Research & Engineering
Building reliable infrastructure for AI agents - from prototype to production.
What I'm building
LLM agents need infrastructure that is both efficient (handling long contexts, optimizing memory, reducing redundancy) and secure (enforcing least-privilege access, resisting adversarial manipulation). I build systems at this intersection - from research prototypes to shipped products. Memory management, context optimization, authorization, and observability.
Focus areas
Context Efficiency & Reliability
"How do we make LLM outputs reliable and deterministic through better context management?"
Building systems that clean, deduplicate, and optimize context before it reaches the model. Deterministic algorithms over probabilistic heuristics.
Least-Privilege Tool Authorization
"How do we enforce fine-grained, capability-based authorization for LLM agents accessing external tools?"
Applying Google Zanzibar-style authorization models to agent-tool interactions, with dynamic capability tokens and audit logging.
Adversarial Robustness in Tool Environments
"How can agents maintain safety under prompt injection, tool poisoning, and adversarial tool responses?"
Building observability and tracing infrastructure to detect and mitigate attacks on agent tool-use pipelines.
Products & Prototypes
Distill
RAG context deduplication - deterministic, auditable, fast
AuthorizationAgentic Authorization
ReBAC patterns for autonomous AI agents with OpenFGA
Context EngineeringContextLab
LLM context engineering toolkit - analyze, compress, visualize
Memory SystemsTokenVM
KV-cache virtual memory with page-based eviction
SecuritySentinel AI
Security scanning with LLM-powered triage
Agent SystemsAgentflow
Agent orchestration with capability-based security
SecurityA2AS
Agent-to-agent security protocol
ObservabilityLLMTraceFX
Distributed tracing for LLM inference pipelines
DevSecOpsactionsec
GitHub Actions security analyzer
AuthorizationOpenFGA
Google Zanzibar-style authorization (maintainer)
Working with me
I bring a combination of systems engineering experience and research curiosity. Here's what I offer as a collaborator:
- Shipping: from research prototype to production - built Distill, contribute to OpenFGA as maintainer
- Systems depth: production infrastructure at Ona (formerly Gitpod)
- Open source: OpenFGA maintainer (CNCF), GitHub1s maintainer
- Cross-domain: security, distributed systems, ML infrastructure
- Communication: technical writing on Dev.to and Medium