Most CI/CD pipelines are built to detect failure, not to resolve it. As software systems grow more distributed and complex, that limitation is becoming a bottleneck for resilience.<br /><br />In this episode, David sits down with Tomer Karin, a seasoned software architect in the automotive industry, to explore a new paradigm he calls Continuous Integration and Continuous Solution (CI/CS). Tomer argues that the future  of automated software development isn’t just faster feedback loops, it's systems that can autonomously remediate failures using AI.<br /><br />Tomer shares how his years of working on large-scale automotive software revealed the inefficiencies of traditional development pipelines, where engineers spend significant time diagnosing and fixing issues instead of building new capabilities. With CI/CS, AI agents don’t just identify failing builds, they apply fixes that are verified through existing test pipelines, allowing teams to start the next day with a healthier codebase.<br /><br />Join us as we discuss:<ul><li>Why traditional CI/CD breaks down as systems scale and complexity increases </li><li>What Continuous Integration and Continuous Solution looks like in practice</li><li>How AI agents can safely diagnose and fix software failures</li><li>Where human oversight fits into autonomous development pipelines</li><li>The economic and productivity impact of autonomous software workflows</li></ul>