Note from the Founder - David Kershaw
Published August 22, 2025
AI is part of my work every day. I use it to brainstorm, to prototype, and to vibe code with Claude.
AI speeds up the same problems already common in no-code and automation. Code sprawl, documentation drift, fragile systems, and unowned debt now show up in hours instead of months. Without governance, teams can't keep up.
The Four-Zone Governance Topology defines how systems hold together across platforms and time. Each zone addresses a critical governance layer:
- Zone A – Execution: What runs (scenarios, triggers, data handling, logic)
- Zone B – Control: What changes (deployment, rollback, access, failure containment)
- Zone C – Signal: What's visible (logging, documentation, traceability)
- Zone D – Stewardship: What lasts (ownership, cost, long-term hygiene)
AI fits into this model, only with sharper edges. Seven risks stand out, each breaking specific governance zones:
The Risks and Where They Break Governance
1. Surface Area (Primarily Zone A + D) AI inflates codebases, documentation, and workflow branches. Dead code and redundant artifacts pile up unless pruned. A single change can generate dozens of new files or scripts that no one maintains. Execution becomes unwieldy while Stewardship loses track of what exists.
2. Opacity (Primarily Zone C)
Outputs are hard to explain or trace. Decision paths disappear and accountability goes with them. When no one can describe how an answer was reached, issues linger because no one knows where to start. Signal breaks down—you can't debug what you can't see.
3. Drift (Spans Zone A + C) Models, code, and documentation slip away from intent. Misalignment comes from inside the system — weak feedback loops and unsynchronized changes. Features look finished but behave differently than the original process required. Execution diverges while Signal fails to catch it.
4. Velocity (Primarily Zone B) Change frequency overwhelms review. Controls turn into empty process. Teams rubber-stamp approvals because the pace is too high to check meaningfully. Control zone processes collapse under volume.
5. Fragility (Primarily Zone A) AI-generated code often runs, but it breaks at the edges. Exceptions and special cases aren't handled. A script that works in test fails in production as soon as inputs vary. Execution appears solid but lacks robustness.
6. Ownership (Primarily Zone D) Outputs arrive with no steward. Without ownership, quality, cost, and hygiene decline. An integration may run for weeks before anyone notices it has been failing silently. Stewardship gaps create systemic rot.
7. Landscape Drift (Spans all zones) The external environment shifts. Tools, APIs, and platforms change too quickly for static processes or documentation to keep up. Even untouched systems rot because the ground beneath them moves — a connector suddenly deprecates, and the process built on it collapses. All zones become vulnerable when foundations shift.
The Governance Response
These are everyday realities when deploying AI at speed. The Four-Zone Topology provides the structure to address them:
Zone A (Execution) needs enhanced testing and validation patterns to catch AI fragility before production.
Zone B (Control) requires new review processes designed for high-velocity, high-opacity changes.
Zone C (Signal) must evolve beyond traditional logging to trace AI decision paths and catch drift.
Zone D (Stewardship) needs clear ownership models for AI-generated assets and automated hygiene processes.
AI increases both value and chaos. To keep the value, the chaos has to be governed across all four zones simultaneously. The principle holds: Structure Before Speed.
— David Kershaw - Founder, NoCodeEngineering
Have you seen AI deployments drift out of control?