Agentic Maturity Model.
Where does your AI sit on the scale from Chaos (Level 1) to Governance (Level 5)?
Most AI Agent startups are operating at Level 1 Maturity. They have brilliant "hero engineers" who stay up late fixing prompts, patching hallucinations, and manually restarting stuck loops.
This is fine for a demo. It is fatal for enterprise adoption.
To be compliant with ISO 42001 and the EU AI Act, you must demonstrate Evidence-Based Management (Level 4). Here is the scale we use to audit your readiness.
Success depends on individual heroics. Processes vary every time. No replayability. "It works on my machine."
Risk: Uninsurable.
Basic evaluations exist. Prompts are versioned in Git. You track failure rates, but fixes are reactive patches.
A shared "Agent Protocol" exists. Deterministic State Machines (like Temporal) are introduced. The "Happy Path" is documented.
This is the Goal. Process performance is quantitatively understood. Real-time drift detection is active. You have a "Stop Button" (Article 14). You can replay any state.
Self-healing agents. Feedback loops are embedded in the culture. The system improves itself without manual intervention.
Process Variance = Liability
In industrial systems, variance is the enemy. If your factory produces a widget differently every time, you have a quality problem. If your AI Agent solves a ticket differently every time, you have a Liability Problem.
Every non-deterministic path is a potential hallucination, security breach, or customer support ticket. The cost of this variance is the "Vibe Coding Tax."
"If you cannot replay the error state deterministically, you do not own the software. You are renting it from probability." — The Governance Manifesto