Resources
A curated library of books, essays, papers, and tools that shaped how I think about growth systems, discoverability infrastructure, and the AI-search era, annotated with operator commentary, not just bibliography.
Everything here earned its place. If a book is missing, it’s either because I haven’t read it yet, or because reading it didn’t change anything I do.
Some book links are Amazon affiliate links, which means I earn a small commission if you buy through them. It costs you nothing extra, and nothing is on this list because it pays. Every book here is one I have actually read.
If you read nothing else
The five resources that changed how I work. Different categories, different mediums, but every one shifted my operating model.
Dense Passage Retrieval for Open-Domain Question Answering
The paper that showed retrieval works on learned embeddings alone, beating BM25 by 9 to 19 percent. This is the mechanism that ended keyword matching as the whole story.
ColBERT: Late Interaction over BERT
Scoring at token granularity rather than document granularity. This is the technical reason assistants retrieve passages instead of pages, and therefore the reason a section has to make sense on its own.
BEIR: zero-shot evaluation of retrieval models
Eighteen datasets, ten retrieval systems, one uncomfortable finding: BM25 is a hard baseline to beat out of domain. Useful antidote to the assumption that embeddings win everywhere.
ColBERTv2: retrieval via lightweight late interaction
The follow-up that made late interaction affordable, cutting the storage cost six to tenfold. Read after ColBERT if the first one convinced you.
Lost in the Middle: how language models use long contexts
Models attend to the beginning and end of a context window and lose the middle. If your answer is buried in paragraph nine, it may as well not be there.
Pretrained Transformers for Text Ranking: BERT and Beyond
Book-length and worth it. The clearest survey of how neural ranking actually works, written for people who want the mechanism rather than the metaphor.
How LLMs retrieve and cite (Perplexity Engineering blog)
Operator-level writing from the team building the retrieval layer. The closest you’ll get to ground truth.
One Useful Thing (newsletter)
The most consistently useful operator-level writing on practical AI. Subscribe and read every issue.
SEO Systems
Related writing: the internal link graphIntroduction to Information Retrieval
The standard IR textbook, free in full from Stanford. Inverted indexes, BM25, ranking, evaluation. Every argument about how search works either agrees with this book or has to explain why not.
In-depth guide to how Google Search works
Google’s own account of crawling, rendering, indexing and serving, including that it renders JavaScript with a recent Chrome. Settles more arguments than any third-party post.
SEO Mythbusting (YouTube series)
Skip the SEO podcast circuit. Source material from the people who actually build the indexing pipeline.
Google Search Quality Rater Guidelines
The 180-page document that tells you exactly what Google considers quality. Underread by 90% of the SEO industry.
Koray Tu\u011fberk \u00b7 Semantic SEO blog
Dense, sometimes overwhelming, but the deepest thinking on semantic SEO and entity-based ranking I’ve found.
Indexing for Search (paper)
Foundational read on how modern search indexes actually work under the hood.
Operator Practice
Related writing: why audits do not compoundTrustworthy Online Controlled Experiments
Written by the people who ran experimentation at Microsoft, Google, LinkedIn and Amazon. The chapter on why interesting results are usually wrong is worth the whole book. Companion site carries free chapters.
High Output Management
Still the foundational text. Read it once a year, it reveals something new each time.
The Score Takes Care of Itself
On building systems over outcomes. Reframed how I think about team-building inside growth orgs.
Right Kind of Wrong
On experimentation as discipline, not chaos. Useful framework for utility-led prototyping.
Growth Systems
Related writing: the operator’s guide to B2B SEOTraction
The "Bullseye Framework" alone is worth the read. Most distribution thinking still starts here.
Obviously Awesome
Positioning that operators can actually apply. Don’t skip the worksheet at the end.
The Cold Start Problem
Network effects mental models. Essential if your SaaS has any multi-sided dynamics.
Working Backwards
Amazon’s six-pager and PR-FAQ system. I use the PR-FAQ template for every new growth project.
Writing & Distribution
Related writing: which free tool to build firstOn Writing Well
For anyone publishing under their own name. Read once, then again every two years.
Show Your Work
On the discipline of working in public. Shaped how I think about /now pages and operator distribution.
Stratechery
Strategic analysis at a depth no other publication matches. Aggregation Theory alone is worth the subscription.
Know a resource that should be here?
I’m always looking for sharp writing on growth systems, AI-search, and operator practice. If something genuinely changed how you work, I want to read it.