Learning How Neighbourhoods Regenerate...Together

Civic CAD (Collectively Aligned Development) is a civic learning and action ecosystem that helps communities, institutions and researchers move from complex plans to coordinated, real-world progress.

 

At its core is a simple idea:

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Regeneration doesn’t happen through better plans alone. It happens when people learn, align and act together around shared conditions.

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Civic CAD provides the architecture to make that possible.

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What Civic CAD Is

Civic CAD is not a single tool or framework.

It is a layered ecosystem designed to support collective learning, coordinated action and ongoing adaptation.

It is made up of three tightly connected layers:

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1. The Concept Layer

 

The Compass

 

The foundation of Civic CAD is The Compass: A Civic Platform for Regeneration

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The book provides the shared language, principles and system logic for understanding how neighbourhoods behave and how regenerative change actually unfolds.

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It introduces:

• Regenerative Neighbourhood Principles (RNPs)

• Vitality, synchronicity and trust as system conditions

• Civic algorithms that explain how learning, momentum and legitimacy emerge over time

 

The Compass is available in hard copy via Amazon and as a free digital edition, so the ideas remain open and accessible.

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2. The Learning Layer

 

The Civic CAD Coach

 

The Civic CAD Coach is an AI learning companion that helps people and practitioners make sense of the Compass in their own context or scenario.

 

It is not a course and it does not tell people what to think.

 

Instead, it helps users:

• Interpret the ideas through their lived experience

• Reflect on real situations, not abstract theory

• Translate concepts into practical insight

• Learn in their own language, at their own pace

 

The Coach acts as a bridge between ideas and reality, supporting individuals and groups as they navigate complexity without oversimplifying it. Importantly, it meets you where you are at on your regenerative development journey and can literally speak in your language if English is not your preferred mode of learning.

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3. The Application Layer

 

Triangulated Civic Practice

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The Application Layer is where learning turns into action. It consists of three interconnected Streams that triangulate insight from different angles:

 

Community Stream
Supports local groups, residents and facilitators to surface lived truths, values and priorities, and to test small, meaningful actions together.

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Research Stream
Helps researchers, planners and institutions interpret what’s happening systemically, connect practice to theory and place local experience within broader evidence and policy frameworks.

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Strategy Stream
Turns insight into coordinated pathways by helping councils, organisations and cross-sector partners align action, sequence effort and generate momentum without rigid plans.

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Each Stream plays a distinct role, but none operates alone. Their value comes from working together.

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Why We Built Civic CAD

Neighbourhoods are living systems full of relationships, culture and energy. But we continue to plan and govern them as if they were machines.

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The result is familiar:

• Strategies that look good on paper but stall in practice

• Communities that lose confidence or feel excluded

• Institutions working hard but in silos

• Genuine effort without shared direction or flow

• Great research and programming but no enduring impact

 

Civic CAD was built in response to this gap.

 

Not to replace planning or strategy, but to make them work in the real world by embedding learning, alignment and feedback into how change actually unfolds at a system level.

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How Civic CAD Works

Civic CAD operates as a learning system, not a static framework.

 

At its heart are three simple civic algorithms that describe how collective change becomes possible:

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Reflexivity: Systems learn when they can see themselves clearly.

Convexity: Small, well-placed actions can generate outsized impact when networks are aligned.

Recursion: Feedback loops sustain trust, adaptation and legitimacy over time.

 

These algorithms connect shared understanding, shared action and shared learning into one continuous flow.

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From Plans to Momentum

Civic CAD does not replace your existing strategies or reports.

 

It helps bring them to life.

 

By working across the Concept, Learning and Application layers, Civic CAD can:

• Translate existing plans and data into grounded pathways people can rally behind

• Reveal where energy already exists and how to channel it

• Identify small, decisive moves that build confidence early

• Strengthen legitimacy and trust through visible progress

• Align partners without forcing artificial consensus

• Adapt to the real constraints that are ever present

• Helps navigate complex adaptive system environments

• Helps engineer system coherence to allow more favourable conditions to emerge

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The result is not another plan on the shelf, but a living, learning strategy that evolves as the system learns.

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What Makes the Civic CAD Different

Nine Nested Design Properties

 

These properties describe how Civic CAD operates as a system.

 

They are not rules or steps but nested design properties that reinforce one another and shape how Collectively Aligned Development becomes possible. 

 

Civic CAD shifts how civic change is understood and designed. Each shift replaces a familiar planning habit with a regenerative design logic.

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1. Principles before policies

Instead of relying on prescriptive rules, Civic CAD starts with shared principles that can travel across cultures and contexts. This allows coherence to emerge without forcing uniform solutions.

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2. Vectors before visions

Rather than locking communities into a single imagined future, Civic CAD focuses on direction of travel. It aligns effort around movement and momentum, not a fixed end state.

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3. Fractals before hierarchies

Change does not scale through command chains. Civic CAD looks for repeating patterns across neighbourhoods, institutions and regions so learning can scale without central control.

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4. Algorithms before doctrine

Civic CAD is guided by simple civic algorithms, such as reflexivity, convexity and recursion, rather than ideological models. These algorithms describe how systems actually adapt over time.

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5. Learning before models

Instead of perfecting models in advance, Civic CAD treats real-world action as the source of learning. Models evolve through testing, reflection and iteration.

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6. Legitimacy before authority

Legitimacy is not assumed. It emerges through the triangulation between community insight, research evidence and governance, rather than from top-down singular authority alone.

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7. Synchronicity before conformity

Civic CAD does not aim for conformity. It seeks synchronicity, where different actors move in alignment while retaining local identity and diversity.

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8. Conditions before control

Rather than attempting to manage outcomes directly, Civic CAD focuses on creating the conditions that allow agency, trust and emergence to take hold.

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9. Regenerative capacity before master plans

Success is not measured by whether a plan is followed, but by whether the system becomes more capable of adapting, learning and regenerating over time.

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Together, these shifts describe Civic CAD as a living learning ecosystem. Action research and real-world use feed learning back into the system over time, allowing principles, tools and methods to evolve while the core purpose remains intact.