Notes on governed AI.
Notes on AI governance, event modeling, CQRS and outcome-driven context — from the team building Model My Context.
Design vs. Describe (Part 2): The Trap of Structural Specs vs. The Chaos of Prompting
Design vs. Describe (Part 1): The Illusion of "Design-First" and the Rise of Prompt Bias
The Hidden Killer of AI Agents Isn't Hallucination — It's the Bill
The 2026 AI cost crisis is an architecture problem. Why naive agents burn tokens on context rot — and how slice-based, outcome-driven modeling cuts ~11,500 tokens per turn down to ~950.
AI is Like a Bucking Horse. It Needs a Harness.
Why prompt engineering and AI-native orchestration fail at enterprise scale — and how context architecture takes the reins.
Governing AI, not scripting it
Why we model the outcome a process must reach — not the steps an agent should take — and what that buys you when the agent meets the real world.
The API Price War Is Over — Now You Have to Govern the Swarm
Post-Google I/O 2026, multi-agent networks are the standard and raw intelligence is a commodity. Why context rot is the real bottleneck — and how outcome-driven context modeling tames the swarm.
What Does AI Governance Actually Mean?
Moving beyond 'Prompt & Hope' in the era of the Headless Internet — why real governance is a deterministic, execution-level standard, not a policy doc or a perimeter filter.
The Visionary's Dilemma: When Infinite Potential Meets Human Limits
Agentic AI removed the friction between idea and execution — and introduced a hidden tax: 'God Complex' burnout. The signs you're redlining, and how to sustain the spark.