À PROPOS DE CET ÉPISODE
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.
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.
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.
Join us as we discuss:
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.
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.
Join us as we discuss:
- Why traditional CI/CD breaks down as systems scale and complexity increases
- What Continuous Integration and Continuous Solution looks like in practice
- How AI agents can safely diagnose and fix software failures
- Where human oversight fits into autonomous development pipelines
- The economic and productivity impact of autonomous software workflows
Anglais
États-Unis
TRANSCRIPTION 🔗
Are you the producer of this podcast?
Add a podcast transcript
Need Audio-to-Text?
Transcribe with Listen411 in Just 60 Seconds
RECHERCHER LES ÉPISODES PASSÉS
Rechercher les épisodes précédents de Big Ideas in App Architecture.
AUTRES ÉPISODES DANS CE PODCAST
In this episode, David sits down with Nishant Raman, a seasoned data infrastructure expert, to explore the evolving world of data engineering, AI integration, and building scalable systems from the ground up. With experience across logistics, healthcare, and fintech, Nishant shares hard-won insight…
Most databases are designed for success cases. Real systems fail– the difference is whether they’re built and tested for it. In this episode, David sits down with Spencer Kimball, co-founder and CEO of Cockroach Labs, to explore the architectural and testing decisions behind CockroachDB, and why va…
In this episode, David sits down with Masaru Hoshi, a cloud architect at Qlik, to explore his unexpected journey into cloud architecture, the cultural influences that shaped his career, and the evolving disciplines transforming enterprise technology today. Join as we discuss:
Masaru’s path from d…
In this episode, David sits down with Peter Mattis, co-founder, CTO, and CPO of Cockroach Labs, to dive into the world of resilient databases, the evolution of AI in tech, and the journey of building a company that’s transforming how engineers approach scalability and performance. Peter shares insi…
Avertissement: Le podcast et les illustrations intégrés sur cette page proviennent de Cockroach Labs, qui est la propriété de son propriétaire et n'est ni affilié ni approuvé par Listen Notes, Inc.
MODIFIER
Merci de nous avoir aidé à tenir la base de données de podcasts à jour.
