Ship useful AI products in weeks, not months. Learn the agent lab architecture, how to identify net-new work opportunities, make your data AI-ready, and execute a 4-8 week development cycle from insight to production. Focuses on outcomes over capabilities, deep integration over generic tools, and rapid iteration with real users.
Practical UX patterns for AI systems that balance autonomy and control. From pure suggestion to observation mode, learn how to design AI interfaces users actually trust—with React examples, confidence indicators, reasoning transparency, and reversible actions.
Why generic AI chatbots fail and how to build bespoke AI applications that solve real problems. Learn the three critical components of successful AI integration - deep system integration, human-in-loop UX patterns, and solving one specific problem extremely well.
Exploring three approaches to LLM state management for TypeScript applications — whole state serialization, persistent memory, or selective context. A Frontend Maximalist perspective on LLM integration architecture and the tradeoffs between simplicity, token costs, and code complexity.
Detailed comparison of Model Context Protocol (MCP) feature support across leading clients — including Claude Desktop, Nanobot, Cline, Cursor, Windsurf, and Postman — examining how each handles tools, resources, prompts, sampling, OAuth, and other key capabilities.
A comprehensive technical guide to building production MCP servers. Learn tools, resources, authentication, MCP-UI, and why MCP is the future of enterprise AI integration.
Utility-first CSS turns style concerns into composable, testable, and portable component behavior.
For most modern React applications in 2025, a combination of Tailwind CSS with shadcn/ui provides the optimal balance of developer experience, maintainability, and AI compatibility.
React development tools key trends across performance monitoring, testing, frameworks, state management, APIs, monorepos, and deployment trends with adoption metrics and strategic recommendations for 2024–2025.
Making complex systems explorable through React visualization and outcome-driven AI.
Case studies: Making fraud networks visible, building production AI pipelines, monitoring distributed IoT fleets. Custom systems for problems that demanded them.