Loading video...

Video Failed to Load

Go Home

Get the inside story on the development of Gemini's coding capabilities. Listen as the product and research leads for Gemini share their philosophy on what makes a great coding model, the impact of "vibe coding," and the future of programming languages with Logan Kilpatrick, Connie Fan and Danny Tarlow....

googleaidevs's profile picture

Google AI Developers

84,143 subscribers

65,474 views • 1 year ago •via X (Twitter)

Science & TechnologyNews & PoliticsEducation
LIVE

Anya Rossi• Live Now

Private livecam show

4 Comments

Andrew R's profile picture
Andrew R1 year ago

@OfficialLoganK Ayyy its Logan

snoopy19's profile picture
snoopy191 year ago

@OfficialLoganK This is nice! Can you consider also enhancing formatting generally speaking? Especially on mobile app that would be great!

Prime Domains (for Startups 🏆)'s profile picture
Prime Domains (for Startups 🏆)1 year ago

@OfficialLoganK This is great. Integrate flutter vibe coding app deployment directly to Google Play Store 🏆 though firebase studio

IAM + Mike's profile picture
IAM + Mike1 year ago

@OfficialLoganK Love hearing the “inside story” on #AI and coding models. But out here, the real work is being done by folks adapting on the fly, solving in production, and teaching others without the mic. Theory is cool. Practice builds the runway. 👁️‍🗨️

Related Videos

New podcast on vibe coding - A Return to Code. A Return to Coding 00:20 The Personal App Store 03:17 Vibe Coding Is a Video Game with Real-World Rewards 06:22 Pure Software Is Uninvestable 10:33 A Place for Each Model 14:22 AI Is Eager to Please 17:57 Why Math and Coding? 22:10 The Beginning of the End of Apple’s Dominance 24:17 Coding Agents As Customer Service Reps 27:55
29:36

New podcast on vibe coding - A Return to Code. A Return to Coding 00:20 The Personal App Store 03:17 Vibe Coding Is a Video Game with Real-World Rewards 06:22 Pure Software Is Uninvestable 10:33 A Place for Each Model 14:22 AI Is Eager to Please 17:57 Why Math and Coding? 22:10 The Beginning of the End of Apple’s Dominance 24:17 Coding Agents As Customer Service Reps 27:55

Naval

627,279 views • 3 months ago

The end of coding? *Epic* conversation with Guillermo Rauch of Vercel on vibe coding, MCP, agents and building products in the AI era. (00:00) - Intro: Guillermo's Story (02:08) - What is v0 and Why Did It Take Off So Fast? (04:10) - Building a hit product with < people (07:51) - Cursor, Replit, etc: v0 vs Other AI Coding Tools (10:35) - Everyone can cook - What is Vibe Coding? (17:05) - Is v0 Just Frontend? Moving Toward Full Stack 19:40 - How to Become a Great Vibe Coder (23:35) - A GUI for AI: The Future of Interfaces (29:46) - Developer Love vs Agent Love (33:41) - The Importance of Taste in the AI Era (39:10) - MCP: The Protocol for AI-to-AI Communication (43:11) - Security and the Risks of Agentic Web (45:25) - Are Enterprises Ready for the Agentic Future? (49:42) - Building a Data Flywheel (56:06) - The Vercel AI Cloud: From Pixels to Tokens (1:10:14) - Adapting to a Non-Developer Persona (1:13:47) - Retention, Margins, and the Business of AI (1:16:51) - The Secret Behind Vercel Last Year Growth (1:24:15) - The importance of Online Presence (1:30:49) - Everything, Everywhere, All at Once: Keeping your Sanity as a CEO (1:34:59) - Guillermo's Advice to Younger Self
1:45:40

The end of coding? *Epic* conversation with Guillermo Rauch of Vercel on vibe coding, MCP, agents and building products in the AI era. (00:00) - Intro: Guillermo's Story (02:08) - What is v0 and Why Did It Take Off So Fast? (04:10) - Building a hit product with < people (07:51) - Cursor, Replit, etc: v0 vs Other AI Coding Tools (10:35) - Everyone can cook - What is Vibe Coding? (17:05) - Is v0 Just Frontend? Moving Toward Full Stack 19:40 - How to Become a Great Vibe Coder (23:35) - A GUI for AI: The Future of Interfaces (29:46) - Developer Love vs Agent Love (33:41) - The Importance of Taste in the AI Era (39:10) - MCP: The Protocol for AI-to-AI Communication (43:11) - Security and the Risks of Agentic Web (45:25) - Are Enterprises Ready for the Agentic Future? (49:42) - Building a Data Flywheel (56:06) - The Vercel AI Cloud: From Pixels to Tokens (1:10:14) - Adapting to a Non-Developer Persona (1:13:47) - Retention, Margins, and the Business of AI (1:16:51) - The Secret Behind Vercel Last Year Growth (1:24:15) - The importance of Online Presence (1:30:49) - Everything, Everywhere, All at Once: Keeping your Sanity as a CEO (1:34:59) - Guillermo's Advice to Younger Self

Matt Turck

86,153 views • 1 year ago

My conversation with Amjad Masad, CEO of Replit. 0:00 Intro 1:05 Who is Replit for? 3:00 What's New from Replit 9:05 How Vibe Coding has Progressed 11:58 Vibe Coding Reliability Issues 13:02 The Edges of Vibe Coding 18:36 What Makes the Best Model 21:24 How Replit Stands Out 26:40 Platform Risk 29:24 Should You Still Learn to Code 33:21 The Agentic Future 37:57 End to End Neural Networks 39:58 White Collar Work 46:58 Permanent Underclass 51:42 10 Year Overnight Success
56:44

My conversation with Amjad Masad, CEO of Replit. 0:00 Intro 1:05 Who is Replit for? 3:00 What's New from Replit 9:05 How Vibe Coding has Progressed 11:58 Vibe Coding Reliability Issues 13:02 The Edges of Vibe Coding 18:36 What Makes the Best Model 21:24 How Replit Stands Out 26:40 Platform Risk 29:24 Should You Still Learn to Code 33:21 The Agentic Future 37:57 End to End Neural Networks 39:58 White Collar Work 46:58 Permanent Underclass 51:42 10 Year Overnight Success

Matthew Berman

32,935 views • 11 months ago

Claude Code is a major (and accidental!) hit for Anthropic that surprised even its creator, Boris Cherny. Claude Code, an Agentic AI coding product that lives in the terminal. Most of the new code at Anthropic is created through it today. And in the last 5 months since it was launched publicly, Claude Code went from $0 to $400M in revenue run rate (as per The Information). 00:00 – Intro 01:15 – Did You Expect Claude Code’s Success? 04:22 – How Claude Code Works and Origins 08:05 – Command Line vs IDE: Why Start Claude Code in the Terminal? 11:31 – The Evolution of Programming: From Punch Cards to Agents 13:20 – Product Follows Model: Simple Interfaces and Fast Evolution 15:17 – Who Is Claude Code For? (Engineers, Designers, PMs & More) 17:46 – What Can Claude Code Actually Do? (Actions & Capabilities) 21:14 – Agentic Actions, Subagents, and Workflows 25:30 – Claude Code’s Awareness, Memory, and Knowledge Sharing 33:28 – Model Context Protocol (MCP) and Customization 35:30 – Safety, Human Oversight, and Enterprise Considerations 38:10 – UX/UI: Making Claude Code Useful and Enjoyable 40:44 – Pricing for Power Users and Subscription Models 43:36 – Real-World Use Cases: Debugging, Testing, and More 46:44 – How Does Claude Code Transform Onboarding? 49:36 – The Future of Coding: Agents, Teams, and Collaboration 54:11 – The AI Coding Wars: Competition & Ecosystem 57:27 – The Future of Coding as a Profession 58:41 – What’s Next for Claude Code
1:00:16

Claude Code is a major (and accidental!) hit for Anthropic that surprised even its creator, Boris Cherny. Claude Code, an Agentic AI coding product that lives in the terminal. Most of the new code at Anthropic is created through it today. And in the last 5 months since it was launched publicly, Claude Code went from $0 to $400M in revenue run rate (as per The Information). 00:00 – Intro 01:15 – Did You Expect Claude Code’s Success? 04:22 – How Claude Code Works and Origins 08:05 – Command Line vs IDE: Why Start Claude Code in the Terminal? 11:31 – The Evolution of Programming: From Punch Cards to Agents 13:20 – Product Follows Model: Simple Interfaces and Fast Evolution 15:17 – Who Is Claude Code For? (Engineers, Designers, PMs & More) 17:46 – What Can Claude Code Actually Do? (Actions & Capabilities) 21:14 – Agentic Actions, Subagents, and Workflows 25:30 – Claude Code’s Awareness, Memory, and Knowledge Sharing 33:28 – Model Context Protocol (MCP) and Customization 35:30 – Safety, Human Oversight, and Enterprise Considerations 38:10 – UX/UI: Making Claude Code Useful and Enjoyable 40:44 – Pricing for Power Users and Subscription Models 43:36 – Real-World Use Cases: Debugging, Testing, and More 46:44 – How Does Claude Code Transform Onboarding? 49:36 – The Future of Coding: Agents, Teams, and Collaboration 54:11 – The AI Coding Wars: Competition & Ecosystem 57:27 – The Future of Coding as a Profession 58:41 – What’s Next for Claude Code

Matt Turck

82,327 views • 1 year ago

Caught up with Andrej Karpathy for a new No Priors: on the phase shift in engineering, AI psychosis, claws, AutoResearch, the opportunity for a SETI-at-Home like movement in AI, the model landscape, and second order effects 02:55 - What Capability Limits Remain? 06:15 - What Mastery of Coding Agents Looks Like 11:16 - Second Order Effects of Coding Agents 15:51 - Why AutoResearch 22:45 - Relevant Skills in the AI Era 28:25 - Model Speciation 32:30 - Collaboration Surfaces for Humans and AI 37:28 - Analysis of Jobs Market Data 48:25 - Open vs. Closed Source Models 53:51 - Autonomous Robotics and Atoms 1:00:59 - MicroGPT and Agentic Education 1:05:40 - End Thoughts
1:06:31

Caught up with Andrej Karpathy for a new No Priors: on the phase shift in engineering, AI psychosis, claws, AutoResearch, the opportunity for a SETI-at-Home like movement in AI, the model landscape, and second order effects 02:55 - What Capability Limits Remain? 06:15 - What Mastery of Coding Agents Looks Like 11:16 - Second Order Effects of Coding Agents 15:51 - Why AutoResearch 22:45 - Relevant Skills in the AI Era 28:25 - Model Speciation 32:30 - Collaboration Surfaces for Humans and AI 37:28 - Analysis of Jobs Market Data 48:25 - Open vs. Closed Source Models 53:51 - Autonomous Robotics and Atoms 1:00:59 - MicroGPT and Agentic Education 1:05:40 - End Thoughts

sarah guo

3,040,581 views • 5 months ago

i tested a fully local ai coding setup: gemma4 from Google DeepMind running through LM Studio, paired with pi which is a minimal open source coding harness this is part 1 of a two part series. here we cover the why and the complete hands-on setup 0:00 - Running a coding agent fully local 0:47 - Why Pi as the coding agent harness 1:39 - Why Gemma 4 and which variant to pick 2:44 - Architecture: Pi, LM Studio and Gemma 4 3:45 - LM Studio setup and model download 5:01 - Starting the local server 5:19 - API sanity check with curl 6:08 - Installing the Pi coding agent 6:20 - Configuring models.json for local models 8:20 - First run: selecting the model in Pi 8:58 - Fixing the context length error 10:16 - Testing the working setup 10:50 - What is coming in Part 2
11:32

i tested a fully local ai coding setup: gemma4 from Google DeepMind running through LM Studio, paired with pi which is a minimal open source coding harness this is part 1 of a two part series. here we cover the why and the complete hands-on setup 0:00 - Running a coding agent fully local 0:47 - Why Pi as the coding agent harness 1:39 - Why Gemma 4 and which variant to pick 2:44 - Architecture: Pi, LM Studio and Gemma 4 3:45 - LM Studio setup and model download 5:01 - Starting the local server 5:19 - API sanity check with curl 6:08 - Installing the Pi coding agent 6:20 - Configuring models.json for local models 8:20 - First run: selecting the model in Pi 8:58 - Fixing the context length error 10:16 - Testing the working setup 10:50 - What is coming in Part 2

Nidhi Singh

16,289 views • 2 months ago

New Benchtalks with John Yang: on ProgramBench (0% frontier models at launch) and the lineage/future of coding benchmarks, from SWE-bench/InterCode to now 01:29 ProgramBench launch and reception 03:41 Why artifact-level evaluation, not code-level 06:03 Why models love Python 08:29 ProgramBench as a research tool 12:45 From SWE-bench & InterCode to ProgramBench 17:47 How to grade a coding model 21:53 The position paper & humans in the loop 25:01 Managing quality with agents-in-the-loop 28:40 Internet access and benchmark integrity 35:26 Where models may surpass human abilities 38:56 When a model hits 80% on ProgramBench 43:55 Benchmarks worth paying attention to 46:24 What benchmark do you wish existed 49:32 Will benchmarks still look like benchmarks in 5 years 52:02 How to contribute to ProgramBench
54:13

New Benchtalks with John Yang: on ProgramBench (0% frontier models at launch) and the lineage/future of coding benchmarks, from SWE-bench/InterCode to now 01:29 ProgramBench launch and reception 03:41 Why artifact-level evaluation, not code-level 06:03 Why models love Python 08:29 ProgramBench as a research tool 12:45 From SWE-bench & InterCode to ProgramBench 17:47 How to grade a coding model 21:53 The position paper & humans in the loop 25:01 Managing quality with agents-in-the-loop 28:40 Internet access and benchmark integrity 35:26 Where models may surpass human abilities 38:56 When a model hits 80% on ProgramBench 43:55 Benchmarks worth paying attention to 46:24 What benchmark do you wish existed 49:32 Will benchmarks still look like benchmarks in 5 years 52:02 How to contribute to ProgramBench

vincent sunn chen

26,838 views • 2 months ago

Vibe Coding: The act of using only your voice in Cursor Composer to build apps, forgetting the code even exists Complete Video Tutorial Some people are skeptical about this new method of programming so why don't we build a ChatGPT clone with real time voice ( Andrej Karpathy 's voice) without typing, using Whispr Flow. For me "vibe coding" is my only option. Because i've never written a line of code. Time Stamps: 00:00 Intro to Vibe Coding (pretty corny) 03:02 Opening Cursor 04:07 Starting Your First Project from Template Link (Pinned to bio of @senior_swc ) 05:12 Building a ChatGPT Clone, Getting Started 06:38 Prompting, API's and Documentation Explanation 08:49 Using Perplexity (Input output custom spaces for coding) 12:07 Vibe Code Prompt 1 13:58 Result of Vibe Coding Prompt 1 15:22 Seeing Prompt 2 15:43 Managing Cursor Composer Context Length 16:25 Designing 17:21 Debugging with Inspect on Web View 18:20 Fixing Formatting 19:04 More Vibing, Lol 20:51 Saving and Uploading Projects to GitHub 21:59 Enhancing the User Experience 22:33 Honoring Andrej Karpathy 26:26 Implementing Real Time Karpathy Voice 28:30 Getting Karpathys Voice (Don't Do this It's Illegal) don't ban me i love you
33:47

Vibe Coding: The act of using only your voice in Cursor Composer to build apps, forgetting the code even exists Complete Video Tutorial Some people are skeptical about this new method of programming so why don't we build a ChatGPT clone with real time voice ( Andrej Karpathy 's voice) without typing, using Whispr Flow. For me "vibe coding" is my only option. Because i've never written a line of code. Time Stamps: 00:00 Intro to Vibe Coding (pretty corny) 03:02 Opening Cursor 04:07 Starting Your First Project from Template Link (Pinned to bio of @senior_swc ) 05:12 Building a ChatGPT Clone, Getting Started 06:38 Prompting, API's and Documentation Explanation 08:49 Using Perplexity (Input output custom spaces for coding) 12:07 Vibe Code Prompt 1 13:58 Result of Vibe Coding Prompt 1 15:22 Seeing Prompt 2 15:43 Managing Cursor Composer Context Length 16:25 Designing 17:21 Debugging with Inspect on Web View 18:20 Fixing Formatting 19:04 More Vibing, Lol 20:51 Saving and Uploading Projects to GitHub 21:59 Enhancing the User Experience 22:33 Honoring Andrej Karpathy 26:26 Implementing Real Time Karpathy Voice 28:30 Getting Karpathys Voice (Don't Do this It's Illegal) don't ban me i love you

Riley Brown

73,901 views • 1 year ago

Sonnet 4.5 & the AI Plateau Myth — epic conversation with Sholto Douglas of Anthropic 0:00 - Intro 1:09 - What's Behind The Rapid Pace of AI Releases at Anthropic 2:49 - Opus, Sonnet, and Haiku Model Tiers 4:14 - Sholto's Story: From Australian Fencer to AI Researcher 12:01 - The YouTube Effect: Mastery Through Observation 16:16 - Breaking Into AI Research Without Traditional Academic Signals 18:29 - DeepMind, Gemini, and Building Inference Stacks 23:05 - Why Anthropic? Culture and Mission Differences Amongst AI Research Labs 25:08 - What Is "Taste" in AI Research? 31:46 - This Week's Big Launch: Sonnet 4.5, Best Coding Model in the World 36:40 - From 7 Hours to 30 Hours: The Long-Running AI Agent Breakthrough 38:41 - How AI Agents Self-Correct and Maintain Coherence 43:13 - The Role of Memory in Extended Coding Sessions 47:42 - Pre-Training vs. RL: Textbooks vs. Worked Problems 52:11 - Test-Time Compute & Reinforcement Learning 55:55 - Why RL Finally Started Working on LLMs in 2024 59:38 - The Path to AGI 1:02:05 - Are We Hitting a Plateau in AI? So Many Low Hanging Fruits 1:03:41 - Beyond Coding: GDPVal & Impact Economic Sectors 1:05:47 - Preparing for 10-100x Individual Leverage & The Upcoming Robotics Explosion
1:10:03

Sonnet 4.5 & the AI Plateau Myth — epic conversation with Sholto Douglas of Anthropic 0:00 - Intro 1:09 - What's Behind The Rapid Pace of AI Releases at Anthropic 2:49 - Opus, Sonnet, and Haiku Model Tiers 4:14 - Sholto's Story: From Australian Fencer to AI Researcher 12:01 - The YouTube Effect: Mastery Through Observation 16:16 - Breaking Into AI Research Without Traditional Academic Signals 18:29 - DeepMind, Gemini, and Building Inference Stacks 23:05 - Why Anthropic? Culture and Mission Differences Amongst AI Research Labs 25:08 - What Is "Taste" in AI Research? 31:46 - This Week's Big Launch: Sonnet 4.5, Best Coding Model in the World 36:40 - From 7 Hours to 30 Hours: The Long-Running AI Agent Breakthrough 38:41 - How AI Agents Self-Correct and Maintain Coherence 43:13 - The Role of Memory in Extended Coding Sessions 47:42 - Pre-Training vs. RL: Textbooks vs. Worked Problems 52:11 - Test-Time Compute & Reinforcement Learning 55:55 - Why RL Finally Started Working on LLMs in 2024 59:38 - The Path to AGI 1:02:05 - Are We Hitting a Plateau in AI? So Many Low Hanging Fruits 1:03:41 - Beyond Coding: GDPVal & Impact Economic Sectors 1:05:47 - Preparing for 10-100x Individual Leverage & The Upcoming Robotics Explosion

Matt Turck

93,678 views • 10 months ago

VIBE CODING TUTORIAL: Creating a Viral Meme Mobile App Without Any Coding in 20 minutes! You can now build multi-step AI workflows on a drag and drop platform, and then connect that workflow to your vibe coded mobile app, in a single cursor prompt. This only scratches the surface on the different workflows you can create like this. IN THIS VIDEO 00:00 Intro 00:36 Overview: MultiStep AI Backend on GLIF 01:33 Using Glif as an API 03:49 The backend for our app 04:36 Structured Outputs (Important for Vibe Coding, skip if you know what these are) 06:40 Image Workflow for the meme 08:34 Let's Protototype on 11:09 Setting this up with Cursor 18:40 Testing with
19:37

VIBE CODING TUTORIAL: Creating a Viral Meme Mobile App Without Any Coding in 20 minutes! You can now build multi-step AI workflows on a drag and drop platform, and then connect that workflow to your vibe coded mobile app, in a single cursor prompt. This only scratches the surface on the different workflows you can create like this. IN THIS VIDEO 00:00 Intro 00:36 Overview: MultiStep AI Backend on GLIF 01:33 Using Glif as an API 03:49 The backend for our app 04:36 Structured Outputs (Important for Vibe Coding, skip if you know what these are) 06:40 Image Workflow for the meme 08:34 Let's Protototype on 11:09 Setting this up with Cursor 18:40 Testing with

Riley Brown

58,068 views • 1 year ago

Raising An Agent - Episode 5 In this episode, Beyang interviews Thorsten Ball and Quinn Slack to unpack what has happened in the world of Amp in the last five weeks: how predictions played out, how working with agents shaped how they write code, how agents are and will influence model development, and, of course, all the things that have been shipped in Amp. Timestamps: 0:00 Opening Teaser 1:24 Introduction and Casual Conversation 2:02 Changes in Coding Agents Over Five Weeks 3:28 Challenges and Misconceptions 6:52 Optimizing Tools and Prompts 9:15 User Feedback and Best Practices 15:29 Advanced User Strategies 22:41 Balancing Integration and Flexibility 24:17 Cost and Accessibility of Agents 28:05 Feedback Loops and Model Training 35:12 The Evolution of AI Coding Agents 35:35 Training Data, Tool Affinity, and Tool Integration 36:50 User Feedback and Model Training 43:22 Product Evolution and New Features 55:55 Remote Execution and Multi-Agent Workflows 1:02:47 Future Directions and Improvements
1:05:38

Raising An Agent - Episode 5 In this episode, Beyang interviews Thorsten Ball and Quinn Slack to unpack what has happened in the world of Amp in the last five weeks: how predictions played out, how working with agents shaped how they write code, how agents are and will influence model development, and, of course, all the things that have been shipped in Amp. Timestamps: 0:00 Opening Teaser 1:24 Introduction and Casual Conversation 2:02 Changes in Coding Agents Over Five Weeks 3:28 Challenges and Misconceptions 6:52 Optimizing Tools and Prompts 9:15 User Feedback and Best Practices 15:29 Advanced User Strategies 22:41 Balancing Integration and Flexibility 24:17 Cost and Accessibility of Agents 28:05 Feedback Loops and Model Training 35:12 The Evolution of AI Coding Agents 35:35 Training Data, Tool Affinity, and Tool Integration 36:50 User Feedback and Model Training 43:22 Product Evolution and New Features 55:55 Remote Execution and Multi-Agent Workflows 1:02:47 Future Directions and Improvements

Amp

18,896 views • 1 year ago

Benedict Evans on Why AI Feels Like the Internet in 1997 Benedict Evans joins Erik Torenberg for a conversation on the state of AI, including how coding agents hit product-market fit, why foundation models should be thought of as infrastructure, the value of vertical products, and more. 00:00 Intro 00:44 What's changed since last year 05:53 OpenAI vs Anthropic strategy 10:31 The pricing crunch & platform history 22:48 What comes after coding 38:18 AI & the future of enterprise software 48:43 The CapEx problem 55:07 Will models become commodities? Benedict Evans Erik Torenberg
1:00:32

Benedict Evans on Why AI Feels Like the Internet in 1997 Benedict Evans joins Erik Torenberg for a conversation on the state of AI, including how coding agents hit product-market fit, why foundation models should be thought of as infrastructure, the value of vertical products, and more. 00:00 Intro 00:44 What's changed since last year 05:53 OpenAI vs Anthropic strategy 10:31 The pricing crunch & platform history 22:48 What comes after coding 38:18 AI & the future of enterprise software 48:43 The CapEx problem 55:07 Will models become commodities? Benedict Evans Erik Torenberg

a16z

103,588 views • 2 months ago

Forgot to post on twitter - my conversation with dax from OpenCode Talked a lot about how programming is changing & not changing. I really enjoyed a lot of the historical takes that Dax has. He's building one of these "agentic coding" tools, so he sees the value in it, but he also has a healthy amount of skepticism. A lot of the core debates about "vibe code" vs "traditional code" aren't new. They already existed in many forms, e.g. go fast break things vs overengineering, microservices vs monolith, testing, etc. I also really resonated with his idea of competition - was probably my favorite part, but there were many great ones! 0:00 - Intro 3:56 - Dax's developer workflow 6:54 - Is code no longer written by humans? 11:32 - Competition, Claude Code 19:04 - Positioning vs Product 23:49 - Will OpenAI acquire OpenCode? 28:02 - The Future of Coding, effort vs impact 37:16 - Code Quality 42:23 - Did AI take the fun out of programming? 45:56 - Will programming skills decay long term? 51:56 - Technical skills alone are useless 58:56 - Becoming an Elite Developer Thank you to our sponsors PostHog and Greptile You can find the NeetCode podcast on YT, Spotify & Apple Podcast - links below
1:12:51

Forgot to post on twitter - my conversation with dax from OpenCode Talked a lot about how programming is changing & not changing. I really enjoyed a lot of the historical takes that Dax has. He's building one of these "agentic coding" tools, so he sees the value in it, but he also has a healthy amount of skepticism. A lot of the core debates about "vibe code" vs "traditional code" aren't new. They already existed in many forms, e.g. go fast break things vs overengineering, microservices vs monolith, testing, etc. I also really resonated with his idea of competition - was probably my favorite part, but there were many great ones! 0:00 - Intro 3:56 - Dax's developer workflow 6:54 - Is code no longer written by humans? 11:32 - Competition, Claude Code 19:04 - Positioning vs Product 23:49 - Will OpenAI acquire OpenCode? 28:02 - The Future of Coding, effort vs impact 37:16 - Code Quality 42:23 - Did AI take the fun out of programming? 45:56 - Will programming skills decay long term? 51:56 - Technical skills alone are useless 58:56 - Becoming an Elite Developer Thank you to our sponsors PostHog and Greptile You can find the NeetCode podcast on YT, Spotify & Apple Podcast - links below

NeetCode

41,213 views • 5 months ago

My conversation with Jesse Zhang Decagon is building a customer service agent with AI, with plans for much more than that. It’s one of the more successful early AI applications, with tons of lessons for the rest of the market. I love how Jesse developed which problem to solve first, a set of lessons applicable to all entrepreneurs Enjoy Timestamps: 0:00 Intro 2:00 Competing in the AI Era 11:35 Finding Product-Market Fit 14:25 Anatomy of a Great Customer Interview 17:37 Everyone’s Wrong Until You Talk to Customers 19:25 AI Agents Replacing Human Labor 21:55 Why Customer Service 23:30 Coding vs. Customer Service 35:44 The Future of Voice and the Human UI 38:54 Why Voice-to-Voice Is So Hard 43:18 Learning from Customer Data 44:36 How CEOs Should Think About AI 47:06 The ROI of Coding and Productivity Tools 48:20 Every Brand Will Talk to You Through AI 56:00 Recruiting, Capital, and Demand 1:00:42 Investor Frenzy 1:22:17 The Long-Term Vision for Decagon 1:25:05 Kindest Thing
1:26:12

My conversation with Jesse Zhang Decagon is building a customer service agent with AI, with plans for much more than that. It’s one of the more successful early AI applications, with tons of lessons for the rest of the market. I love how Jesse developed which problem to solve first, a set of lessons applicable to all entrepreneurs Enjoy Timestamps: 0:00 Intro 2:00 Competing in the AI Era 11:35 Finding Product-Market Fit 14:25 Anatomy of a Great Customer Interview 17:37 Everyone’s Wrong Until You Talk to Customers 19:25 AI Agents Replacing Human Labor 21:55 Why Customer Service 23:30 Coding vs. Customer Service 35:44 The Future of Voice and the Human UI 38:54 Why Voice-to-Voice Is So Hard 43:18 Learning from Customer Data 44:36 How CEOs Should Think About AI 47:06 The ROI of Coding and Productivity Tools 48:20 Every Brand Will Talk to You Through AI 56:00 Recruiting, Capital, and Demand 1:00:42 Investor Frenzy 1:22:17 The Long-Term Vision for Decagon 1:25:05 Kindest Thing

Patrick OShaughnessy

49,418 views • 10 months ago

After many months, a lot of model releases and even more Amp releases, here it is: A new episode of Raising An Agent with Quinn Slack and Thorsten Ball. They discuss: - Why Gemini 3 might have been the inflection point, not Opus 4.5 - What changed over Christmas and why everybody talks about agents now - "The assistant is dead, long live the factory" - How codebases need to adapt for agents - Why small/local models don't give you an impression of the frontier - What does it mean for a codebase to be agent-friendly? - New things coming to Amp Enjoy! And happy hacking! Timestamps: 1:51 The Impact of Gemini 3 and Opus 4.5 5:28 Shifting Perceptions of AI Agents 10:17 Adapting Codebases for AI Efficiency 14:48 The Future of Software Development with AI Agents 19:29 Challenges and Opportunities Ahead 24:00 The Importance of Frontier Models 25:12 Adapting to AI-Driven Workflows 26:57 The Future of Coding Agents 28:07 Building an Agentic Code Base 30:22 Rethinking Development Tools 31:44 Amp's Evolution and Team Dynamics 33:00 Discord Q&A 39:18 Teasing New Features: Deep
40:50

After many months, a lot of model releases and even more Amp releases, here it is: A new episode of Raising An Agent with Quinn Slack and Thorsten Ball. They discuss: - Why Gemini 3 might have been the inflection point, not Opus 4.5 - What changed over Christmas and why everybody talks about agents now - "The assistant is dead, long live the factory" - How codebases need to adapt for agents - Why small/local models don't give you an impression of the frontier - What does it mean for a codebase to be agent-friendly? - New things coming to Amp Enjoy! And happy hacking! Timestamps: 1:51 The Impact of Gemini 3 and Opus 4.5 5:28 Shifting Perceptions of AI Agents 10:17 Adapting Codebases for AI Efficiency 14:48 The Future of Software Development with AI Agents 19:29 Challenges and Opportunities Ahead 24:00 The Importance of Frontier Models 25:12 Adapting to AI-Driven Workflows 26:57 The Future of Coding Agents 28:07 Building an Agentic Code Base 30:22 Rethinking Development Tools 31:44 Amp's Evolution and Team Dynamics 33:00 Discord Q&A 39:18 Teasing New Features: Deep

Amp

36,150 views • 7 months ago

There's a reason Cognition keeps winning deals against companies 10x their size. Vivek Gopalan sat down with Theodor Marcu, Bryce Hunt and Moritz Stephan (all former founders!) to discuss hiring philosophy, infinity stories, enterprise coding agents, and what it actually takes to compete. (00:00) Introduction (03:45) Cognition team & hiring philosophy (06:00) Infinity stories (13:15) Product surface area and future goals (17:20) Activation energy, experimentation, and customer-driven innovation (19:00) Adoption, operational changes, and ownership (22:05) Vibe coding hot takes (24:15) AI-first engineering organizations and managing AI agents (28:40) Future of software engineering roles and misconceptions about Devin (30:00) Model development, learnings, and Cognition's journey in vertical integration (38:10) What should you do as a new grad?
43:48

There's a reason Cognition keeps winning deals against companies 10x their size. Vivek Gopalan sat down with Theodor Marcu, Bryce Hunt and Moritz Stephan (all former founders!) to discuss hiring philosophy, infinity stories, enterprise coding agents, and what it actually takes to compete. (00:00) Introduction (03:45) Cognition team & hiring philosophy (06:00) Infinity stories (13:15) Product surface area and future goals (17:20) Activation energy, experimentation, and customer-driven innovation (19:00) Adoption, operational changes, and ownership (22:05) Vibe coding hot takes (24:15) AI-first engineering organizations and managing AI agents (28:40) Future of software engineering roles and misconceptions about Devin (30:00) Model development, learnings, and Cognition's journey in vertical integration (38:10) What should you do as a new grad?

8VC

754,552 views • 4 months ago

Perplexity co-founder and CEO Aravind Srinivas (Aravind Srinivas) on the race to build the AI browser of the future. At AI Startup School in San Francisco. 00:48 - Perplexity's Current Status and Challenges 01:16 - Future Plans: The Browser Bet 03:18 - Competition and Market Dynamics 04:43 - The Importance of Speed and Innovation 05:51 - Founding Perplexity: The Early Days 09:18 - Product Evolution and User Experience 19:44 - Running the Company and Future Outlook 20:15 - AI Tools in Software Engineering 20:31 - Adoption and Implementation of AI Coding Tools 21:11 - Challenges and Benefits of AI in Development 22:35 - Brand Value and Competition 23:56 - Network Effects and Integrations 27:40 - Business Model and Revenue Streams 29:54 - Advice for Founders 31:33 - Audience Q&A
43:12

Perplexity co-founder and CEO Aravind Srinivas (Aravind Srinivas) on the race to build the AI browser of the future. At AI Startup School in San Francisco. 00:48 - Perplexity's Current Status and Challenges 01:16 - Future Plans: The Browser Bet 03:18 - Competition and Market Dynamics 04:43 - The Importance of Speed and Innovation 05:51 - Founding Perplexity: The Early Days 09:18 - Product Evolution and User Experience 19:44 - Running the Company and Future Outlook 20:15 - AI Tools in Software Engineering 20:31 - Adoption and Implementation of AI Coding Tools 21:11 - Challenges and Benefits of AI in Development 22:35 - Brand Value and Competition 23:56 - Network Effects and Integrations 27:40 - Business Model and Revenue Streams 29:54 - Advice for Founders 31:33 - Audience Q&A

Y Combinator

236,501 views • 1 year ago