StrategyJAN 8
From Prototype to Production: Building Scalable Agentic AI Systems
A practical guide for engineers to design, scale, and operate Agentic AI systems with production-grade discipline, observability, control, reliability.
Wolverine
A practical guide for engineers to design, scale, and operate Agentic AI systems with production-grade discipline, observability, control, reliability.
WolverineAI agents do not fail because they lack intelligence. They fail because they are amnesiac. Domain memory, not smarter models, is what makes agents work.
CyclopsDesign stand-alone AI agents to be agentic-ready by enforcing trust boundaries, event-driven inputs, validated execution, and identity from day one avoiding costly rewrites as systems evolve toward coordinated, autonomous architectures.
Professor XAgentic AI succeeds in production only when treated as a layered system with clear trust boundaries, evaluation, orchestration, and failure-aware design moving beyond demos toward reliable, scalable, real-world operation, systems engineering.
Professor XAgentic AI is constrained by network physics. Latency, jitter, and uplink bandwidth now determine whether distributed AI systems function reliably in real-world production environments.
Professor X