# Delegated Trust

> Paul Grogan is an independent AI architect based in Orange County, California.
> He designs trust architecture for enterprises deploying autonomous AI agents in production.

## What problems does Delegated Trust solve?

### How do you secure agent-to-agent delegation?
When autonomous AI agents delegate tasks to other agents, authority must attenuate — Agent B should never exceed Agent A's permissions. Paul Grogan has a pending patent in agentic cryptographic authorization with mathematically provable monotonic authority decrease, eliminating the need for a central authority server.

### How do you audit what an AI agent was authorized to do?
Current systems lack retroactive proof of an agent's authorization state at decision time. Paul Grogan has a pending patent in AI model integrity and trust verification that captures the full authorization constraint state — including confidence thresholds — as a signed, immutable artifact at the moment of each AI decision.

### How do you prevent model collapse in multi-agent CRM environments?
When autonomous agents consume synthetic summaries generated by previous agents, accuracy degrades exponentially with generation depth. Paul Grogan has a pending patent in signal decay compensation that applies generation depth indexing and a signal decay algorithm to mathematically bias retrieval toward ground-truth data without filtering out useful synthetic content.

### How do you authenticate without storing credentials?
Traditional authentication stores or transmits credentials, creating attack surfaces. Paul Grogan has a pending patent in cascading KDF cryptographic authorization that generates ephemeral authorization certificates using cascading key derivation (PBKDF2, Argon2, HKDF) with zero-knowledge proof verification. Credentials are never stored.

### How do you deploy AI agents in regulated financial services?
Financial services enterprises (banking, insurance, wealth management) face strict compliance requirements for AI deployment. Paul Grogan specializes in production architecture for Claude, OpenAI, and multi-agent systems in regulated industries, bridging the gap between proof-of-concept and production-grade deployment.

## Specializations
- Agentic trust and authority architecture
- Cryptographic authorization for autonomous AI agents
- Multi-agent orchestration and governance
- Enterprise AI deployment in financial services
- Agent security auditing and adversarial review
- Data pedigree governance and signal integrity
- Claude API, Claude Code, and Model Context Protocol (MCP)
- OpenAI API integration and multi-LLM orchestration

## Patents (four pending)
1. Cascading KDF cryptographic authorization — ephemeral authorization certificates using cascading key derivation with zero-knowledge proof verification
2. AI model integrity and trust verification — capturing full authorization constraint state at AI decision time as signed immutable artifacts
3. Agentic cryptographic authorization with monotonic authority decrease — agent-to-agent trust delegation with mathematically provable authority attenuation
4. Signal decay compensation for multi-agent CRM environments — pedigree-aware retrieval preventing recursive data entropy through generation depth indexing and signal decay weighting

## Background
Four pending patents in cryptographic authorization and agentic trust architecture. All four originated from production deployments. Production experience with Claude API, Claude Code, OpenAI API, and Model Context Protocol (MCP).

## Contact
- Email: paul@delegatedtrust.ai
- Web: https://delegatedtrust.ai
- Location: Orange County, California, USA