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 

----------------------------------------------------------------------------------------------------------------------------------------------
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

--------------------------------------------------------------------------------------------------------------------------------------------------
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

--------------------------------------------------------------------------------------------------------------------------------------------------
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

--------------------------------------------------------------------------------------------------------------------------------------------------
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

--------------------------------------------------------------------------------------------------------------------------------------------------
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

--------------------------------------------------------------------------------------------------------------------------------------------------
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

--------------------------------------------------------------------------------------------------------------------------------------------------
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

--------------------------------------------------------------------------------------------------------------------------------------------------
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

--------------------------------------------------------------------------------------------------------------------------------------------------
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