Deterministic Code Modernization, Multi-Repo Governance, and AI-Driven Technical Debt | AppDevANGLE скачать в хорошем качестве

Deterministic Code Modernization, Multi-Repo Governance, and AI-Driven Technical Debt | AppDevANGLE

AI coding tools are accelerating software development, but they are also accelerating technical debt. In this episode of AppDevANGLE, Principal Analyst Paul Nashawaty speaks with Jonathan Schneider, CEO and Co-Founder of Moderne, about why deterministic, cross-repository modernization is becoming critical in the AI coding era. As 84% of developers now use or plan to use AI coding tools, enterprises face a new challenge: governing hundreds of millions, and sometimes billions, of lines of code across multi-repo, multi-language environments. Generative AI can write code, but it cannot safely refactor entire portfolios at scale without deterministic controls. This conversation explores how semantic code modeling, structured transformations, and repeatable “recipes” enable auditable, enterprise-wide modernization, reducing security risk, regulatory exposure, and vendor lock-in. 🔎 Key Research Highlights: Why AI code generation increases modernization risk at scale The difference between probabilistic code generation and deterministic transformation How multi-repository complexity limits traditional DevOps tooling Why governance frameworks (EU CRA, supply chain security) demand structured remediation How deterministic “recipes” enable horizontal modernization across business units The concept of a “liquid tech stack” and strategic vendor shifts 00:00 - Intro 00:07 - Transforming Software Development: AI Integration and Modern Challenges 03:26 - Enhancing Code Safety: Integrating AI with Comprehensive Change Strategies 05:44 - Managing Large-scale Codebases 09:14 - Challenges of Multi-language and Multi-repo Environments 11:58 - Preparing for the Rise of Agentic AI: Governance, Development, and Future Insights