Volume 341, Issue 3 · 15 articles from 5 issues
Databricks introduces Genie Code to translate proprietary warehouse dialects into open ANSI SQL during migration. Read more
Databricks describes building a self-serve infrastructure 'vending machine' for the agentic era. Read more
Databricks argues a purpose-built data agent beats general coding agents on quality and cost. Read more
Databricks shows how manufacturing agents make trusted real-time decisions when a production line fails mid-shift. Read more
Databricks argues AI automating SQL and dashboards shifts analysts toward judgment rather than query writing. Read more
Eleven academic teams tested agents live on OfficeQA Pro V2, built from about 120,000 pages of US Treasury documents. Read more
Databricks shares how it manages AI coding costs at scale after measurable gains from agentic coding. Read more
Databricks explains what AI hallucinations are, why they occur and how organisations can reduce them. Read more
Databricks argues fragmented context and API boundaries stall AI projects, and platform-native agents remove that overhead. Read more
Databricks publishes an explainer on tool calling and how models interact with external systems. Read more
Databricks publishes an explainer defining AI assistants and the components behind them. Read more
Databricks argues retail AI's next bottleneck is trusted context, given how sensitive the customer data behind it is. Read more
Databricks Feature Store now reaches 200ms p99 latency for streaming features using Spark Real-Time Mode. Read more
Databricks explains how Genie Agents build domain-specific agents from one prompt by grounding them in governed context. Read more
Databricks adds Precision Mode to its ai_extract API, pairing fine-tuned models with an agentic harness for hard documents. Read more