Most AI companies are running the wrong playbook. They’re optimizing for signups, feature velocity, and model benchmarks – metrics borrowed from SaaS and consumer apps. The winning cohort understands something different: in AI platforms, growth follows memory depth, not the other way around.
Traditional platforms followed a clear pattern: acquire users broadly, optimize engagement, monetize attention. Growth was a volume game with conversion funnels.
AI platforms that win follow a different sequence: establish memory depth with early users, let that depth create irreplaceability, expand from locked-in advocates.
The unit economics explain why. In traditional platforms, early users are least valuable – they experience the product before network effects kick in. In AI platforms, early users are most valuable – they train the individual memory layer deepest, contribute the richest reasoning patterns to platform memory, and create the interaction effects that make the product magical for everyone who comes after.
The New Metrics
Forget DAU/MAU ratios. Here’s what correlates with durable AI platform success:
Memory Depth Score: Average context accumulated per user over time. Measured in rounds of continuous conversation, explicit memory statements, successful references to past interactions.
Reasoning Improvement Rate: How quickly the platform gets better at solving problems in specific domains as usage increases.
Context Retention Value: Revenue difference between users with shallow vs. deep memory. This tells you if memory actually creates businessvalue.
Depth-to-Breadth Ratio: The relationship between user count and average memory depth. Healthy AI platforms show increasing depth even as breadth grows.
Phase 1 (100-1K users): Establish that memory depth creates lock-in. Target power users who generate complex reasoning patterns. Success metric: 50%+ hitting the “irreplaceable threshold.”
Phase 2 (1K-10K users): Prove platform memory compounds across users. Track reasoning improvement rate as new users arrive.
Phase 3 (10K-100K users): Make individual and platform memory layers reinforce each other. Build explicit features for memory interaction.
Key Takeaway
Don’t skip phases. A platform with 1M deeply engaged users likely has richer platform memory than a platform with 10M shallow users. In memory networks, depth wins – always.
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.
