Afleveringen
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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
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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.
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Zijn er afleveringen die ontbreken?
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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.
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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.
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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.
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In this episode, Jordi Montes interviews Josh Meyer, a founding engineer at Tollbit. Josh discusses the evolution of AI agents, LLMs (Large Language Models), and how tools are being integrated into AI applications.Josh shares insights from his work at Tollbit, a company helping publishers monetize AI systems that scrape their websites. He also explains his project BrowserPassport, which provides authentication and authorization solutions for AI agents. At the end he exposes the main benefits of being in San Francisco when building a startup related to AI.
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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.
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In this episode, Jordi Montes and Thorsten Ball discuss the evolving landscape of AI agents, particularly in the context of Sourcegraph and software development.
Thorsten is back to working at Sourcegraph after one year helping to develop the Zed code editor. He is well know in the Golang and software engineering communities as the author of "Writing An Interpreter In Go"and "Writing A Compiler In Go".
Sourcegraph accelerates how software gets built, helping developers search, understand, and write code in complex codebases with AI.
This conversation explores the definition of AI agents, the integration of AI into Sourcegraph's operations, and the implications of AI on code search and software development practices. The discussion highlights the transformative potential of AI tools, the importance of performance, and the need for developers to adapt to new paradigms in coding and tool usage. They explore the transformative impact of Large Language Models (LLMs) on software development. They discuss how LLMs enhance the developer experience by improving code context management, shifting programming paradigms, and revolutionizing code interaction. This episode also touches on the future of commit messages and documentation, emphasizing the need for tools that adapt to the evolving landscape of coding and AI integration.
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In this episode, Jordi Montes and David from Aomni discuss the evolving landscape of AI agents, their definitions, and their implications for software interaction and sales operations. David and his projects went viral multiple times the last one being an open source version of Deep Research. His company, Aomni, enables B2B sales reps save more than 7 hours per week on prospect research.David shares insights on building autonomous agents for revenue teams, the challenges of current software stacks, and the future of AI in enterprise sales. We talk about the role of tool calling in AI development and the potential for integrating coding with AI capabilities. We cannot stress enough importance of not underestimating their capabilities. The dialogue also touches on user interaction, the role of context and memory in AI applications, and the challenges of service discovery and performance evaluation in agent-based systems.
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In this episode, Jordi Montes and Matt Wyman discuss the evolving landscape of AI agents, exploring their definitions, applications, and the challenges faced in building complex systems. Matt shares his journey from engineering to product management, highlighting the importance of understanding user behavior and the need for new monitoring tools tailored for AI systems. They delve into diverse use cases for AI agents, from parts catalogs to onboarding processes, and debate the merits of fine-tuning versus in-context learning. In this conversation, Matt Wyman and Jordi Montes discuss the evolving landscape of AI performance metrics, the importance of establishing baselines for continuous improvement, and the role of data scientists in engineering. They explore the shift towards multimodal AI solutions, the challenges of agent deployment and orchestration, and innovations in authentication for AI agents. The discussion also touches on the future of AI model evaluation and adaptation, emphasizing the need for organizations to embrace constant measurement and experimentation.
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In this episode of Agents at Work, Jordi Montes interviews Christopher David, founder and CEO of OpenAgents, discussing the evolution of AI agents, their functionality, and the future of coding agents. Christopher shares insights on the development of ONYX, a mobile app for coding agents, and the importance of transparency and trust in AI development. The conversation also touches on the impact of new AI models, the role of interfaces, and the vision for a Bitcoinized economy where agents can operate autonomously.
