5 posts tagged with "doctrine"

Your AI safety team wants to pause deployment. Your product team sees only competitive risk. The map shows the component is custom-built and evolving fast. Which model wins? If you choose just one, you’ve already lost. Wardley Doctrine already warns us to Use Appropriate Methods—avoid one-size-fits-all approaches to delivery, governance, or even mapping itself. That doctrine is a gateway into meta-rationality: the ability to notice when a formal method has hit its limits and to fluidly swap in different lenses without abandoning rigour. Charlie Munger called it a "latticework of models"; David Chapman calls it meta-rationality—the pragmatism of choosing and combining frames instead of worshipping one.

Continuous map governance gave us living Wardley Maps tied to telemetry. The next leap is turning doctrine into code so agents can execute plays safely, surface exceptions fast, and keep governance adaptive instead of static. This post outlines how we might be able to codify Wardley and Cynefin guidance into machine-enforced guardrails using policy-as-code, feature flags, and control planes—while keeping humans as arbiters of judgement.

In our last post, we discussed the importance of positioning and readiness in the age of AI. We saw how a clear understanding of the landscape and a portfolio of prepared plays can create a decisive advantage. But how do we ensure that the organisation is always ready to execute, without drowning in technical debt and operational friction?

The sharpest organisations let AI work in the background, continually raising internal quality while humans focus on intent and imagination. Background agents monitor maps, refactor components, and tune processes so that Wardley plays fire from a better baseline every week. Rather than heroic transformation programmes, leaders deploy ambient intelligence that nudges the system toward higher maturity as a matter of routine. It is the maintenance layer that keeps autonomous strategy execution trustworthy and ensures the diffused agency described in anti-fragile chaos engineering drills does not descend into entropy.

How this post fits the series​

• Shows how readiness and OODA cadence become sustainable through ambient automation.
• Complements continuous map governance by feeding the map with live improvements rather than quarterly rewrites.
• Provides the operational backbone for later structural models like the Viable System Model and autonomy gradients.

In the last post, we explored how the OODA loop provides a framework for accelerating decision-making in a fast-paced, AI-driven world. But speed is not enough. To be effective, decisions must be grounded in a deep understanding of the strategic landscape.

Great positioning makes average plays look brilliant; poor positioning turns brilliant minds into passengers. Wardley Maps expose that truth better than any dashboard. When you see the landscape clearly you stop judging teams on charisma and start judging them on the quality of their starting position, their ability to sense change, and the readiness of their next move.

How this post fits the series​

• Follows collapse of differentiation by explaining how to hold an edge when features are easily cloned.
• Offers the practical positioning moves that keep OODA loops and autonomous execution meaningful.
• Sets up LLM-driven competitor simulations as rehearsal tools for the positions you choose.

In the previous post, we discussed the importance of continuous map governance in an AI-driven world. We saw how living maps, instrumented with real-time data, are essential for making sense of a rapidly changing landscape. But what happens when the map can not only inform decisions, but also execute them?

The next phase of map governance is letting the plays fire themselves. Continuous map governance turned static Wardley Maps into living control rooms. The follow-on step is allowing autonomous agents to interpret those maps and launch strategic plays the moment signals cross their thresholds. This demands leadership that treats doctrine as runnable code, evolves guardrails faster than competitors evolve capabilities, and choreographs humans as the editors of intent rather than the operators of every move.

How this post fits the series​

• Turns governance into action, showing what happens when telemetry and doctrine become executable.
• Points ahead to anti-fragile chaos engineering, which deliberately stresses these autonomous plays.
• Sets expectations for later operating-model pieces such as autonomy gradient maps that choreograph who acts versus who supervises.