4 articles
Learn how to build deterministic, zero-cost evaluation harnesses for AI agents and Model Context Protocol (MCP) servers without mutating production data.
Learn how to build transparent mock layers and deterministic AX evaluation suites for tool-calling AI agents and MCP servers without mutating production data.
Stop draining API budgets and mutating test DBs during AI agent evals. Learn how to architect local proxy layers to test MCP servers and agent skills deterministically.
Explore the shift from static LLM wrappers to agentic front-end systems. Learn how Anthropic's Model Context Protocol (MCP) and OpenAI's reasoning models reshape state management and UX.