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She literally broke down how to run evals in Claude Code (built the whole thing live): 01:34 - What people get wrong with evals 04:35 - Why product taste is the alpha now 09:28 - Building a PM agent from one prompt 19:00 - Instrumentation without writing code 22:00...

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Aakash Gupta

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150,362 Aufrufe • vor 3 Monaten •via X (Twitter)

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New session with Shreya Shankar on How to Automate Evals with AI (correctly) The most important part of the eval workflow is finding issues. Shreya does a live demo of how to steer the AI iteratively to find unknown unknowns Chapter summaries: 00:00:00 Introduction 00:00:55 Why vendors want to automate evals for you 00:01:45 Why no tool can fully automate evals 00:06:00 Mistake #1: Asking AI to just "find the issues" in your data 00:08:11 What good AI-assisted error analysis actually looks like 00:11:12 Live demo: building a review interface from scratch 00:15:10 Annotating traces and building a failure mode taxonomy 00:19:31 Mistake #2: Only reviewing your data once 00:22:53 Mistake #3: Treating all apps with the same accuracy bar 00:25:10 General-purpose agents vs. dedicated eval tools 00:25:48 Summary: three rules for automating evals correctly YT links and more in reply
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New session with Shreya Shankar on How to Automate Evals with AI (correctly) The most important part of the eval workflow is finding issues. Shreya does a live demo of how to steer the AI iteratively to find unknown unknowns Chapter summaries: 00:00:00 Introduction 00:00:55 Why vendors want to automate evals for you 00:01:45 Why no tool can fully automate evals 00:06:00 Mistake #1: Asking AI to just "find the issues" in your data 00:08:11 What good AI-assisted error analysis actually looks like 00:11:12 Live demo: building a review interface from scratch 00:15:10 Annotating traces and building a failure mode taxonomy 00:19:31 Mistake #2: Only reviewing your data once 00:22:53 Mistake #3: Treating all apps with the same accuracy bar 00:25:10 General-purpose agents vs. dedicated eval tools 00:25:48 Summary: three rules for automating evals correctly YT links and more in reply

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34,196 Aufrufe • vor 1 Monat

I'm often asked for the best public example of AI evals done right for a real, production product. I finally have an answer. Teresa Torres shares how she shipped an AI interview coach, and used evals to rapidly squash bugs and improve the product. Teresa shows how she: 1. did error analysis FIRST to find real issues (instead of using generic metrics) 😍 2. used Jupyter notebooks to analyze errors 3. built custom annotation tools + custom widgets in notebooks 4. built a LLM-judge and assertions to test for specific errors 5. iterated through this feedback loop until it worked. 6. kept things simple the whole time It's also probably the best commercial for Jupyter notebooks you can imagine. 🥰 Chapter summary below. Link to YT in next thread 00:00:00 - Intro 00:01:45 - The Product: Building an AI Interview Coach 00:06:34 - The Problem: How Do I Know if My AI Coach is Any Good? 00:10:15 - Using Airtable for Traces and Annotation 00:12:15 - Discovering Jupyter Notebooks and Designing the First Evals 00:15:15 - Example Evals: LLM-as-Judge vs. Code-Based Assertions 00:21:00 - Learning Python with ChatGPT to Analyze Eval Results 00:31:00 - VS Code, Custom Tools, and an Eval Investigation Notebook 00:39:45 - Building a Custom Annotation Tool with Claude 00:41:00 - From Personal Project to Production App 00:46:02 - How Should PMs and Engineers Collaborate on AI Products? 00:55:45 - Q&A: Capturing Feedback and Annotations from End Users 00:58:11 - Q&A: Is a Technical Background Necessary to Build AI? 01:02:28 - Q&A: What's Next for Teresa? 01:03:13 - Q&A: Unpacking the Micro-Decisions of Building an AI App
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I'm often asked for the best public example of AI evals done right for a real, production product. I finally have an answer. Teresa Torres shares how she shipped an AI interview coach, and used evals to rapidly squash bugs and improve the product. Teresa shows how she: 1. did error analysis FIRST to find real issues (instead of using generic metrics) 😍 2. used Jupyter notebooks to analyze errors 3. built custom annotation tools + custom widgets in notebooks 4. built a LLM-judge and assertions to test for specific errors 5. iterated through this feedback loop until it worked. 6. kept things simple the whole time It's also probably the best commercial for Jupyter notebooks you can imagine. 🥰 Chapter summary below. Link to YT in next thread 00:00:00 - Intro 00:01:45 - The Product: Building an AI Interview Coach 00:06:34 - The Problem: How Do I Know if My AI Coach is Any Good? 00:10:15 - Using Airtable for Traces and Annotation 00:12:15 - Discovering Jupyter Notebooks and Designing the First Evals 00:15:15 - Example Evals: LLM-as-Judge vs. Code-Based Assertions 00:21:00 - Learning Python with ChatGPT to Analyze Eval Results 00:31:00 - VS Code, Custom Tools, and an Eval Investigation Notebook 00:39:45 - Building a Custom Annotation Tool with Claude 00:41:00 - From Personal Project to Production App 00:46:02 - How Should PMs and Engineers Collaborate on AI Products? 00:55:45 - Q&A: Capturing Feedback and Annotations from End Users 00:58:11 - Q&A: Is a Technical Background Necessary to Build AI? 01:02:28 - Q&A: What's Next for Teresa? 01:03:13 - Q&A: Unpacking the Micro-Decisions of Building an AI App

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Our new podcast on evals, with Max Niederman, Ege Erdil, and Stephen Yang. 0:00:00 – What's an eval, and how's it different from an RL environment? 0:19:33 – Why are models bad at building an emulator when the task is fully verifiable? 0:42:00 – How does training on bad data teach models to write terrible code? 1:04:00 – Why is continual learning still so bad? 2:25:24 – Why haven't software engineers been replaced when coding is basically solved? Listen to the Mechanize Podcast on YouTube, Spotify, etc. Enjoy!
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Bret Weinstein, Viva Frei and Jimmy Dore tangle over who shot Charlie Kirk, and how. 00:00:00 Three people, three positions, one killing 00:01:16 Sponsor: SaunaSpace 00:03:39 Sponsor: MUD\WTR 00:05:27 Where each of us has landed as of today 00:05:47 Viva Frei: it was a bullet from the Losee roof 00:08:41 Jimmy Dore: the case for a cover-up 00:16:41 When a Question Becomes an Accusation 00:18:15 Morality as a Substitute for Argument 00:21:27 Sponsor: Helix 00:22:42 A Biologist's Toolkit 00:25:35 George Zinn and the Reflex to Confess 00:29:42 Paving the Courtyard 00:38:11 The Exploding Microphone 00:45:09 Joe Kent Says He Was Stopped 00:46:50 The Mic That Should Have Recorded It 00:52:58 O'Neill, the Hamptons, and 39 Minutes 00:57:28 "You Don't Have an FBI" 00:59:26 Butler and the Roof Nobody Covered 01:06:27 Harpole, Shawn Ryan, and the Drones 01:11:48 The Prosecutor's Fallacy 01:15:29 Drones and a Plane at 200 Feet 01:22:06 Foreign Nexus, or Domestic 01:29:07 Retroactive Continuity 01:33:21 What Ballistics Can and Cannot Show 01:38:10 A Potemkin Explanation 01:44:14 TPUSA After Charlie 01:49:20 Iran, Motive, and What Charlie Opposed 01:51:26 "Who I Fear Is the People..." 01:56:31 A Nation, or Whatever Controls It 02:00:43 The Phone, the Necklace, the Car 02:04:39 The Emergency Cleanup Order 02:07:20 When No Answer Will Be Believed 02:09:34 Conspiracy Psychosis 02:10:47 Closing Thoughts

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The DarkHorse Podcast

11,252 Aufrufe • vor 6 Monaten

It's brain versus AI time. Here's our full episode with Sebastian Seung. He's started a new company to reverse engineer the brain and master the intelligence created by nature with the hopes of informing the intelligence we've created with machines. Sebastian has done pioneering AI and neuroscience work and is now blending the two to make a digital brain. Mostly, he's fun to listen to. The Core Memory podcast is made by possible by the intelligent finance powerhouse Brex and the people who back the biggest ideas @e1ventures. Timestamps 00:00:00 - Intro 00:01:42 - Who is Sebastian Seung? 00:03:23 - What is a Connectome? 00:07:08 - The Connectome Winter 00:09:08 - Diamond Knives & AI 00:12:10 - When Will We Map the Human Brain? 00:18:09 - The "Brain Crystal" & Visual Neurons 00:26:31 - New Startup 00:33:55 - Simulating a Mind in Software 00:37:40 - Biology vs. Nvidia 00:44:04 - Is AI a Religious Quest? 00:50:05 - Mind Uploading & Transhumanism 00:59:26 - Brain-Computer Interfaces 01:06:41 - From Physics to Neuroscience 01:12:22 - Will Uploads Be Conscious? 01:19:37 - Neuromorphic Chips & Future Robotics
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39,041 Aufrufe • vor 8 Monaten

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Riley Brown

57,794 Aufrufe • vor 5 Monaten

Some personal news - I am launching a podcast HD in HD Podcast to share what would normally be offline conversations with exceptional people online. Have had the great fortune of co-founding BRex which has led to several great relationships with other builders over the years. I find that the best way to learn anything is through conversations with brilliant people. To kick things off, listen in on a thoughtful conversation with Vlad Tenev. Hope you enjoy these off the script conversations. 00:00:00 Introduction 00:01:00 Decision to stop drinking 00:07:26 Day of the IPO feeling 00:12:37 How Vlad was as a kid 00:19:51 Raising kids 00:24:01 Source of motivation 00:24:48 Getting into Stanford 00:30:05 Time at Stanford 00:33:32 Grad school 00:42:25 First company 00:48:35 Second company 00:53:10 Beginning of Robinhood 00:59:54 Positioning of Robinhood 01:04:04 Being depicted in movies 01:12:06 Trader influencers 01:15:27 Serving active traders 01:20:26 Meeting wife 01:27:13 Downsides & upsides of being a CEO 01:31:30 Minimizing phone addiction 01:35:06 GameStop 01:49:02 Final learnings
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Some personal news - I am launching a podcast HD in HD Podcast to share what would normally be offline conversations with exceptional people online. Have had the great fortune of co-founding BRex which has led to several great relationships with other builders over the years. I find that the best way to learn anything is through conversations with brilliant people. To kick things off, listen in on a thoughtful conversation with Vlad Tenev. Hope you enjoy these off the script conversations. 00:00:00 Introduction 00:01:00 Decision to stop drinking 00:07:26 Day of the IPO feeling 00:12:37 How Vlad was as a kid 00:19:51 Raising kids 00:24:01 Source of motivation 00:24:48 Getting into Stanford 00:30:05 Time at Stanford 00:33:32 Grad school 00:42:25 First company 00:48:35 Second company 00:53:10 Beginning of Robinhood 00:59:54 Positioning of Robinhood 01:04:04 Being depicted in movies 01:12:06 Trader influencers 01:15:27 Serving active traders 01:20:26 Meeting wife 01:27:13 Downsides & upsides of being a CEO 01:31:30 Minimizing phone addiction 01:35:06 GameStop 01:49:02 Final learnings

Henrique Dubugras

27,801 Aufrufe • vor 1 Jahr

It’s been almost a year since Samantha Steele Ponder was abruptly fired by ESPN. Since then, she has been in a self-described hibernation…until now. This is not an interview, it’s a conversation. It’s Sam’s story. Her story of why she believes she was fired, how that awful moment prompted endless self-reflection…changing her life in the most beautiful ways. Being fired helped her marriage, helped her relationship with her kids, changed her perspective on so much, and strengthened her beliefs in many other ways. (00:02:18) – How Sam Got Fired From ESPN (00:14:22) – Men in Women’s Sports (00:19:17) – What Money & Fame Does to You (00:28:17) – Being Disciplined by God (00:34:28) – Our Friendship (00:43:01) – Being a Woman in Sports (00:50:19) – Life at ESPN (00:59:15) – Life After TV (01:08:33) – The Stressful Reality of Live TV (01:23:09) – Hearing the Voice of God (01:46:06) – Sam’s Message to the People
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The Left's Renee Good Narrative Has Completely Collapsed. Here's Why. TIMESTAMPS: 00:00 - 00:25 Opening 00:50 - 38:59 The Left's Renee Good Narrative Has Completely Collapsed. Here's How. 40:23 - 45:00 Portland Police Chief Breaks Down In Tears Over "Historic Injustice" 48:15 - 58:50 Ashley St. Clair Is Moving Rapidly Toward The Left 58:51 - 01:03:22 Liberal White Woman Cries And Paints Her Face To Honor Renee Good In Cringy TikTok 01:03:22 - 01:09:45 Matt Reads Amanda Gorman's Abysmal Poem About Renee Good

The Matt Walsh Show

15,104 Aufrufe • vor 7 Monaten

💥NEW AI CODING TUTORIAL: 12 Months of Claude Code Lessons in 46 Minutes Claude Code just turned 1. So here's 52 lessons on how to get the most out of Claude Code, organized into 3 levels: Beginner, Intermediate, and Master. TIMESTAMPS 00:00 12 Months of building with Claude Code 02:01 LEVEL 1: Beginner 02:09 Installation and Setup 04:55 Models and Modes 09:04 CLAUDE.md (and what to put in) 10:30 Context Management 11:31 Debugging with Claude 12:22 Version control 14:12 Prompting, Just ask Claude 16:01 LEVEL 2: Intermediate 16:24 Customizations (Skills, Plugins, MCPs) 24:42 Workflows: Plan, Build, Test 29:52 Verifying and Documenting with Claude 33:10 LEVEL 3: Master 34:17 Multi-Agent Development (multi-clauding with git worktrees) 37:07 Self-improving Systems 38:45 Ralph Wiggum Agent Loops 40:11 Async Task Delegation 42:00 Agent Teams, Pre-configure permissions, Hooks 44:42 Continue your learning
45:47

💥NEW AI CODING TUTORIAL: 12 Months of Claude Code Lessons in 46 Minutes Claude Code just turned 1. So here's 52 lessons on how to get the most out of Claude Code, organized into 3 levels: Beginner, Intermediate, and Master. TIMESTAMPS 00:00 12 Months of building with Claude Code 02:01 LEVEL 1: Beginner 02:09 Installation and Setup 04:55 Models and Modes 09:04 CLAUDE.md (and what to put in) 10:30 Context Management 11:31 Debugging with Claude 12:22 Version control 14:12 Prompting, Just ask Claude 16:01 LEVEL 2: Intermediate 16:24 Customizations (Skills, Plugins, MCPs) 24:42 Workflows: Plan, Build, Test 29:52 Verifying and Documenting with Claude 33:10 LEVEL 3: Master 34:17 Multi-Agent Development (multi-clauding with git worktrees) 37:07 Self-improving Systems 38:45 Ralph Wiggum Agent Loops 40:11 Async Task Delegation 42:00 Agent Teams, Pre-configure permissions, Hooks 44:42 Continue your learning

Avthar

62,263 Aufrufe • vor 5 Monaten

California is America's most populous, prosperous, and perhaps most beautiful state, and it sets trends for the rest of the country. But it's also perhaps the most broken state. Today, California Sheriff Chad Bianco is running for Governor and wants to lead California back to sanity: zero-income tax, oil independence, parental rights, and so much more. Can he do it? 00:00:00 - Intro 00:03:18 - Understanding California Governor elections 00:06:10 - Sheriff Chad’s background 00:14:40 - What does it mean to be sheriff? 00:18:12 - Gavin Newsom Rant 00:21:13 - Making life better in Riverside County 00:35:17 - Discretion in Law Enforcement 00:48:28 - Policy Differences Between Candidates 00:56:22 - Steve Hilton’s criticism of Chad 01:04:11 - First person to end the riots 01:10:59 - Eliminating Income Tax?! 01:20:00 - Wildlife 01:23:29 - Parental Rights, Education, Vaccines 01:27:53 - Pregnancy Resource Centers 01:35:19 - Why are you going to win?
1:41:15

California is America's most populous, prosperous, and perhaps most beautiful state, and it sets trends for the rest of the country. But it's also perhaps the most broken state. Today, California Sheriff Chad Bianco is running for Governor and wants to lead California back to sanity: zero-income tax, oil independence, parental rights, and so much more. Can he do it? 00:00:00 - Intro 00:03:18 - Understanding California Governor elections 00:06:10 - Sheriff Chad’s background 00:14:40 - What does it mean to be sheriff? 00:18:12 - Gavin Newsom Rant 00:21:13 - Making life better in Riverside County 00:35:17 - Discretion in Law Enforcement 00:48:28 - Policy Differences Between Candidates 00:56:22 - Steve Hilton’s criticism of Chad 01:04:11 - First person to end the riots 01:10:59 - Eliminating Income Tax?! 01:20:00 - Wildlife 01:23:29 - Parental Rights, Education, Vaccines 01:27:53 - Pregnancy Resource Centers 01:35:19 - Why are you going to win?

lilaroseshow

76,657 Aufrufe • vor 6 Monaten

Is Jason Arday just a liar? Peter Boghossian joins me on DarkHorse to discuss. 00:00:00 Jason Arday Exposes the Academy 00:02:34 Sponsor: Sundays for Dogs 00:04:25 Sponsor: Vanman 00:06:18 Evergreen Was the Warning 00:14:15 How DEI Creates a Niche for Fraud 00:17:27 What If Arday Was the Ultimate Hoax? 00:24:18 Sponsor: Branch Basics 00:26:10 When DEI Reaches High-Stakes Fields 00:34:53 Trust, Race and Meritocracy 00:50:46 The Academy Is Broken 00:58:08 What Can Be Done? 01:02:18 Will AI Replace the Trades? 01:07:33 The West Has an Honesty Crisis 01:10:44 The Consent of the Governed 01:15:43 Why We Need Difficult Conversations
1:20:43

Is Jason Arday just a liar? Peter Boghossian joins me on DarkHorse to discuss. 00:00:00 Jason Arday Exposes the Academy 00:02:34 Sponsor: Sundays for Dogs 00:04:25 Sponsor: Vanman 00:06:18 Evergreen Was the Warning 00:14:15 How DEI Creates a Niche for Fraud 00:17:27 What If Arday Was the Ultimate Hoax? 00:24:18 Sponsor: Branch Basics 00:26:10 When DEI Reaches High-Stakes Fields 00:34:53 Trust, Race and Meritocracy 00:50:46 The Academy Is Broken 00:58:08 What Can Be Done? 01:02:18 Will AI Replace the Trades? 01:07:33 The West Has an Honesty Crisis 01:10:44 The Consent of the Governed 01:15:43 Why We Need Difficult Conversations

Bret Weinstein

97,639 Aufrufe • vor 19 Tagen