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SDLC, re-engineered around AI.

AI as a central collaborator across the lifecycle — planning, decomposition, design, and real-time work alongside engineers. Humans stay accountable for validation, decisions, and oversight.

One of two pillars under "How we ship." Velocity, governed. The other pillar is Governance & Trust.

Why SDLC needs reimagining

AI's capabilities now extend well beyond code generation — into requirements elaboration, planning, task decomposition, design, and real-time collaboration with developers. That shift is fuelling the AI-driven orchestration of the development process itself.

But existing software-development methods were designed for human-driven, long-running processes. They are not aligned with AI's speed, flexibility, or its more advanced agentic capabilities. Their reliance on manual workflows and rigid role definitions limits the ability to fully leverage AI.

To leverage AI's transformative power, the SDLC has to be reimagined. The reimagining puts AI at the centre of the workflow — aligning roles, iterations, and decisions to enable faster execution, seamless task hand-off, and continuous adaptability.

How the roles change

AI orchestrates planning, task decomposition, and architectural suggestions. Product managers, developers, and QA/DevOps engineers retain ultimate responsibility for validation, decision-making, and oversight.

AI orchestrates

Planning. Task decomposition. Architectural suggestions. Domain mapping. Documentation. Real-time hand-off between stages.

Humans validate

Product managers, engineers, QA, and DevOps own the gates. Accept, reject, refine. Final accountability stays with the team that ships.

The workflow

A typical accelerated-deployment loop, with the candidate tools we use at each stage. Each step has a human reviewer; AI generates the first draft and adapts on feedback.

Accelerated Deployment Workflow Six-stage circular workflow: Stakeholder Input, Extract Entities, Visualize Domain Map, Generate Architecture, Data & API Design, Document. Each feeds the next; the last informs the first. AI-Driven SDLC START Input 01 Domain 02 Visualize 03 Architect 04 Data & API 05 Document
  1. S
    Stakeholder InputBusiness problem, constraints, and success criteria captured in plain language.
  2. 01
    Extract Entities & Bounded ContextsLLM Domain design from the brief.
  3. 02
    Visualize Domain MapMiro AIeraser.io Refined visually before architecture hardens.
  4. 03
    Generate Logical ArchitectureLLM + StructurizrC4 model Components, containers, relationships — reviewable.
  5. 04
    Logical Data & API DesigndbdiagramStoplight Schemas and API contracts kept in sync.
  6. 05
    Document the WorkflowNotion AIConfluence AI Living documentation. Findings inform the next stakeholder brief — the loop closes.

Where it fits

Accelerated Deployment is one of the two pillars under How we ship. Every tier of the engagement model passes through this pillar — alongside Governance & Trust, which enforces the gates AI cannot cross unsupervised.

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