Overview
Most organizations adopting AI coding tools see individual developer speed increase while team-level delivery throughput stalls. DORA 2025 research confirms AI amplifies the system it lands in--the bottleneck is the operating model, not the tools.
Liatrio's Readiness Assessment provides engineering leadership a clear, measured picture of where the organization stands and a concrete path forward aligned to the AWS AI-DLC framework.
Assessment Stages:
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Scoping and Alignment - Align on priorities, select target teams, repositories, and value stream targets.
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AI Fluency Baseline and Value Stream Map - Baseline AI fluency across five maturity levels. Map the end-to-end value stream to identify friction points, rework loops, and wait states across the product development lifecycle.
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Delivery, Deployment, and Codebase Analysis - Assess codebase AI readiness, CI/CD maturity, and operating model alignment against AI-DLC requirements. Identify which work is safe to automate first.
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Roadmap and Executive Readout - Leadership receives the full picture: fluency baseline, value stream map, prioritized transformation roadmap, recommended pilot workloads, and measurable success criteria.
This assessment is led by a Principal-level consultant with hands-on AI-driven development experience, ensuring actionable recommendations grounded in real-world delivery expertise.
Highlights
- Proven AI Fluency Framework - Five-level assessment that gives leadership a clear read on where each team stands on AI development competency, from awareness through autonomous agentic workflows.
- Value Stream Visibility - See exactly where friction, rework, and wait states across your product development lifecycle will limit AI adoption impact, with baselines to measure improvement.
- Actionable Transformation Roadmap - Know which task classes are ready to automate first, in priority order, with recommended pilot teams and measurable success criteria to track progress.