A practical framework for data platform AI-readiness - 5 dimensions, before-and-after examples, quick wins, and a scorecard you can run with your team.
Ido Bronstein
An edited Q&A from the Data Splash podcast, hosted by Ido Bronstein and brought to you by Upriver. Our guest is Prakash Reddy, Head of Data Engineering & AI Enablement at Atlassian. Prakash started his career in big data when "big" meant Oracle, was one of the early data practitioners at LinkedIn leading data products for Ads, and is an active investor and advisor for startups.
Omri Lifshitz
A practical framework for data platform AI-readiness - 5 dimensions, before-and-after examples, quick wins, and a scorecard you can run with your team.
Omri Lifshitz
Lessons learned from analyzing Claude Code's leaked sources
Omri Lifshitz
Knowledge engineering disappeared into data pipelines and infrastructure. Now AI is bringing it back. Here's why 95% of AI investments fail without it - and what the new knowledge engineer looks like.
Ido Bronstein
Why AI agents fail on data platforms - and what makes data fundamentally different from application code.
Omri Lifshitz
My response to a16z’s article
Ido Bronstein
How Upriver & Nimble together allow building real-time pricing pipelines natively in Snowflake with UDTFs.
Ido Bronstein
Ido Bronstein
Omri Lifshitz
Omri Lifshitz
In this post, we’ll break down why monitoring data in motion—as it’s pulled, interpreted, and acted on—is essential for building reliable agentic systems
Ido Bronstein
Shifting Data Left: Data Quality Starts at the Source Giving data producers full ownership of their data unlocks faster feedback, fewer silos, and better quality — but only if they have the right tools
Ido Bronstein
Bring your messiest ticket. Our agent solves it before your coffee gets cold.
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