System Architecture
4 stories filed under System Architecture on Beyond Market Intelligence. The newest of them: “From Demo to Production: Structuring a Reliable Backend for Your AI Agent”, “Three Layers That Define Every RAG System You Build”, and “HubSpot Rebuilds Access Control with a Rule Engine for Smarter Governance”. Turning a demo LangGraph agent into something that can actually hold onto real booking data is where the practical work begins. Every RAG system stands on three engineering layers, each stacked on a single LLM call: the prompt that makes the call, the context that fills the model's window, and the loop that decides when the next call fires and… Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work… The list below is every System Architecture story on Beyond Market Intelligence, newest first.
From Demo to Production: Structuring a Reliable Backend for Your AI Agent
Turning a demo LangGraph agent into something that can actually hold onto real booking data is where the practical work begins. Building a proper backend for that transition is a useful look at moving from proof-of-concept to something dependable. The focus stays on structure and persistence, not hype. For readers interested in how AI handles complexity at a deeper level, our piece on paragraph structure in LLMs offers a complementary perspective worth exploring.
Three Layers That Define Every RAG System You Build
Every RAG system stands on three engineering layers, each stacked on a single LLM call: the prompt that makes the call, the context that fills the model's window, and the loop that decides when the next call fires and when it stops. Knowing which layer you are on is half the battle in building and debugging. This breakdown keeps things practical and grounded. For deeper exploration of where AI understanding gets murky, our piece on verifying your AI's understanding offers a timely companion.
HubSpot Rebuilds Access Control with a Rule Engine for Smarter Governance
HubSpot's redesign of its JITA authorization system is a smart move toward clarity. By adopting a rule engine architecture that structures access decisions as a directed acyclic graph, the company replaces tangled conditional logic with something more observable and governable. The added decision metadata and rule-level insights are practical steps for teams wrestling with complexity. It's a thoughtful, human-centered approach to security. For more on how such architectures are evolving, our coverage of QCon AI New York offers useful context.
How Cloud Databases Gain Agility by Separating Compute from Storage
Cloud economics are reshaping how we think about databases, and Murat Demirbas is here to show us the way. His presentation on disaggregated systems reveals how decoupling compute from storage unlocks elastic scaling, cost efficiency, and fault isolation. What's striking is how classical Paxos roles foreshadowed this shift, proving the blueprint was always there. He doesn't shy away from network tradeoffs or the evolution of shared memory, either.