Claude

Introduction Anthropic’s Claude has become a cornerstone for enterprises that need safe, reliable, and controllable large‑language‑model (LLM) capabilities. While the model itself garners most of the headlines, the real differentiator for production‑grade deployments is the Claude Control Plane (CCR) – a dedicated orchestration layer that separates control from compute. CCR (sometimes referred to as Claude Control Runtime) is not a single monolithic service; it is a collection of APIs, policies, and observability tools that enable: ...

Introduction Algorithmic trading has moved from a niche hobby of a few quant firms to a mainstream tool for retail and institutional investors alike. The secret sauce behind successful strategies is real‑time market data: price ticks, order‑book depth, news headlines, and even social‑media sentiment that arrive in milliseconds and must be processed instantly. In the past, building a low‑latency data pipeline required deep knowledge of networking protocols (FIX, UDP multicast), specialized hardware, and expensive data‑vendor licenses. Today, the combination of Python—the lingua franca of data science—and Claude, Anthropic’s large language model (LLM), offers a surprisingly powerful, cost‑effective way to ingest, enrich, and act upon live market streams. ...

Introduction Claude Code introduces a powerful feature called Skills—a way to teach Claude repeatable, specialized capabilities that persist across sessions. Think of Skills as plugins for behavior: structured instruction sets that define exactly what Claude should do, when to do it, and which tools it can use. Unlike one-off prompts that you type into chat, Skills are persistent, discoverable, and automatically selected by Claude based on context. They transform Claude from a general-purpose assistant into a specialized agent that can reliably perform complex, domain-specific tasks. ...