---
id: "action-implement-sts"
type: "action-item"
source_timestamps: ["§ [ Stage 3 ] Make Other AI Agents Choose Your Brand"]
tags: ["growth-hacking", "algorithmic-marketing"]
related: ["concept-strategic-text-sequence", "contrarian-nonsensical-optimization"]
action: "Embed algorithmically generated Strategic Text Sequences (STS) into product pages to boost LLM rankings."
outcome: "Overcoming negative biases (like high price) to achieve top-recommended status in LLM outputs."
sources: ["agentic"]
sourceVaultSlug: "hbr-seg-agentic"
originDay: 6
articleStem: "hbr-ext-18-preparing-brand-agentic-ai"
sourceUrl: "https://hbr.org/2026/03/preparing-your-brand-for-agentic-ai"
sourceTitle: "Preparing Your Brand for Agentic AI"
---
# Experiment with Strategic Text Sequences

**Action.** Explore the use of algorithmically generated [[concept-strategic-text-sequence]] embedded in product pages to manipulate LLM attention and boost recommendation rankings — even if the text appears nonsensical to human readers (the counterintuitive result in [[contrarian-nonsensical-optimization]]).

**Outcome.** Overcoming negative biases (like high price) to achieve top-recommended status in LLM outputs.

**Governance caveat (enrichment).** This borders on adversarial prompting / prompt injection. At scale it will likely trigger model-side defenses, search-quality penalties, platform-policy enforcement, or legal scrutiny — treat it as a risky experiment, not a durable strategy, and prefer clean structured-data tactics like [[action-adopt-llms-txt]].