"Tools for those who would govern uncertainty, not just measure it."
This repository represents the systematic transformation of 90+ production-grade projects into a unified toolkit for emerging technology risk assessment.
| Original Project | Domain | Plundered Pattern | UURF Instrument |
|---|---|---|---|
| Credit Risk Prediction | Finance | Risk scoring with feature engineering | foundry/risk-scorer/ |
| Sales Forecasting | Business | Time-series trend prediction | foundry/forecasting/ |
| Customer Churn Analysis | Marketing | Predictive maintenance triggers | foundry/reliability/ |
| Stock Market Analysis | Finance | Intelligence gathering & caching | core/intelligence/ |
| Supply Chain Optimization | Operations | Systemic dependency mapping | foundry/systems/ |
Key Insight: The mathematics remain; the domain transforms. We kept the battle-tested patterns, but redirected them toward technology risk governance.
instruments/sceptre/- The classification gateway (pure UURF)- Forces categorical thinking before analysis
- Intentional friction as learning mechanism
foundry/risk-scorer/- From credit risk → technology riskfoundry/forecasting/- From sales → risk trendsfoundry/reliability/- From churn → system failurefoundry/systems/- From supply chain → dependency risk
core/intelligence/- Risk data gathering engine- Plundered from stock market analysis patterns
patterns/- Extracted mental models, not codeprotocols/- How to think, integrate, and governdocs/- Strategic context and case studies
These instruments are intentionally frustrating to casual users. They provide structure before convenience, forcing you to learn the UURF taxonomy to use them effectively.
We extract patterns, not code. The credit risk model's feature engineering becomes technology risk scoring. The sales forecast's seasonality becomes risk cyclicality.
We're not building point solutions. We're establishing the cognitive rails on which risk decisions will run for the next decade.
# This will frustrate you initially - that's by design
from instruments.sceptre.classifier import classify_incident
result = classify_incident("AI trading algorithm exploited due to oracle manipulation")
print(result) # You'll need to learn what these categories mean- Study First: Read /docs/strategic-context/MANIFESTO.md
- Learn Taxonomy: Master the categories in instruments/sceptre/
- Request Access: Follow /protocols/access-control/REQUEST_ACCESS_PROTOCOL.md
- Start Small: Integrate one instrument into one workflow
- Think Systemically: Move from incidents to patterns
- Sovereign Codex: Private canonical taxonomy (restricted access)
- Risk-Throne: Public implementation toolkit (this repository)
- LinkedIn: Kione Mjigelo
- Engagement: For substantive dialogue on technology risk infrastructure
We measure adoption by friction overcome, not downloads:
- How long does it take a team to think in UURF categories?
- How much faster do cross-functional teams align?
- How many "that's obvious in retrospect" moments occur?
- How often do teams catch themselves about to use old mental models?
This isn't a portfolio. It's not a startup. It's infrastructure capture.
We're building the tools that will define how emerging technology risks are assessed, discussed, and governed. The patterns are proven—they just needed redirection.
"First we build the tools. Then the tools build the kingdom."
Note: These tools are useless without understanding the underlying taxonomy. Start with The Sceptre. Embrace the friction. Learn the categories. Then the rest will make sense.