Last night at Open Lakehouse + AI in Paris 🇫🇷 Aravind Segu and Edwin He presented Omnigent: A Meta Harness for AI Agents covering why adopting agents is easy and operating them isn’t, then a live demo. Thanks to everyone who came out! 🗓️ Upcoming Omnigent events:  #OpenLakehouse# #Omnigent#

An AI-ready open lakehouse has three layers: Apache Iceberg for storage, catalog federation for governance, and MCP for AI agent access. More on our borderless lakehouse with @googlecloud: 🧊

Querying JSON in open lakehouse tables means parsing everything at runtime — no predicate pushdown, no skipping. Iceberg v3 Variant flips that by: ✦ Shredding nested data into typed columns at write time ✦ Enabling predicate pushdown at the column level Result: In an 11-query benchmark on identical Iceberg tables, Snowflake was 2.3x faster at equivalent compute.

📣 Hey Paris: Join us on Sept 23 for the next Open Lakehouse + AI meetup! Aravind Segu and Edwin He will cover why to use a meta-harness: collaborate on your work, exercise control, and choose your coding agent harnesses. The talk includes a demo of Omnigent’s workflow, including @opentelemetry traces in tools like @MLflow. 🗓️ Wed, Sept 23 | 6:00–9:30 PM GMT+2 📍 La Fondation, Paris 🎟️ Register: #Paris# #Omnigent# #OpenSource#