More The AI Native Dev episodes
Published 27 Jan 2026
Duration: 3407
Software development is evolving with the increasing use of AI tools for tasks like code generation, collaboration, and routine tasks.
You have to prioritize between the thing you want to do and the thing that actually is driving the business, thats what really big companies are fight...
The podcast examines how software development is evolving with the increasing use of AI tools, marking a transformative shift in the field. While it's difficult to predict specific changes in the next one to two years, the industry is expected to continue managing large existing codebases while incorporating AI in various aspects of development, such as brainstorming, code generation, and collaboration. AI agents are becoming integral to development workflows, assisting with tasks like code cleanup and security checks, and developers are turning more frequently to cloud-based tools and AI-driven ideation before writing code.
Despite these advancements, traditional development practices remain prominent, and there are ongoing challenges in managing AI-generated outputs without disrupting existing workflows. The discussion also covers the dynamic between innovation driven by startups and established companies, shifts in the developer tools market, and the potential for AI to redefine productivity, collaboration, and the long-term role of software engineers.
16 Jun 2026 AI Security & the Agent-Ready Web: Experts Weigh In
Agentic AI systems face critical security risks from overconfidence, prompt-injection vulnerabilities, bypassable guardrails, and performance-driven development, requiring foundational security measures, developer education, and intent-based design to bridge readiness gaps and ensure safe innovation.
9 Jun 2026 Ryan Lopopolo: OpenAI's Framework for Shipping Code at 70 PRs/Week
The text explores Codex's integration via Chrome DevTools and TypeScript daemons, agentic development's emphasis on autonomous workflows and trustworthiness, harness engineering's structured tool integration, code QA with automation and feedback loops, shifts in code reviews toward strategy, AI agents as onboarding tools, persistent specs over code, balancing specification precision with adaptability, computational costs of token-heavy processes, and adapting team dynamics to agent-centric workflows.
2 Jun 2026 Why Developers Hit a Wall at 4 AI Agents
AI integration in software development faces challenges like limited agent management (1-2 per developer), lower acceptance of AI-generated code (60% merge rate vs. 80% for human), scalability barriers, and the need for improved observability, workflow alignment, and strategic business integration to balance productivity gains with quality and security.
26 May 2026 Don't Secure the Code. Secure the Coder.
The text addresses security challenges in AI and agentic systems, emphasizing unintended risks like reward-seeking behaviors, the need for developer-centric security strategies, novel attack vectors, frameworks adopting agentic principles, and proposed solutions such as the "AI Bill of Materials" alongside risks like data leakage and governance challenges.
19 May 2026 The Hidden Security Risks of AI Coding Agents
Agentic systems introduce heightened security risks through text-based interactions enabling malicious intent encoding, sensitive data access, untrusted inputs, and external system communication, requiring mitigation via SCA, restricted agent access, dynamic analysis, and balancing security with productivity through transparency and adapted security frameworks.