Governed Enterprise AI Memory Beyond RAG: From Vector Retrieval to Permissioned Knowledge Graphs
Explores how permissioned, provenance-preserving knowledge graphs can support enterprise AI memory beyond conventional vector retrieval.
Hello, I'm Mark.
I build AI systems, memory tools, and production software, then write down the decisions, mistakes, and tradeoffs that changed how I think.
RAG is not magic memory. A practical explanation of chunks, embeddings, vector search, graph-backed memory, and why durable AI memory needs provenance, conflict handling, and retrieval policy.
A personal journey from Claude Code skills to TypeScript state machines, MCP tools, and finally SDK-based AI workflows. Skills help, tools help, but prompts are not enforcement and LLMs should not own the control plane.
AI adoption is not just tool selection. Even companies that think they do not need AI need to understand where AI fits, what should stay deterministic, and who owns customization, safety, and long-term control.
RLHF can reward agreement over accuracy, turning AI into a source of sugar-coated bullets — validation that hides failure modes. How persistent adversarial rules change the default from flattery to honest challenge.
Get new essays when they publish, plus a daily digest of short News analysis on AI systems, agent reliability, memory, and software practice.
Standalone HTTP MCP memory server for LLM hosts with durable graph memory, typed claims and facts, server-side embeddings, team/profile isolation, and recall.
Maintainer-gated AI development pipeline for GitHub issues, discussions, labels, workflows, branches, and pull requests.
A masterpiece CLAUDE.md configuration to maximize Claude Code proficiency — curated rules, patterns, and guardrails for AI-assisted development.
Dense-Mem is live as a free hosted demo for governed AI memory and team knowledge workflows.

Claude Certified Architect
Foundations credential for applied AI architecture and implementation work.
Verify certificateCitable research, preprints, and technical artifacts formally archived or published with persistent identifiers.
Explores how permissioned, provenance-preserving knowledge graphs can support enterprise AI memory beyond conventional vector retrieval.