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Autonomously Executed Strategy

· 6 min read
Dave Hulbert
Dave Hulbert
Builder and maintainer of Wardley Leadership Strategies

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.

Continuous Map Governance

· 5 min read
Dave Hulbert
Dave Hulbert
Builder and maintainer of Wardley Leadership Strategies

In our last post, we explored how to use the Cynefin framework to navigate the complexities of AI leadership. We saw that in a rapidly changing landscape, leaders need to be able to switch between different modes of decision-making. But to do that effectively, they need a clear and up-to-date picture of the landscape itself.

AI-native leadership depends on maps that move as fast as the agents they command. Traditional strategy cycles assumed that the landscape stayed still long enough for quarterly reviews. Wardley Mapping showed that components evolve, value chains shift, and doctrine must respond. In an era where autonomous agents execute in minutes, leaders must treat their maps as living systems, instrumented with telemetry, guardrails, and feedback loops that keep decisions aligned with reality. Sensemaking frameworks such as Cynefin only reach their potential when the underlying map reflects what the organisation is actually experiencing right now.

How this post fits the series​

Navigating AI Leadership with Cynefin

· 5 min read
Dave Hulbert
Dave Hulbert
Builder and maintainer of Wardley Leadership Strategies

In the previous post, we explored how AI is making it possible for everyone to be a CEO, by lowering the barriers to execution and putting powerful tools in the hands of individuals. This newfound agency creates a more dynamic and unpredictable landscape. To navigate this, leaders need new sense-making tools.

AI leadership needs Cynefin's sensemaking discipline to decide when to experiment, when to codify, and when to get out of the way. Wardley Mapping explains how components evolve along the value chain, but leaders still have to choose the right play for the terrain in front of them. Cynefin complements Wardley Mapping by framing how decision-making should adapt when the landscape is obvious, complicated, complex, or chaotic—exactly the challenge AI agents introduce.

How this post fits the series​

  • Anchors the series in a shared sensemaking language after the opening essay on AI-enabled agency.
  • Sets up the need for continuous map governance so Cynefin decisions rest on live data instead of static diagrams.
  • Prepares the ground for autonomous strategy execution, where that governance becomes executable doctrine.

Everyone a CEO

· 3 min read
Dave Hulbert
Dave Hulbert
Builder and maintainer of Wardley Leadership Strategies

Artificial Intelligence is lowering the barriers to leadership and execution. Starting and scaling an initiative once required significant capital, staff, and infrastructure. Today, a single person with a set of AI models and tools can operate like a small company. The essential resources of production—knowledge, labour, and coordination—are becoming commodities, available to anyone with the drive to use them.

This series explores how leaders can navigate this new landscape. It follows a deliberate path: we start with the collapse of execution costs, then layer in sensemaking, governance, and autonomous doctrine. Each post is designed to stand alone, but together they form a playbook for building AI-native organisations. We'll introduce the core frameworks here and then return to them in later articles as we add more nuance.

A quick guide to key concepts​

  • The Cynefin framework is a sense-making tool that helps leaders understand the kind of situation they are in, so they can make better decisions. It identifies five different domains—Clear, Complicated, Complex, Chaotic, and Confused—each requiring a different leadership style.
  • Agency refers to the capacity of an individual or system to act independently and make its own choices. In this series, we'll explore how AI is diffusing agency, giving individuals the power to execute tasks that once required entire organisations.
  • Doctrine refers to the fundamental principles that guide an organisation's actions and decisions. It's the playbook that helps a team coordinate and adapt.