Marco Palladino, CTO and co-founder of Kong, dives into the transformative power of AI in the tech landscape. He discusses the evolution from simple chatbots to intelligent AI agents that enhance organizational efficiency. Key topics include Kong's AI Gateway, which simplifies AI integration while addressing security concerns. Palladino highlights the automated Retrieval-Augmented Generation (RAG) feature that minimizes errors. He emphasizes the critical need for consistent security measures to empower developers to drive innovation safely.

Mallory Haigh, Director of Customer Success at Humanitec, and Nathen Harvey, DORA Lead and Developer Advocate at Google, dive into the complexities of platform engineering. They discuss the pitfalls of rushing into building internal development platforms without a clear purpose. Mallory emphasizes that success hinges more on cultural change than technical skills. The transformative role of AI in streamlining processes and enhancing developer satisfaction is also explored, suggesting that the future of platform engineering will involve integrating AI-driven automation with a focus on user needs.

Mark Hinkle, CEO of Peripety Labs and a veteran in serverless technologies, discusses the intriguing role of AI agents in software development. He describes these agents as 'dumb robots' that automate tasks but rely on large language models for real intelligence. Hinkle highlights the transformative potential of AI in creating bespoke tools on-the-fly and emphasizes the necessity of effective management practices. The conversation also spans his three-decade journey through technological evolution and the shift towards innovative GPU utilization in AI.

Join Janakiram MSV, a seasoned analyst known for his insights into data evolution and AI, as he discusses the shift from traditional SaaS to intelligent AI agents. He highlights how data management has advanced over the years, emphasizing the journey from spreadsheets to sophisticated AI solutions. Janakiram delves into the complexities of orchestrating these agents, akin to Kubernetes managing containers, and the new challenges of handling dynamic data. The conversation offers a glimpse into the future of service delivery and the transformative role of actionable AI in enterprises.

Amazon Q Developer is streamlining the software development lifecycle by integrating AI-powered tools into AWS. In an interview at AWS in Seattle, Srini Iragavarapu, director of generative AI Applications and Developer Experiences at AWS, discussed how Amazon Q Developer enhances the developer experience. Initially focused on inline code completions, Amazon Q Developer evolved by incorporating generative AI models like Amazon Nova and Anthropic models, improving recommendations and accelerating development. British Telecom reported a 37% acceptance rate for AI-generated code.Beyond code completion, Amazon Q Developer enables developers to interact with Q for code reviews, test generation, and migrations. AWS also developed agentic frameworks to automate undifferentiated tasks, such as upgrading Java versions. Iragavarapu noted that internally, AWS used Q Developer to migrate 30,000 production applications, saving $260 million annually. The platform offers code generation, testing suites, RAG capabilities, and access to AWS custom chips, further flattening the SDLC by automating routine work. Listen to The New Stack Makers for the full discussion.Learn more from The New Stack about Amazon Q Developer: Amazon Q Developer Now Handles Your Entire Code Pipeline Amazon Q Apps: AI-Powered Development for All Amazon Revamps Developer AI With Code Conversion, Security Join our community of newsletter subscribers to stay on top of the news and at the top of your game. 

Maya Kaczorowski, a respected technologist and founder of Oblique, dives into the intersection of OAuth, AI agents, and identity management. She reveals how developers perceive AI agents as extensions of themselves, thus relying on OAuth for secure access. Kaczorowski highlights the growing challenges in managing vast numbers of AI identities, emphasizing the need for scalable solutions. The discussion addresses the complexities of integrating AI with SaaS, the balance of AI autonomy versus security safeguards, and ongoing evolution in access control methods.

Yam Marcovitz, tech lead at Parlant.io and CEO of emcie.co, dives into the evolution of large language models (LLMs) and their comparison to programming languages. He discusses how LLMs have progressed from simple text generation to more sophisticated reasoning and decision-making capabilities. Marcovitz highlights the importance of attentive reasoning queries for maintaining accuracy and consistency in AI interactions. He also addresses the subjectivity inherent in AI interpretation, emphasizing the need for nuanced approaches in developing AI agents, especially for customer service.

Adam Jacob, Co-founder and CEO of System Initiative, dives into the future of enterprise automation. He discusses the shift from writing code to building models for quick simulations, likening it to Formula One racing for optimization. The conversation highlights how this approach enhances collaboration among engineers and simplifies complex tasks. Adam also touches on the role of digital twins in model accuracy and emphasizes the importance of evolving organizational culture to leverage these technologies effectively.

Morgan McLean, co-founder of OpenTelemetry and senior director at Splunk, shares insights from his extensive experience in observability for large-scale systems. He discusses the evolution of OpenTelemetry, born from OpenTracing and OpenCensus, and its crucial role in simplifying distributed tracing and application metrics. McLean anticipates that profiling will emerge as a key observability signal by 2025. He also explores the integration of AI with observability and the community's collaborative efforts aimed at improving adoption and standardization across diverse environments.

Christine Yen, Co-founder and CEO of Honeycomb.io, discusses the rising costs of observability in modern cloud-native systems. She highlights how traditional logging and monitoring tools struggle to cope with today's software complexities, leading to inefficiencies. Yen emphasizes the need for innovative solutions that prioritize user experience, like Service Level Objectives (SLOs). She also explores the role of AI and OpenTelemetry in addressing these challenges, showcasing the potential for enhanced insights in software management.