PERSONAL RESEARCH NOTES
AgenticXYZ
A coordinate system for Agentic AI.
Building agent-based knowledge collaboration and self-improving agent systems.
More than a name
A coordinate system.
My initials.
A research framework.
A research framework—not a benchmarked maturity scale. The operators are metaphors, not measured performance claims.
X · Crossing
Agents with People.
Humans and agents shape intent, act, verify, and preserve provenance together.
Human in the Loop
The role of the Harness
Agents should enter environments, take action, and observe consequences.
The Harness connects intent, tools, permissions, memory, state, and outcomes. That is how a model begins to participate in the world.
Y · Yours
Agents for People.
A persistent, user-owned personal agent. You define its goals, permissions, and intervention thresholds; it keeps context and acts over time.
Human on the Loop
Z · Zero
Agents improving Agents.
Z explores evidence-carrying, gated, and reversible self-improvement—not unconstrained self-modification.
Human beyond the Execution Loop
Research direction · not a deployed capability claim
The open learning loop
Models now work inside the world.Most of what they experience never becomes verified knowledge.
Agents act, fail, recover, and get corrected. Too often, those outcomes remain logs instead of returning through a structured learning path.
The evolving digital knowledge center
Experience becomes knowledge only when it carries evidence.
Knowledge moves at three speeds
The model is the capability core—not the only place knowledge lives.
Model parameters
Stable, general, transferable capabilities.
Skills
Explicit, editable, versioned procedural knowledge.
Memory
Private, fresh, and task-specific context.
Four systems · one knowledge lifecycle
From an observed method to a validated capability.
Agentic Software
Discovers methods through human-agent interaction.
Knowledge-based PR
Packages intent, conditions, evidence, and counterexamples.
Agentic Runtime
Tests transfer across tools, schemas, and permissions.
Agentic Internet
Connects capabilities with provenance and authorization.
Post-training candidate
Promotion is considered only after transfer is verified.
Promotion is earned
Zero routine intervention. Never zero human authority.
Skills do not update model weights by themselves.
Private and time-sensitive knowledge stays external by default.
Internalization requires held-out gains without the original Skill.
Latest from AgenticXYZ
Follow the work as it evolves.
Essays, paper notes, experiments, and moments across Agentic AI.
AgenticXYZ Prototype 1: A Knowledge Collaboration Layer for People and Agents
AgenticXYZ: Controlled Intelligence, Superintelligent Organizations, and the Fourth Industrial Revolution
GLM-5.3 Released
Z.ai released GLM-5.3, a post-training-driven update focused on stronger coding, longer agent tasks, and newly observed cybersecurity capabilities.
Browse Moments →