Why Companies Run This Workshop

Engineering teams face pressure to deliver faster. AI-assisted development shortens build cycles. Most teams lack proven patterns, governance, and standardization.

This workshop standardizes your team around AI-native development practices. Teams learn how to:

  • Write specs that AI tools can interpret
  • Use AI systems to generate, refactor, and test code
  • Apply guardrails that reduce rework and defects
  • Build a functional prototype from a scoped problem

What the Two-Day Workshop Delivers

Your team completes structured labs on day one and builds a working prototype on day two. The structure ensures engineers learn patterns before building.

Day 1: AI-Native Development Patterns (Hands-On Labs)

Teams learn and apply:

  • Spec-driven development
  • Multi-file generation workflows
  • AI-assisted test creation
  • Code review and refactoring using AI
  • Security and dependency analysis using AI
  • Prompt patterns that increase accuracy
  • Repository organization for AI tools

Outcome: Each engineer adopts a consistent workflow that reduces time spent writing and reviewing code.

Day 2: Hackathon on Your Real Use Cases

Teams choose a scoped business problem. They build a working prototype using the patterns from day one.

Examples

  • Data extraction agent for internal documents
  • Case-study generator for sales motions
  • Ticket triage agent for support queues
  • Internal knowledge search interface
  • Engineering automation (tests, docs, dependency updates)

Outcome: You receive a prototype tied to a real problem. The team documents what they built and how AI automated the work.

What Your Team Walks Away With

Each team receives:

  • A functioning prototype in your environment
  • A GitHub repository with code, docs, and tests
  • Recorded demos for internal review
  • A repeatable workflow used across exercises
  • A set of patterns that reduce build time

You also receive:

  • A post-workshop readiness assessment
  • A list of follow-on opportunities for internal adoption

Follow-On Enablement Program (Optional)

Companies use the enablement program to maintain momentum and integrate AI into production workflows.

The program includes:

  • Slack access to AI engineering expertise
  • Periodic briefings on tool updates
  • Code assessments using AI-driven metrics
  • Advisory on model selection and deployment
  • Build a micro-POC together

Micro-POC definition:

  • 1-2 day collaborative engagement
  • Demonstrates one capability
  • Without committing to full delivery or production ownership

Outcome: Your team receives a predictable cycle for learning and adoption.

Who Benefits Most

This workshop is designed for:

  • Engineering teams adopting AI-assisted development for the first time
  • Teams that want consistent workflows for multi-file code generation
  • Leaders exploring AI-driven automation
  • Teams preparing to build internal agents or AI-powered interfaces

Teams with at least moderate DevOps capabilities see faster results.

What We Do Not Promise

This workshop does not:

  • Deliver production-ready software in two days
  • Replace existing SDLC controls
  • Guarantee deployment to regulated environments without further work

We focus on skills, patterns, and prototypes. Your team will still follow your normal processes for security, data governance, and production deployment.

About the Founder

Paul Duvall has delivered cloud and DevSecOps solutions for more than 15 years. Led large-scale engineering and security programs at AWS and co-founded Stelligent, the first company focused exclusively on Continuous Delivery/DevOps on AWS.

Career Highlights

  • Jolt Award-Winning Author: Authored Continuous Integration: Improving Software Quality and Reducing Risk, part of the Martin Fowler Signature Series
  • Company Builder: Co-founded and scaled Stelligent, helping nearly 100 enterprise customers apply DevOps principles, practices, and techniques, achieving AWS Premier Partner status and $10M+ in annual revenue before a successful $25M exit in 2018
  • AWS Hero (2016-2021): Recognized for significant contributions to the cloud community
  • AWS Security Leadership (2021-2024): Led DevSecOps and Security Innovation teams at AWS
  • Hands-On AI Practitioner: Extensive experience with AI coding assistants including Claude Code, Kiro, Codex, Cursor, and other tools, with proven patterns for production deployments

Now focuses on helping engineering teams adopt AI-native development through structured training and enablement.

Pricing

Provided on request. Pricing scales based on team size, preparation needs, and follow-on support. Most engagements follow a two-day structure with defined add-ons.