Case Study

70%+ Autonomous Incident Response: Charting the Future of AI-Powered Engineering

Australian Major eCommerce Company

Challenge

A major eCommerce delivery service company, operating mission-critical logistics and online commerce platforms, sought to modernise its engineering and delivery governance practices.

With multiple large, complex transformation programs on the horizon and an engineering workforce exceeding 600+ engineers, the CTO engaged Fabric Group to conduct an enterprise-wide review. The objective was to ensure the technology organisation was primed to deliver upcoming high-stakes programs with elevated transparency, developer ease, and architectural quality.

As the organisation prepared for rapid business expansion, leadership identified critical operational and delivery risks across its engineering ecosystem:

  • Navigating Increased Pace of Change: Multiple concurrent strategic programs required teams to accelerate output without compromising reliability across core eCommerce and dispatch systems.
  • Complex Multi-Team Coordination: Scaling delivery across 600+ engineers distributed across various domains created visibility gaps and uneven delivery quality.
  • Tooling Fragmentation: Disparate toolchains and ad-hoc engineering practices led to friction in onboarding, knowledge sharing, and everyday developer experience.
  • Partnering & Governance Inconsistencies: The organisation required a cohesive governance framework to oversee mixed delivery models, spanning internal squads, staff augmentation, and fixed-scope partner engagements.
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PRocess

Fabric executed a structured three-stage framework (Define, Assess, Recommend) to align executive vision with ground-level engineering realities:


1. Define

  • Established a shared definition of success across executive leadership and active working groups.
  • Set transparent, measurable objectives at the outset to evaluate developer experience, delivery velocity, and governance standards.

2. Assess

  • Conducted in-depth qualitative interviews with engineering leads, product managers, and developers.
  • Performed deep technical reviews of codebase architecture, repositories, and documentation.
  • Shadowed critical squad ceremonies and architectural forums to observe operational mechanics firsthand.
  • Audited the complete engineering toolset and pipeline across the 600+ person engineering organisation.

3. Recommend: The Three-Horizon Plan

Fabric charted a definitive "North Star" roadmap for engineering practices, partner governance, and an AI-accelerated SDLC:

  • Horizon 1 (Business as Usual): Establish baseline AI adoption through GitHub Copilot Agent rollouts, pilot agentic IDEs (such as Cursor), define Model Context Protocol (MCP) usage processes, explore AI features in existing tooling, and implement strict guardrails to eliminate non-deterministic code risks.
  • Horizon 2 (Disruptive Innovation): Expand coding agents to handle feature implementation and defect resolution autonomously, roll out agentic IDEs broadly, standardise internal MCP deployment patterns, and introduce agentic DevOps to create an automated observability feedback loop.
  • Horizon 3 (Emerging Future): Deeply integrate agentic IDEs into a unified developer workspace, expose internal enterprise systems via MCP for autonomous agents, and implement advanced SRE agents targeting 70%+ autonomous incident response.
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Results

Fabric provided actionable blueprints and governance models that enabled the enterprise to scale engineering output while lifting developer satisfaction:

  • Modernised Tech Tooling Roadmap: Delivered a clear tooling strategy identifying immediate platforms to adopt and future technologies to watch, ensuring competitive developer experience.
  • Enterprise Engineering Standards: Established scalable, governed engineering practices that balance rapid feature delivery with technical excellence and high code standards.
  • Robust Multi-Model Governance: Formulated comprehensive engineering governance covering multiple partnering structures, from staff augmentation and squad augmentation to fixed-bid vendor engagements.
  • Continuous Uplift & Self-Evaluation: Implemented an ongoing organisational model allowing engineering teams to self-evaluate, course-correct, and stay ahead of rapid shifts in modern software delivery.
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