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Sources and Frameworks

CDS is not built from a single discipline. It’s a synthesis layer: it pulls stable functions from multiple fields and arranges them around one job — turning meaning into decision-grade intent and formal commitments.

This page is not a bibliography. It’s a map of intellectual neighborhoods CDS draws from, and the specific kinds of problems each neighborhood helps address.

How to read this page

Use it to:

  • understand what CDS is compatible with (and why)
  • recognize familiar ideas without assuming CDS “is just” that thing
  • find good upstream reading when deepening a specific CDS capability

Systems thinking and cybernetics

What it contributes: feedback loops, control under uncertainty, drift, governance as regulation, system boundaries.
CDS uses it for: revisit triggers, change protocol, “inspectability”, and re-entry behavior.

Common neighbors:

  • systems thinking (boundaries, leverage points)
  • cybernetics (control loops, sensing/actuation)
  • second-order thinking (observer effects, narrative risk)

Socio-technical systems and organizational design

What it contributes: work as coordination across people + tools + incentives; failure modes from misaligned structures.
CDS uses it for: decision rights, dependency obligations, “delivery reality” capture, escalation prevention.

Common neighbors:

  • socio-technical design
  • Team Topologies / Conway’s Law dynamics
  • organizational incentives and principal–agent problems

Communication, facilitation, and negotiation

What it contributes: alignment mechanics, surfacing disagreement safely, shared language formation, decision hygiene.
CDS uses it for: Meaning Handshake facilitation, tradeoff ownership, commitment ceremonies without theater.

Common neighbors:

  • facilitation practices (workshop design, alignment prompts)
  • negotiation (interests vs positions)
  • conflict-aware collaboration (psychological safety, escalation design)

Product discovery and problem framing

What it contributes: meaning as user/customer progress; separating needs from solutions; evidence-driven learning.
CDS uses it for: Meaning Discovery and early Intent shaping without collapsing into feature lists.

Common neighbors:

  • JTBD and related discovery approaches
  • design research and qualitative inquiry
  • hypothesis-driven discovery

Strategy and sensemaking

What it contributes: framing choices, option spaces, constraints as strategic posture, “why now” clarity.
CDS uses it for: situation framing, tradeoff explicitness, scope boundaries, and commitment coherence.

Common neighbors:

  • Wardley Mapping (context + evolution + strategic moves)
  • VMOSA-style clarity (vision/mission/objectives)
  • systems sensemaking practices

Requirements, intent, and decision quality

What it contributes: structured articulation of intent, ambiguity management, traceability, acceptance thinking.
CDS uses it for: “decision-grade intent”, boundaries, assumptions/unknowns, and acceptance evidence.

Common neighbors:

  • requirements engineering (without treating it as ticket-writing)
  • architecture decision records (ADRs) as “decision memory”
  • testability and acceptance thinking

Governance, contracts, and procurement

What it contributes: commitments as agreements with obligations; change control; accountability; risk allocation.
CDS uses it for: Commitment Formalization, Commitment Envelope, procurement-friendly “compatibility mode”.

Common neighbors:

  • SoW / RFP / RFI structures
  • contract change control patterns
  • accountability models (RACI-like clarity where useful)

Delivery methods and execution runtimes

What it contributes: ways to run work once a commitment exists (cadence, coordination, flow).
CDS uses it for: runtime handoff, governance cadence realism, avoiding “method wars”.

Common neighbors:

  • Agile / Scrum / Kanban (execution mechanics)
  • Lean delivery (flow, WIP, feedback)
  • DevOps and continuous delivery (release posture, operability expectations)

CDS position: above delivery methods. CDS produces the commitment those methods should execute.

Architecture, quality attributes, and operability

What it contributes: constraints and quality attributes as first-class; reversibility; production reality.
CDS uses it for (software profile): NFR intent, reversibility classification, feasibility probes, operational posture.

Common neighbors:

  • quality attributes (reliability, performance, security, maintainability)
  • observability practices
  • release/cutover strategies and production risk management

Risk, safety, and reliability thinking

What it contributes: risk as posture, not a checklist; failure modes; escalation design; safe-to-fail learning.
CDS uses it for: risk posture, early signals, revisit triggers, escalation paths that aren’t political.

Common neighbors:

  • SRE-style reliability thinking
  • incident learning culture
  • risk framing and mitigation planning

AI-assisted work and tooling

What it contributes: acceleration of drafting, summarization, and option exploration—plus new failure modes (confidence without grounding).
CDS uses it for: better artifact production and review, while defending against “coherent nonsense”.

CDS stance: AI can help generate artifacts, but CDS quality checks must still be satisfied (signals, ownership, decision rights, tradeoffs).

What CDS contributes (the synthesis)

Many frameworks describe parts of the space. CDS contributes a specific integration:

  • A stable Meaning → Intent → Commitment model as a translation pipeline
  • Three canonical artifacts with clear boundaries:
    • Meaning Handshake
    • Intent Package
    • Commitment Envelope
  • A consistent system of quality checks and re-entry rules
  • A profile mechanism that keeps the core universal while enabling runtime-specific extensions (e.g., Software Delivery → 3SF)

In short: CDS is a commitment formation system, designed to work with your existing methods—by making the upstream commitment explicit, inspectable, and governable.