I built this chart to stress-test AI narratives by separating two ideas that are often conflated: structural alignment with long-horizon AI value creation, and expectation tension, how much of that story appears to be reflected in current pricing.
X-axis (M.I.N.D.) represents structural alignment using the Last Economy framing: Material leverage, Intelligence leverage, Network effects, and Diversification. Roughly speaking: Material captures control over scarce physical inputs, Intelligence reflects leverage over computation and models, Network captures ecosystem and data flywheels, and Diversification reflects exposure across multiple AI value paths.
Scores are synthesized (0.0-1.0) per public entity after a skills / assets / capabilities analysis and a review of analyst research, using an LLM as a structured aggregation tool rather than an oracle. M.I.N.D. = M * I * N * D, which intentionally penalizes missing legs. (Log scale.)
Y-axis (Valuation Tension) is a rough proxy for expectation saturation. It compares relative long-term opportunity (2030 horizon) to price position, defined as the current price's location within its 52-week low / high range. I'm using this for interpretability rather than precision, and treating it as a secondary signal rather than a valuation model. (Log scale.)
This chart is meant to act as a simple stress-test: a single view that surfaces where AI narratives feel structurally grounded versus where they appear primarily expectation-driven.
I'm using the quadrants as a loose taxonomy:
- Top-right: high alignment, high tension (strong positioning, high expectations)
- Bottom-right: high alignment, low tension (structural beneficiaries with muted expectations)
- Top-left: low alignment, high tension (crowded narratives, weaker grounding)
- Bottom-left: low alignment, low tension (out-of-favor or structurally weaker)
I'm less interested in prediction than in whether this kind of framing helps make sense of uncertainty, especially for people who already follow AI closely but feel the limits of narrative-driven or price-action-led discussion.
Feedback I'd value: where the M.I.N.D. framework feels wrong or incomplete, whether multiplication is the right way to combine dimensions, and where this framing would clearly fail or mislead.