GPT-5 shipped this week. The announcement positioned it as a unified system: a fast model and a deeper reasoning model behind a real-time router that decides how much thinking the query deserves. You don't choose o-series vs. GPT-series anymore — you just send the request
Lakeflow hit general availability at DAIS, and the scope of what it covers is broader than the old DLT story. End-to-end data engineering: ingestion from external sources, transformation via Delta Live Tables, orchestration, and monitoring — all under one product surface. The declarative pipelines authoring experience in particular is
Serverless GPU availability in Databricks was one of the quieter DAIS announcements, but it's worth talking through because the "serverless = cheaper and easier" assumption that applies to SQL warehouses and notebook compute doesn't hold the same way for GPU workloads. The economics are meaningfully
The model evaluation was useful, but it produced a conclusion that might seem discouraging: none of the alternatives I tested solved the problem I was trying to solve. Let me be more precise about what that means, because "they don't work" and "none of them
Databricks announced full Iceberg support in Unity Catalog at DAIS — managed Iceberg tables, the Iceberg REST Catalog API, read/write from external engines like Spark, Flink, and Kafka. The format wars between Delta Lake and Iceberg have been running for years. This announcement doesn't end them, but it
Databricks announced Lakebase at DAIS — a fully managed, Postgres-compatible operational database built on their acquisition of Neon. The announcement landed harder than I expected, because it isn't just a new product. It's a structural argument that the lakehouse can absorb the OLTP workload that'
When you've decided the current tool isn't doing the job, the responsible move is to evaluate the alternatives before building from scratch. I spent the better part of three months doing that evaluation. The alternatives were Claude, Pi Coder, and Hermes — each with a different set
The headline from DAIS this week was Agent Bricks — Databricks' take on what it should feel like to build a capable agent without hand-tuning every component. You describe the task, connect your data, and the platform auto-optimizes the agent: selects the model, tunes prompts, wires the retrieval
DAIS 2025 is in three weeks. I've spent the last year building on the themes that emerged from the 2024 Summit — compound AI, governance expansion, open formats, the cost reality of enterprise GenAI. Looking further out, at what the data + AI landscape looks like from 2025 to 2030,
When something that worked well stops working well, the question is whether it's your setup or the environment. I spent two months trying to distinguish between those before accepting the answer: it was both, and neither was fully fixable from my side. The persona system had been delivering
A year ago at DAIS 2024, I made some predictions. It's May 2025, DAIS 2025 is a month out, and it's time for an honest accounting. What did I get right, what surprised me, and what changed my mind. What I Got Right The compound AI
Meta shipped Llama 4 this month and it changes the open-weight calculus significantly. The architecture is natively multimodal — text, images, video, documents — and it's built on a Mixture of Experts design that lets them pack a lot of capability into a manageable active parameter count. Scout runs