--- title: "#semantic-search articles | Hashnode" description: "Explore 147 articles tagged #semantic-search on Hashnode. Tutorials, guides, and how-tos from the community." url: "https://hashnode.com/tag/semantic-search" --- Tag # #semantic-search 147 posts · 2 followers [Sotiris Zacharopoulos](https://hashnode.com/@sz-codapus-studio) · [2d ago](https://hashnode.com/posts/semantic-search-playbook-retrieval-negation/6af31c6b12d97dbc275567a9) ### [Semantic Search Found the Playbook but Missed the “Not”](https://blog.codapus.studio/semantic-search-playbook-retrieval-negation?utm_source=hashnode&utm_medium=feed) A containerised experiment compares phrase matching with semantic search, showing recovered matches, missed negation, and the trade-offs of rejection rules. 7 min read · [blog.codapus.studio](https://blog.codapus.studio/semantic-search-playbook-retrieval-negation?utm_source=hashnode&utm_medium=feed) [3](https://hashnode.com/posts/semantic-search-playbook-retrieval-negation/6af31c6b12d97dbc275567a9) [N Chandra Prakash Reddy](https://hashnode.com/@ChandraPrakash1996) · [Nov 2](https://hashnode.com/posts/beyond-keyword-search-building-multimodal-semantic-search-with-amazon-nova-embeddings-and-s3-vector/6ae83f03c45f3736c24e72cb) ### [Beyond Keyword Search: Building Multimodal Semantic Search with Amazon Nova Embeddings and S3 Vector](https://devopstour.hashnode.dev/beyond-keyword-search-building-multimodal-semantic-search-with-amazon-nova-embeddings-and-s3-vector?utm_source=hashnode&utm_medium=feed) Key insights from AWS Community Day Bengaluru | July 11, 2026 11 min read · [devopstour.hashnode.dev](https://devopstour.hashnode.dev/beyond-keyword-search-building-multimodal-semantic-search-with-amazon-nova-embeddings-and-s3-vector?utm_source=hashnode&utm_medium=feed) [Hassan Aziz](https://hashnode.com/@hassandevelopment) · [Oct 31](https://hashnode.com/posts/how-semantic-search-works-with-a-python-example/6ae5c34c2935df66e5d78ac4) ### [How semantic search works, with a Python example](https://hassanrants.hashnode.dev/how-semantic-search-works-with-a-python-example?utm_source=hashnode&utm_medium=feed) Semantic search matches meaning instead of keywords. How embeddings and cosine similarity work, and a movie search in Python with sentence-transformers. 14 min read · [hassanrants.hashnode.dev](https://hassanrants.hashnode.dev/how-semantic-search-works-with-a-python-example?utm_source=hashnode&utm_medium=feed) [Vikkurthi Manikanta](https://hashnode.com/@vmanik) · [Oct 30](https://hashnode.com/posts/why-enterprise-ai-agents-fail-without-structured-knowledge/6ae4b92d022f362cb402cc4c) ### [Why Enterprise AI Agents Fail Without Structured Knowledge](https://structured-intelligence.hashnode.dev/why-enterprise-ai-agents-fail-without-structured-knowledge?utm_source=hashnode&utm_medium=feed) Your agents aren't hallucinating because the models are bad. They're failing because they have no world model of your enterprise. The inconsistency problem Picture this: your team has just deployed a 4 min read · [structured-intelligence.hashnode.dev](https://structured-intelligence.hashnode.dev/why-enterprise-ai-agents-fail-without-structured-knowledge?utm_source=hashnode&utm_medium=feed) [RONI DAS](https://hashnode.com/@ronidas) · [Oct 15](https://hashnode.com/posts/i-cut-embeddinggemma-2s-vectors-to-a-sixth-of-their-size-it-got-more-answers-right-and-that-was-the-/6ad03ab8b8db4be913f902a7) ### [I cut EmbeddingGemma 2's vectors to a sixth of their size. It got more answers right, and that was the worrying part.](https://systemdesignacademy.hashnode.dev/i-cut-embeddinggemma-2s-vectors-to-a-sixth-of-their-size-it-got-more-answers-right-and-that-was-the-?utm_source=hashnode&utm_medium=feed) What EmbeddingGemma 2 is, what Google says it can do, and a MacBook Air test of search by meaning, pictures, shorter vectors and speed. 17 min read · [systemdesignacademy.hashnode.dev](https://systemdesignacademy.hashnode.dev/i-cut-embeddinggemma-2s-vectors-to-a-sixth-of-their-size-it-got-more-answers-right-and-that-was-the-?utm_source=hashnode&utm_medium=feed) [Asfaq Leeon](https://hashnode.com/@leeonscoding) · [Oct 9](https://hashnode.com/posts/embeddings-vector-search-rag-from-scratch-with-node-js-and-postgresql-pgvector/6ac886790b56f76134c18b6f) ### [Embeddings, Vector Search & RAG from Scratch with Node.js and PostgreSQL (pgvector)](https://leeonscoding.hashnode.dev/embeddings-vector-search-rag-from-scratch-with-node-js-and-postgresql-pgvector?utm_source=hashnode&utm_medium=feed) Learn the building blocks before you touch LangChain 13 min read · [leeonscoding.hashnode.dev](https://leeonscoding.hashnode.dev/embeddings-vector-search-rag-from-scratch-with-node-js-and-postgresql-pgvector?utm_source=hashnode&utm_medium=feed) [3](https://hashnode.com/posts/embeddings-vector-search-rag-from-scratch-with-node-js-and-postgresql-pgvector/6ac886790b56f76134c18b6f) [praveenkulharee](https://hashnode.com/@praveen-dev) · [Oct 4](https://hashnode.com/posts/exploring-genai-retrieval-with-a-resume-keyword-semantic-and-hybrid-search/6ac2492734776c6712e86346) ### [Exploring GenAI Retrieval with a Resume: Keyword, Semantic, and Hybrid Search](https://dev-praveen.hashnode.dev/exploring-genai-retrieval-with-a-resume-keyword-semantic-and-hybrid-search?utm_source=hashnode&utm_medium=feed) A GenAI learning project exploring resume retrieval using embeddings, keyword search, semantic search, and hybrid search with document chunking. 6 min read · [dev-praveen.hashnode.dev](https://dev-praveen.hashnode.dev/exploring-genai-retrieval-with-a-resume-keyword-semantic-and-hybrid-search?utm_source=hashnode&utm_medium=feed) [2](https://hashnode.com/posts/exploring-genai-retrieval-with-a-resume-keyword-semantic-and-hybrid-search/6ac2492734776c6712e86346) [Chidinma](https://hashnode.com/@ChidinmaKO) · [Oct 2](https://hashnode.com/posts/the-index-is-a-bet-you-made-at-write-time/6abfb51ef89f8496ad1cc061) ### [The Index Is a Bet You Made at Write Time](https://chidinma.dev/the-index-is-a-bet-you-made-at-write-time?utm_source=hashnode&utm_medium=feed) Search indexes are representations built before the query exists, preserving some distinctions, discarding others, and shaping what retrieval can see. 21 min read · [chidinma.dev](https://chidinma.dev/the-index-is-a-bet-you-made-at-write-time?utm_source=hashnode&utm_medium=feed) [Pranshu Bansal](https://hashnode.com/@pranshubansal) · [Oct 1](https://hashnode.com/posts/i-tested-qdrant-quantization-and-mmap-on-ev-charger-search/6abe241d512cd299a68261c6) ### [I Tested Qdrant Quantization and mmap on EV Charger Search](https://pranshubansal.hashnode.dev/i-tested-qdrant-quantization-and-mmap-on-ev-charger-search?utm_source=hashnode&utm_medium=feed) What got smaller, what stayed accurate, and where the memory really went 23 min read · [pranshubansal.hashnode.dev](https://pranshubansal.hashnode.dev/i-tested-qdrant-quantization-and-mmap-on-ev-charger-search?utm_source=hashnode&utm_medium=feed) [Mohammed Yahya Ahmed](https://hashnode.com/@yahyaahmed) · [Sep 25](https://hashnode.com/posts/building-consistent-semantic-search-updates-embeddings-concurrency-in-brainzen/6ab6c88c353e54cf15813657) ### [Building Consistent Semantic Search: Updates, Embeddings & Concurrency in BrainZen](https://learningwithyahya.hashnode.dev/building-consistent-semantic-search-updates-embeddings-concurrency-in-brainzen?utm_source=hashnode&utm_medium=feed) What I learned building a consistent semantic search pipeline in BrainZen — covering embeddings, updates, versioning, concurrency, and MongoDB. 9 min read · [learningwithyahya.hashnode.dev](https://learningwithyahya.hashnode.dev/building-consistent-semantic-search-updates-embeddings-concurrency-in-brainzen?utm_source=hashnode&utm_medium=feed)