Postgres won the performance argument, serverless pricing floors broke the pay-as-you-go promise, and the Three-Tool Trap is still quietly killing RAG reliability.
Read PostEmbedding models have a lexical blind spot. Why Reciprocal Rank Fusion beats score normalization, and why you probably don't need a heavyweight vector database at all.
Read PostFive quantization techniques for 70B models on one GPU, the inference optimizations production stacks need, and building a custom RAG eval metric from scratch.
Read PostNightly re-indexing leaves a ten-hour staleness gap and costs 100x more than embedding the delta. CDC ingestion, semantic caching, and the SKIP LOCKED pattern.
Read PostIt's almost never the LLM. Precision beats recall, BM25 beats state-of-the-art embeddings on identifiers, and CPU-first retrieval is a perfectly valid architecture.
Read PostRebuilding Claude Code's 6-layer harness in CrewAI, why small models alone won't cut your inference bill, and the four agent loop patterns — plus Kimi K3's 2.8T drop.
Read PostSpeculative decoding, continuous batching, and the KV cache memory tax — the mechanics that decide whether serving an LLM is affordable or ruinous.
Read PostThe prefill/decode split, the 4-bit sweet spot and the quality cliff below it, and why reflexively reaching for an H100 is often a multi-thousand-dollar mistake.
Read PostKV caching rethought with LMCache and 14x faster TTFT, the 4-stage production routing pipeline, and Fable-as-Advisor at 92% quality for 63% of the cost.
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