Definition
Inference Costs
The computational expense generated when an AI model processes user queries. High inference costs signal heavy, active user engagement.
From the episode “Will VC Destroy Your Startup?”How founders on the podcast use it
The compute costs incurred each time an AI model processes a query. High inference costs signal active, ongoing platform usage and are treated by VCs as a proxy for retention and real engagement — not a liability.
Will VC Destroy Your Startup?Hear it on the podcast1 episode
Learn the language of AI-native founders
Every week: the new terms, tools, and workflows founders are using, straight from the podcast.
Related terms in AI Fundamentals
Humane AIAI designed to strengthen human connection and meaning rather than maximize engagement.Hybrid AIDeliberately splitting workloads across frontier models, self-hosted open source models, and fully sealed environments.HyperparameterA setting chosen before training begins, like learning rate or model size, that shapes how a model learns.InferenceWhen a trained model is put to work on new inputs, making predictions or generating answers. It is what happens each time you use an AI product.Inference Engine (AI Context)In the context of Loman.ai, a system that draws contextual inferences from every customer interaction and stores them as a persistent diner profile. Rather than simply transcribing what the caller says, the inference engine captures implicit signals: background noise suggesting children or a social context, dietary patterns suggested by order history, regular timing patterns, and other behavioral cues. These inferences are used to personalize future interactions (surfacing likely orders, suggesting relevant upsells) and will eventually enable personalized outreach. The term distinguishes this layer of contextual reasoning from simple speech transcription or menu lookup - it is the layer that makes the AI agent feel like it knows the customer rather than merely recognizing their phone number.Intelligence boundaryTarun's term for the undefined line between the data you hand a model and the understanding that model derives from it.Intelligence layerThe analysis and decision-support layer built on top of the knowledge layer.InterpretabilityHow well people can understand why an AI model produced a particular decision or output.