Evaluating Agent Workflows with Traces, Feedback, Human Labels, and LLM Judges
A practical evaluation stack for agent systems: collect traces, use feedback to find pain points, add human labels, and apply LLM judges with calibration.
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Articles
The latest news, trends, and tutorials regarding modern AI and web application development.
Securing and Observing AI Coding Agents Before Repository and Shell Access
How to sandbox, gate, and instrument AI coding agents before giving them repo write access or a shell.
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What standards, test harnesses, and trust controls make MCP integrations production-ready?
Production MCP needs more than protocol support: contract tests, capability policy, trust scoring, and hardened auth and session handling.
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Reliable AI Agents Need Boundaries, Not More Loops
The hardest production problem with AI agents is not adding more tools. It is making the system reliable, secure, observable, and cheap enough to trust.
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MCP in Production Means Solving Auth, Streaming, and Context Boundaries
Model Context Protocol has become a useful interface layer for tools, but the production work starts after the demo: auth, context shaping, multi-server routing, and streaming semantics.
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RAG Is Not the Default: Decide When Retrieval Actually Helps
A retrieval step can improve an AI application, but it can also increase cost, latency, and hallucination surface area. The real engineering question is when retrieval earns its place.
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Step-by-Step Next.js
Learn to set up a usable new Next.js application. Go beyond the standard tutorial descriptions and get your repository ready for prime time. This article will show you how, step by step.
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