Claim
Models improve faster than products can diffuse the new capabilities. You ship onboarding for Opus 4, run tests, get learnings, ship a new flow — and Opus 4.5 is out. Your learnings are stale. The structural challenge for AI growth is not "use more AI"; it is "build artifacts that auto-update when the model changes."
Mechanism
Traditional growth experiments assume the underlying product is stable across the test window. AI products break that assumption every few months when a new capability wave lands. Hard-coded copy, scripted onboarding, and feature scaffolds built around current-model limits become net-negative the moment the limit lifts. The compounding asset is anything that adapts: configurable prompts, capability-detection branches, copy generated at runtime against the current model.
Conditions
Holds when:
- The product depends on a frontier model whose capability is improving on a known cadence.
- The team can build adaptive scaffolding without over-investing in plumbing that will itself be obsoleted.
Fails when:
- The product depends on a stable model (open-source, on-prem). Capability overhang is not your problem.
- The team uses "models will improve" as an excuse to defer real product work today.
Evidence
"Models are getting better so fast that the real challenge is on the product side — diffusing those benefits to people. You ship onboarding for Opus 4. By the time you've learned, Opus 4.5 is out and your learnings are obsolete."
— Amole Naik on Lenny's Podcast, 2026-04-27
Signals
- Onboarding copy is generated, not hand-crafted, against the current model's behavior.
- Feature flags include "capability detection" so the product unlocks affordances when the model gets better.
- Test windows are kept short (weeks, not quarters) so learnings still apply when shipped.
Counter-evidence
Sherwin Wu's "the models will eat your scaffolding" cuts the same way. Both are warnings against over-investment. The opposite failure mode is also common: teams use capability overhang as an excuse to defer hard product work indefinitely. Calibration matters; the rule is "build adaptive, not no scaffolding."
Cross-references
- When a new model lands, re-read the system prompt and remove crutches — Cat Wu's cleanup half of this same pattern
- Plan in seasons keyed to secular changes, not 6-month roadmaps — the planning cadence implication