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RCT Protocol

The FDIA Equation

F = (D^I) × A — Mathematical foundation for intent-centric AI. Future equals Data raised to the power of Intent, multiplied by the Architect.

F=(DI)×A

Future = (DataIntent) × Architect

F
Future
Output
D
Data
Base (foundation)
I
Intent
Exponent (amplifier)
A
Architect
Multiplier (human-in-loop)

Component Deep Dive

FFutureF = (D^I) × A

The constructed outcome — not a prediction, but a result consciously designed and built through the entire FDIA pipeline.

In the equation: F is the output — the Future that emerges when Data is amplified by Intent and guided by the Architect.
DDataD = Base

The knowledge base — vault of experiments, code, documentation, real-time signals, and historical context.

In the equation: D is the base of the exponential — the foundation that Intent amplifies. More quality data = exponentially better outcomes.
IIntentI = Exponent

The explicit human instruction and specification — the understood purpose behind every request.

In the equation: I is the exponent — it determines how powerfully Data is amplified. Weak intent = linear results. Strong intent = exponential results.
AArchitectA = Multiplier

The Human-in-the-Loop decision maker — the Architect who ensures ethical, strategic AI governance.

In the equation: A is the multiplier — the Architect's judgment scales the entire output. Without human oversight (A→0), the system produces nothing meaningful.

Three Key Principles

Data Without Intent Is Potential

High-quality data with weak intent (I→0) produces mediocre results — (D^0) = 1 regardless of D's quality. Intent unlocks data's value.

Intent Is an Exponential Lever

Intent acts as an exponent on Data. High intent with good data = explosive growth in outcome quality. This is why clear specifications matter.

The Architect Is Non-Negotiable

When A = 0, the entire equation collapses to 0. Human oversight isn't optional — it's the final gate that gives AI outputs their meaning and accountability.

Real-World Examples

Scenario
D
I
A
F / Grade
Enterprise Chatbot
Strong intent amplification
85%
90%
75%
67 / A
Perfect Data, Weak Intent
Good data doesn't overcome vague intent
95%
40%
80%
73 / A
No Architect (A=0)
Zero oversight = zero trusted output
99%
99%
0%
0 / F
Medical Diagnosis AI
High rigor across all dimensions
98%
92%
95%
90 / A+
Early Stage Startup
All dimensions need improvement
50%
60%
55%
36 / C

Note: F = round(Math.pow(D/100, I/100) × (A/100) × 100). When A=0, output=0 regardless of D and I.

Try It Yourself

Interactive FDIA Demo

Adjust Data, Intent, and Architect sliders to see real-time FDIA scores. Load preset scenarios and get AI recommendations.

Open FDIA DemoRCT-7 Mental Model