Agents at work

In this episode of Agents at Work Jordi Montes interviews Saqib Ameen, a founding engineer at Langbase. They explore the evolution of AI development beyond Silicon Valley, Saqib's journey from working on symbolic programming to building sophisticated AI agents, and the exciting launch of Chai, a platform for building and deploying production-ready AI agents.Discover how Langbase's primitives-first approach and emphasis on developer experience are revolutionizing the way engineers and companies integrate AI into their workflows. Jordi and Saqib unpack topics ranging from the technical intricacies of symbolic programming and transformer models, to practical insights on deploying scalable, version-controlled AI solutions without the DevOps headache.Whether you're an AI enthusiast, developer, or entrepreneur looking to understand how AI agents can streamline and empower your applications, this episode provides invaluable perspectives and actionable takeaways. Tune in to hear about the future of AI infrastructure, what's next for Langbase, and the key trends shaping the AI landscape in the next year.Build your agents today at https://chai.new

In this conversation, Jordi Montes and Anita from Vellum discuss the evolving landscape of AI solutions, particularly in enterprise settings.Anita, Head of Growth at Vellum.ai , emphasizes the importance of building reliable AI systems in the enterprise context. She shares her experiences building solutions for real world use cases in companies like Headspace or Redfin.The discussion also touches on client expectations, the evolution of user satisfaction, and the internal adoption of AI tools within companies.The cherry on the cake is the best definition about AI Agents I heard so far. Long story short, is about control.

In this conversation, Jordi Montes and Tereza Tizkova dive deep into the challenges and opportunities around running AI-generated code safely and efficiently. Tereza explains how their E2B provides essential cloud sandbox infrastructure designed specifically for AI agents.The discussion explores why AI-generated code must be executed in secure, isolated environments and how E2B’s solution leverages micro virtual machines (micro VMs) to offer enhanced security, scalability, and speed. She highlights real-world applications like web app generation, deep research, data analysis, and computer-use agents,.They also address critical questions about open-source strategy, evolving LLM capabilities, industry benchmarks, and the exciting growth of AI agents in production settings.00:00 Introduction to E2B and AI Agents03:10 The Infrastructure Behind AI Agents05:48 The Evolution of E2B and Its Market Impact09:00 Customer Insights and Use Cases12:01 The Future of AI Agents and E2B's Role14:52 Open Source and Community Engagement18:02 Challenges and Opportunities in AI Development21:06 The Role of Data in AI Agents23:48 Exciting Developments and Future Directions27:13 Getting Started with E2B33:01 AI Hackathon in Prague: A New Era for Europe34:11 The European AI Landscape: Challenges and Opportunities35:44 Innovative Projects: Surprising Uses of E2B37:03 Understanding LLMs: Code Generation and Reasoning39:00 Versioning and Iteration: Enhancing Code Execution41:04 The Future of AI Infrastructure: Pricing and Data Insights45:32 The Evolution of AI Agents: What Lies Ahead51:00 Defining AI Agents: Capabilities and Future Trends

In this episode, Jordi Montes and Sully Omar discuss the evolution of AI agents, emphasizing the importance of hands-on tinkering in understanding and developing these technologies. They explore the definition of AI agents, the future of their simplification and intelligence, and the implications of frameworks like MCP for AI interactions. The conversation also touches on the role of payment systems in AI, the paradigm shift in agent functionality, and the categorization of AI models through a structured framework. In this conversation, Sully discusses the tiered structure of AI models, emphasizing the importance of evaluating new models based on their performance and use cases. He shares insights on integrating AI into business products, particularly through innovative workflows that leverage spreadsheets.

In this episode, Jordi Montes and Johno Whitaker (https://answer.ai) discuss the evolving landscape of AI agents, exploring definitions, the impact of generative AI, and how AI development is becoming more accessible. Answer.AI is a new kind of AI R&D lab which creates practical end-user products based on foundational research breakthroughs. You can think about it as Xerox Labs for the AI era.They delve into notebook-driven development, integration of AI in software workflows, and debate whether the future will feature powerful single models or cooperative networks of smaller agents. The conversation emphasizes empowering users through thoughtful interaction design and innovative frameworks like LLMs.txt and FastHTML, highlighting AI's potential to enhance human creativity and cautioning against over-reliance on automation.

In this conversation, Jordi Montes and Roy Derks discuss the evolution of AI agents, the role of IBM in the AI landscape, and the capabilities of the WatsonX platform. Roy explores the concept of agents in AI, industry adoption of AI technologies, and the balance between legal and engineering perspectives in large organizations. He also shares his journey from startups to IBM, highlighting the changes in development tools and the significance of GraphQL in AI integration. The discussion concludes with insights on the future of data access through MCP and the importance of making data easily accessible.

In this episode of Agents at Work, Jordi Montes interviews Aiswarya from Entelligence, a company building AI engineering agents to help large engineering teams reduce overhead and focus on product development. Aiswarya explains how Entelligence's tools assist with code reviews, documentation, and team coordination. She explains how their AI agents can catch issues in code, keep documentation continuously updated, and provide insights for managers about team productivity. She shares insights about the limitations of current AI coding models and how their product complements code generation tools by serving as an "auditor" that catches potential bugs and enforces best practices. The discussion highlights how AI tools are transforming engineering team dynamics, making information more transparent across organizations, and changing how engineering performance is measured in the age of AI-assisted coding.

In this engaging discussion, Josh Meyer, founding engineer at Tollbit, dives into the exciting world of AI agents and their integration with large language models. He shares insights on BrowserPassport, a novel solution for AI agent authentication. The conversation also highlights the challenges of web security and the innovative frameworks shaping AI technology. Josh emphasizes the unique advantages of being in San Francisco for AI startups, offering a fascinating glimpse into the future of AI and its potential impact on publishing and decision-making.

In this episode, Jordi Montes speaks with Arjun Chintapalli and Bhavani Kalisetty, co-founders of Retriever (https://rtrvr.ai), about the evolution of browser AI copilots. Arjun shares his background in federated learning at Google before founding RTRVR in December. Browser extension approach to AI assistance represents a significant advancement over traditional automation methods. By interpreting DOM representations rather than screenshots, this technology achieves greater speed, accuracy, and reliability compared to vision-based alternatives. The conversation explores how browser-based AI agents can simultaneously work across multiple tabs, extract structured data from websites, and integrate directly with productivity tools. All at a fraction of traditional web scraping costs. The technical advantages of operating within the user's browser environment include bypassing anti-bot systems, utilizing existing user credentials, and maintaining minimal performance overhead. They also discuss their vision for a workflow exchange marketplace where users can share automation recipes.

Thorsten Ball, a software engineer at Sourcegraph and author of influential coding books, dives into the future of coding with AI agents. He shares insights on how AI, particularly through large language models, is transforming software development. The conversation highlights the role of AI in enhancing coding productivity and user interaction tools. Thorsten emphasizes the need for developers to adapt to new paradigms, reshape code practices, and embraces AI tools to improve documentation and commit messages for a seamless coding experience.