Webinar: Git For Data- How Agents Write to Production Without Breaking It | July 14th | 9am PT

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Rethinking the Semantic Layer in an Agent-Native Data Stack

The semantic layer existed because humans could not read SQL. Agents can. Jacopo Tagliabue (CTO, Bauplan) makes a contrarian case: most of what a semantic layer provides for agents already lives in well-written pipeline code- decorators, type hints, Pydantic classes, and docstrings, persisted next to data in Iceberg.

Chapters

00:00 - Introduction

‍07:27 - What the semantic layer is and why it exists

‍14:17 - The contrarian thesis: LLMs and open formats change the equation

‍17:21 - Example: revenue by country, in code

‍40:25 - Q&A

Git for Data: How Agents Write to Production Without Breaking It
Who Has the Best Lakehouse Design? A Round Table Discussion.
Forgiveness, Not Permission: Running Agents On Production Data
Rethinking the Semantic Layer- Part II: The Builders Response
Quality Checks With Bauplan and Claude Code
Data Assessment With Bauplan and Claude Code
Fixing Data Pipelines with Bauplan and Claude Code
ML Ops at Reasonable Scale feat. Jacopo Tagliabue
The Post Modern Stack // Jacopo Tagliabue // MLOps Meetup #103
Jacopo Tagliabue on Recommender Systems
Building a Data Science Platform on Apache Iceberg and Nessie
How to Make Your Data Science Reproducible (and Why You Should Care)
Are your Data Pipelines Complex?
Unapologetically Technical Jacopo Tagliabue - Bauplan Ep.19
Miracle on Ice(berg): How we Moved Europe’s Largest Broadcaster to Python-on-Iceberg in Days
The Bucket Brigade: Why S3 is the Missing Piece in your AI Architecture - Jacopo Tagliabue
How Jacopo Tagliabue is Cutting Data Pipeline Latency with Fast Functions
Python Over Data Lakes: Declarative Environments, Data Management & Other Things w/ Feathers
OpenXData - Data as Software and the programmable lakehouse
Building Scalable Data Pipelines
Speedrunning the Lakehouse & AMA with Jacopo Tagliabue
Open Lakehouse + AI: From Functions to AI Agents: Reimagining the Lakehouse for an Agentic Future
Speedrunning the Lakehouse
Inside the Minds of Two CTOs: The Future Is Apache Iceberg | Fireside Chat by OLake
Getting started with Bauplan Labs
Safe, Untrusted, "Proof-Carrying" AI Agents: Toward the Agentic Lakehouse with Jacopo Tagliabue
Speedrunning the Lakehouse by Jacopo Tagliabue | DC Systems 011
An AI Agent Built My Entire Data Pipeline. Here's How I Kept It From Breaking Production
Agentic Data Lakehouses, Claudio and More w/ Bauplan
Bauplan Platform Primitives Demo: Python, Iceberg, and Git-for-Data
AI Agents Debug Data Pipelines Automatically | Bauplan Agent Demo with Claude
Bauplan Demo: Git-for-Data and AI Agents on Production Data | with Claude Code
Celebrating Python SDKs: Bauplan gets it!
Spending 10 Minutes with Bauplan - A Serverless Data Lakehouse!
Build Modern Python Data Pipelines with Prefect and Bauplan
Simplify Apache Iceberg Adoption with Python: A Bauplan + Orchestra Demo
From Claude to Pipelines: AI-Assisted Data Engineering
From Alerts to Agents: Rethinking Data Quality with Claude Code
Trusting AI with Your Data: Safe Automation from Branch to Production
Python Based Data Infra for AI Agents
Rethinking the Semantic Layer in an Agent-Native Data Stack
Ingest S3 Data Safely with Bauplan Skills for Claude Code
Generate a Data Pipeline from a Prompt with Bauplan Skills for Claude Code
Explore Production Data Safely with ClaudeCode and Bauplan