Merrill Lutsky, co-founder and CEO of Graphite, discusses their evolution from stack diff workflows to Diamond, an AI code review agent that just helped secure their $50M Series B. He shares insights on building reliable AI review systems, why over-generating and pruning comments works better than single responses, and the shift from RAG to agentic code browsing. Merrill offers a provocative vision where developers define requirements and AI agents build the code, potentially eliminating traditional IDE coding. This episode provides valuable perspectives on how AI is fundamentally reshaping software development workflows and engineering roles.

Chapters:
00:00 - Introduction and Graphite overview
01:58 - Evolution from stack diffs to AI review
07:39 - Diamond: The AI code reviewer explained
10:13 - Human vs AI review: Finding the balance
11:44 - Engineering challenges of reliable AI review
17:38 - Over-generate and prune: A winning strategy
24:49 - From RAG to code browser agents
28:12 - The bitter lesson of AI engineering
30:48 - The future of software engineering
37:33 - Is AI over or under-hyped?

This week Raza is joined by Amit Jain, CEO and co-founder of Luma AI, to explore why the future of artificial intelligence lies beyond language. Amit shares Luma’s bold mission to build world models through multimodal training and why video is the most overlooked and critical data source in AI today.

Chapters:
00:00 - Introduction
03:40 - Competing with Big AI Labs: Language vs. Multimodality
08:09 - Joint Training and Why Current Multimodal Models Fall Short
11:01 - Language is Discrete, the World is Continuous
14:36 - Do These Models Have World Models?
18:18 - Planning, Counterfactuals, and Causal Reasoning in AI
22:08 - Capabilities of Ray 2 and Real-World Use Cases
26:14 - Rethinking Video Length and Creative Workflows
29:18 - Solving Coherence Across Shots and Characters
30:00 - When Will AI Create a Feature-Length Film?
31:27 - What You Can Build with Luma’s API Today
35:49 - Overlooked Ideas and Noise in the AI Industry
38:34 - Why Video is the Missing Link in AI

In this episode, Raza is joined by Shahriar Tajbakhsh, the co-founder of Metaview. They discuss how Metaview’s AI scribe automates interview note-taking, how AI agents can surface top candidates from thousands of resumes, and why hiring managers should think of AI as a co-worker, not just a tool. Raza's recomended reading: Creating a LLM-as-a-Judge That Drives Business Results.

Chapters:
00:00 - Introduction
03:32 - How AI Co-Workers Are Transforming Recruiting
06:21 - Inside MetaView: AI Scribe and Workflow Automation
09:11 - Unlocking Hiring Insights with AI-Driven Conversations
11:30 - Balancing AI Innovation and User Adoption
14:05 - Metaview’s Tech Stack and the Role of LLMs
18:29 - How MetaView Generates Superhuman Interview Notes
23:18 - The Challenges of Building Reliable AI Hiring Agents
32:40 - The Future of AI in Hiring: Automating Job Descriptions
40:26 - AI Co-Workers That Work While You Sleep
47:08 - Why Vertical AI Will Win Over General AI Agents
50:24 - The Underrated Power of Graph-Based AI

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Humanloop is the LLM evals platform for enterprises. We give you the tools that top teams use to ship and scale AI with confidence. To find out more go to humanloop.com 

In this episode, Raza Habib chats with Zach Lloyd, CEO and founder of Warp, about how AI is transforming the developer experience. They explore how Warp is reimagining the command line, the power of AI-driven automation, and what the future holds for coding workflows.

Chapters:
00:00 - Introduction
04:06 - Why the terminal needed reinvention
07:11 - AI’s role in Warp’s evolution
08:55 - Key AI features in Warp
12:49 - Balancing safety, reliability, and usability
19:43 - Challenges in AI-Powered development
22:33 - Changing developer behavior with AI
27:24 - Prompt engineering and context optimization
31:05 - Lessons for building AI products
37:50 - The future of AI in software development
46:42 - Underappreciated AI innovations
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Humanloop is the LLM evals platform for enterprises. We give you the tools that top teams use to ship and scale AI with confidence. To find out more go to humanloop.com

Will Bryk, CEO of Exa, sits down with Raza Habib to reveal why traditional search engines are becoming obsolete and how his startup is building an AI-powered search engine for the future. From constructing a massive GPU cluster to predicting AI will surpass human mathematicians by 2026, Will shares fascinating insights about the technological breakthroughs that will reshape society in the coming months.

Chapters:

00:00 - Introduction 
05:13 - Exa as a Tool for LLMs and Neural Search  
06:19 - Introducing "Websets" and Its Use Cases  
10:16 - Building a Compute Cluster: Why Own vs. Rent?  
12:00 - The Bitter Lesson and Scalability in AI  
17:11 - Interesting Use Cases for Exa  
19:44 - People Search and CRM Opportunities   
21:10 - Predictions for AI Progress and Test-Time Compute  
27:10 - Implications of AI on Creative Tasks and Society  
29:15 - Automation, Jobs, and the Knowledge Economy  
33:57 - What Could Stop AI Progress?  
36:22 - Advice for AI Builders and Entrepreneurs

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Humanloop is the LLM evals platform for enterprises. We give you the tools that top teams use to ship and scale AI with confidence. To find out more go to humanloop.com

In this episode, Jesse Zhang joins Raza to discuss building cutting-edge AI agents for customer support. They explore how his early passion for LLMs led to creating a company that’s transforming the way businesses like Rippling, Duolingo, and Webflow interact with customers. Jesse breaks down the challenges of scaling AI systems, the importance of customer feedback, and his predictions for the future of AI.

Chapters:
00:00 - Introduction and Jesse Zhang's Background  
01:17 - First Exposure to LLMs and Building Early Projects  
04:32 - Decagon’s Rapid Growth and Differentiation in AI  
06:37 - Understanding Decagon’s AI Customer Support Product  
10:21 - Challenges in Building High-Performance AI Systems  
13:14 - Evolution from Simple RAG to Agent Architectures  
16:54 - Measuring Accuracy with Evals and Customer Feedback  
19:05 - Balancing Customization and Reusability Across Clients  
22:35 - Handling Customer Data and Incremental Deployment  
25:21 - Restructuring Support Teams for AI Integration  
27:03 - Team Composition and the Role of Domain Expertise  
29:19 - Advice for New AI Builders: Customer-Driven Development  
32:21 - Key Insights on AI Agents and Enterprise Adoption  
36:34 - Predictions for AI Advancements in 2025  
39:41 - Is AI Overhyped or Underhyped?  
41:07 - Closing Remarks and Final Thoughts

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Humanloop is the LLM evals platform for enterprises. We give you the tools that top teams use to ship and scale AI with confidence. To find out more go to humanloop.com

On this week's episode, former GitHub Copilot lead Ryan Salva breaks down how AI coding tools became ubiquitous almost overnight. They discuss the critical differences between what novice and expert developers expect from AI, why starting with predictive text was both a blessing and a curse, and how the rapid adoption of AI assistance is reshaping the future of software development.

Chapters:
00:00 - Introduction 
01:09 - The Creation of GitHub Copilot  
05:39 - From Prototype to Product: Challenges in Scaling  
07:37 - How GitHub Copilot Works Behind the Scenes  
11:18 - Metrics That Matter: Evaluating AI Success  
14:43 - Building Momentum: What It Feels Like to Launch a Hit  
17:51 - The Evolution of AI Tools for Developers  
21:13 - Evaluations and Testing in AI Development  
26:00 - The Role of Automation and the Future of Coding  
30:53 - Will Engineers Still Write Code in the Future?  
33:16 - Advice for Aspiring AI Builders  
36:51 - Is AI Overhyped or Underhyped?  
38:17 - Closing Reflections 

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Humanloop is the LLM evals platform for enterprises. We give you the tools that top teams use to ship and scale AI with confidence. To find out more go to humanloop.com

In this week's episode, Raza speaks with James Theuerkauf, CEO of Syrup Tech, and Sara Ittelson, Partner at Accel, to explore the challenges and opportunities for entrepreneurs in this transformative era. They discuss building AI-first companies and the lessons learned from scaling in a rapidly evolving space. With practical tips on leveraging data, creating competitive advantages, and sustaining passion for the long haul, this episode offers invaluable guidance for founders in AI.

Chapters:
00:00 - Introduction and Guest Backgrounds  
01:27 - Syrup Tech’s Approach to AI in Retail  
03:29 - The Role of AI in Demand Forecasting  
08:49 - Building Effective AI Systems and Teams  
15:30 - How Generative AI is Shaping Businesses  
19:18 - Advice for Founders in the AI Era  
28:15 - Building an AI-First Company 
33:26 - Innovations and Trends in AI  
38:47 - Is AI Overhyped or Underhyped?  
42:46 - Closing Thoughts and Reflections

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Humanloop is the LLM evals platform for enterprises. We give you the tools that top teams use to ship and scale AI with confidence. To find out more go to humanloop.com

In this episode, Noam Rubin, a Software Developer at Vanta reveals how his team uses data-driven strategies to design, test, and improve cutting-edge AI features. Learn how customer insights, rapid prototyping, and iterative development transform raw ideas into tools that make compliance and security easier for businesses everywhere.

Chapters:

00:00 - Introduction
02:47 - The process of building AI products at Vanta
04:51 - The role of customer feedback in product development
06:59 - Integrating AI into security and compliance workflows
08:06 - Using data specifications to guide product development
10:10 - Collaborating with subject matter experts to refine AI models
12:14 - Iterative testing and refining AI features
14:10 - Quality control and ensuring AI accuracy
16:00 - The importance of dogfooding and internal feedback loops
18:23 - Scaling AI features and rolling them out to wider audiences
20:50 - Educating engineers and democratizing AI at Vanta
22:20 - Key lessons learned from building AI products
24:12 - Maintaining AI quality through continuous feedback
26:00 - The future of AI in business and product development

In this episode of High Agency, former OpenAI researcher Stan Polu shares his journey from AI research to founding Dust, an enterprise AI platform. Stan offers a contrarian view on the future of AI, suggesting we may be hitting a plateau in model capabilities since GPT-4. He discusses why startups should focus on product-market fit before investing in GPUs, shares practical lessons for building AI products, and predicts increased competition between AI labs and API developers. 

Chapters:
00:00 - Introducing Dust: an enterprise AI platform
06:07 - From Stripe to OpenAI: Stan's journey
10:29 - Why research wasn't enough: building Dust
15:10 -  Best practices for building an AI product
20:50 - Is prompt engineering here to stay
23:40 - Understanding language models and their limitations
32:56 - Predictions for AI in 2025
39:53 - Measuring progress toward AGI
42:26 - The true value of AI technology

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Humanloop is the LLM evals platform for enterprises. We give you the tools that top teams use to ship and scale AI with confidence. To find out more go to humanloop.com