TruthFast — AI Agent Containment & Assurance Reference System
The problem
How can organizations get meaningful benefit from increasingly capable AI agents without simply handing those agents unlimited trust?
What I built
TruthFast is a reference system exploring identity, authorization, containment, artifact integrity, execution boundaries, evidence, and deterministic validation for agentic workflows.
My work centered on problem definition, architecture, specification, AI-agent orchestration, acceptance criteria, runtime evaluation, and repeated adversarial review. Coding agents performed much of the implementation work.
Process
The architecture evolved through multiple generations rather than one-shot implementation.
Design ideas were explored conversationally, progressively formalized into specifications, implemented through coding agents, exercised against real runtime behavior, and challenged through hostile review.
When evidence contradicted the intended architecture, the implementation was repaired, replaced, or redesigned rather than preserved for sunk-cost reasons.
Result
A substantial working reference architecture with repeatable validation and qualified runtime evidence on tested revisions.
TruthFast is intentionally presented as a reference system, not a turnkey enterprise product. A real enterprise deployment would require integration with that organization’s infrastructure, identity systems, operational constraints, and risk model.
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TruthFast — AI Agent Containment & Assurance Reference System The problem How can organizations get meaningful benefit from increasingly capable AI agents wi...
