High Agency: The Podcast for AI Builders

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

In this episode, we explore how Replicate is breaking down barriers in AI development through its open-source platform. CEO Ben Firshman shares how Replicate enables developers without machine learning expertise to run AI models in the cloud.

00:00 Introduction 
00:29 Overview of Replicate 
03:13 Replicate's user base 
05:45 Enterprise use cases and lowering the AI barrier 
07:45 The complexity of traditional AI deployment 
10:24 Simplifying AI with Replicate's API 
13:50 ControlNets and the challenges of image models 
19:42 Fragmentation in AI models: images vs. language 
25:05 Customization and multi-model pipelines in production 
26:33 Learning by doing: skills for AI engineers 
28:44 Applying AI in governments 
31:12 Iterative development and co-evolution of AI specs 
33:13 Final reflections on AI hype 
35:18 Conclusion

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Humanloop is an Integrated Development Environment for Large Language Models. It enables product teams to develop LLM-based applications that are reliable and scalable. To find out more go to humanloop.com

How do you build AI tools that actually meet users’ needs? In this episode of High Agency, Raza speaks with Lorilyn McCue, the driving force behind Superhuman’s AI-powered features. Lorilyn lays out the principles that guide her team’s work, from continuous learning to prioritizing user feedback. Learn how Superhuman’s "learning-first" approach allows them to fine-tune features like Ask AI and AI-driven summaries, creating practical solutions for today’s professionals. 

00:00 - Introduction
04:20 - Overview of the Superhuman
06:50 - Instant Reply and Ask AI
10:00 - Building On-Demand vs. Always-On AI Features
13:45 - Prompt Engineering for Effective Summarization
22:35 - The Importance of Seamless AI Integration in User Workflows
25:10 - Developing Advanced Email Search with Contextual Reasoning
29:45 - Leveraging User Feedback
32:15 - Balancing Customization and Scalability in AI-Generated Emails
36:05 - Approach to Prioritization
39:30 - Real-World Use Cases: The Versatility of Current AI Capabilities
43:15 - Learning and Staying Updated in the Rapidly Evolving AI Field
46:00 - Is AI Overhyped or Underhyped?
49:20 - Final Thoughts and Closing Remarks

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Humanloop is an Integrated Development Environment for Large Language Models. It enables product teams to develop LLM-based applications that are reliable and scalable. To find out more go to humanloop.com

This week on High Agency, Raza Habib is joined by Chroma founder Jeff Huber. They cover the evolution of vector databases in AI engineering, challenge common assumptions about RAG and share insights from Chroma's journey. Jeff shares insights from Chroma's development, including their focus on developer experience and observations about real-world usage patterns. They also get into whether or not we can expect a super AI any time soon and what is over and under hyped in the industry today. 

00:00 - Introduction
02:30 - Why vector databases matter for AI
06:00 - Understanding embeddings and similarity search
12:00 - Chroma early days
15:45 - Problems with existing vector database solutions
19:30 - Workload patterns in AI applications
23:40 - Real-world use cases and search applications
27:15 - The problem with RAG terminology
31:45 - Dynamic retrieval and model interactions
35:30 - Email processing and instruction management
39:15 - Context windows vs vector databases
42:30 - Enterprise adoption and production systems
45:45 - The journey from GPT-3 to production AI
48:15 - Internal vs customer-facing applications
51:00 - Advice for AI engineers

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Humanloop is an Integrated Development Environment for Large Language Models. It enables product teams to develop LLM-based applications that are reliable and scalable. To find out more go to humanloop.com

In this episode of High Agency podcast, Peter Gostev shares his experiences implementing LLMs at NatWest and Moonpig. He discusses creating an AI strategy, talks about challenges in deploying LLMs in large organizations, and shares thoughts on underappreciated AI developments.

00:00 - Introduction
00:44 - OpenAI dev day reactions  
03:47 - Using AI to automate customer service  
10:43 - Impact of AI products
13:41 - Who are the users of LLMs
14:47 - Challenges building with AI in a large enterprise  
21:22 - AI use cases at Moonpig
24:34 - How to create an AI strategy
28:10 - Underappreciated AI developments

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Humanloop is an LLM evals platform for enterprises. It enables product teams to develop LLM-based applications that are reliable and scalable. To find out more go to humanloop.com

In this episode of High Agency, we're joined by Surojit Chatterjee, former CPO of Coinbase and now CEO of Ema. Surojit unveils his audacious plan to create universal AI employees and revolutionize Fortune 1000 workforce. Drawing from his career at tech giants like Google and Coinbase, he shares how these experiences fueled his vision for Ema. Surojit dives into the challenges of building AI agents, explores the concept of artificial humans, and predicts how this technology could transform the future of SaaS

(00:00:00) Introduction and Surojit’s background

(00:03:00) Founding story of Ema (Universal AI Employee)

(00:04:53) How the Universal AI Employee works

(00:08:39) Ema’s data integration and security

(00:12:57) AI employee use cases in enterprises

(00:15:02) Challenges with building AI agents

(00:16:45) Evaluations, hallucinations, customizing models

(00:19:52) Artificial human metaphor 

(00:25:42) AI employee vs humans

(00:31:25) Advice for AI builders

(00:37:14) Is AI overhyped or underhyped?

(00:39:28) How the business model of SaaS will change

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Humanloop is an Integrated Development Environment for Large Language Models. It enables product teams to develop LLM-based applications that are reliable and scalable. To find out more go to humanloop.com

Hamel Husain is a seasoned AI consultant and engineer with experience at companies like GitHub, DataRobot, and Airbnb. He is a trailblazer in AI development, known for his innovative work in literate programming and AI-assisted development tools. Shawn Wang (aka Swyx) is the host of the Latent Space podcast, the author of the essay 'Rise of the AI Engineer,' and the founder of the AI Engineer World Fair. In this episode, Hamel and Swyx share their unique insights on building effective AI products, the critical importance of evaluations, and their vision for the future of AI engineering.

Chapters
00:00 - Introduction and recent AI advancements

06:14 - The critical role of evals in AI product development

15:33 - Common pitfalls in AI product development

26:33 - Literate programming: A new paradigm for AI development

39:58 - Answer AI and innovative approaches to software development

51:56 - Integrating AI with literate programming environments

58:47 - The importance of understanding AI prompts

01:00:37 - Assessing the current state of AI adoption

01:07:10 - Challenges in evaluating AI models

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Humanloop is an Integrated Development Environment for Large Language Models. It enables product teams to develop LLM-based applications that are reliable and scalable. To find out more go to humanloop.com

Raz Nussbaum is a Senior Product Manager in AI at Gong — the leading AI platform for revenue teams. He is an absolute legend when it comes to building and scaling AI products that genuinely deliver value. In this episode, he opens up about what it takes to build successful AI products in an era where things change at lightning speed.

Chapters
00:00 - Introduction
01:16 - How LLMs Changed Product Development at Gong AI
08:32 - Including Product Managers in Development Process
13:05 - Testing and Monitoring Pre vs Post-deployment
17:53 - New Challenges in the Face of Generative AI
19:39 - Shipping Fast and Interacting with the Market
23:25 - What's Next For Gong AI
25:13 - The Psychology of Trusting AI 
28:19 - Is AI Overhyped or Underhyped?

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Humanloop is an Integrated Development Environment for Large Language Models. It enables product teams to develop LLM-based applications that are reliable and scalable. To find out more go to humanloop.com

In this episode, we dive deep into the world of AI-assisted creative writing with James Yu, founder of Sudowrite. James shares the journey of building an AI assistant for novelists, helping writers develop ideas, manage complex storylines, and avoid clichés. James gets into the backlash the company faced when they first released Story Engine and how they're working to build a community of users.

00:00 - Introduction and Background of Sudowrite
02:26 - The Early Days: Concept, Skepticism, and User Adoption
05:20 - Sudowrite's Interface, Features, and User Base
10:23 - Developing and Iterating Features in Sudowrite
17:29 - The Evolution of Story Bible and Writing Assistance
24:27 - Challenges in Maintaining Coherence and AI-Assisted Writing
29:12 - Evaluating AI Features and the Role of Prompt Engineering
33:35 - Handling Tropes, Clichés, and Fine-Tuning for Author Voice
40:43 - The Controversy and Future of AI in Creative Work
51:37 - Predictions for AI in the Next Five Years

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Humanloop is an Integrated Development Environment for Large Language Models. It enables product teams to develop LLM-based applications that are reliable and scalable. To find out more go to humanloop.com

In this episode, LiveKit CEO Russ d'Sa explores the critical role of real-time communication infrastructure in the AI revolution. From building voice demos to powering OpenAI's ChatGPT,  he shares insights on technical challenges around building multimodal AI on the web and what new possibilities are opening up.

00:00 - Introduction and Background
01:34 - The Evolution of AI and Lessons for Founders
05:20 - Timelines and Technological Progress
10:32 - Overview of LiveKit and Its Impact on AI Development
13:39 - Why LiveKit Matters for AI Developers
19:08 - Partnership with OpenAI
21:25 - Challenges in Streaming and Real-Time Data Transmission
30:07 - Building a global network for AI communication
37:21 - Real-world applications of LiveKit in AI systems
40:55 - Future of AI and the Concept of Abundance
43:38 - The Irony of Wealth in an Age of AI

I hope you enjoy the conversation and if you do, please subscribe!

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Humanloop is an Integrated Development Environment for Large Language Models. It enables product teams to develop LLM-based applications that are reliable and scalable. To find out more go to humanloop.com

This week we’re talking to Lin Qiao, former PyTorch lead at Meta and current CEO of Fireworks AI. We discuss the evolution of AI frameworks, the challenges of optimizing inference for generative AI, the future of AI hardware, and open-source models. Lin shares insights on PyTorch design philosophy, how to achieve low latency, and the potential for AI to become as ubiquitous as electricity in our daily lives.

Chapters: 
00:00 - Introduction and PyTorch Background
04:28 - PyTorch's Success and Design Philosophy
08:20 - Lessons from PyTorch and Transition to Fireworks AI
14:52 - Challenges in Gen AI Application Development
22:03 - Fireworks AI's Approach
24:24 - Technical Deep Dive: How to Achieve Low Latency
29:32 - Hardware Competition and Future Outlook
31:21 - Open Source vs. Proprietary Models
37:54 - Future of AI and Conclusion

I hope you enjoy the conversation and if you do, please subscribe!

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Humanloop is an Integrated Development Environment for Large Language Models. It enables product teams to develop LLM-based applications that are reliable and scalable. To find out more go to humanloop.com

In this episode of High Agency, we are speaking to Paras Jain who is the CEO of AI video generation startup Genmo. Paras shares insights from his experience working on autonomous vehicles, why he chose academia over an offer from Tesla, and the research-minded approach that has lead to Genmo's rapid success.

Chapters:
(00:00) Introduction
(01:52) Lessons from selling an AI company to Tesla
(07:01) Working within GPU constraints and transformer architecture
(11:18) Moving from research to startup success
(14:36) Leading the video generation industry
(16:05) Training diffusion models for videos
(19:36) Evaluating AI video generation
(24:06) Scaling laws and data architecture
(28:34) Issues with scaling diffusion models 
(33:09) Business use cases for video generation models
(36:43) Potential and limitations of video generation
(40:59) Ethical training of video models

In this week’s episode of the High Agency podcast, Humanloop Co-Founder and CEO Raza Habib sat down with Eddie Kim, co-founder and Head of Technology at Gusto and guest host Ali Rowghani to discuss how Gusto has applied AI to revolutionize ops-heavy processes like payroll and HR admin. Eddie also elaborates why Gusto is choosing to build, and not buy, the majority of their GenAI tech stack.

Chapters
00:00 - Introduction and Background
02:15 - Overview of Gusto's Business
05:59 - Operational Complexity and AI Opportunities
08:51 - Build vs. Buy: Internal vs. External AI Tools
10:07 - Prioritizing AI Use Cases
13:53 - Human-in-the-Loop Approach
19:39 - Centralized AI Team and Approach
22:53 - Measuring ROI from AI Initiatives
32:25 - AI-Powered Reporting Feature
38:46 - Code Generation and Developer Tools
42:52 - Impact of AI on Companies and Society
47:22 - AI Safety and Risks
49:54 - Closing Thoughts

I hope you enjoy the conversation and if you do, please subscribe!

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Humanloop is an Integrated Development Environment for Large Language Models. It enables product teams to develop LLM-based applications that are reliable and scalable. To find out more go to humanloop.com/podcast