If you're deploying agents and still manually seeding every workflow, PMF hasn't arrived yet — and the signal, when it comes, will be unmistakable and operational, not anecdotal.
Tren Griffin's guide cuts through the mythology around product-market fit by treating it as a measurable condition rather than a feeling. The core insight is that fit isn't declared, it's revealed — customers pull the product toward use cases the team never fully anticipated, retention becomes the floor not the ceiling, and the organization's real problem shifts from generating demand to not fumbling the demand that already exists. Before fit, the only metric that matters is learning velocity: how fast can you invalidate wrong assumptions?
The agent-native version of Griffin's framework is sharper and more unforgiving. When agents handle the work, fake PMF hides longer — usage numbers look real because automation keeps things running even after a human would have quit. The pull signal still works, but you're watching for customers who expand agent scope without being asked, who complain loudly when an agent is down, who start routing new problems your architecture wasn't designed for. That unsolicited scope creep is the tell. Before that moment, every agent you ship is a learning instrument, not a product.
- Retention is the floor, not the ceiling — if agents aren't being missed when absent, fit hasn't arrived
- before fit, instrument agents for learning speed above all else
- unsolicited expansion of agent scope by customers is the clearest pull signal in an automated stack.
