The Transformation Trap: Why Software Modernization Is Harder Than It Looks
In this episode of Screaming in the Cloud, Corey Quinn talks with Jonathan Schneider, CEO of Moderne and author on Java microservices and automated code remediation. They explore why upgrading legacy systems is so hard, Schneider’s journey from Netflix to building large-scale code transformation tools like OpenRewrite, and how major companies like Amazon, IBM, and Microsoft use it.They also discuss AI in software development, cutting through the hype to show where it genuinely helps, and the human and technical challenges of modernization. The conversation offers a practical look at how AI and automation can boost productivity without replacing the need for expert oversight.Show Highlights(2:07) Book Writing and the Pain of Documentation(4:03) Why Software Modernization Is So Hard(6:53) Automating Software Modernization at Netflix(8:07) Culture and Modernization: Netflix vs. Google vs. JP Morgan(10:40) Social Engineering Problems in Software Modernization(13:20) The Geometric Explosion of Software Complexity(17:57) The Foundation for LLMs in Software Modernization(21:16) AI Coding Assistants: Confidence, Fallibility, and Collaboration(22:37) The Python 2 to 3 Migration: Lessons for Modernization(27:56) The Human Element: Responsibility, Skepticism, and the Future of WorkLinksCrying Out Cloud Podcast & Newsletter: https://www.wiz.io/crying-out-cloudModern (Jonathan Schneider's company): https://modern.aiLinkedIn (Jonathan Schneider): https://www.linkedin.com/in/jonathanschneider/
--------
33:26
--------
33:26
AI's Security Crisis: Why Your Assistant Might Betray You
On this episode of Screaming in the Cloud, Corey Quinn talks with Simon Willison, founder of Datasette and creator of LLM CLI about AI’s realities versus the hype. They dive into Simon’s “lethal trifecta” of AI security risks, his prediction of a major breach within six months, and real-world use cases of his open source tools, from investigative journalism to OSINT sleuthing. Simon shares grounded insights on coding with AI, the real environmental impact, AGI skepticism, and why human expertise still matters. A candid, hype-free take from someone who truly knows the space.Highlights: 00:00 Introduction and Security Concerns02:32 Conversations and Kindness04:56 Niche Museums and Collecting06:52 Blogging as a Superpower08:01 Challenges of Writing and AI15:08 Unique Use Cases of Dataset19:33 The Evolution of Open Source21:09 Security Vulnerabilities in AI32:18 Future of AI and AGI Concerns37:10 Learning Programming with AI39:12 Vibe Coding and Its Risks41:49 Environmental Impact of AI46:34 AI in Legal and Creative Fields54:20 Voice AI and Ethical Concerns01:00:07 Monetizing Content CreativelyLinks: Simon Willison’s BlogDatasette ProjectLLM command-line tool and Python libraryNiche MuseumsGitHub MCP prompt injection exampleHighlights from the Claude 4 system promptAI energy usage tagAI assisted search-based research actually works nowPOSSE: Publish on your own site, syndicate elsewhereBellingcatLawyer cites fake cases invented by ChatGPT, judge is not amused (May 2023)AI hallucination cases databaseSponsor Simon to get his monthly summary newsletterhttps://simonwillison.net/https://www.linkedin.com/in/simonwillisonhttps://datasette.io/
--------
1:05:01
--------
1:05:01
Betting on AI: The Delusion Driving Big Tech
In this deep-dive episode, Corey Quinn and Ed Zitron break down the complex and often murky world of AI and the tech giants fueling today’s rapid innovation. From Nvidia’s soaring valuations to OpenAI’s shaky finances and Microsoft’s high-stakes gambles, they reveal the cracks hidden beneath all the hype.They navigate the tangled web of corporate finance, big investments, and what could happen if the AI boom falters whether it reshapes the economy or crashes spectacularly.With sharp takes on the crossroads of AI, crypto hype, SaaS economics, and enterprise software, Cory and Ed cut through the noise to separate myth from reality. They ask: Is today’s tech gold rush truly transformative, or just another bubble pumped up by money, media, and wishful thinking?If you’re into tech or investing, this episode challenges you to look past the buzzwords and understand the real forces shaping the future of technology.Highlights (00:00) Introduction and Initial Thoughts on AI(00:53) AI Skepticism and Financial Realities(03:01) Economic Analysis of AI Companies(07:44) Microsoft and OpenAI: A Complex Relationship(11:23) The Broader AI Market and Its Challenges(16:49) Comparing AI to Other Technological Innovations(34:45) The Salesforce AI Buzzword Craze(35:09) The Disconnect Between Business Press and Valuations(36:37) Google's AI Economics and TPU Insights(39:34) Meta's Midlife Crisis and AI Investments(47:11) The Nvidia GPU Dependency(58:40) OpenAI's Financial StrugglesAbout Ed ZitronEd Zitron is the CEO of EZPR, a national public relations agency focused on technology and business. He writes the popular tech and culture newsletter Where’s Your Ed At and is the author of two books: This Is How You Pitch: How To Kick Ass In Your First Years of PR and Fire Your Publicist. Ed has been named one of Insider’s Top 50 Best Public Relations People in Tech four times.Links: Where's your ed at https://www.ezpr.com/about-usBetter off Line Snark bot https://bsky.app/profile/aws-snarkbot.lastweekinaws.com
--------
1:08:33
--------
1:08:33
Reliable Software by Default with Jeremy Edberg
Reliable software shouldn't be an accident, but for most developers it is. Jeremy Edberg, CEO of DBOS and the guy who scaled Reddit and Netflix, joins Corey Quinn to talk about his wild idea of saving your entire app into a database so it can never really break. They chat about Jeremy's "build for three" rule, a plan for scale without going crazy, why he set Reddit's servers to Arizona time to dodge daylight saving time, and how DBOS makes your app as tough as your data. Plus, Jeremy shares his brutally honest take on distributed systems cargo cult, autonomous AI testing, and why making it easy for customers to leave actually keeps them around.Public Bio: Jeremy is an angel investor and advisor for various incubators and startups, and the CEO of DBOS. He was the founding Reliability Engineer for Netflix and before that he ran ops for reddit as its first engineering hire. Jeremy also tech-edited the highly acclaimed AWS for Dummies, and he is one of the six original AWS Heroes. He is a noted speaker in serverless computing, distributed computing, availability, rapid scaling, and cloud computing, and holds a Cognitive Science degree from UC Berkeley.Show Highlights(02:08) - What DBOS actually does(04:08) - "Everything as a database" philosophy and why it works(08:26) - "95% of people will never outgrow one Postgres machine"(10:13) - Jeremy's Arizona time zone hack at Reddit (and whether it still exists)(11:22) - "Build for three" philosophy without over-engineering(17:16) - Extracting data from mainframes older than the founders(19:00) - Autonomous testing with AI trained on your app's history(20:07) - The hardest part of dev tools(22:00) - Corey's brutal pricing page audit methodology(27:15) - Why making it easy to leave keeps customers around(34:11) - Learn more about DBOSLinksDBOS website: https://dbos.devDBOS documentation: https://docs.dbos.devDBOS GitHub: https://github.com/dbos-incDBOS Discord community: https://discord.gg/fMqo9kDJeremy Edberg on Twitter: https://x.com/jedberg?lang=enAWS Heroes program: https://aws.amazon.com/developer/community/heroes/
--------
35:54
--------
35:54
See Why GenAI Workloads Are Breaking Observability with Wayne Segar
What happens when you try to monitor something fundamentally unpredictable? In this featured guest episode, Wayne Segar from Dynatrace joins Corey Quinn to tackle the messy reality of observing AI workloads in enterprise environments. They explore why traditional monitoring breaks down with non-deterministic AI systems, how AI Centers of Excellence are helping overcome compliance roadblocks, and why “human in the loop” beats full automation in most real-world scenarios.From Cursor’s AI-driven customer service fail to why enterprises are consolidating from 15+ observability vendors, this conversation dives into the gap between AI hype and operational reality, and why the companies not shouting the loudest about AI might be the ones actually using it best.Show Highlights(00:00) - Cold Open(00:48) – Introductions and what Dynatrace actually does(03:28) – Who Dynatrace serves(04:55) – Why AI isn't prominently featured on Dynatrace's homepage(05:41) – How Dynatrace built AI into its platform 10 years ago(07:32) – Observability for GenAI workloads and their complexity(08:00) – Why AI workloads are "non-deterministic" and what that means for monitoring(12:00) – When AI goes wrong(13:35) – “Human in the loop”: Why the smartest companies keep people in control(16:00) – How AI Centers of Excellence are solving the compliance bottleneck(18:00) – Are enterprises too paranoid about their data?(21:00) – Why startups can innovate faster than enterprises(26:00) – The "multi-function printer problem" plaguing observability platforms(29:00) – Why you rarely hear customers complain about Dynatrace(31:28) – Free trials and playground environmentsAbout Wayne SegarWayne Segar is Director of Global Field CTOs at Dynatrace and part of the Global Center of Excellence where he focuses on cutting-edge cloud technologies and enabling the adoption of Dynatrace at large enterprise customers. Prior to joining Dynatrace, Wayne was a Dynatrace customer where he was responsible for performance and customer experience at a large financial institution. LinksDynatrace website: https://dynatrace.comDynatrace free trial: https://dynatrace.com/trialDynatrace AI observability: https://dynatrace.com/platform/artificial-intelligence/Wayne Segar on LinkedIn: https://www.linkedin.com/in/wayne-segar/SponsorDynatrace: http://www.dynatrace.com
Screaming in the Cloud with Corey Quinn features conversations with domain experts in the world of Cloud Computing. Topics discussed include AWS, GCP, Azure, Oracle Cloud, and the "why" behind how businesses are coming to think about the Cloud.
Brasil