Readpodcast AI

Forgiveness, Not Permission: Running Agents On Production Data | Bauplan

AI Council
17.06.202632:32117 просмотровСмотреть на YouTube

[2026 - DAY 1 - AGENT INFRASTRUCTURE] As coding assistants ramp up adoption, the data industry’s focus is rapidly shifting on making agents trustworthy by sacrificing capabilities for trustworthiness. We argue that this is the wrong problem to solve, as systems should not need to trust agents, but be robust to mistakes and correct under concurrency. To that end, we introduce a correct-by-design lakehouse, where illegal states are (provably) unrepresentable: ill-typed pipelines should not be planned, inconsistent plans should not be run, failed runs should not be published. This results in agentic infrastructure with correctness guarantees for humans and agents, by combining Git-like APIs with MVCC-style transactions: data changes are always immutable but never fatal. We conclude by sharing best practices from the trenches for automation in data engineering, and outlining open challenges as we re-think OLAP infrastructure for agentic AI. SPEAKER: Jacopo Tagliabue - Founder, Bauplan 👉 Sign up for our "No BS" Newsletter to get the latest technical data & AI content: https://aicouncil.com/newsletter ABOUT AI COUNCIL: AI Council brings together the brightest minds in data to share industry knowledge, technical architectures and best practices in building cutting edge data & AI systems and tools. FIND US: Website: https://aicouncil.com/ LinkedIn: https://www.linkedin.com/company/aicouncilconf/ X: https://x.com/aicouncilconf

Read Video · Транскрипция и инсайты

Расшифровка и AI-анализ — бесплатный пробный доступ

Бесплатный аккаунт · без карты · 150 кредитов при регистрации, достаточно для этого эпизода

  • 📄 Полная транскрипция с временными метками
  • ✨ AI-резюме, ключевые слова и ментальная карта
  • 💡 Ключевые тезисы и цитаты

Эпизоды и видео готовы к чтению