Unlocking Data and AI
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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’s AI Conference, several colleagues independently…
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 as the primary bellwether for how…
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 are tuning roles, prompts, routing, memory,…
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 data backs up the intuition that…
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