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 remarks

Links:

Alyss’s LinkedIn: https://www.linkedin.com/in/alyssnoland/

Alyss’s Personal Website: https://dev.to/preciselyalyss

Sponsored 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 Mike

Links:

Website: https://mikemcquaid.com

Homebrew: https://brew.sh

GitHub: https://github.com/homebrew

Sponsored 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 Updog

Links:

Datadog: datadoghq.com

Omir’s LinkedIn: https://www.linkedin.com/in/omri-sass-65632a14/

Sponsored by:
duckbillhq.com