Join Simon Maple as he sits down with Bouke Nijhuis, the Chief Technology Officer of CINQ, a consultancy based in Amsterdam. Bouke, an experienced Java developer and international speaker, delves into the world of Test-Driven Development (TDD) and the role of AI in modern software development. Throughout the episode, Bouke discusses his experiences with various AI coding assistants, and the innovative concept of generating code from human-written tests using AI. Learn about Bouke's practical implementations, the challenges faced, and his vision for a future where tests are the primary artifacts in software development. Whether you're a seasoned developer or just starting out, this episode offers valuable insights into the evolving landscape of AI-assisted coding.

In this episode of AI Native Dev, Guy Podjarny sits down with Jason Warner, a veteran in software development and AI. Jason's impressive career includes roles such as CTO at GitHub, where he contributed to the creation of GitHub Actions and GitHub Copilot, GM at Heroku, and positions at Canonical and Redpoint Ventures. Now, as the founder of Poolside, Jason focuses on developing state-of-the-art language models for software development. This episode covers the evolution of code generation, the impact of AI on software development, the challenges and limitations of current models, and speculations on the future role of developers in an AI-native world.Join the AI Native Dev Community on discord: https://tessl.co/4ghikjh Register to the monthly live event: http://tessl.co/podcastliveAsk us questions: podcast@tessl.io

James Ward, a developer advocate at AWS, shares his fascinating journey in software development and testing. He dives into AI's potential to automate coding tasks and the critical need for comprehensive testing. Ward discusses the delicate balance between using AI tools like AWS Q Developer and maintaining human oversight. He addresses AI's strengths and limitations, notably its inaccuracies, while emphasizing the evolving role of developers from coding to high-level design. Insights into the future of development highlight the essential blend of AI efficiency and human creativity.

James Ward, a seasoned software developer with deep expertise in cloud computing and AI, shares his insights on Q Developer, an AI assistant that seamlessly integrates with AWS services. He discusses its features like code explanation and test generation, emphasizing how it enhances coding productivity. James explores AI-assisted coding for complex topics like Java concurrency, showcasing the tool's effectiveness in problem-solving. His practical advice and personal experiences provide invaluable tips for developers looking to boost their productivity.

Itamar Friedman, co-founder and CEO of Codium AI, dives into the transformative power of AI in software testing. With a background in chip verification, Itamar discusses how AI enhances test planning, generation, and maintenance across various testing types. He contrasts traditional methods with AI-driven strategies, addressing common developer concerns about trusting AI-generated tests. The conversation also covers the future of autonomous AI test generation and the vital balance between innovation and human oversight in maintaining software accuracy.

Hosts dive into the effectiveness of AI tools, tackling the nuanced challenges developers face in evaluating their performance. They discuss the critical importance of context in AI code generation and highlight the reality of AI hallucinations, balancing user trust with AI's creative output. The conversation shifts to the trade-offs between integrated and specialized developer tools, emphasizing the role of data in functionality. Plus, anticipate format changes for richer audience engagement and insights from upcoming expert guests.

Devin Stein, a visionary behind the AI-driven tool Dosu, shares insights into how it transforms software development. He explains how Dosu triages issues, maintains documentation, and enhances knowledge retrieval by integrating diverse data sources. The discussion highlights AI's role in open-source projects, automating responses, and optimizing developer efficiency. Devin emphasizes the critical balance between AI capabilities and human oversight, shedding light on the importance of testing to navigate the pitfalls of AI in development.

Devin Stein, the innovative founder of Dosu, is on a mission to ease developers' maintenance burdens with AI. He discusses how AI is shifting the software development landscape by automating tasks beyond the traditional coding environment. The conversation dives into the challenges of integrating AI into workflows, including the complexities of maintaining large codebases and ensuring context in coding assistance. Devin also highlights the evolving role of developers as they adapt to AI, opening up new opportunities for both veterans and newcomers.

In this episode, Simon Maple dives into the world of AI testing with Rishabh Mehrotra from Sourcegraph. Together, they explore the essential aspects of AI in development, focusing on how models need context to create effective tests, the importance of evaluation, and the implications of AI-generated code. Rishabh shares his expertise on when and how AI tests should be conducted, balancing latency and quality, and the critical role of unit tests. They also discuss the evolving landscape of machine learning, the challenges of integrating AI into development workflows, and practical strategies for developers to leverage AI tools like Cody for improved productivity. Whether you're a seasoned developer or just beginning to explore AI in coding, this episode is packed with insights and best practices to elevate your development process.Join the AI Native Dev Community on discord: https://tessl.co/4ghikjh Register to the monthly live event: http://tessl.co/podcastliveAsk us questions: podcast@tessl.io

Intercom Co-Founder, Des Traynor, discusses the evolution from AI-assisted tools to autonomous AI agents, organizational changes, and future of AI-powered customer support. Topics include AI integration in chat-based support, challenges in AI-driven software development, continuous deployment and pre-deployment testing in AI applications, team structures and skillsets in AI product development, chat-based AI interfaces, AI in customer engagement, and the future role of support personnel in an AI-driven customer service landscape.