Existing Framework

AI system that takes actions to achieve goals, often across tools.

Designing processes from scratch around AI capability.

Teams built around AI from day one vs. teams adding it to existing workflows.

Attention is the most contested resource in modern work.

We judge frequency by how easily examples come to mind.

A conversational discipline where participants suspend assumptions and inquire collectively into meaning.

AI bolted onto existing workflows to look forward-leaning.

We overweight outcomes that are certain relative to merely probable ones.

We remember our past choices as better than they were.

The relationship between inputs and outputs changes.

How much input the model can process at once.

Underlying data distribution changes over time.

Incompetent employees are promoted to management to limit their workflow damage.

Vector representation of content for similarity and search.

Evaluation suites that no longer reflect real-world conditions.

Systematic testing of model quality, safety, and capability.

Neurological state of peak performance and engagement.

Recurring aid flows can entrench recipient governments and crowd out domestic capacity-building.

Believing past events were obviously predictable once we know how they ended.

Brain structure central to memory formation, spatial navigation, and learning.

Models learning from examples in the prompt.

Without active design, incentives decay toward gameable proxies.

Turning raw input (books, talks, conversations) into proprietary frameworks by re-explaining through your own lens.

We climb from raw data to action through selection, meaning-making, and assumption — usually invisibly.

How much delay the user experience tolerates.

When all you have is a hammer, everything looks like a nail.

Relying solely on metrics that are easily quantified while ignoring what matters.

We treat money differently depending on which bucket it's in.

Familiarity breeds approval.

Knowing what you know — and how confidently you know it.

Treating the measure as the goal it was meant to approximate.

Train a smaller model to imitate a larger one.

Performance degradation as real-world data shifts.

Multiple specialized agents coordinating on tasks.

Where the model runs shapes privacy, latency, cost, and capability.

We judge experiences by their peak moment and how they ended.

Insurer approval workflows delay or deny care to lower medical-loss ratios.

Money flows after ecosystems collapse, not to protect them in advance.

Overweighting whatever just happened.

Generate based on retrieved documents, not just trained weights.

We remember the past as better than it was.

A developmental model of human value systems (vMemes) emerging in response to life conditions.

Stocks are accumulations; flows are rates of change that affect them.

Unlimited anonymous donations flow through 501(c)(4) shells into elections.

Generated training data that mimics real data.

Models calling external functions and APIs.

Database optimized for high-dimensional similarity search.