Independent AI architecture practice. Production multi-agent orchestration, autonomous AI agents, and consumer AI with layered guardrails. IEEE service in AI readiness for critical infrastructure.
Licensed P.E. · IEEE PES SC-5 (AI) Co-Chair · 22 U.S. Patents (9 pending; 2 filed 2026 in AI Agent Safety) · CISSP · CCSP
LangGraph pipelines coordinating concurrent agents across vendors. Cross-vendor adversarial verification catches hallucinations that single-model review misses.
Deterministic first-contact architectures, audit-queue gating on AI-proposed actions, state-machine escalation triggers, and operator-takeover flags. Safe-by-design.
AI architecture review boards, NIST AI RMF, ISO/IEC 42001, EU AI Act readiness. Authority anchored in IEEE-SA standards work on grid readiness for data center deployment.
Two-layer guardrail systems, tiered model routing, adversarial test coverage across prompt injection, jailbreak, and homoglyph evasion. Privacy-constrained observability.
Publicly verifiable at github.com/martymcenroe.
A live venue where a player runs a data center at the grid interface for a simulated day — buying power, working a battery, curtailing load, answering events as they arrive — and is scored against a certified optimal line. The thesis is that where players consistently bend a technical rule is evidence about what the rule should say, which makes this an instrument for discovering standards needs rather than a simulator. Scenarios are data rather than code, so a new one is a compiled pack instead of a deployment. Each pack carries an optimum solved offline by mixed-integer linear programming and replayed through the same engine that scores play, so a published target is engine-verified rather than asserted. Six scenarios are live at palaestra.thrivetech.ai; the architecture and the interface every player and every agent speaks are published for inspection.
Five-stage LangGraph StateGraph pipeline (Triage→Design→Spec→TDD→PR) coordinating concurrent Claude and Gemini agents. Cross-vendor adversarial verification — Claude generates, Gemini reviews. Five-layer evaluation framework: execution-based verification, AST structural analysis, cross-model review, stagnation detection, longitudinal learning. Python, LangGraph 1.0, DynamoDB, GitHub Actions.
Seven-stage handler pipeline for consumer-facing AI with independent short-circuiting at each stage. Two-layer guardrails: deterministic denylist plus semantic LLM classifier with five-category taxonomy. Tiered routing — Haiku as default classifier, Opus invoked only as verifier when Haiku flags candidate prompt-injection. Privacy-constrained observability. AWS Lambda, Bedrock, DynamoDB, CloudFront, Chrome and Firefox extensions.
AI governance study platform for IAPP AIGP preparation. Built on the same orchestration and guardrail patterns as the production platforms.
Methodology and tooling for AI-assisted technical authorship at institutional scale. Forces substantive human contribution at every step. Anchored in USPTO Inventorship Guidance and Pannu v. Iolab. PolyForm Noncommercial 1.0.0.
Chrome extension for extracting LLM conversations to structured JSON. Preserves message ordering, role, code blocks, and tool-use markers across ChatGPT, Claude, and Gemini.
Active applied research on agent-context permission bits as an alternative to the "agent inherits user permissions" model that creates excessive blast radius for autonomous agents. Manifest specification, capability authorization design, filesystem-level prototype.
Independent practice. Engaged via C2C contract.
recruit@martymcenroe.ai