Awesome Search — Note History
Chronological log of notes added to this knowledge graph. Newest first.
2026-06-01 — History Audit & Comprehensive Catch-Up (~175 notes)
Catch-up log — notes present in the vault but not individually recorded in prior entries (initial import, May 16 batch, and later additions).
Articles — RRF is Not Enough (by Doug Turnbull, 2024-11-03), Agentic search models (by Doug Turnbull, 2026-05-11), Agents turn simple keyword search into compelling search experiences (by Doug Turnbull), Beyond Semantic Similarity - Rethinking Retrieval for Agentic Search via Direct Corpus Interaction (TIGER-Lab, 2026-05-08), Superintelligent Retrieval Agent SIRA (Meta / Rice University, 2026), You Say Search I Say Recs - Spotify Agentic Query Understanding (Spotify Research, 2025), Qwen3 Embedding Series (Alibaba Qwen Team, 2025-06-05), Fine-Tuning Qwen3 Embeddings for Product Category Classification, LLM-as-a-Judge When to Use Reasoning CoT and Explanations (by Aparna Dhinakaran, 2025-08-20), Incremental AI Adoption for E-commerce Search (2026-01-18), On Search Leadership (by Daniel Tunkelang), Canva Search Pipeline Part I, Bayesian BM25 is Cool, Can BM25 be a Probability, Broad and Ambiguous Search Queries, Click Residual - A Query Success Metric, Deconstructing E-Commerce Search - The 12 Query Types, Diversity Metrics for Recommender Systems, Ecommerce Search Governance - Move Faster Not Slower, How Context-Aware Embeddings Are Transforming Enterprise Search, Late Interaction Models - How to Scale and Optimize in Elasticsearch, LLM-Powered Query Extraction for Autocomplete, Metadata - The 3rd Kind of Retrieval, Mirror Mirror - All About Search Suggestions, Mutually Assured Distraction, My Journey Building Elasticsearch for Retail, Patterns for Personalization, Probability-Proportional-to-Size Sampling for Relevance Evaluation, Real Talk About Synonyms and Search, Searching for Goldilocks, Session vs Query based Search Evals, Statistical and Human-Centered Approaches to Search Improvement, Three Pillars of Search Quality - Findability, Three Pillars of Search Quality - Discovery and Inspiration, Autosuggest Ranking, Autosuggest Retrieval Data Structures and Algorithms.
New Section — Case Studies (9 notes) — Airbnb - ML-Powered Experiences Ranking, Canva - Search Pipeline Modernization, Etsy - Search Quality and Query Understanding, Kleinanzeigen - Vespa Migration for Homepage Feed, Netflix - Content Search Architecture, Skyscanner - Learning to Rank for Flights, Slack - Enterprise Message Search with LTR, Uber Eats - Scaling Search for Food Delivery, Zalando - Self-DoS via Facet Aggregation. Structured use-case notes synthesising engineering lessons from each company’s published work.
New Section — Datasets (4 notes) — Amazon ESCI Dataset, ESCI-S Dataset, Home Depot Product Search Relevance, WANDS Dataset. Benchmark datasets for search relevance evaluation.
Concepts — Bag-of-Documents Model, Clean Context, Click Signals, Direct Corpus Interaction, GGUF, Hit Rate at K, Intent Drift, IVF, LoRA, PEFT, QLoRA, SIRA, Session-Based Evaluation, Task-Aware Embeddings, Token Pooling, UDCG, WAND.
People — Omar Khattab (Stanford, ColBERT author), Aparna Dhinakaran (Arize AI), Thibault Formal (SPLADE co-author), Stéphane Clinchant (SPLADE co-author), Antoine Chaffin, Florent Krzakala, Han Xiao (Jina AI), James Briggs, Shaw Talebi, Matei Zaharia (Databricks / MLflow), Laura Ham (Weaviate), Marianne Haugvaldstad, Lester Solbakken, Brage Vik, Rudolf Batt, Nicolò Rinaldi, Luca Arnaboldi, Hugo Galvão, Honza Král, Jodi Sloan, Michael Ryaboy, Michael Hannecke, Peter Straßer, Siegfried Schüle, Andrea Schütt, Andreas Wagner, Alexander Marquardt, Amélie Chatelain, Asif Makhani, Benjamin Trent, Dai Sugimori, Daniel Doro, David Argüello Sánchez, Dima Kan, Dmitriy Meyerzon, Jaideep Ray, Maryna Kryvko, Prateek Chandra Jha, Ravindra Harige, Taylor Roy, Trey Grainger.
Companies — Empathy, Jina AI, LightOn AI, Meta, Sease, searchHub, Shopify.
Topics — Elasticsearch vs OpenSearch, Multilingual Search, Personalization in Search, Relevance Program Setup, Search Platforms, Search UX, Spelling Correction in Search.
Tools — OpenSearch.
2026-05-31 — LLM Judges, Agentic Retrieval & Bias Concepts (~20 notes)
Articles — Classic ML to Cope with Dumb LLM Judges (by Doug Turnbull, published 2025-01-21), What AI Engineers Should Know about Search (by Doug Turnbull, published 2024-06-25), Search Quality Assurance with AI as a Judge (by Tao Ruangyam at Zalando, published 2026-03-17), This Is What Agentic Retrieval Looks Like (by Jo Kristian Bergum at Hornet, published 2026-05-20), Agentic Search for Context Engineering (by Leonie Monigatti at Elastic, published 2026-05-27).
Concepts — LLM as Judge, Pointwise Relevance Evaluation, Pairwise Relevance Evaluation, Listwise Relevance Evaluation, Position Bias, Presentation Bias, Relevance Feedback, Context Engineering.
Companies — Hornet (agentic retrieval infrastructure), Zalando (European fashion e-commerce).
People — Jo Kristian Bergum (Hornet co-founder, former Vespa AI Chief Scientist), Tao Ruangyam (Zalando search engineering), Leonie Monigatti (Elastic developer advocate).
Topics — Search Quality Assurance and Conversational and Agentic Search expanded.
2026-05-28 — Topic Expansion (1 note)
Topics — Enterprise Search — new topic page covering enterprise-specific search challenges, internal knowledge bases, and vendor landscape.
2026-05-26 — Recent Articles (2 notes)
Articles — When Reranking Becomes a System Boundary (by Ravindra Harige, published 2026-05-25), From Elasticsearch to Vespa - Rebuilding the Kleinanzeigen Homepage Feed Part 1 (by Andre Charton at Kleinanzeigen, published 2026-05-22).
2026-05-19 — Tools, Vector DBs & Hybrid Search (~9 notes)
Tools — Elasticsearch, Qdrant Vector DB, Weaviate Vector DB.
Companies — MongoDB, Voyage AI.
Concepts — Semantic Boosting, Relative Score Fusion.
People — Erik Hatcher (MongoDB).
Articles — Hybrid Search Blueprint Series Semantic Boosting.
2026-05-17 — Consultancy, Tools & Niche Topics (~12 notes)
People — Charlie Hull (The Search Juggler, 25+ years in search).
Tools — Querqy (query rewriting library), Quepid (search relevance evaluation platform).
Companies — The Search Juggler.
Concepts — Signal Downboosting.
Topics — Understaffed Search Team, Search Consultancy, Events and Conferences, Fun and Philosophy, Books.
Articles — Your Obsidian Vault Is a Knowledge Graph, Getting Started on Search Relevance for the Understaffed Search Team.
2026-05-16 — Concepts, Companies & Topics Expansion (~49 notes)
Concepts — BERT, Reranking, TurboQuant, RaBitQ, Query Expansion, Collocations, Stopwords, Clicks Residual, MMR, APD, Linear Score Combination, Modality Gap, Contrastive Gap, Conversational Search, Knowledge Distillation, Dimensionality Reduction, Click Models, Query Sampling.
Companies — Qdrant, Netflix, Canva, Carousell, Etsy, Twitter, Spotify, OpenSource Connections, Skyscanner, Grubhub, Cohere.
Topics — A-B Testing for Search, Economics of Search, E-commerce Search, Autocomplete and Autosuggest, Synonyms and Vocabulary Management, Query Understanding in Practice, Managing a Search Team, Search Quality Assurance, Search Result Diversity, Hiring for Search.
People — Ivan Pleshkov, Jonas Schulz (Qdrant engineers), Neal Lathia (Skyscanner), Stuart Cam (Canva), Hassam Chundrigar (Daraz), Isabella Tromba (Slack), Mihajlo Grbovic (Airbnb), Sergey Feldman (AI2).
Articles — TurboQuant in Qdrant.
2026-05-15 — Initial Import (~200+ notes)
The founding batch. Core articles, concept definitions, MOCs, and key people were imported from the Awesome Search curated list.
Articles — full Query Understanding series (Query Understanding - Introduction through all sub-topics by Daniel Tunkelang), ranking articles (Multi-Stage Ranking, Compute Mean Reciprocal Rank (MRR) using Pandas), embedding articles (Hypothetical Document Embeddings (HyDE), Fine-tuning Multimodal Embedding Models), and many more.
Concepts — foundational IR concepts: BM25, Reciprocal Rank Fusion, Hybrid Search, Synonyms, Bayesian BM25, Knowledge Graph Search, Query Understanding, Autocomplete, Faceted Search, Spelling Correction, Embeddings, Learning to Rank, NDCG, MRR, RAG, and many others.
MOCs — 6 Maps of Content created: MOC - Search UX and Discovery, MOC - Ranking and Retrieval, MOC - Agentic Search and Embeddings, MOC - Search Quality Assurance and Query Understanding, MOC - Architecture and Search Team.
People — Daniel Tunkelang, Doug Turnbull, James Rubinstein, Giovanni Fernandez-Kincade, Wolf Garbe, Eugene Yan, Piotr Mazurek, Karthik Ramasamy, Janani Narayanan, Thomas Veasey, Quynh Nguyen, David Albrecht, Max Irwin, Ted Underwood, and others.
Stats Over Time
| Date | Notes Added | Running Total (approx.) |
|---|---|---|
| 2026-06-01 | ~175 | ~468 |
| 2026-05-31 | ~20 | ~293 |
| 2026-05-28 | 1 | ~273 |
| 2026-05-26 | 2 | ~272 |
| 2026-05-19 | ~9 | ~270 |
| 2026-05-17 | ~12 | ~261 |
| 2026-05-16 | ~49 | ~249 |
| 2026-05-15 | ~200 | ~200 |
See All about Information Retrieval & Search for current vault totals.