For merchants, the strategic choice in the agentic commerce era is binary: become so strong that AI agents must route around you (Brand Override Strategy), or optimize so thoroughly that you win on algorithmic preference (Technical Excellence Strategy). The middle – moderately known with moderate technical implementation – loses to competitors who commit to either extreme.
Brand Override Strategy: Become so strong that consumers specify you by name. When users say “buy me Nike shoes” rather than “buy me running shoes,” the AI agent has no choice but to route to Nike. Brand becomes the override command that bypasses algorithmic selection. This requires massive brand investment but creates defensibility that technical optimization cannot replicate.
Technical Excellence Strategy: Optimize so thoroughly for agent selection that you win on algorithmic preference regardless of brand awareness. Data quality, schema completeness, pricing competitiveness, inventory accuracy, fulfillment speed – every variable that agents use to select merchants. This requires operational excellence but creates advantages that brand advertising cannot match.
Framework Analysis
The middle position fails because AI agents optimize for clear signals. A moderately known brand with moderate technical implementation provides neither strong brand override commands nor strong algorithmic signals. Agents route to extremes – the brand users specify or the merchant that scores highest on selection criteria.
This is similar to how Amazon Marketplace rewards either brands that customers search for specifically or merchants who optimize titles, pricing, and fulfillment to win the Buy Box. The middle tier of “decent brand, decent execution” gets squeezed.
Strategic Implications
For established brands, the path is clear: double down on brand investment so that consumers specify you by name in agent interactions. Nike, Apple, Glossier – brands that users request directly are insulated from algorithmic competition.
For emerging merchants, technical excellence offers a viable path. Optimize for the Agentic Commerce Stack: perfect product feeds, complete schema markup, competitive pricing, fast fulfillment, high ratings. Win on the metrics that agents use to select.
The Deeper Pattern
Barbell dynamics apply to merchant strategy as well as hardware pricing. Extreme positions – maximum brand or maximum technical optimization – succeed. Middle positions that commit to neither fail against competitors who choose extremes.
Key Takeaway
Merchants face a binary choice: Brand Override (consumers name you specifically) or Technical Excellence (agents select you algorithmically). The middle loses to competitors who commit to either extreme.
Gennaro is the creator of FourWeekMBA, which reached about four million business people, comprising C-level executives, investors, analysts, product managers, and aspiring digital entrepreneurs in 2022 alone | He is also Director of Sales for a high-tech scaleup in the AI Industry | In 2012, Gennaro earned an International MBA with emphasis on Corporate Finance and Business Strategy.
