Wizeline | AWS AI-DLC Rapid Enablement Workshop

Most organizations see little productivity gain from AI coding assistants because the constraint isn't coding—it's the friction between intent and release. AI-DLC solves this by replacing legacy Agile rituals with short, AI-augmented cycles that keep people as decision-makers while automating construction.

The Methodology

• Mob Elaboration: Collaborative rituals to transform business goals into verifiable, machine-executable Units of Work.
• Units of Work: Modular, cohesive feature slices optimized for autonomous AI construction and testing.
• Bolt Execution: A high-intensity two-day cycle where AI-native construction meets production-quality verification.

Engagement Structure

1. Phase 1: Prep & Alignment (1-2 Weeks, part time, - Remote): Alignment on strategic intent, backlog decomposition into AI-ready Units, and environment/security readiness. We also capture what the selected sprint was expected to take, in elapsed time and engineering hours, which becomes the comparison point on day two.
2. Phase 2: The Workshop (2 Days - On-site / Hybrid): Hands-on "Bolt" execution including architectural design, AI-generated construction, automated verification, and deployment to a dev environment.

Deliverables:

• Working, tested code from your own sprint, deployed to a development or non-production environment
• The complete set of AI-DLC artifacts produced during the two days, versioned in your own repository, covering intent, requirements, Units of Work, design and test instructions
• A record of every decision and approval made during the workshop
• A comparison of the effort the sprint was expected to take against what was actually achieved
• A leadership readout covering what the team completed, what limited the result, and what would need to change for the pace to be sustained

Reference Technologies: We work with a number of different partners to accelerate your AI-DLC initiatives, and can incorporate your preferred ISV’s :

• Plan & Design: Atlassian, Miro, Vercel, Figma
• Code: Kiro, Claude Code, Codex, Cursor, Windsurf
• Verify: Snyk, AWS Security Agent, Nova Act
• Release: LaunchDarkly
• Deploy: Control Monkey, AWS DevOps Agent
• Monitor & Operate: Dynatrace, CloudWatch, DataDog, Grafana, New Relic
• Governance & Orchestrate: AWS Bedrock AgentCore, Lite LLM, JellyFish, DX (Atlassian), CrewAI, Strands, Maestra, GitLab

Who Should Attend:

• Product Owners: To lead intent definition and prioritization.
• Engineering Leads & Developers: To pilot and orchestrate AI construction.
• DevOps & Security: To ensure compliance, observability, and scalability.
• Executive Sponsors: To ensure alignment

Prerequisites

• Executive alignment & sponsorship
• One sprint already planned and scoped with backlog available
• Repository access provisioned for all participants
• Agentic coding tool licenses or evaluation access
• AWS account with appropriate model and service access
• A development/non-production target environment
• A named decision maker available for both full days

Out of Scope

• Deployment to production
• Organizational change work beyond leadership readout
• Procurement of third-party tooling licenses
• Ongoing delivery or managed services

Getting Started Book a 30-minute call to confirm fit and identify a candidate sprint. Contact gino.bautista@wizeline.com .

• Before purchase: Scoping call with an engagement lead to confirm fit and validate prerequisites.
• During preparation: Readiness checks and scheduling support to ensure workshop success.
• During the workshop: Full facilitation by Wizeline experts, on-site or hybrid.
• After the workshop: Leadership readout and 30-day post-delivery question support.