Field notes from inside enterprise analytics.
Periodic essays on analytics strategy, data engineering, and reporting — written for leaders building durable data operations.
No spam. Unsubscribe anytime.
Past issues
- August 3, 2026
Signals — week of August 3, 2026
This week’s signal is less about “AI everywhere” and more about where AI is becoming operational inside analytics stacks: cheaper query patterns, more agent-facing data products, and tighter control over governance and execution. The most relevant developments are coming from pla
Read issue → - July 27, 2026
Signals — week of July 27, 2026
This week’s analytics and data stack news is being shaped by two themes: vendors are pushing harder to embed AI directly into BI and data workflows, and enterprise buyers are still sorting out where those capabilities actually remove work versus add complexity. The most relevant
Read issue → - July 20, 2026
Signals — week of July 20, 2026
This week’s analytics landscape is defined by a shift from passive reporting to active, AI-driven decision-making, with agentic AI and real-time intelligence becoming the new baseline for enterprise data teams. The modern data stack is evolving around autonomous systems that not
Read issue → - July 13, 2026
Signals — week of July 13, 2026
This week’s signal is operational: a new frontier model and action surface land together (GPT‑5.6 + ChatGPT Work), while Google converts agentic search into an ad workflow and Tencent offers a production‑scale MoE checkpoint. For data leaders, the priority is moving from benchmar
Read issue → - July 6, 2026
Signals — week of July 6, 2026
This week's analytics landscape is defined by the convergence of AI agents into BI tools and early operational wins from LLM-powered data stacks, while Snowflake and Databricks continue to cement their dominance through aggressive product launches. Data leaders at mid-market and
Read issue → - June 29, 2026
Signals — week of June 29, 2026
This week centers on the tangible integration of AI agents into analytics workflows and the strategic consolidation of the modern data stack. With significant power demands from data centers and urgent LLM training initiatives, data leaders must balance infrastructure scaling wit
Read issue →