Implementing RAG in a React Native App: On-Device and Cloud Retrieval
Build production Retrieval-Augmented Generation for React Native with one engine that runs both on-device and behind a Claude Opus 4.8 cloud service.
8 articles tagged with Claude
Build production Retrieval-Augmented Generation for React Native with one engine that runs both on-device and behind a Claude Opus 4.8 cloud service.
Anthropic signed a deal to take the entire 300-megawatt, 220,000-GPU capacity of SpaceX's Colossus 1 data center in Memphis, and inside the same month doubled Claude Code's five-hour rate limits, removed the Pro and Max peak-hours throttle, and raised Opus API ceilings. xAI sold compute to its direct frontier rival. The agent-workload demand curve has outpaced what the three biggest labs planned for. Here is the structural argument the rent reveals.
The AI code review landscape has transformed from simple linting assistants to autonomous agent-powered reviewers that understand architecture, security, and business context. A comprehensive analysis of tools, patterns, economics, and what happens when your reviewer never sleeps.
Step-by-step tutorial for building an AI-powered code review agent using the Claude Agent SDK in Python. From basic diff analysis to custom MCP tools, severity classification, and GitHub integration. Includes a working project inspired by CodeSentri.
The Pentagon has given Anthropic 48 hours to strip safety guardrails from Claude or face blacklisting, contract termination, and wartime production law. This is the most consequential confrontation between AI safety principles and state power in history.
A comprehensive breakdown of Anthropic Academy's 12 free courses across two learning paths, analyzing who benefits from each track and which professionals need this training most urgently.
Anthropic claims engineers use Claude for 60 percent of their work with 50 percent productivity gains and that Claude has achieved AGI by some definitions. A rigorous METR study shows experienced developers are actually 19 percent slower with AI tools, exposing a 40-point gap between self-reported and measured performance.
Fortune 500s are combining Knowledge Graphs ($3.54B by 2029), Graph Neural Networks (stopping $403B in fraud), and Multimodal AI (92% adoption) into a unified architecture that achieves 300-500% ROI while 70% of standalone AI projects fail. Here''s the implementation playbook CTOs are using.