Grounded in the work,
not the hype cycle.
Reach Works is one person's practice — built on a decade and a half of making content authoritative, structured and found, plus current research into how AI models decide what to cite.
Getting cited by AI isn't a growth hack. It's the problem newsrooms have always had — being authoritative, structured and legible to whatever decides what people see — pointed at a new reader that happens to be a machine.
I'm Leandro Oliva. For fifteen years I've worked on exactly the levers answer-engine optimization depends on: editorial authority and trust, structured and machine-readable content, and audience distribution. I held accuracy and standards at The Wall Street Journal and The Intercept, built the review systems that let subject-matter experts publish cleanly at an agency, and turned dense institutional research into briefs at Brookings.
Now I do it deliberately for machines. I'm completing a Research Master's in Cultural Data & AI at the University of Amsterdam, I co-authored an empirical audit of how models answer, and I build the source-verification and claim-extraction tooling that the structuring work runs on. Reach Works is where that lands as a service — not a template I bought last week.
Three things AEO needs. I've done all three for years.
Editorial authority & trust
A decade holding accuracy, sourcing and standards across two national newsrooms. E-E-A-T — experience, expertise, authoritativeness, trust — isn't a checklist to me; it was the daily job.
Structured, legible content
Making dense material machine- and human-legible — from Brookings policy briefs to a claim-extraction pipeline that turns arguments into records a model can quote.
Primary research on models
A UvA research master's and published studies on how models answer, cite and represent — so the advice tracks how the systems actually behave, not how a blog post guesses they do.
Fifteen years of getting content found and trusted
Reverse chronological. The relevance to AEO is in the right-hand read, not a stretch.
Independent writer & analyst — AI political economy
Published analysis of AI pricing and procurement, compute markets, publisher licensing and the AI scraper economy — including a working paper on the three-layer enclosure of the open web. This is the exact terrain AEO sits on: who gets to read, and cite, the web.
Editorial Director / Director of AI Strategy — JLH Strategies (contract)
Built the review standards and workflows that let subject-matter experts and outside writers produce publishable work without central rewriting, and ran a B2B health-technology thought-leadership programme end to end — category position, message guidance, executive publishing and placed op-eds.
Director of Digital Operations — The Intercept
Owned the editorial agenda and digital presence across web, newsletter and social; edited dense technical investigations for accuracy and framing; translated editorial requirements into product and engineering decisions across content and platform.
Audience Engagement Editor — The Wall Street Journal
Wrote and edited to strict accuracy and style standards, ran multi-variable A/B testing on headlines and copy against engagement and conversion data, and produced the analytics the newsroom worked from. Optimizing what gets found — the discipline AEO now points at machines.
Communications Specialist — The Brookings Institution
Synthesised dense institutional research into structured briefs and background material for senior decision-makers across four research programmes.
Research Master's, Cultural Data & AI — University of Amsterdam
A research degree, not a taught course — the designated route to doctoral study, focused on data, media and machine systems.
Research & standards on how AI uses content
The parts most directly load-bearing for this work — with sources, because that's rather the point.
- [1] Co-researcherAn empirical audit of AI answer behaviour — 84 structured prompts across Gemini and Claude, classifying task-fulfilment into five outcome modes. Published in Appification in the Age of AI (ASI Sprint Report No. 3), App Studies Initiative, 2026.
- [2] ContributorContent Telemetry — an open standard for reporting how AI systems use content; authored a provenance-schema contribution adopted into the v0.1 specification.
- [3] AuthorThe Tautology of Recursivity: AI, "Context Rot," and the Society of the Spectacle — a peer-reviewed conference paper presented in the Artificial Intelligence panel at EUPOP 2026.
- [4] Independent analysisOngoing published work on the AI scraper economy, AI procurement and compute markets, and the EU Code of Practice on AI-generated content transparency — verified against the AI Act text and primary sources.
The machinery, not just the slide deck
The structuring and verification work Reach Works sells runs on tooling I designed and directed.
Source-verifying content OS
Verifies every source a draft cites against Crossref and OpenAlex, checks that each source actually supports its claim, and decomposes drafts into facts, quotations and argument beats. The engine behind claim-level structuring.
Local, read-only content tool
Open-source. Scores a writer's feed against their topics and drafts tailored angles — runs locally with the user's own model, reads only, collects nothing, never posts. The privacy stance the service inherits.
Retrieval & evaluation pipeline
Open-source retrieval-and-evaluation pipeline over EU legislation (EU AI Act, GDPR), with a Ragas-evaluated ablation of chunking strategies, hybrid retrieval and cross-encoder reranking. How I know what "machine-legible" actually measures.
Find the work: leandrooliva.com · github.com/landomo · linkedin.com/in/leandrooliva
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