'd say is a generational crisis when it comes to housing. We have to be willing to treat it like a crisis, rather than what I think we've done so far, which is take incremental steps at different levels to try and solve this. That's one thing that I wanted to make sure that I said, because I think it's the most important thing that we can do at the moment.Kyla: Absolutely. During your time there, the Treasury was doing so much with zoning reform, with financial incentives. What I really liked about our last conversation was how much you talked about how important it is that workers can live close to work. Are you optimistic that we will be able to address the problem, or do you think we are sinking into quicksand?I'd say a little bit of both, and the thing that I'm doing now is getting hyperlocal. One of the projects I'm working on in my post-administration life is I'm working with 15 churches in D.C., where they have vacant land and want to use it to build affordable housing as quickly as possible.I'm learning that even when you have the land donated for free and you're willing to work as quickly as possible, it's still quite hard because you have regulations and financial issues that often get in the way of building things. Part of what we have to do now is just launch as many natural experiments as possible to see what works.What I've learned already from this lived experience is that even cities that are trying to get out of the way and make it easier to build housing struggle because of what you all know to be true, which is that the local politics of this is quite complicated. Oftentimes, the way that you get them over the line is by creating incentives or disincentives.In the past, I talked a lot about incentives in terms of “giving people money to do things.” I'm now in favor of “not giving money to people who don't do things” — if you don't take steps to fix your zoning, some of the federal money that you regularly get is not coming to your jurisdiction. I'm going to reallocate that money to places that are doing this activity. I think we have to take those types of radical steps.It's similar to what we did with the Emergency Rental Assistance Program, where if you didn't spend your money, we could take your money back and reallocate it to people who were giving away emergency rental assistance money.That motivates people a lot — when they feel like something's going to be taken away from them. I'm of the view that we have to find more radical things that we can do to get housing built. If we don't, costs will continue to rise faster than people's incomes.Santi: Wally, I have to ask after that point you just made: did you read the paper by my colleague Chris Elmendorf on using LIHTC funds? The idea is to re-allocate those federal funds away from big, expensive cities and into other places in a state, if the cities don't commit to basic zoning reforms.I completely agree with him, and I think I would go even further than just LIHTC money. I would reallocate non-housing money as well, because from my standpoint, if you think about the most important issue for a family, it's being able to find housing that is affordable near their place of work and where their kids go to school. I said that on purpose. I didn't say “affordable housing.” I said “housing that is affordable,” because affordable housing is, in lots of ways, targeted towards a population of people who need it the most. But for even people who are middle income in this country, it crowds out their ability to pay for other things when housing costs continue to creep higher.The only way we solve that problem is if you get rid of restrictive zoning covenants and fix permitting. The natural thing that every city and state is thinking about right now is throwing more money at the problem. There's going to need to be money here, just in light of some of the headwinds, but it's going to be more costly and less effective if we don't fix the underlying issues that are making it hard to build housing where we want it.Right now in California, we're having a huge debate over what we do with infill housing in urban areas. A simple solution — you don't have to do another environmental review if one was already done in this area— is taking months to work through the California legislature, which demonstrates that we're going too slow. California's seeing an exodus of people. I just talked to a CEO who said, “I'm moving my business because the people who work for me can't afford to live in California anymore.” This is the kind of problem that you can solve. State legislatures, Congress, and executives have to get together and take some radical steps to make it easier to build housing.I appreciate what you said about what we were doing at Treasury, but from my standpoint, I wish we had done more earlier to focus on this issue. We had a lot going on, but fundamentally, the most important thing on housing is taking a step to try and build housing today, which is going to have an impact on the economy 10, 20, 30 years from now. We just have to start doing that as soon as possible.Thanks to Emma Hilbert for her transcript and audio edits. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.statecraft.pub

In this episode of the Mainframe Connect podcast's I am a Mainframer series, Richelle from Beta Systems shares her inspiring journey from the Philippines to Austria in the mainframe industry. Starting as a COBOL programmer trainee, Richelle transitioned through roles in systems programming and open-source development, becoming a key contributor to the Zowe community as a Scrum Master for Zowe Explorer. She discusses mainframe modernization, the power of the Zowe community, and her passion for teaching modern mainframe tools like VS Code and CLI to apprentices and colleagues. A highlight of the conversation is Richelle's vision for a hybrid mainframe future and her advocacy for greater visibility of women in the industry through the upcoming Mainframe Coven podcast.

Shiv is in conversation with Allen Cooper, President and CEO of Ancilla Ventures. Their focusis in providing tools to healthcare support staff to improve patient outcomes.In this conversation, Allen talks about:Allen's Origin Story: Transitioning from accounting to computer science, and entering the consulting world at Anderson Consulting (now Accenture).Consulting to Startups: The transition from corporate consulting to entrepreneurship.Building Ancilla: How Allen became a partner and eventually the sole proprietor.Choosing Healthcare Tech: The path to focusing on healthcare IT solutions.Finding Industry Problems: How products like WriteList and VR-90 were born.User Adoption Challenges: Strategies for getting hospital staff to engage with software solutions.Managing Development Team Motivation: Keeping engineers engaged despite stable enterprise tech.Scrum & Agile Benefits: How these methodologies helped balance planned work and incoming client requests.AI & Coding: How AI might change development roles, but won't replace programmers entirely.Advice for IT Careers: Guidance for both new entrants and mid-career professionals wondering about their next steps.Personal Productivity & Balance: Allen's tips for staying organized, healthy, and grounded while running a company.Allen Cooper is the Co-Founder and CEO of ReadyList, Inc., a mobile-friendly software that transforms how hospital ancillary and support service teams operate. Allen co-founded ReadyList with a deep passion for helping the behind-the-scenes workers who keep hospitals running smoothly. ReadyList's software modules guide them through best-practice cleaning and room prep protocols, resulting in cleaner, safer facilities for both patients and staff. Allen believes the right kind of software can save hospital systems money, time, and even lives. https://www.linkedin.com/in/allen-cooper-4a07598

Scott Wu is the co-founder and CEO of Cognition, the company behind Devin—the world's first autonomous AI software engineer. Unlike other AI coding tools, Devin works like an autonomous engineer that you can interact with through Slack, Linear, and GitHub, just like with a remote engineer. With Scott's background in competitive programming and a previous AI-powered startup, Lunchclub, teaching AI to code has become his ultimate passion.What you'll learn:1. How a team of “Devins” are already producing 25% of Cognition's pull requests, and they are on track to hit 50% by year's end2. How each engineer on Cognition's 15-person engineering team works with about five Devins each3. How Devin has evolved from a “high school CS student” to a “junior engineer” over the past year4. Why engineering will shift from “bricklayers” to “architects”5. Why AI tools will lead to more engineering jobs rather than fewer6. How Devin creates its own wiki to understand and document complex codebases7. The eight pivots Cognition went through before landing on their current approach8. The cultural shifts required to successfully adopt AI engineers—Brought to you by:Enterpret—Transform customer feedback into product growthParagon—Ship every SaaS integration your customers wantAttio—The powerful, flexible CRM for fast-growing startups—Where to find Scott Wu:• X: https://x.com/scottwu46• LinkedIn: https://www.linkedin.com/in/scott-wu-8b94ab96/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Scott Wu and Devin(09:13) Scaling and future prospects(10:23) Devin's origin story(17:26) The idea of Devin as a person(22:19) How a team of “Devins” are already producing 25% of Cognition's pull requests(25:17) Important skills in the AI era(30:21) How Cognition's engineering team works with Devin's(34:37) Live demo(42:20) Devin's codebase integration(44:50) Automation with Linear(46:53) What Devin does best(52:56) The future of AI in software engineering(57:13) Moats and stickiness in AI(01:01:57) The tech that enables Devin(01:04:14) AI will be the biggest technology shift of our lives(01:07:25) Adopting Devin in your company(01:15:13) Startup wisdom and hiring practices(01:22:32) Lightning round and final thoughts—Referenced:• Devin: https://devin.ai/• GitHub: https://github.com/• Linear: https://linear.app/• Waymo: https://waymo.com/• GitHub Copilot: https://github.com/features/copilot• Cursor: https://www.cursor.com/• Anysphere: https://anysphere.inc/• Bolt: https://bolt.new/• StackBlitz: https://stackblitz.com/• Cognition: https://cognition.ai/• v0: https://v0.dev/• Vercel: https://vercel.com/• Everyone's an engineer now: Inside v0's mission to create a hundred million builders | Guillermo Rauch (founder and CEO of Vercel, creators of v0 and Next.js): https://www.lennysnewsletter.com/p/everyones-an-engineer-now-guillermo-rauch• Inside Bolt: From near-death to ~$40m ARR in 5 months—one of the fastest-growing products in history | Eric Simons (founder and CEO of StackBlitz): https://www.lennysnewsletter.com/p/inside-bolt-eric-simons• Assembly: https://en.wikipedia.org/wiki/Assembly_language• Pascal: https://en.wikipedia.org/wiki/Pascal_(programming_language)• Python: https://www.python.org/• Jevons paradox: https://en.wikipedia.org/wiki/Jevons_paradox• Datadog: https://www.datadoghq.com/• Bending the universe in your favor | Claire Vo (LaunchDarkly, Color, Optimizely, ChatPRD): https://www.lennysnewsletter.com/p/bending-the-universe-in-your-favor• OpenAI's CPO on how AI changes must-have skills, moats, coding, startup playbooks, more | Kevin Weil (CPO at OpenAI, ex-Instagram, Twitter): https://www.lennysnewsletter.com/p/kevin-weil-open-ai• Behind the product: Replit | Amjad Masad (co-founder and CEO): https://www.lennysnewsletter.com/p/behind-the-product-replit-amjad-masad• Windsurf: https://windsurf.com/• COBOL: https://en.wikipedia.org/wiki/COBOL• Fortran: https://en.wikipedia.org/wiki/Fortran• Magic the Gathering: https://magic.wizards.com/en• Aura frames: https://auraframes.com/• AirPods: https://www.apple.com/airpods/• Steven Hao on LinkedIn: https://www.linkedin.com/in/steven-hao-160b9638/• Walden Yan on LinkedIn: https://www.linkedin.com/in/waldenyan/—Recommended books:• How to Win Friends & Influence People: https://www.amazon.com/How-Win-Friends-Influence-People/dp/0671027034• The Power Law: Venture Capital and the Making of the New Future: https://www.amazon.com/Power-Law-Venture-Capital-Making/dp/052555999X• The Great Gatsby: https://www.amazon.com/Great-Gatsby-F-Scott-Fitzgerald/dp/0743273567—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. Get full access to Lenny's Newsletter at www.lennysnewsletter.com/subscribe

In this episode of Liquid Weekly, Karl and Taylor sit down with Ole Thorup, seasoned Shopify developer and creator of Accentuate Custom Fields and now Shopify Apps Espresso Editor and Espresso Live Metafields, to explore the power and possibilities of CloudFlare in Shopify app development.Episode Highlights* Ole's journey from COBOL developer to Shopify merchant to app developer* Deep dive into CloudFlare's features including Workers, Queues, and Durable Objects* How to handle app scaling and performance optimization* Tips for managing large-scale Shopify stores with 100,000+ products* Insights into building Espresso apps and live metafields* The evolution from traditional hosting to serverless architectureAbout Ole ThorupOle is a developer with 40 years of experience who transitioned from banking and telecom to Shopify development. After creating and selling the successful Accentuate Custom Fields app, he now runs Espresso with his son, continuing to innovate in the Shopify ecosystem.Find Ole Online* Twitter/X - https://x.com/olethorup* Espresso Apps - https://espressoapps.com/Timestamps00:00 - Introduction05:30 - Ole's Background12:45 - CloudFlare Deep Dive30:20 - App Architecture45:10 - Scaling and Performance52:30 - Shopify Dev Changelog57:00 - Picks of the WeekResources:* Cloudflare - https://www.cloudflare.com/* Cloudflare Learning Center - https://www.cloudflare.com/learning/* Cloudflare Developer docs - https://developers.cloudflare.com/* Peacock's Serverless Apps of Cloudflare - https://pragprog.com/titles/apapps/serverless-apps-on-cloudflare/* Flared Up - https://research.cloudflare.com/outreach/updates/mailinglist/* How Shopify Uses Cloudflare - https://www.cloudflare.com/case-studies/shopify/* Tanstack - https://tanstack.com/* Shadcdn/ui - https://ui.shadcn.com/Dev Changelog* New opacity controls for theme colors - https://shopify.dev/changelog/new-opacity-controls-for-theme-colors* App ratings now factor in trust signals, with reviews from lower-trust shops carrying less weight. - https://shopify.dev/changelog/app-ratings-now-factor-in-trust-signals* New Inventory Transfers experience available for testing in Dev Preview - https://shopify.dev/changelog/new-inventory-transfers-experience-available-for-testing-in-dev-preview* Introducing PRODUCT_CATEGORY_ID_WITH_DESCENDANTS in CollectionRuleColumn for smart collections - https://shopify.dev/changelog/introducing-productcategoryidwithdescendants-in-collectionrulecolumn-for-smart-collectionsPicks of the Week* Ole: Black Mirror Season 7* Karl: King Solomon's Mines by H. Rider Haggard* Taylor: TalkingShop.dev PodcastSign Up for Liquid WeeklyDon't miss out on expert insights and tips—subscribe to Liquid Weekly for more content like this: https://liquidweekly.com/

When Hackaday editors Elliot Williams and Al Williams need a break from writing posts, they hop on the podcast and talk about their favorite stories of the past week. Want to know what they were talking about? Listen in below and find out! In an unusual twist, a listener sent in the sound for this week's What's This Sound competition, so it turns out Elliot and Al were both stumped for a change. See if you can do better, and you might just score a Hackaday Podcast T-shirt. On the hacking front, the guys talked about what they hope to see as entries in the pet hacking contest, quantum diamonds (no kidding), spectrometers, and several science projects. There was talk of a tiny robot, a space mouse—the computer kind, not a flying rodent—and even an old-fashioned photophone that let Alexander Graham Bell use the sun like a string on a paper cup telephone. Things really heat up at the end, when there is talk about computer programming ranging from COBOL to Vibe programming. In case you've missed it, Vibe programming is basically delegating your work to the AI, but do you really want to? Maybe, if your job is to convert all that old COBOL code.

Elon Musk's Department of Government Efficiency, or DOGE, has been edged out of the headlines this past week, or so, by the administration's current flirtation with a constitutional crisis. But the DOGE team is still busy. One project on the office's agenda, originally reported by WIRED late last month, is to rewrite the Social Security Administration's code base—in other words, the agency's computer programs, which handle millions of Americans' personal and financial data. Brooke sits down with Clive Thompson, author of Coders: The Making of a New Tribe and the Remaking of the World, contributing writer to New York Times Magazine, and monthly columnist for Wired, to discuss the coding language under DOGE's microscope.    On the Media is supported by listeners like you. Support OTM by donating today (https://pledge.wnyc.org/support/otm). Follow our show on Instagram, Twitter and Facebook @onthemedia, and share your thoughts with us by emailing onthemedia@wnyc.org.

In this episode of Project Synapse, join our group of AI-obsessed IT professionals as they discuss the intriguing concept of AI-generated code, specifically focusing on 'vibe coding.' Marcel Gagne, a former system administrator turned author, dives deep into the history and potential of writing code through AI. The episode covers the evolution from early programming languages like COBOL and Fortran to modern AI coding tools like Cursor and Firebase. Discover how AI tools aid in prototyping, personal productivity, and the future possibilities in enterprise-level applications. The team also explores security implications, testing methodologies, and the importance of responsible AI use in development. Tune in to learn about the present and future impact of AI on programming and systems development. 00:00 Introduction to Project Synapse 00:36 Meet the Hosts 02:53 The Evolution of Programming Languages 08:27 The Rise of Vibe Coding 14:00 Practical Applications and Experiences 19:54 Advanced Tools and IDEs 22:39 Challenges and Solutions in AI Coding 29:56 Starting Fresh: The Importance of Context 33:04 Introduction to Programming by Kenny Rogers 33:28 Legendary Programmer John Carmack 33:38 AI in Game Development 34:19 Nostalgia for Classic Games 35:59 The Evolution of Game Engines 38:04 AI's Role in Modern Coding 38:36 Proof of Concept and Rapid Prototyping 44:20 Security Concerns with AI-Generated Code 50:06 The Future of AI in Enterprise Systems 01:00:27 The Importance of Testing and Security 01:03:44 Final Thoughts and Recommendations

AKA There Is No Trump without Newt. In episode 888 of The Professional Left Podcast, hosts driftglass and Blue Gal dive into the political landscape of April 1st, 2025, where April Fools Day is effectively canceled at the Cornfield Resistance due to the real Fool occupying the Oval Office.The hosts examine how Republicans have weaponized language over decades, tracing the destructive path from Newt Gingrich's slash-and-burn politics through Rush Limbaugh's hate radio to Trump's presidency. They contrast this with Democrats' constant pressure to be "civil" and "bipartisan," recalling Senator Durbin's tearful apology for his anti-Gitmo torture comments while Republicans never apologize for anything.Also covered: Senator Cory Booker's filibuster against hate, the White House Correspondents' Association's capitulation by canceling comedian Amber Ruffin, Elon Musk's dangerous plan to replace the COBOL code running Social Security payments, and a news roundup featuring Trump's latest attacks on democracy—from Signal-gate to tariff impacts, DEI funding cuts, and threats to the Smithsonian.Don't miss this sharp, unapologetic analysis of why "talking to the other side" isn't viable when the other side has abandoned democratic principles entirely.More at proleftpod.com.Driftglass will be on The BradCast with Digby on 4/2/2025.   We are scheduled to be on The Bob Cesca show on 4/9/2025.Support the show at Patreon.com/proleftpod, or send a letter/contribution to The Professional Left PodcastPO Box 9133Springfield, IL 62791Support the show

Tech travel, security bloops, getting the news, rewriting COBOL.

The Personal Computer Show Wednesday April 2nd 2025 PRN.live Streaming on the Internet 6:00 PM Eastern Time In the News  Microsoft Asking Users to Delete Their Passwords  Microsoft Insists Connect to the Internet When Installing Windows 11  IBM Layoffs and Job Shifts to India  Are H-1B Workers Paid Less Than U.S. Workers for the Same Job?  U.S. Proposes H-1B Wage Hike ITPro Series with Benjamin Rockwell  [3/4] Rebutting Common Statements About Why Return to Work is So Important From the Tech Corner  When Does Tech Ageism Start in the U.S.?  COBOL's Relevance In 2025  Masking Your Email Addresses Technology Chatter with Benjamin Rockwell and Marty Winston  Backup Power that Doesn't Come Back Up

Tech News Roundup: Google's Free AI Rollout, Data Privacy Tips for Travelers, CloudFlare's New SSH Tool, and Social Security System Overhaul In this episode of Trending, host Jim Love covers several key tech developments. Google has made its latest AI model, Gemini 2.5 Pro Experimental, available to all users, boosting its accessibility with impressive features like a 1 million token context window. The episode also covers crucial tips for safeguarding personal data while traveling, especially in light of heightened device searches by U.S. Customs and Border Protection. Additionally, CloudFlare has launched O-P-K-S-S-H, an open-source tool aiming to improve Secure Shell (SSH) security by replacing traditional keys with identity-based single sign-ons. Finally, the Department of Government Efficiency (Doge) plans to rewrite the U.S. Social Security Administration's outdated COBOL codebase within a few months, a move that has raised concerns among experts about potential risks and disruptions. 00:00 Latest AI Model from Google: Gemini 2.5 Pro 02:31 Travel Tips: Safeguarding Personal Data 06:11 CloudFlare's New Open Source Tool for Secure SSH 07:39 US Social Security System Overhaul: Risks and Challenges 11:56 Conclusion and Contact Information

A discussion with Divyes Patel, Director, Innovation, Research, & Development at a large Healthcare company based in Tennessee. During his current tenure, as well as past jobs at UnitedHealth Group and Cigna, he's focused on using data to make healthcare more efficient and effective.Divyes talks about how he initially started programming in COBOL, but quickly moved to building reports, and then to analytics. He dives into the complexity and inconsistency of Electronic Medical Records (EMR) systems data with a memorable sarcastic quote of “If you've seen one EMR, you've seen one EMR!” He outlines how #LLMs are helping to not only transcribe discussions, but interpret those discussions and prepopulate medical history entry forms. He provides some advice to young students and professional and also outlines how agentic AI will impact analytics roles. Don't miss his description of how showing business partners a new product energizes him every time!#analytics #datascience #ai #artificialintelligence #healthcare #insurance #payer

Guy Royse, dev advocate at Redis, discusses going beyond the cache with Redis and Node.js. He explores its capabilities as a memory-first database, session management, and even fun use cases like the Bigfoot Tracker API. He also shares insights on Redis OM for object mapping and its future in the JavaScript ecosystem. Links http://guyroyse.com http://github.com/guyroyse https://www.twitch.tv/guyroyse https://www.youtube.com/channel/UCNt5SDc6LosO41E77jr59cQ https://x.com/guyroyse https://www.linkedin.com/in/groyse https://2024.connect.tech/session/693665 We want to hear from you! How did you find us? Did you see us on Twitter? In a newsletter? Or maybe we were recommended by a friend? Let us know by sending an email to our producer, Emily, at emily.kochanekketner@logrocket.com (mailto:emily.kochanekketner@logrocket.com), or tweet at us at PodRocketPod (https://twitter.com/PodRocketpod). Follow us. Get free stickers. Follow us on Apple Podcasts, fill out this form (https://podrocket.logrocket.com/get-podrocket-stickers), and we'll send you free PodRocket stickers! What does LogRocket do? LogRocket provides AI-first session replay and analytics that surfaces the UX and technical issues impacting user experiences. Start understand where your users are struggling by trying it for free at [LogRocket.com]. Try LogRocket for free today.(https://logrocket.com/signup/?pdr) Special Guest: Guy Royse.

In this episode of the IC-DISC Show, I sit down with Brian Schwam to discuss how Interest Charge Domestic International Sales Corporations (IC-DISCs) can help businesses save on taxes. With over 35 years of experience, Brian shares how IC-DISC has evolved since 1972 and why it remains a valuable tool for U.S. exporters. He explains how businesses, particularly in the aerospace industry's Maintenance, Repair, and Overhaul (MRO) sector, can take advantage of this incentive to improve their financial position. We walk through a hypothetical example to illustrate how an exporting business could benefit from IC-DISC. Brian explains how companies involved in manufacturing, repairing, or trading parts can qualify and why many eligible businesses overlook this opportunity. We also discuss the annual MRO conference in Atlanta, where industry professionals gather to share insights and best practices. This event highlights the ongoing impact of IC-DISC within the aerospace sector and beyond. Despite the clear benefits, many businesses hesitate to implement IC-DISC due to a lack of awareness or expertise. Brian talks about how our firm partners with CPA firms to integrate IC-DISCs into existing tax processes, making it easier for businesses to take advantage of these savings. He also highlights the underutilization of IC-DISC and why more companies should consider it as part of their tax strategy. We wrap up by discussing the upcoming MRO America's Conference in Atlanta, where exporting aviation maintenance companies can connect and learn more about IC-DISC applications. Whether you're new to IC-DISC or looking to refine your approach, this conversation provides useful insights for businesses considering this tax-saving opportunity.     SHOW HIGHLIGHTS In this episode, I discuss the intricacies and benefits of Interest Charge Domestic International Sales Corporations (IC-DISC) with tax attorney Brian Schwam, who has over 35 years of experience in the field. We explore the historical context of IC-DISC, including its origins in 1972 and the significant changes it underwent following international scrutiny and U.S. tax reforms, such as the 2003 Bush tax cuts and the 2017 Tax Cuts and Jobs Act. Brian provides insights into how IC-DISC can serve as a valuable tax incentive for U.S. exporters, particularly those in the aerospace industry's Maintenance, Repair, and Overhaul (MRO) sector. Through a detailed hypothetical example, we illustrate how companies can leverage IC-DISC to maximize export profits, highlighting specific benefits for pass-through entities and closely held C corporations. We address common apprehensions businesses face regarding IC-DISC implementation and discuss how collaboration with CPA firms can facilitate a seamless integration into existing tax processes. Despite the clear benefits, IC-DISC remains underutilized, and we emphasize the potential missed opportunities for businesses not taking advantage of this tax-saving strategy. The episode also covers upcoming industry events, such as the annual MRO conference in Atlanta and the ICDISC Alliance Conference, which offer valuable networking and professional growth opportunities.   Contact Details LinkedIn - Brian Schwam (https://www.linkedin.com/in/brian-schwam-b6026a3/) LINKSShow Notes Be a Guest About IC-DISC Alliance About WTP Advisors GUEST Brian SchwamAbout Brian TRANSCRIPT (AI transcript provided as supporting material and may contain errors) Dave: Hey, brian, welcome to the podcast. Brian: Thanks, dave, good to be here. Dave: So where on planet Earth are you calling in from today? It's hard to tell by looking at your background. Brian: Outer space. I am in the sunny South Florida. Dave: Okay. Brian: Breezy, south Florida, okay. Dave: Now are you a native of Florida. Brian: I am not a native of Florida. I spent 50 years of my life in the upper Midwest in Wisconsin. Okay, I had to move to Sunbelt. Dave: Okay, Now were you educated in the Midwest then too. Brian: I was. I'm a proud alum of the University of Wisconsin, both for an undergraduate degree in accounting and also my JD from the law school Okay. Dave: So you've and I take it and I've known you a while, so I think that's been several decades ago that your career was started. Is that about right? Brian: Several would be a good good approximation. Yes, I've been at this for 38 years. I know it doesn't look like it, right, okay? Dave: And so, and how long have you been involved in ICDISC? Then Most of that time 38 years, oh, 38 years in ICDISC. Then most of that time, 38 years, oh, 38 years in the disc, wow, yeah. So how does that do you know? Do you have any way to quantify that? Like how many you know ICDISC returns you've, you know, signed or reviewed or prepared, or Boy, it's a big number, dave. Brian: It's probably five figures. Okay, probably, so you know, somewhere north of 10,000 for sure. Okay, over that time period. Dave: Well, and that is why I'm glad that you are one of the founding members of the IC Disc Alliance with me that when I had a chance to partner up with you and some of your team when we created the IC Disc Alliance, I was really excited because in my book I pretty much knew all the players in the IC Disc space and once the famous Neil Block retired after 50 years to me you were without peer in the IC Disc space. Brian: So I really enjoyed collaborating with you through the years here in the ICDISC space, so I really enjoyed collaborating with you through the years. Dave: Thank, you for that, Dave. I hope to be able to follow Neil into that 50-year stratosphere. Yeah, that's big shoes to follow. So let's just talk a bit about the ICDISC. What the heck is it? Why does everyone use that silly acronym? Brian: Because what it really stands for is a mouthful. Dave: Okay. Brian: Discharged Domestic International Sales Corporation and that is what the ICDISC stands for, short right ICDISC. And I don't know if we'll get into. I'll get into what the IC stands for and everything. But basically this is an export incentive that's been in the Internal Revenue Code since 1972. Okay, in various forms. Initially it was an export incentive that just about any company could use, that was exporting goods that were manufactured, produced, grown or extracted in the US. It came under some fire from our trading partners and in 1984, it was transformed into the ICDISC. It started out just as the DISC in 1972 for the Boston International Sales Corporation and it, like I said, came under scrutiny. Our trading partners said hey, you're a, you can't have an exemption from income because you're not. You know you tax things differently in your country. This flies in the face of the other incentives you give your taxpayers. So they changed it into the ICDIS, which made it into, instead of a permanent tax savings, at least on its face, into a temporary savings where, to the extent a taxpayer saved tax and deferred income from tax, they were required to pay an interest charge to the IRS on that deferred tax. Hence the IC. Dave: Okay, okay. Brian: That rate changes every year. It's based on the one-year average TBLO rate as of September 30th annually. And at the same time they instituted something called the Foreign Sales Corporation, which was widely used by thousands of companies, and that came under attack and eventually became the extraterritorial income exclusion which was immediately attacked and eventually, a couple of years later, it just went away. In the meantime, the disk floundered for quite a number of years. In fact, in the year 2000 there were only 787 disks in existence. Dave: Wow, it seems like a shockingly small number. Brian: Well, the tax laws weren't real conducive to benefiting from the disk at that time. Then, in 2003, the Bush tax cuts brought in the concept of qualified dividend income and it took the disk off of life support and really put it on robust territory for pass-through entities, because they could now, to the extent that they could qualify and we'll get into that, to the extent they could qualify and to the extent that they could benefit it provided a 20% rate benefit between ordinary income and qualified dividend income, so it was a significant savings. Now that's been whittled away over time, where it's been reduced here and there. Various tax law changes and probably the largest or the next biggest reduction came in in 2017 with the Trump tax bill, the Tax Cuts and Jobs Act, which reduced the rate on qualified income on non-qualified income. So it reduced the rate on S-corp income partnership income in an individual's tax return to a 29.6% level, and so now the spread between the qualified dividend rate and the ordinary rate just isn't as great as it used to be. It's approaching 6%. So where it used to be 20, then it went to 15, and now it's 6. But it's still a permanent savings for these past three entities and it's not something that they should ignore, because it can save significant taxes, depending upon the level of export activity. Dave: Okay, and now to be clear, depending on a company-specific fact pattern, that spread could be greater. Right For a pass-through. It could be as high as what like? Brian: 13% or so For a pass-through it could be as high as what like, 13% or so For a pass-through business. Dave: It could be as high as 13.2%, okay, but in general we see that it and it could even be somewhere between that, depending on. Brian: Anywhere in between 5.8 and 13.2. Dave: And our experience has been that most companies tend to gravitate more toward the lower end of the savings than the higher end. Brian: Yes. Dave: Yes, okay. Now what about for a C-Corp? Brian: C-Corp is a different animal. Okay, a C-Corp can't use an disc to pay deductible dividends to its owners if it's a closely held C corp. This is not something that a public company can benefit from. But if a closely held business C corp is paying dividends to its shareholders and would like to be able to deduct those payments, rather than not being able to deduct those payments, using an ICDIS can transform the dividend into a deductible dividend. Now, it doesn't save the shareholders any tax, because they're paying tax on the dividend regardless of where it comes from, but it would eliminate the corporate level tax on the C corporation, so that benefit could be as high as 21%. Dave: Okay. Brian: Okay, another manner in which certain C corporations use the disc is to fund bonuses for shareholders and key employees, and then that saves the shareholders 17% tax the difference between a tax on a wage and a tax on a dividend, qualified dividend. So that's a 17% savings for the shareholder. In that case the C-Corp doesn't save any tax. They're getting a deduction either way wages or commission to the disk. And now that I've mentioned the word commission, that's probably a good segue into how does a disk earn income? Yeah, and what is its income? So most discs are what we call commission discs. They earn a commission when a operating business that's related to that disc makes an export sale of qualified export property. So let's dig down into that first. What's qualified export property? Well, that's property that has been manufactured, produced, grown or extracted in the US. So if I'm manufacturing in Mexico or Canada or China and I'm simply selling what I've made in those other countries, you know the disc is not something that's going to benefit that type of a business. Dave: Okay. Brian: It is there to spur US manufacturing, create US jobs, right in line with the America First proposition that's headlining Washington in 2025. Dave: Okay. Brian: So it should be on safe ground, everything that's going on there. So if a company has property that's been manufactured, produced, grown or extracted in the US and they sell it for export outside the United States and not to a US possession, then that sale can potentially generate an ICDIS commission that would be paid to the ICDIS. And keep in mind this ICDISC is not an entity that the outside world sees or understands or knows about. It's simply an entity that does business, if you will, internally with the operating company, so customers don't know about it. It's really transparent to the world. It's just there to help US exporters save tax. Dave: Okay, it's just there to help US exporters save tax. Okay, and the logistics of it. Like say a company has just for simple math, let's say they have $10 million of export, of qualified export revenue, and the ICDIS commission that's calculated to say 10% of that. Brian: Okay. Dave: So 10% of that would be a million dollars, and so walk me through kind of the that's correct and it accrues the deduction, assuming it's not a cash basis taxpayer. Brian: It accrues that deduction at the end of the year, the DISC accrues the income at the end of the year and then by statute the DISC does not pay income tax. So now we've gotten a deduction on one side, we have non-taxable income on the other side and then when the disc pays a dividend to its owners, that becomes a qualified dividend and is taxed at a lower rate. Dave: Okay, so then, effectively, that million dollars gets reclassified from being taxed at ordinary dividend rates to qualified dividend rates. Brian: From ordinary income rates to qualified dividend rates. Dave: yes, Yep, thank you for that. And where that shows up for a pass-through is going to be on the individual shareholders, k-1, right. That box up near the top that shows ordinary taxable income would basically go down. Let's say there was one shareholder, that number goes down by a million dollars. And then there's a box further down on the K-1 for qualified dividend income and that's where the number's being shifted to right. Brian: Right. Assuming the disc is owned by the operating company, which most of the time it is in the pass-through business context, then the ordinary income gets reduced on the K-1 and the dividend income will increase on the K-1, not necessarily in the same year, but that will be the result over time. Dave: And then that tax savings then will show up on the individual shareholders. 1040, right, because their ordinary income line is a million dollars less. The qualified dividend income line is a million dollars more, and that's where that arbitrage. Brian: They pay less tax if they're getting a distribution from the company to cover their taxes, which is often the case, the company doesn't have to distribute as much cash, therefore increasing the working capital of the business. Dave: Okay, well, thank you. Thank you for that. Now, what I want to drill down into a little more today is looking at the aerospace industry, specifically what's called the MRO space in aerospace. Do you know what MRO stands for? Brian: I believe, I do, I believe maintenance, repair and overhaul. Dave: That's my understanding as well. Brian: That's a significant area in the aviation space. Dave: yes, Okay, and I believe that there's a big conference in Atlanta in April with like something like 17,000 expected attendees. Brian: Yeah, just a small gathering. Dave: A small gathering. Brian: For sure. Yes, that's my understanding as well. In fact, I'll be there. Dave: Yeah, I believe we'll both be there, yeah we'll both be there A few of our colleagues. Brian: Yeah, so it's a one a year significant gathering of companies that operate in this MRO space, supporting airlines and other aviation companies, and basically MRO is important because it keeps planes able to fly. Yeah, and we actually have a booth there. Dave: Yeah, and we actually have a booth there. 1818 BC and it makes it sound like it's a date from a long time ago. But yeah, we'll be there and this will be our first year in attendance or exhibiting. And this has come from, in recent years, I'd say, a big ramp up in the number of MRO companies who we are helping with their IC disk. Is that right? Brian: Yeah, absolutely. In fact, one of the sponsors of the conference was a company I was doing some work with and I asked them if he thought it would be a good idea for us to attend, and it was a resounding absolutely that he thought that we could meet a lot of companies that could benefit from this ICDISC similar to his company. Dave: Okay. What are the elements in the MRO space or the characteristics of the companies that make them a good fit for the ICDISC, because my understanding is it's probably only one out of a hundred of like all the registered corporations in the US are really a fit for the disc. Brian: Yeah, so it takes a specific fact pattern to really benefit. So the companies in the service side of the business so let's say they're carpet cleaners or something to that nature they're not going to be able to benefit from the disk. But let's say it's a repair center and airlines will ship in parts to the repair center because they've worn out and they need it. They need a replacement part so that they can fly this plane. So what happens is maybe the repair center takes their part and repairs it, but they previously repaired another part that's identical and then to the customer and that plane gets back in the air right away. So in that scenario, even though it's a different part that's going back out versus what was coming in, that type of activity qualifies as long as what they're doing qualifies as manufacturing and that repair is occurring in the US. Dave: Okay. Brian: Then that type of a company could definitely benefit Other companies. I don't want to use this term, but it's kind of like horse trading. Sometimes companies will buy a surplus of parts, knowing that eventually they're going to be used by somebody and they hang on to these parts, or they find them from somebody who says I don't want these parts anymore, I haven't been able to sell them. So they take a flyer, they take a risk and they buy these parts and they hang on to them and maybe they sell them at a significant profit and maybe they don't. But there's that space as well that can benefit from the disc, and there's some misconception out there that some of the companies that are similar to what I just described can't benefit from a disc, and so, for example, if parts are obtained outside the US, they stay outside the US. They stay outside the US and they're repaired, recertified and resold. Those aren't going to qualify for the ICBITS. But sometimes parts are acquired outside the US and they're brought into the US, they're repaired, put it back into inventory in the US and then sold for export, and that activity does qualify for the ICs, and so it's very important to know where this refurbishment or remanufacturing is taking place. Dave: Okay and yeah, and there's a US content piece to it, right, like if they buy a part from China and all they do is they just put a little lubricant on it and throw it in a box. Brian: that may not qualify and then they export it. The test is what's the customer's value when that part comes into the US. So if it's a burned out hot engine part, for example, yeah there's no value or very little value and it comes into the US, its customers value is close to zero. It gets repaired, it's going to easily meet the content test and it's easily going to be considered manufactured in the US. It's rare, I think, that we'll find that somebody will buy a new part from outside the US just to inventory it here for export. Dave: Okay, yeah, because there's that it's a 50% US content test, right which? Is also, I think confusing on the surface if you don't really dive down into the rules, right, I mean, the layperson may find it. Brian: How do you know what's 50% US content? Well, the cost of good, I mean. Think of it the other way. The foreign content can't be more than 50%. And the foreign content is the cost, the customs value when it was imported. So if I'm selling something for $100, I imported it for as much as $49.99. That's going to qualify as long as I did something, you know, remanufactured it once it got to the US and once it got to the plus, more often than not, I think the value of those things coming in because they're used and worn and damaged parts, they're going to have a low customs valuation where there'll be no problem meeting that content. Dave: Okay, I can see that. Well, I find and my listeners tell me they really like kind of case studies, little mini of case studies, little mini, you know, client case studies On an anonymous basis. Do you have an example or two of some of the types of companies we've worked with, just to give people a flavor of them and, again, you know, being anonymous to you know? What company it is, but just a sense of like the sense of the size of the company, what the benefit might have been. Brian: The size is sort of across the board, right. So some of them are someone on the smaller side. They might have export sales between $5 and $10 million, and then some of them might have export sales of $100 million. It all depends on the size of their business and the benefits are kind of all over the map. Because we don't just do a simple calculation of the benefits. And the reason we don't is because in this industry what we find is there's a lot of margin variability in the companies that are exporting, and then a transaction-by-transaction analysis of the disk commission is what makes the most sense. That allows us to benefit from the margin variability, allows them to benefit from a higher disk commission and obviously then they're going to save more tax. And in some cases the commission grows by 10x by using the T by T. Sometimes it's two or three x, sometimes it's. You know, I've seen you know where it would have been zero because there was an overall loss in the company, but we were able to get a significant discommission with a T by T approach. So it's hard to pinpoint an exact number, but generally speaking it's 15 to 20, you know the commission ends up being 15 to 20% of sales. And if you look at the statutes, one of the statutes says oh, the commission can be 4% of sales, and another implies that it could be anywhere from 4% to 10%, but we generally see in this industry at least 15% on average. It's significantly higher. Dave: Yeah, and I'd like to drill down into that because I tell, and based on my understanding, we may manage more IC disks than any other organization of the country. I mean we I think our number is somewhere north of 500 companies now that we're helping out, and when I'm having these conversations, you know. So I'm, as you know, I'm more focused on the sales side. You know, and you and your team are more focused kind of on the technical aspect of producing these returns, and what I tell people is that our real value isn't being able to produce an IC disk return. Our value is the incremental benefit that the transaction by transaction calculation yields. That the transaction by transaction calculation yields. Because you know just about any any cpa firm you know most of them their software includes the ic disk return. You know, if they just go do a four percent calculation, it's a, you know, reasonably straightforward calculation. But we find that you know they're capturing only a fraction of the total benefit. Brian: That's true, and while I've seen a good number of interesting looking disc returns, I tend to agree that if you follow the directions, anybody can probably prepare a disc return. We do that as well. That's not where we add the most value. Where we add the most value, adding the value comes in unlocking the highest commission possible so that the tax savings are as great as possible. Yeah, and a lot of businesses that are high margin I'm sorry, low margin high volume businesses. When you look at the disc, on its face it looks like oh, there's not much benefit here, we're only making 2% or 3% of sales on our bottom line. So our disc commission would be 2% or 3% of sales. But, like I said, with the transactional approach, if the commission approach is 15%, well now we've taken the company into a tax loss which could potentially save additional taxes for the owners over and above that 5.8%, because now we're offsetting that loss against other income wages, interest, et cetera and being taxed just on the qualified dividend income of the disc. And so you can't just look at the overall margin or overall profitability of the company and project what that, what it's going to look like, Because they vary all over the place. Dave: Based on this transactional approach, yeah, and I would like to talk a bit about. Oftentimes, when I'm talking to a company that's considering a disk, oftentimes they've never even heard of it. Their CPA firm may not have even mentioned the idea. And they'll say, and they'll ask me hey, does this mean my CPA, you know, screwed up by not telling me about it. In my response, you know I try to be generous and I explain it that, look, you know, in our experience only about one out of 100 companies are a candidate. And so let's just say you have a large local CPA firm and they have 100, you know midsize corporate clients. Statistically we find that only one of them, you know, would be a fit for the disk. And your experience may be a little different, you know, feel free to correct me. And so when you think about it from the CPA's perspective, if there's a special part of the tax code and they only have one client that benefits, it's a difficult economic dynamic for the CPA firm to invest in a whole team and expertise to serve one client, right? Isn't that like part of the challenge that the and I know you've worked at a number of large CPA firms Is my understanding correct? That's part of the problem is just their clientele. There aren't enough of them. That makes it worth doing yeah. Brian: Yeah, I think that's a fair characterization. I might phrase it a little bit differently. I mean, there are thousands of CPA firms and they're all excellent generalists. This is not an area where you can be a generalist. Cpa firms often outsource R&D, tax credit work, cost segregation work. This, to me, falls right in that same category. You don't want to dabble in this, and if you're not sure what you're doing, you can get you and your client in trouble. Have good intentions, but if you don't execute it properly, it can be more of a headache than it's worth. And so, like most people, I think people gravitate towards what they know and understand, and things that they don't know and understand can look and sound scary. Dave: Yeah. Brian: So it's like, oh my God, an IC disc. I've never heard of that. I'm not sure I can bring that to my client because I don't really know what I'm doing. Well, I wish I knew somebody I could call to him. He's not a competitor right who could help me through this and help my client through this, and so that's really one of the reasons why we exist, because, as you stated, you don't want it to be a competitor that you call, and so, because we are so hyper focused on what we do and we don't do the things that I'll call the cpa's generalists, that the generalists do, we're an excellent partner because we're not looking to take away anybody's tax return or any of the other type of work that the CPA might be doing for that client. We just want to play in our space. Dave: Yeah, sometimes I'm sorry. Sometimes you know clients or potential clients will say, yeah, but you know our CPA firm does. You know all of our work. It's a one-stop shop thing and I'm afraid having you do the disc return and then doing the corporate return yeah, but our CPA firm does all of our work, it's a one-stop shop thing and I'm afraid having you do the disc return and then doing the corporate return it's just going to be a nightmare for you all to coordinate your efforts. It just sounds like too much trouble. What would your response be to that? Brian: My response is I work with over 500 companies. Generally we do the disk work for those companies. The regular mainstream CPA does everything else. We coordinate our work with that CPA and it's never a problem. We say, look, we're going to need X number of days to turn this around, so please have a draft of the operating company return by a particular date, and then they work towards that date. They give us the return, we get data from the company and we turn the number around so they can finish their tax return and then we go ahead and finish the disc return and I would say 99.9% of the time it works like we're all part of the same thing. Dave: Yeah, because really the CPA they prepare that final draft corporate return. They then pull two numbers from the disk return that goes into the corporate return and then they're done, basically right. Brian: And they're done and they can go ahead and finish up their disk return, I mean their operating company return and their state returns and everything. And then we just have to get the disc return done. And sometimes you know they file their tax return in april and you know the disc returns aren't due till september. So one might say, oh, you could just sit on them until september. But you know, we try to get them done at the same time. Sure sure Everybody can rest easy. But I mean we think of ourselves as a bolt-on resource to that CPA firm while we're working with that and we work with probably 50 to 75 CPA firms around the country in that role- yeah. It works well. I mean, you can talk to any one of them about what it's like to work with us, and I'm sure you'd get a glowing recommendation for how we work with them and for their clients. Dave: Yeah, no, I'm with you. So, as we're nearing the end here, the other thing that people find interesting you'd mentioned in 2003, there were 700 IC disks under 1,000. Yeah, 787. And then, according, if my recollection is correct, the most recent IRS stats that updated that were published, I think, in 2010. And I believe in 2010, there were like 2000 disks. Brian: Yeah, something like 1926. Okay, To be exact, and that number I'm sure has grown dramatically since then. I would guess there's somewhere between eight and 10,000 disks out there now. Okay, yeah. Dave: Yeah, now what's interesting? This is what people find interesting. I believe there's about 50 million business organization, you know business entities in the country, and so let's just assume that's the number, 50 million. Brian: I mean it's tens of millions. Dave: I'm certain of that. For some reason, I think it's 50 million. Does that sound reasonable? Brian: It does so let's think it's 50 million, does that? Dave: sound reasonable. It does. So let's say it's 50 million and on your average, you know we find around one out of a hundred. You know, maybe one out of 200 companies are fit for the disc. So if we run through the math, you know one percent of 50 million, I believe, is 500, 000. You know approximate companies that we think would benefit from a disc. Yet most recent stats, there's only 2000, you know, and maybe it's 4,000, 6,000, you know. Even, let's say it's 10,000 that exists now. So if you divide 10,000 by 500,000, what is that? Like 2%, I think, of the projected eligible company actually have a disc yeah, and people can't. They always are surprised by that and I usually tell them it might. And tell me if your numbers are consistent. I say about 100. One out of 100 benefit or could benefit. The ones who could benefit 90 percent of them have never heard of the disc, maybe 95%, and the 5% of the 1% who have heard of it, even once they hear about it, they usually haven't implemented it. Brian: Right. Then there's a percent that have implemented it. They're not getting out of it what they can. Dave: Right right. Brian: So it's so. There's a lot of missed opportunities by taxpayers and everyone's always trying to save some taxes. It helps fun, you know. It might help hire another employee might help, you know, if the savings are moderate and it's 50, 6070, 1000 of tax savings that still could pay for an employee to come work at the company. Why do? Dave: you think that utilization is so low? I mean because it'd be shocking if only 2% of the companies who did research and development took advantage of the RMD tax credit. Brian: I think it's just not well known. I mean it's very esoteric, it's been in the tax code for ages and ages and it just doesn't you. You know, there were so many years where it just wasn't relevant when you think that it's not something people think about. And then if you know, if you're a small exporter and you're exporting a half a million dollars a year a million dollars a year unfortunately it probably doesn't benefit you to have a disc and so maybe someone will look at it whether that size and they're like, oh yeah, it doesn't benefit you to have a disk and so maybe someone will look at it whether that size and they're like, oh yeah, it doesn't work. And then they grow and they forget that it might work once they've grown. So once a company hits about three million of export sales really should look at it again, because that's where it starts to have economic relevance that's where it starts to have economic relevance. Dave: Do you think some of it could be that? I mean, in general, public companies don't use disks, right? Brian: They just simply don't. Dave: Okay, and so I've found that oftentimes small to mid-sized privately held companies receive a lot of their sophisticated business knowledge from their Fortune 500 suppliers or clients. You know they'll hear from them about something and you know, like the payroll protection program during COVID, you know I suspect some of those might have heard about that from you know some of their large customers. Maybe that's not a good example, but you know that could be another reason. Right, there's just a dearth of knowledge that the CPAs aren't focused on it because the economics don't make sense. The large sophisticated public suppliers and clients don't use it, so they don't hear about it from them. Right, it's not really in the news, it's just. It just kind of flies below the radar screen, doesn't it? Brian: It definitely does, and that's certainly a reason why it's not as utilized as it probably could be. Dave: Yeah, and it seems like you know most of our, you know virtually all of our clients come as a referral from either an existing client or an advisor who we've worked with other clients you know, like a CPA or attorney or banker. So yeah, it's just a yeah, even though you know the podcast is called the Icy Disc Show. I don't get the sense that I'm ever going to. You know, reach Joe Rogan's audience size. It just seems to kind of fly below the radar screen. Brian: Yeah, and the potential audience is probably a little smaller than Joe's. Dave: Probably Well. So the last thing, the other thing people tell me they're surprised about the first year of the disk return. When they set up a disk is to get everything done. And we tell them the disk return's ready and they say, super good, and e-file it for me, like the CPA does the corporate and personal returns. And what is our response when they tell us to go e-file it for them? Brian: The response is unfortunately, the IRS doesn't provide for e-filing of disk returns and we'll need to send you a paper return. You're going to need to sign it and file it with the IRS and the unfortunate thing there is gosh, I don't know what percent of the time, but it's a growing percentage of the time the IRS loses the return Right and then sends a notice saying, hey, we never filed or whatever. And some of these disk returns are quite large. The fact that they because when you do the transaction by transaction analysis, there's a lot of paper that gets produced and filed and it's shocking to me that the IRS would lose those what they do. Dave: So it's interesting what they do. So it's interesting. I like to say that not only does the ICDISC fly under the radar screen of most everything, it even, in some ways, it's almost like it flies under the radar screen of the IRS itself. Brian: Yeah, and they put some things in place with regard to the ICDISC in 1984 and have never changed it. For example, if you're in the situation where you have to pay interest on deferred tax, which often occurs. First of all, a lot of times taxpayers don't realize it and they don't do it. Secondly, if they do it. It's so antiquated that the instructions to the form where you calculate the interest it says please staple a check to this form and mail it in. I mean, who does that in 2020, right? Nobody. People, businesses prefer to do things electronically to avoid checks being stolen, fraudulent activity, so on and so forth. But here the IRS is saying staple a check to this form and mail it to Kansas City, missouri. Dave: Yeah, and I guess it kind of makes sense that you know if there's only a few thousand of these disks in existence. In the same way, you can't expect the CPA firms to make it a heavy focus, I suppose even the IRS. You know there's a hundred other tax incentives or a thousand other tax incentives that are more highly utilized that you know they maybe are spending their time on. Brian: Yeah, as I like to say, the people at the IRS that understood the disc were working there in the 70s and 80s, OK, and they're long retired. Yeah, and they're long retired. There's really not a lot of bodies at the IRS that understand the DISC and certainly when you're doing a transaction by transaction study and calculating the commission on each individual transaction, there's nobody there that understands that. Dave: Nobody Well, and it's kind of the same thing outside the IRS, right? Nobody Well, and it's kind of the same thing outside the IRS, right? I mean I have this joke that nobody makes partner at a big four firm being the IC disk expert. Oh, that's true, so it even especially nowadays. Yeah, and so it seems like like the average age of IC disks experts is about the same as the average age of the average Fortran computer language programmer. It just seems like you know new people are not coming into the disk and there's just a dearth of knowledge all around. Brian: Right, right. And I myself learned COBOL, which is a choice between Fortran and COBOL, when I was in business school, both equally non-usable. Dave: Is it part of that? Because since the disk came on in 1972, it seems like since 1973, people have been talking about the IC disk going away. So is that maybe part of it? People think, well, why should I learn something if it's going away? Brian: Maybe part of it. People think, well, why should I learn something if it's going away? There's always been a fear that it's either going to go away or that there's a technical correction coming that the disk dividend is not a qualified dividend. But the bottom line is politically, I just don't see that happening. Dave: It stands for too many things that are positive for the US Job creation export sales for too many things that are positive for the US Job creation, export sales, us companies being more competitive in the global market. Brian: So it doesn't really lend itself to be repealed. What can be repealed are some of the tax rates. Some of the tax rates can change and that can change the benefits of the disc. The concept of the disc itself and what it stands for really is very consistent with our country. Dave: Yeah, wow, I can't believe how the time has flown by, brian. Is there anything else that you want to mention about the IC disc or the MRO industry? Brian: No, I can't think of anything specifically other than I'm looking forward to being there and meeting many of the attendees and other exhibitors that are there and spending some time with you and our colleagues in Atlanta. Dave: Yeah, it will be fun. So it's the ICDISC Alliance. If you want to look us up on the website for the conference or stop by 1818BC. We also have a LinkedIn page for the ICDISC Alliance, and so I'd love to meet with any of you who are going to be at the conference. Awesome, well, thank you very much for your time, Brian. This has been really useful. Brian: You're welcome. You're very welcome. Special Guest: Brian Schwam.

What happens when political changes collide with tax enforcement? In this revealing conversation, former IRS revenue agent Jeff Johnson shares his firsthand account of being caught in the recent mass layoffs at the IRS. Having just completed seven months of intensive training, Jeff was among 7,000 probationary employees suddenly terminated as part of a broader federal workforce reduction initiative.Jeff pulls back the curtain on the agency's antiquated systems—including 1960s COBOL programming and cryptic green screens that revenue agents must master—and explains why these cuts could mean fewer audits of non-compliant taxpayers. You'll hear how experienced professionals who left established careers to serve at the IRS were dismissed with minimal notice and why this might be just the beginning of a much more significant reduction targeting up to half of the agency's 90,000 workforce.Meet Our Guest, Jeff JohnstonLinkedIn: http://www.linkedin.com/in/jon-jeffery-johnston-6812875Need CPE?Get CPE for listening to podcasts with Earmark: https://earmarkcpe.comSubscribe to the Earmark Podcast: https://podcast.earmarkcpe.comGet in TouchThanks for listening and the great reviews! We appreciate you! Follow and tweet @BlakeTOliver and @DavidLeary. Find us on Facebook and Instagram. If you like what you hear, please do us a favor and write a review on Apple Podcasts or Podchaser. Call us and leave a voicemail; maybe we'll play it on the show. DIAL (202) 695-1040.SponsorshipsAre you interested in sponsoring the Cloud Accounting Podcast? For details, read the prospectus.Need Accounting Conference Info? Check out our new website - accountingconferences.comLimited edition shirts, stickers, and other necessitiesTeePublic Store: http://cloudacctpod.link/merchSubscribeApple Podcasts: http://cloudacctpod.link/ApplePodcastsYouTube: https://www.youtube.com/@TheAccountingPodcastSpotify: http://cloudacctpod.link/SpotifyPodchaser: http://cloudacctpod.link/podchaserStitcher: http://cloudacctpod.link/StitcherOvercast: http://cloudacctpod.link/OvercastClassifiedsWant to get the word out about your newsletter, webinar, party, Facebook group, podcast, e-book, job posting, or that fancy Excel macro you just created? Let the listeners of The Accounting Podcast know by running a classified ad. Go here to create your classified ad: https://cloudacctpod.link/RunClassifiedAdTranscriptsThe full transcript for this episode is available by clicking on the Transcript tab at the top of this page

In this episode of the Mainframe Connect podcast's I Am A Mainframer series, Gerald Mitchell, Chief Testing Tools Architect and Senior Technical Staff Member at IBM, shares his journey in the mainframe industry. From his early days as an intern at IBM in 1997 to his current role revolutionising testing tools, Gerald offers unique insights into mainframe modernisation. He challenges common misconceptions about COBOL and other mainframe technologies, emphasising that modernisation isn't about abandoning platforms but optimising usage. Gerald discusses his work with Watson Code Assistant and the critical importance of validation in the development process. A highlight of the conversation is Gerald's vision for the future of mainframe technology, focusing on sustainability, AI integration, and bringing testing closer to code.

In another crossover episode, Adam Haman joins Bob to discuss the phenomenon of arguing with midwits on social media. They. beautifully illustrate the bell curve meme. Examples include the COBOL red herring regarding DOGE and Social Security, as well as Krugman's handling of the claim that excessive debt "burdens future generations."Mentioned in the Episode and Other Links of Interest:The YouTube version of this episode.Justin Wolfer's tweet endorsing the COBOL theory.Bob's EconLib article on government debt burdens.The Haman Nature page.Help support the Bob Murphy Show.

O paulistano Roberto passou a se interessar por desenvolvimento quando trabalhou com o suporte técnico dos primeiros totens interativos com um guia de eventos em São Paulo. A manutenção e as atualizações em COBOL lhe colocaram na rota para se aprofundar por front-end e back-end e, posteriormente, no saudoso portal Fulano antes de passar por algumas agências digitais.Em 2011, cansado do mercado dev, Roberto foi para a Irlanda, onde trabalhou por alguns meses na Guinness. Feito isso, ele acabou voltando para o mercado de desenvolvimento, onde ele atua até hoje – quando não está fazendo tours pelo Brasil com sua banda The Four Horsemen, cover do Metallica.Neste episódio, o Roberto conta sobre como equilibra seus hobbies e a vida profissional, além do seu processo de imigração e de adaptação na terra onde há eventos musicais de segunda a segunda. Fabrício Carraro, o seu viajante poliglota Roberto Oliveira, Líder de Tecnologia em Dublin, IrlandaLinks: Instagram da banda Four Horsemen Instagram do RobertoConheça a Formação Arquitetura .NET: da codificação ao deploy na nuvem da Alura e aprofunde seus conhecimentos em arquitetura de sistemas na plataforma .NET, desde o design de código até a implantação de sua solução na plataforma do Azure.TechGuide.sh, um mapeamento das principais tecnologias demandadas pelo mercado para diferentes carreiras, com nossas sugestões e opiniões.#7DaysOfCode: Coloque em prática os seus conhecimentos de programação em desafios diários e gratuitos. Acesse https://7daysofcode.io/Ouvintes do podcast Dev Sem Fronteiras têm 10% de desconto em todos os planos da Alura Língua. Basta ir a https://www.aluralingua.com.br/promocao/devsemfronteiras/e começar a aprender inglês e espanhol hoje mesmo! Produção e conteúdo: Alura Língua Cursos online de Idiomas – https://www.aluralingua.com.br/ Alura Cursos online de Tecnologia – https://www.alura.com.br/Edição e sonorização: Rede Gigahertz de Podcasts

Announcements: NH - Marriage age CFI letter @2:26 MO - 10 Commandments CFI letter @7:05 Follow-ups: SD - 10 Commandments @7:37 ND - 10 Commandments TX - going the other way @11:25 Pakistan arrests @14:35 News: McConnell @20:04 One last thing on RFK @24:10 RFK's problems with SRRIs @30:08 Sen. Cassidy and LA @33:03 Politics: NATO @39:39 Who determines what the law is @42:57 Social Security and COBOL @47:08 AOC v Homan @55:16 Trump effect on Federal Union @58:56 Pseudoscience: Aphrodisiacs @1:00:01 Final Stories: The Bleeding Statue @1:03:01

NO, 150-YEAR-OLDS ARE NOT COLLECTING SOCIAL SECURITY BENEFITS. And No, dead people are not collecting Social Security Benefits. There is no evidence of this fraud. None. Is there fraud somewhere? Maybe. But the reason the two presidents, Musk-Trump, think really, really old (or even dead) people are robbing Social Security is because of COBOL.   This is the definition of COBOL: COBOL an acronym for "common business-oriented language") is a compiled English-like computer programming language designed for business use. It is an imperative, procedural, and, since 2002, object-oriented language. COBOL is primarily used in business, finance, and administrative systems for companies and governments. Here is a link to the Wired article: This is a quote from "Wired." "Computer programmers quickly claimed that the 150 figure (that Musk and Trump are using) was not evidence of fraud but rather the result of a weird quirk of the Social Security Administration's benefits system, which was primarily written in COBOL, a 60-year-old programming language that undergirds SSA's databases as well as systems from many other US government agencies. COBOL is rarely used today, so Musk's cadre of young engineers may well be unfamiliar with it. Because COBOL does not have a date type, some implementations rely instead on a system whereby all dates are coded to a reference point. The most commonly used is May 20, 1875, as this was the date of an international standards-setting conference held in Paris, known as the Convention du Mètre."   Here is a link to the Wired article: https://www.wired.com/story/elon-musk-doge-social-security-150-year-old-benefits/ And a link to a Politifact Story: https://www.politifact.com/article/2025/feb/17/are-150-year-old-americans-receiving-social-securi/ Thank you for the Music Infraction.  Sport Rock Workout" is 100% no copyright royalty free rock sport track by Infraction! ----- Join our community: http://bit.ly/38egfRR  

On this episode of Ford News, Johnathan, and Brian start the show by digging into the fallout as the Department of Justice began to meddle in the work of the Southern District of New York and the indictment of New York Mayor Eric Adams. There were mass resignations and a myriad of letters going back and forth. It's something out of a movie, or, in this case, Trump's America.In segment two, we discuss the courts being the last crumbs of hope as our constitutional republic gets closer to collapse as DOGE continues to weave their way through every federal agency, haphazardly firing people and shutting departments down like they are Big Box stores from a bygone era. Segment three brings us to the "Ford Fact Check," where Johnathan walks us through the many lies told by Elon Musk as he dismantles our government. $50 Million for condoms? Gaza? Social Security Fraud?LINKSThe Southern District of New York  refused to drop charges against Mayor Eric AdamsREAD: Resignation letter from acting US attorney in New York and DOJ's response | CNN PoliticsManhattan US attorney resigns after refusing to drop case against Mayor Adams | AP NewsDanielle Sassoon and Other Officials Resign After Order to Drop Eric Adams Case - The New York TimesDOGE stopped by courtsJudge Upholds Ban on Musk's DOGE From Accessing Sensitive US Treasury Systems - NewsweekRule 4. Arrest Warrant or Summons on a Complaint | Federal Rules of Criminal Procedure | US Law | LII / Legal Information InstituteFord Fact Check Elon Musk walks back GAZA claim ‘Some of the things that I say will be incorrect': Musk backs away from false claim of $50 million for Gaza condoms | CNN PoliticsElon Musk's misinformation about Social Security Nope. There are no 150-year-olds on Social Security. It's COBOL!--UPDATED Feb 15What is COBOL?COBOL - Wikipedia

We have made progress on our new fitness app, currently codenamed, "Bento Fit." This week we provide an update about the UI, using local Swift Packages for modularization of the codebase, creating custom HealthKit metrics, thoughts on data persistence and syncing, and next steps. Plus, tangents about running local LLMs, the fortunes of COBOL programmers, and some really bad monetization ideas. If you want to get into the headspace of some developers working on a side project, this was basically our project meeting recorded, so enjoy, tangents and all!## Show Notes- Bento Fit Progress Report - https://9to5mac.com/2025/02/08/indie-app-spotlight-bentocraft/ - Temp App Icon - Very basic layout for home view - Settings view placeholder - Add view placeholder - HealthKit permissions - WatchKit integration - SPM refactor - https://www.swiftystack.com - Aaron running miles by week adventure- Stats we want to focus on - Heart metrics - Running miles per week - Caffeine / nutrients consumed- Impromptu monetization discussion - Customized metrics for IAP- How to save preference data - Shared keychain items - Swift Data / CloudKit - NSUbiquitousKeyValueStore- Tangents on Cobol, PS5, etc.- Next Steps - Explore app's personality using Sketch - Add HealthKit metrics - Add tests - Xcode Cloud setup - Add ability to add/remove cards from UI- Wrap-Up - http://phillycocoa.org- Not a Sponsor: https://miovino.app## Chapters00:00 Introductions01:09 Catch-up on Bento Fit History07:12 Bento Fit Progress Update09:03 Bento Fit Progress: Local Swift Package Refactor14:22 Bento Fit Progress: Custom HealthKit Metric17:26 Exploring HealthKit Metrics24:03 Tangent: Bad Monetization Ideas26:07 Tangent: Studio Display is Still Expensive!27:24 Tangent: More Realistic Monetization Strategies28:50 Dogfooding the Prototype31:04 Data Persistence and Syncing Strategies39:33 Tangent: Local LLMs44:48 Tangent: The Fortunes of COBOL Developers47:40 Bento Fit Next Steps01:00:53 Wrap-Up: http://phillycocoa.org01:01:14 Not a Sponsor: https://miovino.app01:03:56 TagIntro music: "When I Hit the Floor", © 2021 Lorne Behrman. Used with permission of the artist.

Čistka Elona Muska - pljačka stoljeća ili obračun s uhljebima?  Muskov DOGE (Department of Government Efficiency), državno tijelo čiji je zadatak ustanoviti gdje nepotrebno odlazi novac, ustanovio je da na godišnjoj razini "curi" oko 250 milijardi dolara. Kako bi Musk mogao vidjeti kamo se novac uplaćuje dobio je pristup Državnoj riznici - odnosno računalnim sustavu pomoću kojeg se izvršavaju sva plaćanja za cijelu federalnu vladu. Navodno podtake može samo čitati u svrhu anliziranja isplata, a na kraju će dati prijedloge koje agencije ili tijela ukinuti, a kome dati otkaz.Kada već spominjemo Big Tech igrače, Google je odlužio ažurirati svoje etičke smjernice. Maknuli su obećanje kako neće koristiti AI za razvoj oružja i nadzornih alata - što je potez kojeg opravdavaju globalnim promjenama i pitanjima nacionalne sigurnosti. Ova odluka je donesena baš u trenutku kada je vrijednost njihovih dionica pala za 8 % i kada je najvaljeno ulaganje 75 milijardi u AI. _______________00:00 Uvod01:00 Muskov DOGE je otkrio da "curi" 250 milijardi dolara06:56 Elon je dobio pristup podacima Državne riznice?11:08 Znaju li Elonovi programeri koristiti COBOL?19:03 Google je ažurirao svoje etičke smjernice... i neće proizvoditi oružje?25:13 FLOP ovog tjedna27:38 TOP ovog tjedna_______________

The Pentagon announced Saturday that it selected five small, non-traditional defense contractors to receive funding to help move their emerging technologies into production. Each company will receive $10 million under the Accelerate the Procurement and Fielding of Innovative Technologies (APFIT) pilot program overseen by Heidi Shyu, undersecretary of defense for research and engineering. The awards mark the first batch of APFIT funding distributed in fiscal 2025 and they're being bankrolled through continuing resolution appropriations. Shyu said in a statement: “With the backing of APFIT, these companies have an opportunity to push their innovations over the finish line. We look forward to supporting additional projects important to warfighters as more funding is appropriated.” APFIT is intended to steer existing innovation projects across the so-called “valley of death” — a phenomenon in which emerging technologies that have successful research-and-development efforts with the Defense Department fail to receive additional funding for production.

Ellen Chen's story of navigating a career change after her father's passing is one of introspection and reinvention. Balancing personal grief and professional demands, Ellen chose to resign from her demanding HR role. This pivotal decision allowed her to prioritize family and launch her own consulting firm. Key Questions Answered 1. What prompted Ellen Chen to share her personal story at this moment? 2. What was the health condition of Ellen's father, and what happened to him? 3. How did Ellen Chen manage both her high-demand job and her responsibilities towards her family? 4. What led Ellen Chen to contemplate and eventually decide to quit her job? 5. What structured plan did Ellen follow post-resignation? 6. How did Ellen reconnect with her family and friends during her break? 7. How does Ellen address imposter syndrome in her career and advice for others? Timestamped Overview 00:00 Immigrant, moved to Texas, studied programming, COBOL. 03:56 Imposter syndrome is natural and encourages growth. 06:53 Men apply when underqualified; women fear inadequacy. 12:10 Moved parents to Houston; Dad's passing affected me. 16:02 Quit job in 2024 with husband's support. 19:58 Reconnecting with family, staying busy, building bridges. 23:20 Personal reflection during three-month silent retreat. 25:03 Started networking and exploring job opportunities again. 29:53 Consulting leverages experience, fixes culture, saves jobs. 32:07 Pausing to discuss feelings about career change.See omnystudio.com/listener for privacy information.

Let us know your thoughts. Send us a Text Message. Follow me to see #HeadsTalk Podcast Audiograms every Monday on LinkedInEpisode Title: