Every AI agent conversation in 2026 eventually collapses into a formula: Agent equals Model plus Harness. Databricks put it plainly in its own engineering research: most operational agent failures trace back to the harness, not the model underneath it. Almost everything written about AI harnesses so far is aimed at developers building one. Almost nothing […]
Data Accessibility: What It Means, and Why Most Companies Get It Backwards
Accenture and Qlik surveyed 9,000 employees across nine countries and found that data-related friction costs organizations more than five working days, 43 hours, per employee every year, with only 21% of employees confident in their own data skills. Most companies respond to that number by opening access to everything. That is the wrong fix, and […]
Data Transformation: What It Actually Means, and Why Pipelines Keep Breaking
Fivetran’s 2026 Data Connectivity Report and dbt Labs’ State of Analytics Engineering 2026 survey, both published in April 2026, landed on the same number from different angles: 53% of enterprise data engineering time now goes to maintaining existing pipelines instead of building new capability. Meanwhile Gartner puts the failure rate for data migration projects at […]
AI Adoption: What the Data Actually Shows, and Why Most Pilots Still Don’t Scale
Ask five research firms for the AI adoption rate and you get five different numbers, but the gap that matters is inside a single survey. McKinsey’s 2025 State of AI found 88% of organizations use AI in at least one business function, yet only 6% report significant enterprise-wide impact from it. MIT’s Project NANDA went […]



