Eleanor Berger is an AI and software engineering expert.
A former principal engineering leader at Microsoft and Google, Eleanor also spent years in startups and consulting.
Through Agentic Ventures, she helps power users, engineers, and teams 10x their capabilities and redefine what's possible with agentic AI. Through OKIGU she advises companies directly – helping leaders and teams build robust AI capability, integrate advanced AI, and deliver solutions that drive business value and strategic advantage.
Eleanor's approach: technically rigorous, practically grounded, focused on results, and free of hype.
", "headline": "AI & Software Engineering Leader", "title": "AI & Software Engineering Leader", "linkedin_url": "https://www.linkedin.com/in/intellectronica/", "twitter_handle": "@intellectronica", "custom_social_link": "https://intellectronica.net/", "logos": {"logos": [{"image_url": "https://asset.brandfetch.io/id6O2oGzv-/idjOb2YcqW.svg", "type": "logo", "file_type": "svg", "uuid": "8b4bccc4-ba58-4429-a440-a2e4f52f60f1", "name": "Google"}, {"image_url": "https://asset.brandfetch.io/idchmboHEZ/idc7I0n_oy.svg", "type": "logo", "file_type": "svg", "uuid": "6c3b3247-3ddb-4067-b6d1-7af88f89e576", "name": "Microsoft"}, {"image_url": "https://asset.brandfetch.io/id3KkLe62z/idSdSACndB.svg", "type": "logo", "file_type": "svg", "uuid": "71cd2e1e-a7ff-48cc-8d93-bb09fe98216e", "name": "Canonical"}], "label": ""}, "highlights": null, "highlights_html": "", "preferred_name": null}], "instructor_caption": "AI & Software Engineering Leader", "course_tags": [{"id": 31, "tag_type": "category", "label": "Data & engineering", "slug": "engineering-ll", "description": null, "parent_tag_id": null}, {"id": 35, "tag_type": "category", "label": "AI", "slug": "ai-ll", "description": null, "parent_tag_id": null}, {"id": 80, "tag_type": "deprecated", "label": "AI/ML engineering", "slug": "x-subcategory-ai-ml-engineering", "description": null, "parent_tag_id": 35}, {"id": 110, "tag_type": "deprecated", "label": "Software engineering", "slug": "x-subcategory-software-engineering", "description": null, "parent_tag_id": 31}, {"id": 172, "tag_type": "internal_collection", "label": "AI Affiliates", "slug": "ai-affiliates-nov-24", "description": null, "parent_tag_id": null}, {"id": 244, "tag_type": "internal_collection", "label": "Courses filtered for recommendations", "slug": "courses-filtered-for-recommendations", "description": null, "parent_tag_id": null}, {"id": 293, "tag_type": "persona", "label": "For Engineers", "slug": "for-engineers", "description": null, "parent_tag_id": null}, {"id": 313, "tag_type": "topic", "label": "AI", "slug": "ai", "description": null, "parent_tag_id": null}, {"id": 349, "tag_type": "topic", "label": "Coding with AI", "slug": "ai-coding", "description": null, "parent_tag_id": null}, {"id": 427, "tag_type": "topic", "label": "Context Engineering", "slug": "context-engineering", "description": null, "parent_tag_id": null}]}, "contentPageSlug": "0c0eed", "contentPage": {"id": 6064, "school_id": 15087, "slug": "0c0eed", "content_page_type": "workshop", "sections": [{"uuid": "70aa2839-b33e-45a5-839a-62c2c3f1dade", "title": "Modern Multi-Vector Code Search", "version": 1, "image_url": "https://d2426xcxuh3ht5.cloudfront.net/KxrDrksOTbqueGIv6v7b_Single%20Instructor%20(24).png", "is_visible": true, "topic_desc": "Mixedbread showed in their launch how much faster/better semantic search could make Claude code. Cursor also just announced semantic embedding support, and other agents are soon to follow. I got better quality with 1/2 tokens and almost 2x faster with mixedbread search. \n\nLearn what changed from the leading researchers in the space.", "brand_logos": {"label": "Previously at", "logos": []}, "section_type": "main", "instructor_infos": [{"name": "Aamir Shakir", "uuid": "45b3013f-fd95-46b1-bf5c-a81645bf2cae", "logos": null, "title": "Founder of Mixedbread", "bio_html": "Aamir is the Founder & CEO of Mixedbread, which is building a search API for unstructured data like PDFs, images, and video to provide the right context to both humans and AI.Since the release of BERT, he has been at the forefront of representation learning and retrieval, working on how AI systems can effectively understand and use complex, unstructured data.At Mixedbread, Aamir leads the development of foundational retrieval models that replace outdated, brittle data pipelines, helping organizations make their data AI-ready and turn it into real business outcomes.
", "headline": "", "image_url": "https://d2426xcxuh3ht5.cloudfront.net/hb4HvZkMTiumoMqsRzn2_Aamir%20Headshot%20-%20NEW%20(1).jpg", "highlights": null, "linkedin_url": null, "twitter_handle": null, "highlights_html": null, "image_url_no_bg": null, "custom_social_link": null}, {"name": "Isaac Flath", "uuid": "38208fd6-6359-4519-bd4f-a3a93fb68043", "logos": {"label": "", "logos": []}, "title": "Dev-efficiency and AI expert; Elite AI-Assisted Coding co-instructor", "bio_html": "Isaac is an independent consultant, OSS contributor, and product builder who has helped many companies incorporate AI into their products. I've taught AI efficiency to companies for years and worked for tech startups and cutting edge labs.
As a consultant, I have helped companies of all sizes from startups (such as Ankihub and SpecStory) to enterprise clients (such as Travel & Leisure and Cable and Wireless Communications). Previously, I worked as a researcher at Novetta where I worked on Chatbots, and worked at other cutting edge labs such as Answer AI.
", "headline": "", "image_url": "https://d2426xcxuh3ht5.cloudfront.net/x8HFEtwGRo2JIfDPk423_profile.jpeg", "highlights": [], "linkedin_url": "", "twitter_handle": "", "image_url_no_bg": null, "custom_social_link": ""}], "learning_outcomes": [{"uuid": "948d8f44-cc97-4c7b-839f-7169ddf102f5", "title": "What makes semantic search work for code?", "description": "What's the technical difference between todays semantic search and a \"standard\" hybrid search + reranker from last year"}, {"uuid": "508d1099-5b74-4edf-83de-701b5b6855b7", "title": "What is \"multi-vector\" search and semantic chunking?", "description": "Learn the latest architectures and how a \"single\" vector per chunk is replaced with \"multiple\" for better search"}, {"uuid": "621b6b3e-c698-4dea-a87e-e3739d7d6de6", "title": "Why wasn't multi-vector done before?", "description": "Learn the challenges of a multi-vector search and how extreme quantization with clustering is done to make it possible"}]}], "created_at": "2026-02-12T21:05:51.343094Z", "updated_at": null, "theme": null, "attrs": {"type": "workshop", "is_canceled": false, "is_delisted": false, "connected_course_id": 17014, "course_stripe_promo_code_id": null}, "school_event": {"id": 6064, "slug": null, "title": "Modern Multi-Vector Code Search", "description": null, "start_datetime": "2025-12-11T18:00:00Z", "end_datetime": "2025-12-11T19:00:00Z", "start_date": "2025-12-11", "start_time": "13:00:00", "duration_min": 60, "timezone": "America/New_York", "has_internal_recording": true, "is_recording_public": true}, "num_signups": 156}, "relatedWorkshops": [{"id": 5534, "school_id": 14003, "is_visible_on_discovery_page": true, "is_canceled": false, "is_delisted": false, "connected_course_id": 15495, "workshop_tags": [{"id": 31, "tag_type": "category", "label": "Data & engineering", "slug": "engineering-ll", "description": null, "parent_tag_id": null}, {"id": 293, "tag_type": "persona", "label": "For Engineers", "slug": "for-engineers", "description": null, "parent_tag_id": null}, {"id": 299, "tag_type": "persona", "label": "For Data Scientists", "slug": "for-data-scientists", "description": null, "parent_tag_id": null}, {"id": 313, "tag_type": "topic", "label": "AI", "slug": "ai", "description": null, "parent_tag_id": null}, {"id": 441, "tag_type": "topic", "label": "RAG & Search", "slug": "rag-search", "description": null, "parent_tag_id": null}], "published_content_page": {"id": 6379, "school_id": 14003, "slug": "421011", "content_page_type": "workshop", "sections": [{"uuid": "e468f589-4bfa-4fae-916f-141b78de4c48", "title": "Cheat at Search Essentials: Vectors and Embeddings", "version": 1, "image_url": "https://d2426xcxuh3ht5.cloudfront.net/PkqGyYfRjmryo0xI0Qdv_cheat-at-search-essentials.jpg", "is_visible": true, "topic_desc": "For decades, search techniques were dominated by lexical search. IE some form of 'dumb token matching'. Yet in the last decade, embedding based retrieval has completely upended that paradigm, giving us results focused on semantic search before strings.", "brand_logos": {"label": "Previously at", "logos": [{"name": "Reddit", "type": "logo", "uuid": "e77b2b57-2362-42b2-913d-196971445b6a", "file_type": "svg", "image_url": "https://asset.brandfetch.io/idkKwm0IT0/idklqyFZ_8.svg"}, {"name": "Shopify.com", "type": "logo", "uuid": "d0c67d85-de7a-4ead-88cd-bcb00e3deaf9", "file_type": "svg", "image_url": "https://asset.brandfetch.io/idAgPm7IvG/id85L14isQ.svg"}, {"name": "Wikimedia Foundation", "type": "icon", "uuid": "d7d51da2-c833-443a-b0b2-016728569d07", "file_type": "jpeg", "image_url": "https://asset.brandfetch.io/idLpeBQcRG/id2GMQQdEv.jpeg"}, {"name": "LexisNexis", "type": "logo", "uuid": "2e0bfe2c-46eb-4a6c-a0af-5708c772ca63", "file_type": "svg", "image_url": "https://asset.brandfetch.io/idg2GGIjrA/id9YdSYYup.svg"}, {"name": "Wayfair", "type": "logo", "uuid": "4c930221-7267-48a6-987b-03b05dd5a2a1", "file_type": "svg", "image_url": "https://asset.brandfetch.io/idSfovRbnq/id4Xsg7wCJ.svg"}]}, "section_type": "main", "instructor_infos": [{"name": "Doug Turnbull", "uuid": "669840af-abca-451e-bc6b-09172c483dad", "logos": null, "title": "Author. Builder. Search practitioner.", "bio_html": "Doug helps search teams move beyond hype.
He led machine-learning-driven search at Reddit and Shopify, served as CTO of OpenSource Connections, and co-authored Relevant Search and AI Powered Search.
Doug has trained and advised teams at the Wikimedia Foundation, Wayfair, and AWS, and created Quepid, SearchArray, and the Elasticsearch Learning to Rank plugin.
", "image_url": "https://d2426xcxuh3ht5.cloudfront.net/Sl2N4s1QtekAF1d9KU2g_avatar.jpeg", "highlights": null, "linkedin_url": null, "twitter_handle": null, "image_url_no_bg": null, "custom_social_link": null}], "learning_outcomes": [{"uuid": "3a6a183b-c3d8-4a96-a143-2d61eee7f3d5", "title": "Learn how embeddings implement 'semantic search'", "description": "What is a 'vector embedding' and why do they capture meaning? And how can that be used to build a search system?"}, {"uuid": "9374dc75-af07-4f05-9a38-f089439a1bdb", "title": "Tackle the practical realities vector retrieval", "description": "Why do we need a vector database? And why are they different from traditional search engines? Should they be different?"}, {"uuid": "3844dda2-72c5-4a8a-a10d-0fc4a7de699c", "title": "How are vector + lexical techniques combined?", "description": "Offer a concrete and concise explanation of how you will\nhelp students understand and apply this lesson.\n"}]}], "created_at": "2026-02-12T21:06:54.439827Z", "updated_at": null, "theme": null, "attrs": {"type": "workshop", "is_canceled": false, "is_delisted": false, "connected_course_id": 15495, "course_stripe_promo_code_id": null}, "school_event": {"id": 6379, "slug": null, "title": "Cheat at Search Essentials: Vectors and Embeddings", "description": null, "start_datetime": "2026-01-22T19:00:00Z", "end_datetime": "2026-01-22T20:00:00Z", "start_date": "2026-01-22", "start_time": "14:00:00", "duration_min": 60, "timezone": "America/New_York", "has_internal_recording": true, "is_recording_public": true}, "num_signups": 257}}, {"id": 5066, "school_id": 15363, "is_visible_on_discovery_page": true, "is_canceled": false, "is_delisted": false, "connected_course_id": 17433, "workshop_tags": [{"id": 31, "tag_type": "category", "label": "Data & engineering", "slug": "engineering-ll", "description": null, "parent_tag_id": null}, {"id": 35, "tag_type": "category", "label": "AI", "slug": "ai-ll", "description": null, "parent_tag_id": null}, {"id": 290, "tag_type": "persona", "label": "For Product Managers", "slug": "for-product-managers", "description": null, "parent_tag_id": null}, {"id": 293, "tag_type": "persona", "label": "For Engineers", "slug": "for-engineers", "description": null, "parent_tag_id": null}, {"id": 299, "tag_type": "persona", "label": "For Data Scientists", "slug": "for-data-scientists", "description": null, "parent_tag_id": null}, {"id": 313, "tag_type": "topic", "label": "AI", "slug": "ai", "description": null, "parent_tag_id": null}, {"id": 332, "tag_type": "topic", "label": "Machine Learning", "slug": "ml", "description": null, "parent_tag_id": null}, {"id": 441, "tag_type": "topic", "label": "RAG & Search", "slug": "rag-search", "description": null, "parent_tag_id": null}], "published_content_page": {"id": 473, "school_id": 15363, "slug": "283438", "content_page_type": "workshop", "sections": [{"uuid": "4b225f44-667d-4078-8e88-a46079b388c2", "title": "Optimizing Multimodal Vector Search for E-commerce", "version": 1, "image_url": "https://d2426xcxuh3ht5.cloudfront.net/OJRm4rjQSCm0yMnfnHsw_philippe-canva.png", "is_visible": true, "topic_desc": "Performance lags or poor search results can derail vector search implementations. Inspired by successful large-scale deployments, this session will teach you how to avoid pitfalls and get your vector search into production with the best outcome. Not all embedding models are created equal. You’ll learn how to integrate high quality embeddings for improved search quality at little performance cost", "brand_logos": {"label": "Vectra", "logos": [{"name": "Harvard University", "type": "logo", "uuid": "dfda2685-7383-41d6-9e1e-b821ae18cbf1", "file_type": "svg", "image_url": "https://asset.brandfetch.io/idgP1KuU-N/idJmgAce_I.svg"}, {"name": "Searchkernel", "type": "icon", "uuid": "550f9de9-0990-483f-9305-8259ff8337f2", "file_type": "jpeg", "image_url": "https://asset.brandfetch.io/idJTONuDZB/idvnLUMzvj.jpeg"}, {"name": "Gorillas", "type": "logo", "uuid": "f6ae944a-7017-4184-b708-717b979899d9", "file_type": "svg", "image_url": "https://asset.brandfetch.io/ido01XDvdB/idXG33h27B.svg"}, {"name": "Lucidworks", "type": "icon", "uuid": "d452f2df-265a-41f7-9e9c-0ce2f79b6031", "file_type": "jpeg", "image_url": "https://asset.brandfetch.io/idskYMg_Lc/idsgrCljLm.jpeg"}, {"name": "CareerBuilder", "type": "logo", "uuid": "007823ab-73e8-4adb-a022-7139b673927d", "file_type": "svg", "image_url": "https://asset.brandfetch.io/idRrcMU04X/idPe8dAyv6.svg"}]}, "section_type": "main", "instructor_infos": [{"name": "Philippe Bouzaglou", "uuid": "2438de46-85a6-49be-abe8-f21ac7fca9ff", "logos": null, "title": "Technical Founder at Vectra, the AI foundation model for e-commerce search", "bio_html": "Philippe pioneered the concept of the Social Graph while attending Harvard with Mark Zuckerberg. He has since gone on to achieve significant contributions in the fields of data science and machine learning. Recently, he was VP of Data Science and Machine Learning and responsible for search at Gorillas, the quick-commerce company that pioneered grocery delivery within the hour. He is now the technical founder at Vectra, an AI company creating the foundation model for e-commerce search.
", "headline": "", "image_url": "https://d2426xcxuh3ht5.cloudfront.net/Lx178AewQKeCC3qlravz_philippe-headshot.jpeg", "highlights": null, "linkedin_url": null, "twitter_handle": null, "highlights_html": null, "image_url_no_bg": null, "custom_social_link": null}, {"name": "Trey Grainger", "uuid": "d6a32013-24b9-4683-8fb0-5edbc5dc7f5f", "logos": {"label": "", "logos": []}, "title": "Founder @ Searchkernel, Author of \"AI-Powered Search\"", "bio_html": "Trey is lead author of the book AI-Powered Search and is the founder of Searchkernel, a software company building the next generation of AI-powered search. He is an advisor to several startups and adjunct professor of computer science at Furman University. He previously served as CTO of Presearch, a decentralized web search engine, and as chief algorithms officer and SVP of engineering at Lucidworks, an search company whose search technology powers hundreds of the world’s leading organizations. You can learn more directly with Trey in the popular AI-Powered Search: Modern Retrieval for Humans & Agents course.
", "headline": "", "image_url": "https://d2426xcxuh3ht5.cloudfront.net/yyvVqudqTia1ou8CA46E_trey-headshot-2018.png", "highlights": [], "linkedin_url": "", "twitter_handle": "", "highlights_html": null, "image_url_no_bg": null, "custom_social_link": ""}], "learning_outcomes": [{"uuid": "8ba5f7c7-b6e1-446c-9285-1574b36cc019", "title": "Using visual evals to benchmark embedding quality", "description": "We’ll walk through how to perform comparative evals and visualize the quality of embeddings for your queries and dataset"}, {"uuid": "1d3b9c9c-6752-4220-ab83-48cf5138c487", "title": "Vector search without a performance hit… is that possible?", "description": "Embedding generation takes time and holds back the entire search stack. How can you make it fast?"}, {"uuid": "2eff29cb-df0d-42ff-9d24-cf6c6dc95e79", "title": "How to test and roll out embeddings to production", "description": "We’ll show you how real ecommerce companies actually roll out vector search to avoid operational risk and max out KPIs."}]}], "created_at": "2026-02-04T21:56:37.018304Z", "updated_at": "2026-02-04T21:58:45.294730Z", "theme": null, "attrs": {"type": "workshop", "is_canceled": false, "is_delisted": false, "connected_course_id": 17433, "course_stripe_promo_code_id": null}, "school_event": {"id": 473, "slug": null, "title": "Optimizing Multimodal Vector Search for E-commerce", "description": null, "start_datetime": "2026-02-13T18:30:00Z", "end_datetime": "2026-02-13T19:30:00Z", "start_date": "2026-02-13", "start_time": "13:30:00", "duration_min": 60, "timezone": "America/New_York", "has_internal_recording": true, "is_recording_public": true}, "num_signups": 171}}, {"id": 3147, "school_id": 11275, "is_visible_on_discovery_page": true, "is_canceled": false, "is_delisted": false, "connected_course_id": 12327, "workshop_tags": [{"id": 31, "tag_type": "category", "label": "Data & engineering", "slug": "engineering-ll", "description": null, "parent_tag_id": null}, {"id": 35, "tag_type": "category", "label": "AI", "slug": "ai-ll", "description": null, "parent_tag_id": null}, {"id": 137, "tag_type": "internal_collection", "label": "Instructor", "slug": "Instructor", "description": null, "parent_tag_id": null}, {"id": 293, "tag_type": "persona", "label": "For Engineers", "slug": "for-engineers", "description": null, "parent_tag_id": null}, {"id": 299, "tag_type": "persona", "label": "For Data Scientists", "slug": "for-data-scientists", "description": null, "parent_tag_id": null}, {"id": 313, "tag_type": "topic", "label": "AI", "slug": "ai", "description": null, "parent_tag_id": null}, {"id": 441, "tag_type": "topic", "label": "RAG & Search", "slug": "rag-search", "description": null, "parent_tag_id": null}], "published_content_page": {"id": 3981, "school_id": 11275, "slug": "56f424", "content_page_type": "workshop", "sections": [{"uuid": "8520ab9c-61a3-47da-bba1-d0136131ec4f", "title": "Data is Everything: Finding needles in multimodal haystacks", "version": 1, "image_url": "https://d2426xcxuh3ht5.cloudfront.net/nOZ56MccQoKlam8aAgWL_Panel (4 People) (2).png", "is_visible": true, "topic_desc": "Understanding multimodal data search unlocks vast information potential that would otherwise remain hidden. As data volumes explode across formats, professionals who master these search techniques gain a competitive edge, enabling them to extract valuable insights faster than competitors and build more responsive, intelligent systems that delight users.", "brand_logos": {"label": "worked with", "logos": [{"name": "Kino AI", "type": "logo", "uuid": "d4966216-81e5-4c38-823b-fe22404a77ab", "file_type": "png", "image_url": "https://asset.brandfetch.io/idbcL_yDXV/idMDSFhyTH.png"}, {"name": "Stitch Fix", "type": "logo", "uuid": "539abc80-8920-4818-92ce-33a67ea7cd19", "file_type": "svg", "image_url": "https://asset.brandfetch.io/idTgrRl8nA/idVnuVYfek.svg"}, {"name": "Meta", "type": "logo", "uuid": "8df77364-cb2b-4f5f-9785-5b75f93e9f21", "file_type": "svg", "image_url": "https://asset.brandfetch.io/idWvz5T3V7/idpvCl_Ipb.svg"}, {"name": "University of Waterloo", "type": "logo", "uuid": "a49dbcd3-70d6-463c-b35d-12a851d108f0", "file_type": "svg", "image_url": "https://asset.brandfetch.io/idIfIi7wMZ/ida2LuNMbf.svg"}, {"name": "New York University", "type": "logo", "uuid": "0f539abb-5ee3-4385-9185-aeffeaa2b9f1", "file_type": "svg", "image_url": "https://asset.brandfetch.io/idMj8iq0ev/idShvt3ozm.svg"}]}, "section_type": "main", "instructor_infos": [{"name": "Jason Liu", "uuid": "baaa804e-eb74-454d-bf5b-36b2712b55e9", "title": "Consultant at the intersection of Information Retrieval and AI", "bio_html": "Jason has built search and recommendation systems for the past 6 years. He has consulted and advised a dozens startups in the last year to improve their RAG systems. He is the creator of the Instructor Python library.
", "image_url": "https://d2426xcxuh3ht5.cloudfront.net/vLKLakZTRcCCdR7th6el_Jason.png"}, {"name": "Rajan Agarwal", "uuid": "8c06e5c0-4f13-4c94-b72d-049e2a7e8186", "title": "Research Engineering Intern @ Kino AI", "bio_html": "Rajan Agarwal is a Machine Learning researcher studying at the University of Waterloo, specializing in multimodal models, self-driving software and multi-agent orchestration.
", "image_url": "https://d2426xcxuh3ht5.cloudfront.net/SgbrJpPHSVu0GHB3JUxf_headshot (1).png"}, {"name": "Luke Igel", "uuid": "43bce83b-062c-463d-b7fe-a439492f0760", "title": "CEO, Co-founder at Kino AI", "bio_html": "Luke Igel is the co-founder and CEO of Kino. Previously he worked on autonomous systems at NASA and satellite planning software at SpaceX. He recently graduated from MIT, where he co-created an archival footage documentary on the history of America, inspiring the founding of Kino.
", "image_url": "https://d2426xcxuh3ht5.cloudfront.net/nLlDdxfbRaOd3wgrXMcf_igel portrait.jpeg"}], "learning_outcomes": [{"uuid": "9060bc4a-ee61-459d-bbb8-dbbf2aa43157", "title": "Vector Embedding Strategies", "description": "Master techniques to encode multimodal data for efficient search and retrieval."}, {"uuid": "53fad31d-c6f3-4c54-8ca8-00344b3a7745", "title": "Chunking & Indexing Methodologies", "description": "Master approaches to segment and organize large datasets to enable precise searching across diverse data types."}, {"uuid": "4c5554c0-c598-4617-ba48-1ca1b0141a5f", "title": "Multimodal Query Optimization", "description": "Develop skills to formulate and process complex queries that span multiple data modalities for comprehensive results."}]}], "created_at": "2026-02-12T21:00:34.921937Z", "updated_at": null, "theme": null, "attrs": {"type": "workshop", "is_canceled": false, "is_delisted": false, "connected_course_id": 12327, "course_stripe_promo_code_id": null}, "school_event": {"id": 3981, "slug": null, "title": "Data is Everything: Finding needles in multimodal haystacks", "description": null, "start_datetime": "2025-05-28T18:00:00Z", "end_datetime": "2025-05-28T19:00:00Z", "start_date": "2025-05-28", "start_time": "14:00:00", "duration_min": 60, "timezone": "America/Toronto", "has_internal_recording": true, "is_recording_public": true}, "num_signups": 230}}], "exploreCourses": null, "workshopTags": [{"id": 31, "tag_type": "category", "label": "Data & engineering", "slug": "engineering-ll", "description": null, "parent_tag_id": null}, {"id": 35, "tag_type": "category", "label": "AI", "slug": "ai-ll", "description": null, "parent_tag_id": null}, {"id": 441, "tag_type": "topic", "label": "RAG & Search", "slug": "rag-search", "description": null, "parent_tag_id": null}, {"id": 293, "tag_type": "persona", "label": "For Engineers", "slug": "for-engineers", "description": null, "parent_tag_id": null}, {"id": 299, "tag_type": "persona", "label": "For Data Scientists", "slug": "for-data-scientists", "description": null, "parent_tag_id": null}, {"id": 313, "tag_type": "topic", "label": "AI", "slug": "ai", "description": null, "parent_tag_id": null}], "videoChapters": [{"title": "Introduction and Casual Chat", "start_seconds": 30}, {"title": "Critique of Agentic Frameworks", "start_seconds": 91}, {"title": "The Problem with Unified APIs and OpenRouter", "start_seconds": 196}, {"title": "Building an Agentic Chief of Staff", "start_seconds": 277}, {"title": "The Non-Deterministic Computer: A Mental Model for Agents", "start_seconds": 338}, {"title": "The Simplicity Behind Complex AI Terms", "start_seconds": 394}, {"title": "Planning the Interview Structure", "start_seconds": 463}, {"title": "Pre-Talk Setup and Introduction to Mixpread", "start_seconds": 3310}, {"title": "What is Mixpread and Multi-Vector Search?", "start_seconds": 3656}, {"title": "Why Multi-Vector Search Outperforms Single-Vector", "start_seconds": 3836}, {"title": "Why Multi-Vector Search is Just Now Becoming Viable", "start_seconds": 3985}, {"title": "Understanding Quantization for Efficient Retrieval", "start_seconds": 4076}, {"title": "Advanced Quantization: Mitigating Performance Loss", "start_seconds": 4257}, {"title": "Inside Mixpread's System Architecture", "start_seconds": 4361}, {"title": "Semantic Chunking for Code, PDFs, and Video", "start_seconds": 4592}, {"title": "How Mixpread Evaluates End-User Performance", "start_seconds": 4801}, {"title": "Getting Started in Retrieval Research and Engineering", "start_seconds": 4926}, {"title": "The Continued Importance of Re-rankers and Cross-Encoders", "start_seconds": 5173}, {"title": "The Future of Scoring and Final Wrap-Up", "start_seconds": 5489}], "navPages": [{"category": {"slug": "ai", "href": "/courses/ai", "title": "AI", "palette": {"--palette-category-base": "#460952", "--palette-category-highlight": "#931FAA", "--palette-category-border": "#EDA6FB"}}, "topics": [{"title": "Agentic AI", "slug": "ai/agentic-ai", "href": "/courses/ai/agentic-ai"}, {"title": "Coding with AI", "slug": "ai/ai-coding", "href": "/courses/ai/ai-coding"}, {"title": "AI Workflows", "slug": "ai/ai-workflows", "href": "/courses/ai/ai-workflows"}, {"title": "Claude Code", "slug": "ai/claude-code", "href": "/courses/ai/claude-code"}, {"title": "OpenClaw", "slug": "ai/openclaw", "href": "/courses/ai/openclaw"}, {"title": "Vibe Coding", "slug": "ai/vibe-coding", "href": "/courses/ai/vibe-coding"}, {"title": "AI Evals", "slug": "ai/evals", "href": "/courses/ai/evals"}, {"title": "AI Transformation", "slug": "ai/ai-transformation", "href": "/courses/ai/ai-transformation"}, {"title": "RAG & Search", "slug": "ai/rag-search", "href": "/courses/ai/rag-search"}, {"title": "MCP", "slug": "ai/mcp", "href": "/courses/ai/mcp"}, {"title": "AI for PMs", "slug": "ai/for-product-managers", "href": "/courses/ai/for-product-managers"}, {"title": "AI for Engineers", "slug": "ai/for-engineers", "href": "/courses/ai/for-engineers"}, {"title": "AI for Designers", "slug": "ai/for-designers", "href": "/courses/ai/for-designers"}, {"title": "AI for Marketers", "slug": "ai/for-marketers", "href": "/courses/ai/for-marketers"}, {"title": "AI for Founders", "slug": "ai/for-founders", "href": "/courses/ai/for-founders"}]}, {"category": {"slug": "product", "href": "/courses/product", "title": "Product", "palette": {"--palette-category-base": "#510B00", "--palette-category-highlight": "#B33600", "--palette-category-border": "#F7804D"}}, "topics": [{"title": "AI for PMs", "slug": "for-product-managers/ai", "href": "/courses/for-product-managers/ai"}, {"title": "Agentic AI", "slug": "for-product-managers/agentic-ai", "href": "/courses/for-product-managers/agentic-ai"}, {"title": "AI Evals", "slug": "for-product-managers/ai-evals", "href": "/courses/for-product-managers/ai-evals"}, {"title": "Vibe Coding", "slug": "for-product-managers/vibe-coding", "href": "/courses/for-product-managers/vibe-coding"}, {"title": "Product Sense", "slug": "for-product-managers/product-sense", "href": "/courses/for-product-managers/product-sense"}, {"title": "Product Discovery", "slug": "for-product-managers/product-discovery", "href": "/courses/for-product-managers/product-discovery"}, {"title": "User Research", "slug": "for-product-managers/user-research", "href": "/courses/for-product-managers/user-research"}, {"title": "Prototyping", "slug": "for-product-managers/prototyping", "href": "/courses/for-product-managers/prototyping"}, {"title": "Growth", "slug": "for-product-managers/growth", "href": "/courses/for-product-managers/growth"}, {"title": "Analytics", "slug": "for-product-managers/analytics", "href": "/courses/for-product-managers/analytics"}, {"title": "Tech Foundations", "slug": "for-product-managers/technical-foundations", "href": "/courses/for-product-managers/technical-foundations"}, {"title": "Strategy", "slug": "for-product-managers/strategy", "href": "/courses/for-product-managers/strategy"}, {"title": "Influence", "slug": "for-product-managers/influence", "href": "/courses/for-product-managers/influence"}, {"title": "Leadership", "slug": "for-product-managers/leadership", "href": "/courses/for-product-managers/leadership"}, {"title": "Career Growth", "slug": "for-product-managers/career-growth", "href": "/courses/for-product-managers/career-growth"}]}, {"category": {"slug": "engineering", "href": "/courses/engineering", "title": "Engineering", "palette": {"--palette-category-base": "#00332F", "--palette-category-highlight": "#00746B", "--palette-category-border": "#88B7B2"}}, "topics": [{"title": "AI for Engineers", "slug": "for-engineers/ai", "href": "/courses/for-engineers/ai"}, {"title": "Agentic AI", "slug": "for-engineers/agentic-ai", "href": "/courses/for-engineers/agentic-ai"}, {"title": "Coding with AI", "slug": "for-engineers/ai-coding", "href": "/courses/for-engineers/ai-coding"}, {"title": "Claude Code", "slug": "for-engineers/claude-code", "href": "/courses/for-engineers/claude-code"}, {"title": "OpenClaw", "slug": "for-engineers/openclaw", "href": "/courses/for-engineers/openclaw"}, {"title": "MCP", "slug": "for-engineers/mcp", "href": "/courses/for-engineers/mcp"}, {"title": "RAG & Search", "slug": "for-engineers/rag-search", "href": "/courses/for-engineers/rag-search"}, {"title": "AI Evals", "slug": "for-engineers/ai-evals", "href": "/courses/for-engineers/ai-evals"}, {"title": "Machine Learning", "slug": "for-engineers/ml", "href": "/courses/for-engineers/ml"}, {"title": "LLM Ops", "slug": "for-engineers/llm-ops", "href": "/courses/for-engineers/llm-ops"}, {"title": "Context Eng", "slug": "for-engineers/context-engineering", "href": "/courses/for-engineers/context-engineering"}, {"title": "Security", "slug": "for-engineers/security", "href": "/courses/for-engineers/security"}, {"title": "System Design", "slug": "for-engineers/system-design", "href": "/courses/for-engineers/system-design"}, {"title": "Leadership", "slug": "for-engineers/leadership", "href": "/courses/for-engineers/leadership"}, {"title": "Career Growth", "slug": "for-engineers/career-growth", "href": "/courses/for-engineers/career-growth"}]}, {"category": {"slug": "design", "href": "/courses/design", "title": "Design", "palette": {"--palette-category-base": "#38085F", "--palette-category-highlight": "#772CBB", "--palette-category-border": "#B5A2D0"}}, "topics": [{"title": "AI for Designers", "slug": "for-designers/ai", "href": "/courses/for-designers/ai"}, {"title": "Agentic AI", "slug": "for-designers/agentic-ai", "href": "/courses/for-designers/agentic-ai"}, {"title": "Vibe Coding", "slug": "for-designers/vibe-coding", "href": "/courses/for-designers/vibe-coding"}, {"title": "Prototyping", "slug": "for-designers/prototyping", "href": "/courses/for-designers/prototyping"}, {"title": "Figma", "slug": "for-designers/figma", "href": "/courses/for-designers/figma"}, {"title": "Design Systems", "slug": "for-designers/design-systems", "href": "/courses/for-designers/design-systems"}, {"title": "User Research", "slug": "for-designers/user-research", "href": "/courses/for-designers/user-research"}, {"title": "Product Discovery", "slug": "for-designers/product-discovery", "href": "/courses/for-designers/product-discovery"}, {"title": "UX", "slug": "for-designers/ux", "href": "/courses/for-designers/ux"}, {"title": "UI", "slug": "for-designers/ui", "href": "/courses/for-designers/ui"}, {"title": "Visual Design", "slug": "for-designers/visual-design", "href": "/courses/for-designers/visual-design"}, {"title": "Design Strategy", "slug": "for-designers/strategy", "href": "/courses/for-designers/strategy"}, {"title": "Influence", "slug": "for-designers/influence", "href": "/courses/for-designers/influence"}, {"title": "Leadership", "slug": "for-designers/leadership", "href": "/courses/for-designers/leadership"}, {"title": "Career Growth", "slug": "for-designers/career-growth", "href": "/courses/for-designers/career-growth"}]}, {"category": {"slug": "marketing", "href": "/courses/marketing", "title": "Marketing", "palette": {"--palette-category-base": "#431532", "--palette-category-highlight": "#943170", "--palette-category-border": "#C99EB5"}}, "topics": [{"title": "AI for Marketers", "slug": "for-marketers/ai", "href": "/courses/for-marketers/ai"}, {"title": "Agentic AI", "slug": "for-marketers/agentic-ai", "href": "/courses/for-marketers/agentic-ai"}, {"title": "Vibe Coding", "slug": "for-marketers/vibe-coding", "href": "/courses/for-marketers/vibe-coding"}, {"title": "Automation", "slug": "for-marketers/marketing-automation", "href": "/courses/for-marketers/marketing-automation"}, {"title": "Content Marketing", "slug": "for-marketers/content-marketing", "href": "/courses/for-marketers/content-marketing"}, {"title": "Demand Gen", "slug": "for-marketers/demand-generation", "href": "/courses/for-marketers/demand-generation"}, {"title": "Go-to-Market", "slug": "for-marketers/gtm", "href": "/courses/for-marketers/gtm"}, {"title": "Product Marketing", "slug": "for-marketers/product-marketing", "href": "/courses/for-marketers/product-marketing"}, {"title": "Positioning", "slug": "for-marketers/positioning", "href": "/courses/for-marketers/positioning"}, {"title": "Social Media", "slug": "for-marketers/social-media", "href": "/courses/for-marketers/social-media"}, {"title": "Brand", "slug": "for-marketers/brand", "href": "/courses/for-marketers/brand"}, {"title": "B2B Marketing", "slug": "for-marketers/b2b", "href": "/courses/for-marketers/b2b"}, {"title": "SEO & AEO", "slug": "for-marketers/seo-aeo", "href": "/courses/for-marketers/seo-aeo"}, {"title": "Strategy", "slug": "for-marketers/strategy", "href": "/courses/for-marketers/strategy"}, {"title": "Leadership", "slug": "for-marketers/leadership", "href": "/courses/for-marketers/leadership"}]}, {"category": {"slug": "leadership", "href": "/courses/leadership", "title": "Leadership", "palette": {"--palette-category-base": "#50090E", "--palette-category-highlight": "#A9202A", "--palette-category-border": "#D49C98"}}, "topics": [{"title": "AI for Leaders", "slug": "for-leaders/ai", "href": "/courses/for-leaders/ai"}, {"title": "Agentic AI", "slug": "for-leaders/agentic-ai", "href": "/courses/for-leaders/agentic-ai"}, {"title": "AI Transformation", "slug": "for-leaders/ai-transformation", "href": "/courses/for-leaders/ai-transformation"}, {"title": "AI Governance", "slug": "for-leaders/ai-governance", "href": "/courses/for-leaders/ai-governance"}, {"title": "Communication", "slug": "for-leaders/communication", "href": "/courses/for-leaders/communication"}, {"title": "Influence", "slug": "for-leaders/influence", "href": "/courses/for-leaders/influence"}, {"title": "Strategy", "slug": "for-leaders/strategy", "href": "/courses/for-leaders/strategy"}, {"title": "Management", "slug": "for-leaders/management", "href": "/courses/for-leaders/management"}, {"title": "People Operations", "slug": "for-leaders/people-operations", "href": "/courses/for-leaders/people-operations"}, {"title": "Exec Presence", "slug": "for-leaders/executive-presence", "href": "/courses/for-leaders/executive-presence"}, {"title": "Storytelling", "slug": "for-leaders/storytelling", "href": "/courses/for-leaders/storytelling"}, {"title": "Goal-setting", "slug": "for-leaders/goal-setting", "href": "/courses/for-leaders/goal-setting"}, {"title": "Personal Brand", "slug": "for-leaders/personal-brand", "href": "/courses/for-leaders/personal-brand"}, {"title": "Career Growth", "slug": "for-leaders/career-growth", "href": "/courses/for-leaders/career-growth"}]}, {"category": {"slug": "founders", "href": "/courses/founders", "title": "Founders", "palette": {"--palette-category-base": "#0C3209", "--palette-category-highlight": "#077202", "--palette-category-border": "#69C662"}}, "topics": [{"title": "AI for Founders", "slug": "for-founders/ai", "href": "/courses/for-founders/ai"}, {"title": "Agentic AI", "slug": "for-founders/agentic-ai", "href": "/courses/for-founders/agentic-ai"}, {"title": "AI Workflows", "slug": "for-founders/ai-workflows", "href": "/courses/for-founders/ai-workflows"}, {"title": "Vibe Coding", "slug": "for-founders/vibe-coding", "href": "/courses/for-founders/vibe-coding"}, {"title": "Prototyping", "slug": "for-founders/prototyping", "href": "/courses/for-founders/prototyping"}, {"title": "Product Sense", "slug": "for-founders/product-sense", "href": "/courses/for-founders/product-sense"}, {"title": "Positioning", "slug": "for-founders/positioning", "href": "/courses/for-founders/positioning"}, {"title": "Product Discovery", "slug": "for-founders/product-discovery", "href": "/courses/for-founders/product-discovery"}, {"title": "Management", "slug": "for-founders/management", "href": "/courses/for-founders/management"}, {"title": "Strategy", "slug": "for-founders/strategy", "href": "/courses/for-founders/strategy"}, {"title": "Go-to-Market", "slug": "for-founders/gtm", "href": "/courses/for-founders/gtm"}, {"title": "Personal Brand", "slug": "for-founders/personal-brand", "href": "/courses/for-founders/personal-brand"}, {"title": "Leadership", "slug": "for-founders/leadership", "href": "/courses/for-founders/leadership"}, {"title": "Fundraising", "slug": "for-founders/fundraising", "href": "/courses/for-founders/fundraising"}, {"title": "PMF", "slug": "for-founders/product-market-fit", "href": "/courses/for-founders/product-market-fit"}]}, {"category": {"slug": "more", "href": "/courses/more", "title": "More", "palette": {"--palette-category-base": "#1E2C2B", "--palette-category-highlight": "#4A6361", "--palette-category-border": "#B9C1BE"}}, "topics": [{"title": "Everyone", "slug": "for-everyone", "href": "/courses/for-everyone"}, {"title": "Operators", "slug": "for-operators", "href": "/courses/for-operators"}, {"title": "Data Scientists", "slug": "for-data-scientists", "href": "/courses/for-data-scientists"}, {"title": "Business Analysts", "slug": "for-business-analysts", "href": "/courses/for-business-analysts"}, {"title": "User Researchers", "slug": "for-user-researchers", "href": "/courses/for-user-researchers"}, {"title": "Customer Success", "slug": "for-customer-success", "href": "/courses/for-customer-success"}, {"title": "Project Managers", "slug": "for-project-managers", "href": "/courses/for-project-managers"}, {"title": "HR Professionals", "slug": "for-hr-professionals", "href": "/courses/for-hr-professionals"}, {"title": "Sales People", "slug": "for-sales-people", "href": "/courses/for-sales-people"}, {"title": "Lawyers", "slug": "for-lawyers", "href": "/courses/for-lawyers"}, {"title": "Finance", "slug": "for-finance-professionals", "href": "/courses/for-finance-professionals"}, {"title": "Investors", "slug": "for-investors", "href": "/courses/for-investors"}, {"title": "Real Estate", "slug": "for-real-estate-agents", "href": "/courses/for-real-estate-agents"}, {"title": "Educators", "slug": "for-educators", "href": "/courses/for-educators"}, {"title": "Creators", "slug": "for-creators", "href": "/courses/for-creators"}]}], "navTagLinks": [{"tag": {"id": 441, "tag_type": "topic", "label": "RAG & Search", "slug": "rag-search", "description": null, "parent_tag_id": null}, "link_slug": "for-engineers/rag-search"}, {"tag": {"id": 293, "tag_type": "persona", "label": "For Engineers", "slug": "for-engineers", "description": null, "parent_tag_id": null}, "link_slug": "for-engineers"}, {"tag": {"id": 299, "tag_type": "persona", "label": "For Data Scientists", "slug": "for-data-scientists", "description": null, "parent_tag_id": null}, "link_slug": "for-data-scientists"}], "now": "2026-05-19T22:55:13.921Z"}, "__N_SSG": true}, "page": "/p/[slug]/[...ignored]", "query": {"slug": "0c0eed", "ignored": ["modern-multi-vector-code-search"]}, "buildId": "qPlLjBFLQ9fnkFKJ7n7E-", "isFallback": false, "isExperimentalCompile": false, "gsp": true, "scriptLoader": []}}