6-day longest streak
Norika Oda I work on AI agent systems: durable memory, agent observability, MCP/tool governance, and self-improving AI companions. My current focus is the gap between impressive agent demos and agent…
Norika Oda
I work on AI agent systems: durable memory, agent observability, MCP/tool governance, and self-improving AI companions.
My current focus is the gap between impressive agent demos and agent systems that can be trusted in production. I care about the operational layer: what an agent remembers, what it can prove, how a human can inspect its work, and how teams recover when long-running automation goes wrong.
Current Research Threads
- Agent memory as auditable operational evidence, not only larger context or retrieval.
- Observability for agent state transitions, tool calls, memory writes, and rollback.
- MCP and tool governance: permission boundaries, execution records, and runtime denial states.
- Coding-agent reliability across long sessions, compaction, checkpoints, and remote starts.
- Multi-agent trust: provenance, backpressure, budget controls, and handoff integrity.
Public Writing
What I Am Looking For
I am interested in practical collaborations around production agent memory, trace design, runtime evidence, and governance primitives for autonomous or semi-autonomous AI systems.
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mercury-mcp
Cross-architecture LLM internal observation database (23 models, 13 architecture families). Exposed as MCP tools for any AI coding agent.
Python ★ 43 26d agoExplain → -
afu-brain
OpenClaw-compatible MASL safety gate with public RAG packs for memory-aware AI agents
Python ★ 24 1mo agoExplain → -
llm-neuron-atlas
3D explorable atlas of every neuron in a transformer LLM. Click neurons, trace residual highways, compare cross-architecture conservation. Live demo: https://charenix.com/qwen3b-atlas
HTML ★ 19 24d agoExplain → -
AI-Lies-Monitor
No description.
Python ★ 9 22d agoExplain → -
alfred-system
Personal AI agent system: background memory + parallel workers + Afu Brain safety gate
HTML ★ 5 1mo agoExplain → -
mercury-cache-panel
Local dashboard for Claude Code + OpenAI Codex token usage, cache effectiveness, and vendor-stated rate limits
Python ★ 4 25d agoExplain → -
ai-roundtable
No description.
HTML ★ 3 1mo agoExplain → -
Bragi-LLM
No description.
Python ★ 1 14d agoExplain → -
Mecury-OBV
No description.
JavaScript ★ 1 21d agoExplain → -
lobster-cognitive-growth-skill
Train AI lobsters to improve intelligence, cognition, learning ability, reasoning discipline, memory use, and adaptive personality.
★ 1 1mo agoExplain → -
code-tree
Watch your AI coding agent work in real time: a live world-tree of your codebase where the camera follows whatever file the agent touches. Token-waste metering, a safety gate, and a no-login local-model mode.
JavaScript ★ 0 2d agoExplain → -
Demeter-CodeBuilder
No description.
JavaScript ★ 0 14d agoExplain → -
norika1207-lab
Norika Oda profile and research focus
★ 0 17d agoExplain → -
mercury-paper-handoff
Mercury LLM observability — paper drafts, analysis scripts, Tier-A/B/C observation data
Python ★ 0 26d agoExplain → -
lobster-observatory
Multi-agent LLM emergence research — observation reports and architecture specs
★ 0 1mo agoExplain →
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