stack
stack on Beyond Market Intelligence: a running collection of 3 stories we have gathered and hand-picked because they are worth your time. Every post here touches on stack in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around stack, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.
Presentation: Why Fetch When You Can Sync? Building Local-First Apps on a Sync Engine Architecture
James Arthur’s presentation, “Why Fetch When You Can Sync?”, illuminates a critical shift in frontend architecture. He argues that extending reactivity to the server—using technologies like Electric and TanStack DB—represents the next frontier, replacing traditional fetching with declarative data bindings. Discover how query-driven sync and local optimistic updates empower engineering leaders to build exceptionally fast, collaborative applications. This approach leverages existing stacks to create agentic experiences. For deeper insights into unified architectures, explore "Harper Argues Against the Multi-System Stack."
Harper Argues Against the Multi-System Stack and Releases 5.2
Harper is challenging the status quo of multi-system architectures, advocating for a single-runtime database platform that unifies application code and data. Recent benchmarks demonstrate significantly improved performance on live, personalized-data workloads compared to Vercel-based stacks. Version 5.2 further solidifies this approach, introducing a new record cache and increased throughput per node. Discover how Harper’s streamlined architecture empowers data-driven applications—for context, explore our analysis of Next.js 16.3’s recent performance improvements.
5 Tools for Building and Deploying AI Agents in Production
Navigating the complexities of AI agent deployment can be streamlined with the right tools. This article provides a concise overview of five essential tools, each addressing a critical layer in the agent development stack—from core logic construction to scalable runtime environments. We’ll explore options designed to empower your data journey, ensuring a smooth transition from concept to production. For a deeper look at the foundational importance of data in AI success, see our related piece, "AI isn’t close to curing cancer.