"AI-Powered Search" Course Testimonials

Excited to share that I’ve completed Maven’s AI-Powered Search course .
Over 5 weeks, I went deep on what it takes to build modern, relevance-driven search systems—from classic IR foundations to LLM-era retrieval and ranking.
A few key takeaways I’m walking away with:
Relevance is a product problem as much as a modeling problem: user behavior insights, implicit signals, and evaluation loops matter as much as architecture.
Hybrid retrieval is the default: mixing sparse + dense (e.g., MiniCOIL-style approaches) and tuning the blend for real traffic.
Ranking is the real lever: LTR, click models, bias-aware learning, and active learning to keep improving without endless labeling.
RAG done right: interleaving strategies, retrieval quality, and grounding—because “more context” ≠ “better answers.”
Performance + UX: vector search optimization, semantic query understanding, semistructured embeddings, and agentic search patterns.
Big thanks to the speakers who shared practical lessons and real-world war stories Doug Turnbull and Trey Grainger🙏
Next up: applying these ideas to AI-powered conversational search—improving relevance, grounding, and measurable user outcomes.

Finished the AI-Powered Search maven.com/search-school/a... on Maven Very practical, great real-world examples, and the agentic search concepts are already in use in my projects. Thx @treygrainger @softwaredoug

🚀 I recently completed the AI-Powered Search course (lnkd.in/epgWduxp) by Trey Grainger (lnkd.in/e_uC983F) and Doug Tournbull (lnkd.in/erGqBJ_b) on Maven, and it has been an excellent experience.

What I really appreciated about this course is how clearly it explains search-related concepts using real-world examples, making complex ideas easy to understand and immediately applicable. The content is also very well adapted to real ecommerce use cases, especially when working with large and complex product catalogs, which made it especially relevant for my day-to-day work.

One of the biggest highlights for me was the section on agentic search. The concepts and patterns covered are not just theoretical — I’m already applying them in real projects, with tangible impact.

Highly recommended for anyone working on search, relevance, or AI-powered discovery systems, particularly in ecommerce contexts.

👉 Course link:
lnkd.in/eEZg8Pve

Last week I completed a huge upgrade to my information retrieval skills with @treygrainger & @softwaredoug fantastic course "AI-Powered Search". @aipoweredsearch These are some of the key takeaways 👇 aipoweredsearch.com/live-...

AI-Powered Search by @treygrainger & @softwaredoug & @aiPoweredSearch: the most in-depth course I've taken for leveling up retrieval skills. Moved me from "throw embeddings at it and hope" to actually understanding query intent, ranking signals, and production RAG patterns. Hands-on labs + expert guest speakers from Qdrant, OpenSearch, Superlinked made it incredibly practical. Essential for anyone serious about search & RAG. Next cohort in March 👉

I recently completed the AI-Powered Search course on Maven and want to send a huge thank-you to Trey Grainger and Doug Turnbull for the incredible experience. I really can’t recommend it enough.
If you’re working in search, you know how hard it can be to bridge the gap between theory and production-grade systems. This course does exactly that. We covered a massive amount of ground in a short time, moving from the fundamentals of search relevance and user intent to implementing Learning to Rank (LTR) and the bleeding edge of Agentic Search.
For anyone who has read the AI-Powered Search book, this course is the perfect complement. It doesn't just rehash the text; it offers fresh material and deep dives into the modern components of the search stack.
If you are looking to modernize your search stack for both humans and agents, definitely check this out.
#AI #Search #LearningToRank #AgenticAI #MachineLearning
lnkd.in/eMk6yDNs

I waited many years for the "AI-Powered Search" book to be finished. (lnkd.in/d4Fcv3JD)
Then it came the perfect complement: AI-Powered Search: Modern Retrieval for Humans & Agents" a live course taught by the authors themselves, Trey Grainger and Doug Turnbull:

lnkd.in/dTJccmXj

It's hard to describe the depth and breadth of the topics covered without sounding hyperbolic, but the amount of practical knowledge this course packs is overwhelming (in the best possible sense of the term).

From the basics of query preprocessing to sparse/dense vector representations, relevance evaluation and ranking, hybrid search, and LTR to RAG. All from the perspective of experts who have experienced the evolution of search technology for the past 20 years putting theory into practice.

It feels like downloading a zip file of decades of experience right into your brain that you then need time to digest. But you don't need to do it on your own. The lectures are highly interactive, with Trey and Doug answering any question you might have plus office hours to discuss anything you didn't have the chance to ask.

If you are serious about taking your search skills to the next level, this is THE course. Period.

AI-Powered Search by @treygrainger & @softwaredoug & AI-Powered Search: the most in-depth course I've taken for leveling up retrieval skills.

Moved me from "throw embeddings at it and hope" to actually understanding query intent, ranking signals, and production RAG patterns.

Hands-on labs + expert guest speakers from Qdrant, OpenSearch, Superlinked made it incredibly practical.

Essential for anyone serious about search & RAG. Next cohort in March 👉 https://lnkd.in/gxnkckZa

I just finished the AI-Powered Search: Modern Retrieval for Humans and Agents Course by Maven (delivered by Trey Grainger and Doug Turnbull), and I give it a strong recommendation.
TL;DR: If you work in search, retrieval, or build applications that rely on smart information retrieval, you *need* this course. Trey and Doug don't just teach theory; they provide a toolkit of immediately applicable techniques.

Why I Highly Recommend It:

- Immediate Impact: The notebook based hands-on activities cover all key aspects of the training and are readily applicable to your scenario to see how they could help in your course. This isn't just academic; it delivers real-world performance improvements.
- Modern Curriculum: While I absolutely loved their book (my thoughts on the book: lnkd.in/dVqmByA5), the course dives deep into topics essential for today's landscape: scaling vector search, a deep dive into RAG, and the power of UBI (User Behavior Insights) to name a few.
- Community & Exchange: The direct exchange with trainers, guest speakers, and fellow practitioners was invaluable. The willingness of everyone to share their experience on complex problems was a huge bonus showing how cohort-based learning truly is collaborative. Knowing most of the guest speakers (special shout-outs to my colleague Eric Pugh and Evgeniya Sukhodolskaya with whom I’m organising the BASED meet-up in Munich) personally it was no surprise that they all delivered high value content - not as sales pitches but as practically applicable lessons.

If you thought reading the AI-Powered Search book was enough, I encourage you to think again. I expect Doug and Trey to rework and augment the course material not only based on their learnings of this course but also based on what will happen until the next cohort starts. Speaking of which: the next cohort starts in March! Don't miss out on getting an edge in the AI-powered search space: 👉 lnkd.in/dGk6Cay9
Thank you, Trey and Doug, for the high-quality, hands-on training! #AIPoweredSearch #InformationRetrieval #RAG #VectorSearch

I recently completed the AI-Powered Search course by Trey Grainger and Doug Turnbull. Going in, I felt we were in a pretty good place: we had BM25, embeddings, vector search, and some basic reranking. What I was missing was a coherent mental model that connects all of this with user signals, evaluation, and RAG. The course filled in a lot of those gaps. It pushed me to treat query understanding as a first class problem, to see click and interaction logs as training data rather than just dashboards, and to design RAG around retrieval patterns, chunking and guardrails instead of endless prompt tweaks.

The most useful outcome for me is that I now have a vocabulary and set of patterns I can use with both engineers and product. It has already helped me debug a few “why is this ranked at the top” issues more systematically, rethink how we evaluate retrieval quality in our RAG pipelines, and plan a more realistic roadmap for hybrid search and learning to rank instead of chasing the latest model tweet.

I would recommend this course to anyone who is responsible for search or recommendations in production, especially if you are being asked to “add RAG” on top. It is equally useful for ML and data folks who sit close to logs and want more leverage from them, and for tech leads who need a shared language with their search or platform teams.

lnkd.in/eEFbSG4x

After six months of intensive AI upskilling and building RAG systems, I thought I had a decent handle on retrieval . Then I took the course AI-Powered Search from Maven , and realized how much I'd been missing. Trey Grainger and Doug Turnbull go far beyond the "download embeddings from Hugging Face and hope for the best" approach. They systematically dismantle the naive assumption that hybrid search (BM25 + cosine similarity) is "good enough." As Trey put it in the semantic query understanding session: most people just throw embeddings and keywords at the search engine and hope it comes up with the right thing. This course is about challenging that paradigm.

I really enjoyed the AI-Powered Search course by Trey Grainger and Doug Turnbull.

What stood out to me was the breadth and depth of the content:

- It covers a wide spectrum — from low hanging fruits like signal boosting to state-of-the-art approaches such as vector search, RAG, and late interaction models
- You get the rare opportunity to ask questions directly to some of the top experts in the search field
- The course includes hands-on notebooks that practically demonstrate the concepts instead of just talking about them
- High-quality guest talks that add real-world perspectives and depth

The combination of strong theory, practical examples, and direct access to experts makes this course especially valuable if you’re building or improving real search systems.

I’d highly recommend it to anyone working on search, relevance, or discovery — especially engineers who want to bridge classical IR with modern AI-based approaches.

👉 Course link: lnkd.in/dA6AXZVr

Just wrapped AI-Powered Search by @treygrainger & @softwaredoug—finally get why throwing embeddings at search isn't enough. Pairs perfectly with Cheat at Search. Highly recommend. maven.com/search-school/a...

You get theoretical knowledge 3 times a week plus an additional weekly sessions for your real-world questions. In addition, you get and can do hands-on coding examples without much system setup. Trey and Doug have a lot of experience and deep domain understanding and take you through the last decade of search development. It's a great course and the guest speakers were a great addition, too.

This was a particularly interesting course as I learned a lot of techniques and methodologies related to information retrieval, the part I liked the most is late interaction models and semantic IDs. I still have to revisit hype-encoders to check if it can beat the performance of late interaction models.

The course opened my eyes to the many ways search can be improved. Interesting topics, superb delivery and great guest speakers throughout. I highly recommend it to anyone looking to enhance a product with modern AI-based search techniques.

Extremely Glad to attend a deep dive into agentic search and AI-powered search techniques with Doug Turnbull and Trey Grainger. As an Systems Integerator and prior experience with Large Scale Infrastructure It was crucial to understand how to scale the existing large scale infrastructure for agentic enterprise with respect to bottlenecks caused by massive agentic search expoentital traffic that pounds on the production echo system, what is the fine balance that needs to be get employed by leveraging agentic search models offered by www.sid.ai/ (thanks to Max Rumpf) for a powerful session on the power of agentic search model and how can they be used to empower overall agentic systems life cycle and eliminate bottlenecks by smartely integerating them into the existing production infrastructure. I plan to use these techniques to solve interesting problems with research enthusiasm. I highly recommend the community partner with these industry experts if they want to understand how the new paradigm of search systems works in general, as well as how to empower it by subletting some of that burden with AI models designed specifically to optimize the infrastructure to support exponential agentic search traffic growth. One of the ways you can do it is to attend their courses lnkd.in/gvpxu56p AI-Powered Search

Solid overview of search approaches, from traditional methods to newer innovations. The concepts were well-explained and easy to follow. The external speakers were particularly valuable, bringing different perspectives and practical insights to the discussion. Filipa MARCH-2026 Data Scientist · OLX

I took this course as a software engineer working on search retrieval systems. Bag of documents techniques, wormhole vectors, and search personalisation were all directly relevant to my day-to-day work. The course is practical rather than academic. Would recommend to any engineer working on search.

Tray and Doug shared many keen insights in AI Search. I great class for anyone looking to advance their understanding of Search principles in a meaningful way.

I recently enrolled in the AI-Powered Search course (linked below) to build a more structured, big-picture understanding of modern search systems — beyond the specific problems I work on day to day. It delivered on that goal.
The course is well-organized and spans a broad set of techniques, supported by concrete implementation examples. I especially found the sections on query understanding and intent modelling highly relevant to my work. The coverage of hybrid search — combining sparse and dense retrieval — also helped connect ideas I’ve come across in practice but hadn’t fully mapped out end-to-end.
Overall, I would recommend this course (and the instructors’ books) to anyone working on search or retrieval systems who’s looking to strengthen their foundations while gaining a clearer view of where the field is heading. Trey Grainger Doug Turnbull lnkd.in/gRpWWh-R

The course covers a lot of ground in 5 weeks, and I learned a lot. The weekly office hours provided a wonderful opportunity to pick the brains of Trey and Doug on specific topics relevant to the problems I was tackling at my workplace. And to top it all, the instructors are super-nice people. Highly recommend the course.

Just finished the AI-Powered Search course by @treygrainger & @softwaredoug — hands down the best course on search and retrieval. Highly recommend this one ! @SenjaHQ senja.io/p/ai-powered-sea...

Just completed AI-Powered Search Modern Retrieval for Humans and Agents taught by Trey Grainger and Doug Turnbull. I found this course to be exactly what was missing from other AI engineering courses I’ve taken. Extremely thorough topic coverage (Agentic search, rerankers, hybrid search, Query understanding to name a few), and a great mix of teaching conceptual understanding and providing hands on practice. This course allows you to understand not just the what, but the why behind the process. If you're building AI systems and feel like you're missing some foundational pieces, this course will fill those gaps.

lnkd.in/gV298gvg

The definitive way to stay current with modern retrieval. Period. I've taken both iterations of this course, and it remains the single best investment I've made in my professional development as a search engineer. The landscape of AI-powered search and RAG is shifting so fast that staying ahead of the curve usually means piecing together scattered blog posts and pre-print papers. Trey and Doug have done the hard work of curation, weaving together the essential mental models and the latest techniques into a coherent, actionable framework. The only place where saying "We need to talk about your late interaction" is a compliment. Verdict: 10/10 would compute cosine similarity with this group again.

I found this course to be exactly what was missing from other AI engineering courses I’ve taken. Extremely thorough topic coverage (Agentic search, rerankers, hybrid search, Query understanding to name a few), and a great mix of teaching conceptual understanding and providing hands on practice. This course allows you to understand not just the what, but the why behind the process. If you're building AI systems and feel like you're missing some foundational pieces, this course will fill those gaps.

@aiPoweredSearch is a quality playbook of search techniques. The query understanding sessions are incredible! Having experts like @treygrainger and @softwaredoug answering your specific questions, as well as other course attendees was mega valuable. lnkd.in/eHFpyAD2

I came to the AI search domain completely new, but walked away with a good grounding and appreciation of what it takes to build good search. The content and sessions are very well structured, plenty of labs to get your teeth into and help is always on hand from Trey and Doug.

One of the best course on search and retrieval. Covers the full spectrum from BM25 to semantic query understanding all with hands on labs. If you're building search, or RAG systems don't skip this one. rushit MARCH-2026 Enterprise Architect · TTU

This is a great course even for someone who has experience with search for years but wants to learn the latest search technologies. It's a good mix of materials covering the theory that is in a level sufficient to understand how to use them in practice.

The latest and greatest from the fast-changing field of search and information retrieval. The guests are bringing the latest developments and technologies from their industrial experience, not academic papers. I enjoyed the course very much

I just wanted to share my experiences on the AI-powered search course by Trey Grainger and Doug Turnbull

It's a quality playbook of techniques accompanied with real code labs to implement the concepts. I found the query understanding sessions particularly engaging, which is highly relevant to my current professional work. Having experts like Trey and Doug answering your specific questions, as well as other course attendees was mega valuable.

lnkd.in/eHFpyAD2

My team works heavily on search-related problems, so I took the 𝐀𝐈-𝐏𝐨𝐰𝐞𝐫𝐞𝐝 𝐒𝐞𝐚𝐫𝐜𝐡 course by 𝐓𝐫𝐞𝐲 𝐆𝐫𝐚𝐢𝐧𝐠𝐞𝐫 and 𝐃𝐨𝐮𝐠 𝐓𝐮𝐫𝐧𝐛𝐮𝐥𝐥 to get a more structured, big-picture understanding of how modern search actually works, beyond the specific projects and techniques I deal with day to day. It more than delivered. Search is a fascinating domain that sits right at the intersection of product, machine learning, and AI, and this course honors that complexity. It doesn't treat search as a narrow engineering problem; it gives you the full environment. One unexpected but genuinely valuable win: the community. You end up connecting with a diverse group of practitioners, engineers from companies like Uber, Airbnb, Yelp, and DoorDash, all working through similar challenges. Hearing their experiences and approaches was as enriching as the course content itself. The syllabus is wide-ranging and stays current. Highlights that stood out for me: 🔍 Query understanding and intent modeling — covering query classification, sense disambiguation, and semantic query parsing using both lexical and LLM-based strategies ⚡ Hybrid search — the treatment of mixing sparse and dense retrieval (BM25 + vectors) finally gave me a coherent end-to-end picture of something I'd encountered in practice but never fully mapped out 🤖 Agentic search and RAG — the course dedicates serious attention to optimizing retrieval for LLMs and agents, including chunking strategies, adaptive queries, and guardrails 📊 Signals and reflected intelligence — leveraging behavioral click-stream data to improve ranking models, personalization via collaborative filtering, and click models for automatic judgment generation 🚀 Emerging techniques — things like Wormhole Vectors, SPLADE, MUVERA, and late interaction models that you won't find covered this clearly anywhere else ⚙️ Production optimization — ANN, quantization, reranking, semantic caching, and Learning to Rank (LambdaMART, cross-encoders) If you're serious about search, I'd also strongly recommend picking up the book the instructors co-authored, AI-Powered Search (Manning) — which is essentially the holy grail reference text for this domain. The course and book complement each other well, with only about 30% overlap, so both are worth your time. Whether you're an AI engineer building RAG pipelines, a search practitioner trying to improve relevance, or a tech lead wanting a coherent framework for where the frontier is — this course gives you exactly that. 🔗 Course: lnkd.in/gfGk398Q 📖 Book: lnkd.in/gTzmunq3

Great course for anyone who wants to enter the world of AI applied to search, learning different types of algorithms and their applicability in real-world contexts.

Really solid course—materials were clear and easy to go through. The pre-filled labs made it simple to get hands-on practice without wasting time on setup. Definitely a useful experience.

Just wrapped AI-Powered Search class on Maven (link below) with Doug Turnbull and Trey Grainger. Cannot recommend the course highly enough to both get a lay of the land, and upskill. Thanks Doug and Trey!

lnkd.in/ekrcURTx

As my team works heavily on search-related problems, I took the AI-Powered Search course (linked below) to get a more structured, big-picture understanding of how modern search actually works — beyond the specific projects and techniques I deal with day to day. It delivered on that.

The course is well-organized and covers a wide range of techniques with concrete implementation examples. The sections on query understanding and intent modeling resonated strongly with my daily work, and the treatment of hybrid search — mixing sparse and dense retrieval — clicked well with approaches I'd encountered in practice but never had fully mapped out end-to-end.

I'd recommend this course (and the instructors' books) to any person working with search or retrieval systems who wants a coherent foundation and a clear view of where the frontier is.

lnkd.in/gbf7bggM

Trey Grainger Doug Turnbull AI-Powered Search

I recently completed the AI-Powered Search: Modern Retrieval for Humans & Agents course by Trey Grainger and Doug Turnbull on Maven.

What stood out most was how the course builds a structured framework for thinking about retrieval and relevance, two aspects that are often underestimated but critical for successful AI systems.

This course helped me connect many dots:
• how RAG systems really work beyond simple embeddings
• how to systematically improve search relevance instead of relying on trial and error
• how user intent, context, and domain knowledge influence retrieval quality
• when to use lexical, semantic, hybrid, and re-ranking approaches
• why retrieval is often the biggest lever for improving AI applications

I would highly recommend this course to:
• AI Engineers working with RAG systems
• Solution Architects designing AI-powered products
• Anyone who wants to go deeper than prompt engineering and understand how modern AI search really works

If you are serious about building high-quality AI applications, understanding retrieval is a game changer.
👉 The next cohort starts on July 1st; I highly encourage you to join. Link in the comments.

I recently completed the AI Powered Search course by Trey Grainger and Doug Turnbull, and wanted to share my appreciation.

As someone leading teams at the intersection of AI/ML, Search, and Data, I found this work exceptional, not just for its technical depth, but for the clarity it brings to first principles. The framing of relevance as a holistic system, the interplay of retrieval, ranking, and representation along with the nuanced treatment of personalization, behavioral signals, and guardrails, deeply resonated.

What stood out most is how seamlessly you connect these foundations to modern paradigms from hybrid search and LTR to RAG and emerging agentic patterns, while staying grounded in real-world tradeoffs.

I’m walking away with sharper mental models that will meaningfully shape how I build and lead AI-powered search systems.

If you’re building in this space, I highly recommend their Maven course and their companion book AI Powered Search.

lnkd.in/gwjm7Hwf

#AISearch #MachineLearning #SearchRelevance #GenerativeAI

A course packed with knowledge, Can recommend it to anybody who want to go beyond lexical search.

Just wrapped up the Maven Course: AI-Powered Search - Modern Retrieval for Humans & Agents, and wow—it's a game-changer that left me buzzing with excitement and clarity!​I dove in initially for the product/search angle, but this course delivered extreme value for technical deep-dives and business insights, empowering owners to max out search in development. The content is razor-sharp up-to-date, unpacking complex solutions like personalized behavioral embeddings, agentic search paradigms, and ML ranking with crystal-clear intuition that ties every piece together—no more black-box confusion.​What blew me away? The perfect learning intensity, permanent access to recordings/notebooks/slides, and an amazing community of top-tier lecturers/peers —plus live 'office hours' for diving into any question, even off-scope. It's not just theory; it's hands-on mastery bridging demos to production systems that actually crush relevance for humans and agents.​If you're a dev, founder, or search-curious pro, this is your edge in the AI retrieval revolution—join!

A course that covered search topics extensively, from traditional to modern methods. The amount of work that went into creating it and the ground it covers in about a month is phenomenal.

Trey and Doug have put together and delivered an excellent course that includes both breadth and depth on the topic of AI Powered Search. I appreciated how they brought some dense topics to life through examples and interactive labs. There were plenty of opportunities to ask questions throughout the lectures and they offered weekly office hours to go in depth on topics of interest to the group. I recommend this course to any search practitioners that are looking to evolve their search products with leading edge techniques. I especially recommend this course to Search Product Managers who are new to the AI-Powered Search landscape that need a grounding in the technology.

Can't wait to start signal boosting before diving deeper into LTR.

’m relatively new to the topic of search, and this course gave me both a solid overview of the common technologies and a deep dive into important concepts and tools. I would definitely recommend it.

Broad overview of current techniques from leading experts. The course is especially valuable if you already have a good foundation in the area and bring your own questions to the speakers and cohort.

This is a useful course to help develop intuition for the ongoing interaction of AI with information retrieval - traditional search techniques being helpful for many cases today is a useful baseline, and yet quick wins from AI short-circuiting long dev -> eval cycles need way more attention than they get.

The course is very relevant to current industry problems in Search. I have dealt with the issues discussed in this course but lacked a direction. With this course I feel informed and confident of making suggestions to improve Search experience at my current company

I took this course because, even after doing search work for a couple of years (mostly self-taught), I kept running into the same problem: I could research concepts online, but the pieces didn’t always click into a production-grade mental model. This class was exactly what I needed. Doug and Trey bridge the gap between theory and real systems in a way that’s hard to get from blog posts and docs, especially the practical “how” behind query understanding, making hybrid retrieval behave predictably, and turning behavioral signals into an iteration loop that actually improves ranking. The biggest value for me was the experience transfer: the nuance, the “why,” and the decision-making that comes from having built and tuned search at scale. The live format and Q&A made a huge difference, you can bring your real problems and get grounded guidance. The hands-on labs were also excellent: a reusable set of notebooks and techniques I can apply to my own stack. If you’re building search/RAG systems and feel like you’re missing the foundations (or the production intuition), this course fills that gap fast.

I took this course because we hit a ceiling. We built a RAG-based search, and for a while, we were making progress. But at some point, we were just rearranging deck chairs, getting marginal improvements while the big problems weren't moving. Latency issues, gnarly quality gaps, the things that actually mattered. I realized I needed a deeper understanding of search and retrieval to make real gains. I had previously read Doug and Trey's AI-Powered Search book and decided to take their class. I'm also a fan of Doug's blog. What I found was a much deeper exploration of the topics in the book. They cover a lot of ground in the book, but the nuances come out in the class discussions and Q&A. Doug and Trey have worked in search and information retrieval for over a decade. When anyone in the class asked a question, they could pull from a variety of experiences to give a genuinely useful answer, not a theoretical one. You find yourself leveling up just from the conversation. Before taking the class, I felt like I had exhausted my options. Now I see there's a lot more room for improvement. They gave me new tools, but they also gave me perspective. Since they've worked on high-scale, top-tier search systems, they also set expectations for what excellence actually looks like. So you know what you're aiming for, not just what to try next. If you want to get good in this area, I can't think of a better class. I don't know of anyone else with this level of expertise who's actually teaching it.

Awesome course with most up to date methods on search Robert NOV 2025 BI developer · veterinary information network

Just finished the @aiPoweredSearch Maven course delivered by @treygrainger and @softwaredoug), and if you're in the search space, I highly recommend taking it: Next cohort starts in March: aipoweredsearch.com/live-... See my full review at www.linkedin.com/posts/wr...

Just wrapped up the AI-Powered Search course by @TreyGrainger & @SoftwareDoug. Great mix of IR basics + modern AI search. Learned a lot about hybrid retrieval, LTR, semantic query understanding & RAG. Highly recommend. @aiPoweredSearch 🔗 aipoweredsearch.com/live-...

Just finished AI-Powered Search course by @treygrainger & @softwaredoug. It was a transformative deep-dive into modern search. This course moves beyond basic vector search to cover the production-grade techniques necessary for robust RAG and Agentic systems. From Learning to Rank and user signals to advanced agentic workflows, the hands-on, platform-agnostic curriculum provides the tools to solve real-world retrieval problems. With expert guest lectures and a focus on self-improving systems, it offers the perfect blend of theory and code. Highly recommended for any engineer responsible for retrieval quality—it’s exactly the training I wish I had when I started. Link to the upcoming cohort:

I finished the AI Powered Search course taught by @treygrainger and @softwaredoug . Highly informative and covers a lot of techniques helpful for both search and recsys practitioners. They have opened up a new cohort in March! aipoweredsearch.com/live-...

AI-Powered Search: Modern Retrieval for Humans & Agents course with @treygrainger and @softwaredoug excellent deep dive into modern search and RAG systems. Covered semantic query understanding, and agentic search with practical code notebooks. link: lnkd.in/gdmEpeZr

I am happy to announce that I have completed the AI-powered Search: Modern Retrieval for Humans & Agents course taught by Doug Turnbull and Trey Grainger.

Having worked through their fantastic book, AI-Powered Search, I wanted to advance my understanding of certain topics in a live course setting. Beyond standard topics like Query Understanding, RAG, Reflected Intelligence, and LTR, I really appreciated the guest speakers who covered advanced concepts like mixing sparse & dense representations (miniCOIL) and creating semistructured embeddings.
The experience was excellent: from the community page for peer discussions to the weekly office hours for answering pending questions. I highly recommend this for Engineers in the Search/Information Retrieval space.
#VectorSearch #SearchAI #InformationRetrieval #RAG #VectorSearch #LearningToRank #NLP #Embeddings

lnkd.in/eKkkNKXg

Just completed the AI-Powered Search: Modern Retrieval for Humans & Agents course with Trey Grainger
and Doug Turnbull excellent deep dive into modern search and RAG systems.
Covered LTR, vector search optimization, click models, semantic query understanding, and agentic search with practical code notebooks. The guest lectures from practitioners added real-world context you won't find elsewhere.
Highly relevant for anyone building search, recommendations, or LLM-powered applications at scale. Course link: lnkd.in/gdmEpeZr

I recently completed the AI-Powered Search course by Trey Grainger and Doug Turnbull, and it turned out to be a very solid learning experience.
Some of the advanced topics were a stretch for me, but the high-level exposure was genuinely helpful. The instructors explained concepts like behavioral signals, hybrid retrieval, learning to rank, and semantic query understanding in a way that made them easier to grasp, even for someone still strengthening foundational search skills.
What I found especially useful was how many ideas were directly applicable. I’ve already started thinking about how to bring some of these approaches into our product particularly around improving scoring, retrieval quality, and exploring RAG style workflows. The course also helped me build a foundation of how classical IR and newer AI-driven methods fit together.
I’d recommend this course for:
Search engineers looking to modernize their retrieval stack
Backend/ML engineers exploring vector search, LTR, or RAG
Anyone working on search systems who want both conceptual clarity and practical direction
🔗 Course link: lnkd.in/epMe3YEU
Thanks to Trey, Doug, and the AI-Powered Search team for putting together a well-structured and thoughtful program.

The AI-powered search course taught by Trey Grainger and Doug Turnbull is fantastic. The course arms you with a set of tools that you can use to tackle a variety of search problems. It complements the book AI-Powered Search co-authored by Trey,Doug, and 🟢 Max Irwin. The course covers semantic query understanding, Learning to Rank (LTR), agentic search, and many more topics. They also have hand-on labs that demonstrate the many of the techniques taught in the course.

If you are from a recsys background, this course can add value to you too. I find that some of the search techniques taught in the course (like Wormhole vectors) can be utilized to improve recommender systems.

Consider taking the course if you are looking to improve your search systems - lnkd.in/ebUDYwW4

Just finished AI-Powered Search course by Trey Grainger
& Doug Turnbull

It was a transformative deep-dive into modern search. This course moves beyond basic vector search to cover the production-grade techniques necessary for robust RAG and Agentic systems. From Learning to Rank and user signals to advanced agentic workflows, the hands-on, platform-agnostic curriculum provides the tools to solve real-world retrieval problems.

With expert guest lectures and a focus on self-improving systems, it offers the perfect blend of theory and code.

Highly recommended for any engineer responsible for retrieval quality—it’s exactly the training I wish I had when I started.

Link to the upcoming cohort:

lnkd.in/ex7aK_Gn

Having great educational resources is not always a prerequisite for building great software. At OpenText, our document management and data processing products are mature and cutting edge: stable, flexible, and feature-rich.

But delivery is the final crucial step. For professional services, the learning curve can be steep, especially with such a long product history. I felt this strongly when I joined OpenText 18 months ago.

The developer documentation is excellent – but I am not a developer. So I started looking for external resources that would help me understand the product better and speak the same language as our customers.
That’s how I discovered AI-Powered Search by Trey Grainger, Doug Turnbull, and Max Irwin (2025). Later, I learned that Trey and Doug were launching a live online course to go deeper into modern search.
What I quickly realized is that “search” means much more than indexing files or web pages. We covered ranking with behavioral signals, hybrid lexical/vector search, RAG-oriented retrieval, query understanding, click models, and search performance optimization – all grounded in clear mental models for information retrieval.

The format mixed short lectures, Q&A sessions, group discussions, and hands-on labs in well-designed Jupyter notebooks. Over six weeks, four evenings a week were busy but never boring. I came away with a clearer picture of the field and more confidence for upcoming customer conversations.

If you work with search – whether as an engineer, architect, product manager, or in sales – I can genuinely recommend this course. A new cohort is planned for March 2026, and it’s a great way to build a solid foundation without feeling left behind by more seasoned specialists.

A link to the course: lnkd.in/es25ZAjJ

And discover these pages to find out more about the authors:
lnkd.in/euhiEmS7
lnkd.in/eRassENy
lnkd.in/eNuM7sBH