Subscribe • Previous Issues AI Reliability Patterns That Generalize Beyond Medicine The gap between pilot projects and production deployments has emerged as a defining challenge for enterprise AI teams. Recent surveys indicate that only a small percentage of generative AI initiatives reach full production, with most stalling due to brittle workflows and integration failures. At last year’sContinue reading “Your AI passed benchmarks. Why is it failing in production?”
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Emerging AI patterns in finance (what to watch in 2026)
Subscribe • Previous Issues What’s Emerging in Financial AI: From Foundation Models to Compliance-as-Code While the public discourse remains fixated on Artificial General Intelligence, the more immediate and consequential story is the diffusion of AI into specialized enterprise domains. Having spent time as a quant within the hedge fund industry, I have long viewed financial services asContinue reading “Emerging AI patterns in finance (what to watch in 2026)”
Agent workflows: stop guessing, start measuring
Subscribe • Previous Issues Agent Optimization: From Prompt Whispering to Platform Engineering Agent optimization is the work of making an agent workflow dependable — despite long tool chains, multiple roles, and the inherent variability of large language models. In day-to-day engineering terms, it is closer to debugging a complex system than “making the model smarter”: you areContinue reading “Agent workflows: stop guessing, start measuring”
Data Engineering in 2026: What Changes?
Subscribe • Previous Issues Adapting Your Data Platform to the Agent-Native Era As we settle into 2026, I think data engineering is being pulled in two directions at once: toward more automation(because agents are starting to do real work) and toward more scrutiny (because “close enough” stops being acceptable once software is making decisions). Real usage dataContinue reading “Data Engineering in 2026: What Changes?”
Your holiday reading list: 12 books we loved this year
Subscribe • Previous Issues The Year in Print: 12 Books That Defined 2025 To mark the season, here are twelve non-fiction selections for the twelve days of Christmas. These are books we enjoyed and found worth passing along, ranging from deep dives into semiconductor history to fresh looks at creative collaboration. Whether you need a companion forContinue reading “Your holiday reading list: 12 books we loved this year”
“World Model” is a mess. Here’s how to make sense of it.
Subscribe • Previous Issues The World Model Minefield: A Guide for AI Teams The term “world model” has quickly migrated from research papers to the center of the artificial intelligence conversation, frequently cited in media coverage of next-gen AI. At a high level, the concept promises AI that does not merely predict the next word in aContinue reading ““World Model” is a mess. Here’s how to make sense of it.”
Are Your AI Agents Flying Blind in Production?
Subscribe • Previous Issues Beyond Black Boxes: A Guide to Observability for Agentic AI The core mindset shift for agentic systems is simple: observability isn’t an add-on, it’s a production prerequisite. Enterprises are unwilling to trust black-box agents; they expect to understand behavior, decision-making, and reasoning. This means architecting for visibility from the very first design docContinue reading “Are Your AI Agents Flying Blind in Production?”
The Rise of the Multimodal Lakehouse
Subscribe • Previous Issues Multimodal lakehouses: The architecture AI teams are migrating to When the “lakehouse” was first introduced in 2020, the goal was to reconcile data warehouses and data lakes in a single architecture: open formats on cheap object storage, with ACID transactions, schema enforcement, governance, BI support, and streaming built in. The promise was simple:Continue reading “The Rise of the Multimodal Lakehouse”
AI’s biggest enterprise test case is here
Subscribe • Previous Issues Legal AI Unpacked: What Works, What Fails, What’s Next Law firms were early adopters of tools for searching and classifying large document collections, so their current enthusiasm for generative AI follows a familiar pattern. Business press coverage reinforces this interest: articles forecasting the disruption of knowledge work routinely single out legal services asContinue reading “AI’s biggest enterprise test case is here”
When Text Helps Time Series (and When It Doesn’t)
Subscribe • Previous Issues Time Series Foundation Models: What You Need To Know The recent emergence of Time Series Foundation Models (TSFMs) offers a powerful new tool for forecasting. Their effectiveness, however, is often constrained by an architectural design that analyzes each time series as an independent entity. This approach overlooks the rich, structured context available inContinue reading “When Text Helps Time Series (and When It Doesn’t)”