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DesignCraft Deep Dive: Layout and Publishing with designcraft-cli

A hands-on guide to designcraft-cli v0.5.0: the nine top-level subcommands, the file.new document model, headless rendering, the App control port, script automation, MCP integration and benchmarks — with four real rendered pages.

2026/10/10 · DesignCraft · Layout & Publishing · CLI
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Agent Interfaces: choosing between CLI, API, browser use, computer use, and sandboxes

Which door does an agent act through? Adapted from the MIT-licensed curriculum's Stage 8 concept chapter: eight recurring terms, a 'smallest interface first' decision table, the three tables to draw before letting an agent act (allowlist, actions, approval gates), and the four questions to ask of any browser/computer-use benchmark score. The bigger the door, the higher the risk — the first principle is to pick the smallest, most inspectable one.

2026/10/03 · AI Agent · Browser Use · Computer Use
Evidence

WeChat Open Source WeMM-Embedding Deep Dive: The Multimodal Embedding Model Topping MMEB-v2, Can It Run on Your Mac?

Breaking down WeMM-Embedding from the arXiv 2608.24053 technical report and source code: Qwen3.5 native multimodal backbone, <embedding> token pooling, two-stage training (Semantic-ID resampling + bidirectional KL distillation + model merging), full MMEB-v2/v3 leaderboard results, and local Mac Studio MPS benchmarks (47ms text / 321ms image / 6

2026/08/31 · WeMM-Embedding · Tencent · Multimodal
Evidence

Polyglot Persistence in Practice: A Full-Pipeline Evaluation of a Ten-Database Memory System

From BGE-m3 vector embeddings and ten-way synchronized writes to a comparison of search quality and speed across nine backends: a complete stress test of an AI memory system. Qdrant is the king of semantics, FAISS the king of speed, and Neo4j the king of relationships.

2026/05/22 · MemoryHub · Vector Database · Benchmark
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LLM Evaluation and Selection Guide: How to Scientifically Choose Models in 2026

A systematic LLM selection framework: Benchmark interpretation, real-world scenario testing methods, cost/performance matrix, DeepSeek V4 vs Qwen vs Llama comparison.

2026/05/10 · LLM · Benchmark
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Complete Guide to vLLM Deployment and Performance Tuning

vLLM high-performance LLM inference engine deployment guide: installation, configuration, PagedAttention principles, performance benchmarking.

2026/05/10 · Inference