Fixing Shadow AI and Surviving re:Invent with Chase Douglas

In this episode of Screaming in the Cloud, host Corey Quinn sits down with Roi Lipman, CTO and co-founder of Falco DB, to unpack the evolving role of graph databases in a world overflowing with data stores. Roi shares his journey from building RedisGraph at Redis to spinning it out into Falco DB, along with his enduring love of the C programming language (dad jokes included). The conversation explores why graph databases remain niche, but powerful, especially for pathfinding problems like supply chains and access management, how vector search became a feature rather than a standalone database, and what AI-assisted development means for modern engineering. Along the way, they tackle open source sustainability, Rust rewrites, AI-generated pull request chaos, and the looming question of where the next generation of senior engineers will come from.Highlights: (00:00) C Language(00:27) Welcome(01:18) Database Landscape Overview(03:17) Why Graph Databases Matter(07:25) AI Built Apps and Data Choices(10:29) How FalcoDB Fits In(12:20) Vector Search as a Feature(16:48) FalcoDB Origin Story(19:54) Open Source Business and Rust Rewrite(25:23) Toy Graph Problems and Closing ThoughtsSponsored by: duckbillhq.com

This week on Screaming in the Cloud, Corey sits down with Chris Hill, CEO of Humble Pod, to talk about the messy, nuanced reality of AI in media. From secretly cloning Corey’s voice for an ad using ElevenLabs (and almost getting away with it) to the growing tension between polished production and authentic content, they unpack what AI can actually do versus what it claims to do.They explore the shifting economics of podcasting, the rise of video-first formats, Netflix’s entrance into the space, and why “good enough” production often beats expensive studio perfection. It’s a candid conversation about trust, automation, creative integrity, and why sometimes the most dangerous AI use case is the one no one notices.Show Highlights:(00:00) The AI Voice Clone Ad Nobody Noticed(00:44) 700 Episodes In: Catching Up with Humble Pod’s Chris Hill(01:16) New Studio, New Vibes: Building a Podcast Space in Tennessee(01:51) AI in Podcasting Workflows: Riverside, Editing Promises & Human Judgment(07:50) Authenticity vs Production Value + Duckbill Hiring & Product Shift(14:05) Renewals, churn, and why point solutions fail(14:15) The Doc Tools saga: building the wrong thing (and Disney lawyers)(15:15) Bahamas studio build: consulting where quality really matters(16:34) Gear talk & pro tips: teleprompters, cameras, and looking at the lens(18:50) Podcasting goes video-first: clips, discovery, TikTok, and the wrap-upAbout Chris Hill: Chris Hill is a Knoxville, TN native and founder of Humble Pod, where he helps brands, startups, and thought leaders develop, launch, and grow podcasts across the U.S. and beyond. He works with clients ranging from local Knoxville businesses to entrepreneurs in Silicon Valley and around the world.Chris is the co-host and producer of Our Humble Beer Podcast and lectures on podcasting and marketing at the University of Tennessee. He earned his undergraduate degree in Marketing & Entrepreneurship from the University of Tennessee at Chattanooga and later received his MBA from King University.He currently serves as President of the American Marketing Association Knoxville chapter and enjoys supporting the local craft beer community, traveling internationally, and exploring the outdoors.Links: Humblepod: https://www.humblepod.com/Sponsored by: duckbillhq.com

Eric Anderson, partner at VC firm Scale, talks about why coding agents changed software forever and why the AI bubble can't be avoided. Eric worked on Spot Instances at AWS and data products at Google before becoming a VC. He explains how companies can still compete against Anthropic and OpenAI by staying laser-focused instead of fighting on every front.Corey and Eric discuss why AWS didn’t kill all startups even when they launched competing products, why the AI bubble can't be avoided when companies go from $1 billion to $7 billion in revenue in one year, and why the best AI products don't scream “AI” everywhere in their marketing.Show Highlights:(02:30) Building Spot Instances at AWS(07:41) Why Coding Agents Changed Everything(10:35) Agents Doing Code Review Now(13:53) Competing with Frontier Labs(17:05) Why AWS Didn’t Kill All Startups(19:01) Finding the Right Front to Fight On(22:20) Why the Bubble Is Inevitable(23:36) AI Pricing Will Eventually Crash(26:33) Honeycomb’s AI Done Right(28:04) Where to Find EricLinks: Scale: https://www.scalevp.com/Eric on LinkedIn: https://www.linkedin.com/in/ericmand/Sponsored by: duckbillhq.com

Chase Douglas, CEO at Archodex, talks about AI security problems and why re:Invent has become a nightmare. Chase helps companies capture every AI interaction so they don't get in trouble with compliance. Corey and Chase discuss Shadow AI, why Corey runs Claude Code in an account called “Superfund,” and how re:Invent put metal spikes on benches so people couldn't sit down. They also talk about why AWS released fewer announcement than before, and why Chase is finally optimistic about AI coding tools after months of frustration.Show Highlights: (01:51) What Archodex Does(07:00) The Superfund Account for AI(08:19) Shadow AI Problem(11:41) What Happened at re:Invent (14:59) Sponsorship Costs at re:Invent(17:00) Metal Spikes on Benches(21:39) AWS Releases Declining (25:24) Why Chase Is Finally Optimistic About AI Coding(27:13) Code Review Changed with AI(31:22) Where to Find ChaseLinks: Archodex: https://archodex.comLinkedIn: https://www.linkedin.com/in/chasedouglas/Sponsored by: duckbillhq.com

Alyss Noland, who works on Cloud Dev Ecosystem at Nvidia, is back on the show to talk about building software with AI when you're not a real developer. Alyss runs a program that gives AI startups access to Nvidia GPUs and uses AI tools herself to build production software at Nvidia. Corey and Alyss discuss using AI to help curate newsletters without actually writing them, why humans still need to check everything, and the weird reality of people developing relationships with chatbots. Show Highlights: (01:34) What Alyss Does at Nvidia(05:44) When AI First Worked for Corey(07:34) Building Internal Tools vs Using AI(10:39) Using AI to Help Write Last Week in AWS (13:43) DGX Cloud Innovation Lab (17:11) Building Production Software with AI (20:48) The Future of SEO (25:24) Using AI as a Writing Assistant (29:51) closing remarksLinks:Alyss’s LinkedIn: https://www.linkedin.com/in/alyssnoland/Alyss’s Personal Website: https://dev.to/preciselyalyssSponsored by: duckbillhq.com

Mike McQuaid, Project Leader of Homebrew, joins Corey Quinn to share how a package manager conceived in a London pub became essential for 10 million Mac users. Homebrew lets you install software with one command instead of downloading files and clicking through installers, maintained by just 30 people who each get $300 a month.Mike shares the origin story from a drunken conversation about package management, explains how Homebrew Bundle can set up a new Mac with one command, and why Homebrew refuses to package software with fake open source licenses like Terraform's new versions.Show Highlights:(01:44) Why Homebrew Works on Linux(04:02) The Curl Bash Security Problem(05:02) Homebrew Was Conceived in a London Pub(06:42) Apps That Auto-Update Four Times a Day(08:43) Brew Bundle(14:00) Why Homebrew Auto-Updates Itself(18:18) Homebrew Maintainers Get $300 a Month(22:19) The Brew Doctor Command(29:10) Why Homebrew Doesn't Package Fake Open Source(32:05) Open Source Is Not a Career(35:27) When Someone Blamed Homebrew for Breaking Their Business(37:39) Auto-Update Options for Homebrew(39:40) Where to Find MikeLinks:Website: https://mikemcquaid.comHomebrew: https://brew.shGitHub: https://github.com/homebrewSponsored by: duckbillhq.com

When your website stops working at 3 AM, you need to answer one question fast: Is it my code or is a big cloud provider having problems? Omri Sass from Datadog explains updog.ai, a tool that monitors whether major services like AWS, CloudFlare, and others are actually working. Instead of asking people to report problems like Down Detector does, updog uses real data from thousands of computers to detect when services go down. Omri shares why this took 6 years to build, how they process massive amounts of data with machine learning, and why cloud providers have been strangely upset about these tools existing.About Omri: Omri Sass is a Director of Product Management at Datadog, where he leads and supports a team of 25+ product managers driving initiatives across Bits AI SRE, Data Observability, Service Management, and most recently, the launch of updog.ai. Outside of work, Omri is an avid sci-fi reader, a dedicated yoga practitioner, and happily outmatched by his cat.Show Highlights:(02:12) What is Updog and How Does It Work(03:38) Why Knowing If It's a Global Problem Matters(04:01) The Problem With Testing Every Endpoint Yourself(05:52) How Datadog Discovered EC2 Outages From Their Own Systems(10:38) When AWS Regions Go Down and Cascade Failures(13:13) What Happens When Services Rebuild Completely(16:29) The Most Important Learning During a 3 AM Incident(20:11) Why This Took So Long to Build(23:40) When Datadog Going Down Isn't Critical Path(25:22) How They Picked Which AWS Services to Monitor(27:07) What Comes Next for Updog(30:11) Where to Find Omri and UpdogLinks: Datadog: datadoghq.comOmir’s LinkedIn: https://www.linkedin.com/in/omri-sass-65632a14/Sponsored by: duckbillhq.com

Hunter Leath, CEO of Archil, spent 8 years building Amazon's EFS file storage system, learning exactly why making cloud storage act like a hard drive always fails. Old programs need hard drives, but cloud storage doesn't work like hard drives—a problem that's existed for 20 years.Now Hunter's building Archil, which puts super-fast storage between programs and S3 so they can finally work together. Your programs think they're talking to a regular disk while your data lives safely in the cloud.Hunter explains how they're doing what others couldn't, why it costs less than Amazon's own solutions, and why file systems suddenly matter again in the AI era.Show Highlights:(01:37) What Archil Does and Why It Exists(02:26) Why Mounting S3 as a File System Has Always Failed(03:07) What Building EFS Taught Hunter(06:55) Using Fast SSDs as a Cache Layer for S3(09:45) Attaching Archil to Your Existing S3 Buckets(15:08) Why Archil Costs Less Than EBS When You Do the Math(17:56) What Happens If Amazon Builds This Feature(19:20) Competing With EBS Performance on GP3 Volumes(21:43) Raising $6.7 Million Without an AI Pitch(23:46) What Customers Get Wrong About Archil(28:07) Accessing Data Stored in Glacier Deep Archive(29:24) The Plan to Get Into the Linux Kernel (30:51) Where to Find HunterAbout Hunter Leath: Hunter is the founder and CEO of Archil, which transforms S3 buckets into infinite, local file systems that provide instant access to massive data sets. Prior to Archill, Hunter spent the last ten years in the cloud storage industry, including 8 years building Amazon's Elastic File System product and one year on Netflix's core storage team.Links:Hunter Leath on LinkedIn: https://www.linkedin.com/in/hleath/Hunter Leath on X: https://x.com/jhleath/Archil’s Website: https://archil.comSponsored by: duckbillhq.com

When AWS has a major outage, what actually happens behind the scenes? Ben Hartshorne, a principal engineer at Honeycomb, joins Corey Quinn to discuss a recent AWS outage and how they kept customer data safe even when their systems couldn't fully work. Ben explains why building services that expect things to break is the only way to survive these outages. Ben also shares how Honeycomb used its own tools to cut their AWS Lambda costs in half by tracking five different things in a spreadsheet and making small changes to all of them.About Ben Hartshorne: Ben has spent much of his career setting up monitoring systems for startups and now is thrilled to help the industry see a better way. He is always eager to find the right graph to understand a service and will look for every excuse to include a whiteboard in the discussion.Show highlights: (02:41)Two Stories About Cost Optimization(04:20) Cutting Lambda Costs by 50%(08:01) Surviving the AWS Outage(09:20) Preserving Customer Data During the Outage(13:08) Should You Leave AWS After an Outage?(15:09) Multi-Region Costs 10x More(18:10) Vendor Dependencies(22:06) How LaunchDarkly's SDK Handles Outages(24:40) Rate Limiting Yourself(29:00) How Much Instrumentation Is Too Much?(34:28) Where to Find BenLinks: Linkedin: https://www.linkedin.com/in/benhartshorne/GitHub: https://github.com/maplebedSponsored by: duckbillhq.com

R. Tyler Croy, a principal engineer at Scribd, joins Corey Quinn to explain what happens when simple tasks cost $100,000. Checking if files are damaged? $100K. Using newer S3 tools? Way too expensive. Normal solutions don't work anymore. Tyler shares how with this much data, you can't just throw money at the problem, but rather you have to engineer your way out.About R. Tyler: R. Tyler Croy leads infrastructure architecture at Scribd and has been an open source developer for over 14 years. His work spans the FreeBSD, Python, Ruby, Puppet, Jenkins, and Delta Lake communities. Under his leadership, Scribd’s Infrastructure Engineering team built Delta Lake for Rust to support a wide variety of high performance data processing systems. That experience led to Tyler developing the next big iteration of storage architecture to power large-scale fulltext compute challenges facing the organization.Show Highlights:01:48 Scribd's 18-Year History04:00 One Document Becomes Billions of Files05:47 When Normal Physics Stop Working08:02 Why S3 Metadata Costs Too Much10:50 How AI Made Old Documents Valuable13:30 From 100 Billion to 100 Million Objects15:05 The Curse of Retail Pricing 19:17 How Data Scientists Create Growth21:18 De-Normalizing Data Problems25:29 Evolving Old Systems27:45 Billions Added Since Summer29:29 Underused S3 Features31:48 Where to Find TylerLinks: Scribd: https://tech.scribd.comMastodon:  https://hacky.town/@rtylerGitHub: https://github.com/rtylerSponsored by: duckbillhq.com