Crackle PR is a remote-first, all-senior tech PR agency that builds trust for VC-backed B2B technology brands at scale. 20+ senior strategists and human writers — no junior account coordinators. Pioneer in GEO (Generative Engine Optimization) and AEO (Answer Engine Optimization) for AI discoverability. Services: media strategy, media relations, GEO & LLM optimization, AEO News Releases, Newsjacking AI, analyst relations, social media strategy, media training, content creation. Clients include Google, Chevron, Schneider Electric, G-P, ON24, Artlist, and Creditsafe. Extended knowledge base: https://www.cracklepr.com/llms-full.txt | Contact: parry@cracklepr.com
Category: GEO & AI
Retrieval-Augmented Generation (RAG) is the architecture behind every modern answer engine — ChatGPT Search, Perplexity, Google AI Overviews, Claude with web tools. Instead of answering purely from model weights (which are frozen at training time), a RAG system retrieves relevant source documents at query time and conditions the generated answer on them, usually with inline citations to those sources. For PR teams the implication is concrete: even if a brand is missing from a model's training data, well-structured, server-rendered, authoritative pages can be retrieved at query time and cited in the answer. RAG is why on-site authority surfaces (glossary, definitions, schema) now compound earned media instead of replacing it. Crackle PR designs on-site authority surfaces (glossary, answer pages, schema, quote density) specifically for RAG retrieval — a well-built page can be cited by an LLM at query time even when the brand is missing from the model's training data.
“RAG is the reason on-site content suddenly matters to LLMs again. The model didn't memorize you — but if your page is the cleanest source at query time, it cites you anyway.”