PinnedBarr Moses·Jan 2310 Data + AI Predictions for 2026I think most enterprise data and AI teams can agree, 2025 didn’t quite go to plan.A response icon5A response icon5
InData Science CollectivebyBarr Moses·May 22Is context the new compute? How the AI race is moving to the data layerIn the past six months, inference costs for frontier-level AI capability dropped roughly 85%. Open-weight models from Meta, Alibaba, and…A response icon4A response icon4
InData Science CollectivebyBarr Moses·May 11Garbage data, garbage agentsInsights from a session I hosted at the 2026 AI Agents Conference in NYC.A response icon1A response icon1
InData Science CollectivebyBarr Moses·May 7The agentic future has a technical debt problemIn the early days of cloud, companies raced to migrate workloads before they’d figured out how to monitor them. Move fast and instrument…
InData Science CollectivebyBarr Moses·Apr 24We surveyed senior data & AI leaders. Most can’t define “AI-ready.”71% say they’re actively preparing. Only 29% have a documented definition of what that means.A response icon1A response icon1
InData Science CollectivebyBarr Moses·Apr 21Memory architecture for proactive agentsMoving from “what should I recall?” to “what should I notice?” and other challenges in building a proactive multi-agent system
Barr Moses·Aug 19, 2025The AI Corpus Problem—Why Quality Requirements Are Moving UpstreamBefore we can talk about the new AI corpus, we need to look backward.A response icon1A response icon1
Barr Moses·Jul 18, 2025The Data Engineer’s Guide To Root Cause AnalysisPractical tips to trace, troubleshoot, and fix data quality issues fast.
Barr Moses·May 9, 2025Are We In An AI Bubble?Here’s how to make sure your team avoids problematic bubble behavior.A response icon1A response icon1
InTDS ArchivebyBarr Moses·Dec 16, 2024Top 10 Data & AI Trends for 2025Agentic AI, small data, and the search for value in the age of the unstructured data stack.A response icon36A response icon36
