Worldview Agents: The Next Frontier of Agentic AI
World models (and their agents) require continual learning
Knowledge is for models, Execution is for context
A rose (agent) by any other name would smell as sweet
Recursive Self-Improvement Is Not Code Generation
When the learner improves the learner, it becomes recursion
From Copilot to Cognitive OS: The Future Agentic Harness
The Harness vs Model Debate - opportunity
The Three Modes of Continuous Learning Agents
From Collaboration to Automation - Agentic AI
Cost × Speed × Accuracy × Scale: Rethinking Economics of AI
From Stateless AI to Compounding Intelligence
Why Knowledge worker AI Agents can’t Learn?
Continuous Learning and Collaborative Workflows
Why the Future of AI Agents Is Owned, Not Accessed?
Access Isn’t Ownership: The Real Democratization of Agents
Why AI Coworkers (Agents) Must Actively Learn?
AI Coworkers (i.e. Agents) that learn is essential.
Emergence: From Gradient Descent to Symbols, Reason, Free Will
Will agents need Free Will to execute complex tasks?
Hilbert’s Sixth Problem and the Stabilization of Learning
The Ghost in the Machine: Hilbert’s Unfinished Quest
Symbolic Systems from Continuity: Active Learning within LLMs
Symbolic reasoning emerges when a system learns to regulate itself
In Transformers Inference, “Memory” Has No "Weight"
Stuck Between Groundhog Day and 50 First Dates
Breaking the Monolith: Multi-Model Systems Make Better Agents
Multi-model architectures are reshaping how AI agents are built.
The Haunted Model: When Memory Comes Back to Bite
When memory decays, the mind invents ghosts.