AI Native Developer, hosted by Guy Podjarny and Simon Maple. Interviews looking at how Software Developers are using AI. Released as Audio and Video.
Episodes
21 Apr 2026
Software developers must adapt to AI's complexity by bridging tools with real-world applications, mastering context engineering, shifting toward high-level design and system architecture, and navigating fragmented ecosystems as AGI emerges as an integrated system rather than a standalone model.
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14 Apr 2026
AI in software development shifts from code-centric practices to context- and specification-driven approaches, with humans prioritizing decision-making and oversight while AI handles implementation, but challenges like non-human-readable code, alignment with team practices, and contextual accuracy remain critical.
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7 Apr 2026
The text examines AI development competition, the growing role of open-source models in countering major companies' IP dominance, critiques of restrictive licensing, examples of efficiency-driven innovations, regional strategies, and future trends favoring open-source collaboration and cost-effective solutions.
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31 Mar 2026
Alternative approaches to Large Language Models are gaining traction, with examples like Apple's offline image detection model and the WebMCPa API addressing AI agent limitations through client-side execution, lightweight local models, and streamlined web interactions while navigating challenges in scalability, cost, and dynamic content.
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24 Mar 2026
Phoenix Architecture redefines software development by treating code as disposable, prioritizing enduring system specifications, modularity, AI integration, and balance between automation and human oversight to enable safe, iterative updates and future-ready, adaptable systems.
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17 Mar 2026
AI skills pose significant security risks, with 13.4% containing critical vulnerabilities like prompt injections and unauthorized access, driven by high privileges and obfuscated threats, requiring tools like Sneak/Snyk and complementary measures such as code reviews and supply chain monitoring.
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10 Mar 2026
Agentic development uses automated agents powered by Large Language Models to enhance software engineering processes, with benefits including streamlined coding, testing, and collaboration.
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3 Mar 2026
Agents contribute to knowledge management by retaining and retrieving information through a combination of embedded models, databases, and large language models.
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25 Feb 2026
Experts share strategies for successfully developing AI models by effectively managing context, security, and performance.
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17 Feb 2026
Agentic development uses AI agents to automate software tasks, shifting the focus to speed and intent-driven specifications while relying on context management to achieve accurate results.
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