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Build a Production AI App: Where Vibe Coding Platforms Break Down

Your prototype stopped being optional the moment a real user typed a real password into it. Before that, it was a demo. Now it's a liability with a login screen, and the habits that got you this far won't carry you further. Vibe coding is a good way to explore. It can accelerate exploration, reduce…

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Express for AI Inference in 2026: Build a Low-Latency RAG API with PGVector or FAISS

Latency stopped being optional the moment you put retrieval in front of an LLM. Every millisecond your vector search burns is a millisecond before the first token appears. Express stays lean by design, which leaves the vector store owning most of your retrieval headroom. This guide is a project…

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AWQ in Practice: Quantize LLMs for Faster AI Inference Without Killing Output Quality

AWQ cuts 70B model serving costs from $0.757 to $0.253 per million tokens by moving from two GPUs to one. Llama 3.3 70B quantized to INT4 with AWQ drops 2 MMLU points and 3 HumanEval points versus full precision. AWQ INT4 brings a 70B model's VRAM down from 140GB to roughly 40GB, fitting it on a…

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