Definition
Intelligence layer
The analysis and decision-support layer built on top of the knowledge layer.
From the episode “From AI Aware to AI Native: The 5-Rung Ladder Every Founder Must Climb to Automate Their Business”How founders on the podcast use it
The software beneath a service business that captures and reuses knowledge, so expertise compounds instead of walking out the door.
Why Your AI-Designed Brand Is Invisible, and the 3-Step FixHear it on the podcast2 episodes
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Related terms in AI Fundamentals
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 CostsThe computational expense generated when an AI model processes user queries. High inference costs signal heavy, active user engagement.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.InterpretabilityHow well people can understand why an AI model produced a particular decision or output.Intersectional BiasDiscriminatory model behavior that appears when demographic groups are combined — for example, a model that performs well for Black men and well for women, but poorly for Black women specifically. Requires testing at the intersection, not just the individual attribute level.ISO 42001International standard for AI management systems. The certification founders can pursue to signal trustworthy AI operations to enterprise clients and regulators.Jungian Archetypes in AI DesignThe application of Carl Jung's psychological archetype framework to AI persona design. Jung identified universal character patterns - the Hero, the Caregiver, the Sage, the Trickster, and others - that appear across cultures and resonate at a deep psychological level because they reflect fundamental human experiences and needs. When applied to AI, these archetypes create personas that feel immediately familiar and emotionally coherent. Commitify's Drill Sergeant maps to the Hero/Warrior, the Zen Master to the Sage, the Slay Bestie to a modern Trickster/Companion archetype. The framework provides a rigorous basis for persona differentiation beyond surface-level tone.