Robert Galasso
7 essays

Writing

Each of these covers something I have built or run, and they are written so someone can follow the method and do it themselves.

  1. Generative engine optimization research: what holds up in practice

    A working read of the 2025-2026 arXiv research on generative engine optimization: the critical survey, the measurement papers, the brand-stature data, and what a practitioner should change.

  2. Lessons from building an agency's internal AI platform solo

    Build vs buy, fail-closed AI design, numbers that admit uncertainty, and the adoption fight: what shipping an agency's internal AI platform solo taught me.

  3. How to Get a Google Knowledge Panel When You Share Your Name

    How to get a Google Knowledge Panel when someone famous shares your name: the entity SEO playbook I'm running, from disambiguatingDescription to Wikidata.

  4. Generative Engine Optimization: how brands get cited by AI

    GEO is how brands earn citations in ChatGPT, Gemini, Perplexity, and AI Overviews. The on-page patterns and entity signals that work, plus how I measure it.

  5. How to measure AI visibility using confidence intervals

    How to measure AI visibility in ChatGPT and other LLMs: repeat sampling, Wilson confidence intervals, and alerts that fire only when intervals separate.

  6. Technical SEO for AI search: what still matters in 2026

    What technical SEO means now that LLMs crawl your site: server-rendered HTML, entity signals, citation-ready structure, and some llms.txt skepticism.

  7. How to Train Your Own FLUX Checkpoint: Lessons from 12 Versions

    What it takes to finetune FLUX.1 on your own GPUs: dataset curation, captioning, eval suites, and versioning from 12 shipped Nepotism releases.