All Data and AI Weekly #251–20 July 2026

2026-07-20 · Source: AI on Medium · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Data Science & Analytics, Cloud Computing & IT Infrastructure · Depth: Intermediate, extended

Summary

Snowflake's "All Data and AI Weekly #251" for July 20, 2026, highlights significant advancements in AI and data integration. Google's Gemini 3 is now available on Snowflake Cortex AI, offering enterprise-ready multimodal models. Snowflake also introduced the Agentic Resource Discovery Specification, an open standard for AI agents to find data. Key platform updates include the private preview of Snowflake Data Stream, a Kafka-compatible service for real-time data ingestion with automatic table materialization and sub-second latency. Snowpipe Streaming V2 is generally available, supporting up to 10 GBPS throughput per table, with new elastic channels and durable acknowledgements. Other releases include the Online Feature Store (Preview), CREATE OR ALTER (GA), and a stored procedure for creating Semantic Views from OSSIE YAML. The report also notes Prefect's acquisition of Dagster, zero-copy integrations with SAP and IBM Watsonx, and OpenFlow enhancements, including a GA Oracle connector.

Key takeaway

For AI/MLOps Engineers or Data Architects building real-time AI applications, you should evaluate Snowflake's new Data Stream for simplified, Kafka-compatible data ingestion, especially for agentic workloads. Leverage Snowpipe Streaming V2 for high-throughput pipelines, benefiting from elastic channels and durable acknowledgements. Utilize Cortex Code to streamline the setup and management of these services, accelerating your path to integrated AI solutions within a governed environment.

Key insights

Snowflake is rapidly integrating AI capabilities and real-time data streaming directly into its platform.

Principles

• AI agents require fresh, semantically rich data for effective decision-making.
• Managed services reduce infrastructure complexity for streaming data.
• Zero-copy integration simplifies access to diverse enterprise data sources.

Method

Cortex Code can provision Kafka-compatible Data Stream objects, topics, users, and pipes to materialize real-time data into Snowflake tables with minimal manual setup.

In practice

• Deploy Google Gemini 3 via Cortex AI for multimodal enterprise models.
• Utilize Snowflake Data Stream for Kafka-compatible real-time data ingestion.
• Implement Snowpipe Streaming V2 for high-throughput data pipelines.

Topics

• Snowflake Cortex AI
• Agentic AI
• Real-time Data Streaming
• Data Ingestion
• Apache Kafka
• Data Lakehouse
• Infrastructure as Code

Code references

• tspannhw/SNACKAI-CoCo-AirQuality
• tspannhw/SNACKAI-CoCo-EnviroUrban
• moonshine-ai/moonshine
• capitalone/vulnhunter
• stupside/castor

Best for: Investor, CTO, VP of Engineering/Data, Data Engineer, MLOps Engineer, AI Engineer

Related on AIssential

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• I built an agentic Kafka pipeline watchdog-here’s what 5 AI agents actually do — Agentic AI systems can autonomously detect, diagnose, and remediate real-time data pipeline anomalies, reducing human intervention.
• IBM to Acquire Confluent to Create Smart Data Platform for Enterprise Generative AI — Real-time data streaming is foundational for enterprise generative AI and agentic AI deployments.
• Goodbye Data, Hello AI: My Biggest Takeaway from Snowflake Summit 2026 — Snowflake Summit 2026 signals a paradigm shift from data-centric to AI-first strategies within enterprise data clouds.
• Data Integration Landscape 2026: Event Streaming, API, and Batch in the Era of Agentic AI — Event-driven architecture, with request-response and batch as interfaces, is the strategic core for modern data integration.

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Editorial summary, takeaway, and curation by AIssential. Original article published by AI on Medium.