Original Frameworks
These are the lenses I use to see problems that others often miss.
The Judgment Boundary
When to automate vs. when to advise
This model helps to determine the appropriate level of AI involvement by assessing the stakes and complexity of a given task. It prevents the common error of automating high-stakes decisions or under-utilizing AI for low-stakes tasks.
Trust Compounding
Building authority in YMYL contexts
In high-stakes environments, trust compounds slower, but deeper, than scale. You can automate a thousand decisions in a day, but if one fails catastrophically, trust evaporates.
This model outlines the four key principles for building systems where trust accumulates over time.
Transparency
Show the reasoning, not just the output. The "black box" is the enemy of trust.
Calibration
Be honest about the model's confidence. "I'm 60% sure" is more valuable than a false absolute.
Boundaries
Explicitly define limits. "I don't know" is a valid and necessary answer.
Human Override
Ensure a human expert can always intervene. The system serves the human, not the reverse.