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Beyond "Vibe Checks": The Architect’s Guide to Metric-Driven LLM Evaluation
Moving from subjective "vibe checks" to rigorous engineering, this guide explores the technical architecture of LLM evaluation. Learn to quantify RAG performance using metrics like Contextual Precision, Faithfulness, and Answer Relevancy. Featuring expert insights from SuperAnnotate and Confident AI, we provide programmatic frameworks and code snippets to move your GenAI pipeline from experimental to production-ready. Stop guessing and start measuring with a metric-driven app
Debasish
Jan 193 min read
Beyond Tool Calling: Why AI Agents Should Write Code to Speak with MCP
raditional JSON tool calling is fragile. "Code Mode" changes the game: convert MCP tools to TypeScript APIs and let AI agents write executable code. It’s faster, handles complex logic, and uses secure sandboxes. Get the full code demo here.
Debasish
Dec 4, 20255 min read
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