Brian Scanlan, Senior Principal Engineer at Intercom, the company building Fin.ai, joins Corey Quinn on Screaming in the Cloud to discuss Intercom’s move from AWS Aurora to PlanetScale’s managed Vitess after years of scaling challenges with their Ruby on Rails monolith. He explains how 13 Aurora clusters created operational pain and why PlanetScale’s white-glove, partnership-driven model won out over Amazon’s building-block approach.

The discussion also covers Intercom’s volunteer-based on-call system, their pivot to AI agents after ChatGPT’s launch, concerns about the shrinking pipeline of systems engineers, and how companies like PlanetScale and Snowflake are outpacing AWS by delivering superior user experiences.

About Brian: Brian is an engineer based in Intercom’s Dublin office. He fixes problems, builds things, and grows people.

Show Highlights

(01:34) The Digital Clippy Rant

(2:16) The Good Chatbot vs. Bad Chatbot

(03:51) The AI Chatbot Revolution

(04:33) Unexpected Consequences of Good Chatbots

(05:42) AI Support vs. Human Support

(05:59) The Alexa Problem and Feature Discoverability

(19:03) Amazon's Struggles Moving Up the Stack

(26:55) The Unix Networking Society Origins

(34:43) The Global On-Call Challenge

(42:09) LinkedIn: The World's Largest Porn Site

Links

Intercom: intercom.com

Brian on LinkedIn: https://www.linkedin.com/in/scanlanb/

Brian on Bluesky: https://bsky.app/profile/bscanlan.bsky.social

Sponsor
Wiz - Listen to Crying Out Cloud: wiz.io/crying-out-cloud

AI is rewriting the rules of code review and CodeRabbit is leading the charge. In this featured episode of Screaming in the Cloud, Harjot Gill shares with Corey Quinn how his team built the most-installed AI app on GitHub and GitLab, nailed positive unit economics, and turned code review into a powerful guardrail for the AI era.

Show Highlights

(0:00) Entrepreneurial Journey and Code Rabbit's Origin

(3:06) The Broken Nature of Code Reviews

(5:47) Developer Feedback and the Future of Code Review

(9:50) AI-Generated Code and the Code Review Burden

(11:46) Traditional Tools vs. AI in Code Review

(13:41) Keeping Up with State-of-the-Art Models

(16:16) Cloud Architecture and Google Cloud Run

(18:21) Context Engineering for Large Codebases

(20:52) Taming LLMs and Balancing Feedback
(22:30) Business Model and Open Source Strategy

About Harjot Gill

Harjot is the CEO of CodeRabbit, a leading AI-first developer tools company.

Links

• Harjot on LinkedIn: https://www.linkedin.com/in/harjotsgill/

Sponsor
CodeRabbit: https://coderabbit.link/corey

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 Work

Links

1. Crying Out Cloud Podcast & Newsletter: https://www.wiz.io/crying-out-cloud
2. Modern (Jonathan Schneider's company): https://modern.ai
3. LinkedIn (Jonathan Schneider): https://www.linkedin.com/in/jonathanschneider/

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 Concerns
02:32 Conversations and Kindness
04:56 Niche Museums and Collecting
06:52 Blogging as a Superpower
08:01 Challenges of Writing and AI
15:08 Unique Use Cases of Dataset
19:33 The Evolution of Open Source
21:09 Security Vulnerabilities in AI
32:18 Future of AI and AGI Concerns
37:10 Learning Programming with AI
39:12 Vibe Coding and Its Risks
41:49 Environmental Impact of AI
46:34 AI in Legal and Creative Fields
54:20 Voice AI and Ethical Concerns
01:00:07 Monetizing Content Creatively

Links:

• Simon Willison’s Blog
• Datasette Project
• LLM command-line tool and Python library
• Niche Museums
• GitHub MCP prompt injection example
• Highlights from the Claude 4 system prompt
• AI energy usage tag
• AI assisted search-based research actually works now
• POSSE: Publish on your own site, syndicate elsewhere
• Bellingcat
• Lawyer cites fake cases invented by ChatGPT, judge is not amused (May 2023)
• AI hallucination cases database
• Sponsor Simon to get his monthly summary newsletter
• https://simonwillison.net/
• https://www.linkedin.com/in/simonwillison
• https://datasette.io/

Sponsor
Augment Code: https://www.augmentcode.com/

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 Struggles

About Ed Zitron
Ed 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-us
• Better off Line
• Snark bot https://bsky.app/profile/aws-snarkbot.lastweekinaws.com

Sponsor
Augment Code: https://www.augmentcode.com/

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 DBOS

Links
DBOS website: https://dbos.dev

DBOS documentation: https://docs.dbos.dev

DBOS GitHub: https://github.com/dbos-inc

DBOS Discord community: https://discord.gg/fMqo9kD

Jeremy Edberg on Twitter: https://x.com/jedberg?lang=en

AWS Heroes program: https://aws.amazon.com/developer/community/heroes/

Sponsor
https://wiz.io/scream

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 environments

About Wayne Segar

Wayne 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.

Links

Dynatrace website: https://dynatrace.com

Dynatrace free trial: https://dynatrace.com/trial

Dynatrace AI observability: https://dynatrace.com/platform/artificial-intelligence/

Wayne Segar on LinkedIn: https://www.linkedin.com/in/wayne-segar/

Sponsor

Dynatrace: http://www.dynatrace.com

How do you wrangle the chaos of AWS cost tools and live presentations? In this episode of Screaming in the Cloud, Corey Quinn is joined by AWS’s Bowen Wang and Matt Berk to break down their re:Invent talk and everything that almost went off the rails. From surprise tsunami alerts to last-minute feature changes, they explore the anxiety and art behind presenting at scale. They also look at how power user feedback shapes tools like the AWS Pricing Calculator, why storytelling matters more than specs, and what it’s like co-presenting with notes that say “make the rabbit joke.” They also discuss AWS’s internal planning process, how customers can get involved in talks, and where to catch them next.

Show Highlights

(0:00) Intro

(1:38) The Duckbill Group sponsor read

(2:35) The importance of collecting feedback before launching a product

(4:52) The difference between the intended use of a product and how it’s actually used

(8:52) How Bowen and Matt were able to be so prepared for their presentation

(13:01) What many people don’t realize goes into practicing for a presentation

(17:14) How having a storyline helped Bowen and Matt facilitate better breakout sessions

(18:26) The Duckbill Group sponsor read

(21:02) The importance of being able to go with the flow during presentations

(22:42) Why knowing your audience is essential for having a good presentation

(24:32) Choosing between breadth and depth when giving presentations

(25:05) Bowen and Matt’s advice for people who want to have their opportunity to give a talk with an AWS service team

(34:22) How to keep up with Matt and Bowen

About Matt Berk

Matt Berk is an AWS Principal Technical Account Manager at based in Brooklyn who's passionate about storytelling, cloud technologies, and FinOps. When he's not solving customer issues, Matt can be either be found in nature with his dog Ollie, at popular NYC restaurants, or at home planning his next trip to a theme park.

About Bowen Wang

Bowen Wang is a Principal Product Marketing Manager for AWS Billing and Cost Management Services, where she focuses on enabling finance and business leaders to better understand the value of the cloud and ways to optimize their cloud financial management. In her previous career, she helped a tech start-up enter the Chinese market. When she's not helping customers optimize their cloud costs, you can find her cheering for F1 races with her husband or juggling life as a mom to an energetic toddler and a playful poodle.

Links

• AWS Cloud Financial Management Blog Channel: https://aws.amazon.com/blogs/aws-cloud-financial-management/
• AWS Twitch Channel: https://www.twitch.tv/aws
• AWS Tech Tales: https://community.aws/livestreams/aws-tech-tales
• The authenticated AWS Pricing Calculator is now generally available: https://aws.amazon.com/blogs/aws-cloud-financial-management/the-authenticated-aws-pricing-calculator-is-now-generally-available/