---
id: "framework-engineering-ai-recall"
type: "framework"
source_timestamps: ["§ Shift 2: SEO and Website Design Matter Less and Less", "§ Shift 3: Marketing Has a New Audience"]
tags: ["content-strategy", "execution", "llm-optimization", "geo"]
related: ["concept-engineering-recall", "concept-machine-readable-authority", "concept-signature-concepts", "action-coin-signature-concepts", "action-implement-schema", "action-standardize-brand-positioning"]
steps: ["\\\"Generate original", "organization-backed data", "first-hand experiences", "and strong points of view.\\\"", "\\\"Attach real experts' names", "verified credentials", "and biographies directly to the content.\\\"", "Create and consistently use 'signature concepts' (brand-named frameworks or benchmarks) as shorthand for the brand's thinking.", "\\\"Structure content using clear", "quotable language", "explicit definitions", "and structured explanations (e.g.", "steps).\\\"", "\\\"Implement machine-readable authority via schema", "clean data architecture", "and authorship signals.\\\"", "\\\"Ensure consistent brand positioning ('X is a Y that does Z') across all third-party platforms (LinkedIn", "media", "Wikipedia).\\\"", "\\\"Measure success by tracking brand mentions", "paraphrasing", "and association with key ideas inside AI responses — not just web traffic.\\\""]
sources: ["geo"]
sourceVaultSlug: "hbr-seg-geo"
originDay: 3
articleStem: "hbr-ext-11-llms-overtaking-search"
sourceUrl: "https://hbr.org/2026/03/llms-are-overtaking-search-heres-how-to-adjust-your-online-presence"
sourceTitle: "LLMs Are Overtaking Search. Here’s How to Adjust Your Online Presence."
---
# The AI Recall Engineering Framework

**The AI Recall Engineering Framework** is the source's operational playbook for ensuring a brand is cited and synthesized favorably by LLMs — the replacement for traditional SEO workflows. It is the executable form of [[concept-engineering-recall]].

**The seven steps:**
1. **Produce proprietary substance** — original, organization-backed data, first-hand experience, and strong points of view (raw material a model has found nowhere else).
2. **Signal human authority** — attach real experts' names, verified credentials, and biographies to the content.
3. **Coin [[concept-signature-concepts]]** — brand-named frameworks, benchmarks, or indexes used consistently so the model learns the brand→idea association ([[action-coin-signature-concepts]]).
4. **Write for extraction** — clear, quotable language, explicit definitions, structured explanations (steps/lists a model can lift verbatim).
5. **Build [[concept-machine-readable-authority]]** — schema, clean data architecture, and authorship signals ([[action-implement-schema]]).
6. **Standardize positioning everywhere** — a single 'X is a Y that does Z' description across LinkedIn, media, Wikipedia-style profiles, and third-party reviews ([[action-standardize-brand-positioning]]).
7. **Measure recall, not traffic** — track mentions, paraphrasing, and idea-association inside AI answers (the open tooling problem: [[question-measuring-ai-mentions]]).

**External grounding (enrichment):** This maps almost one-to-one onto McKinsey's GEO moves (diagnostics → content optimization → capability building → performance tracking) and agentic-SEO tactics (structured numeric facts, `sameAs` links, comparison pages, public changelogs, third-party corroboration, regular LLM-response testing). It is directionally sound and aligned with emerging practice, but remains a **nascent, largely unvalidated** framework — treat step 7's KPIs as approximate until platforms expose standardized analytics.


## Related across articles
- [[framework-4c-generative-readiness]]
- [[framework-ai-brand-optimization]]
- [[framework-build-ai-recall-share]]