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4 articles on ai engineering.
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Eval coverage and observability are now table-stakes for production AI. A practical comparison of Langfuse, Braintrust, and Arize — when to pick each, what they cost, and how to wire them into a CI pipeline that catches regressions before customers do.
Most production LLM workloads are 2–5× more expensive than they need to be. A practical FinOps playbook covering routing, caching, model selection, and the gateway patterns that compound the savings.
Model Context Protocol (MCP) became the dominant agent-tool integration pattern in 2026. Here's what it is, why it changes how enterprises build AI, and how to deploy it without giving an LLM more permissions than it should have.
