AI-Driven Development Life Cycle

Learn AI-DLC methodology through hands-on workshop practice

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Build applications using the complete AI-DLC methodology: Inception, Construction, and Operations phases

These workshops recommend using the open-source AI-DLC Workflow rules for a guided, adaptive experience. Copy-paste prompts are also available as an alternative within each workshop.
Each workshop has a predefined use case so your team can jump straight into building — just pick a workshop, start the workflow, and follow the gates.

Workshop 1

Task Manager Application

Build a task manager with Python Flask APIs and deploy to AWS using CloudFormation

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Workshop 2

Job Application with CDK

Build a job application website with React and deploy using AWS CDK with S3 and CloudFront

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Workshop 3

S3 File-Sharing System

Build a web-based file sharing system with S3, DynamoDB, API Gateway, Lambda, and React

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Workshop 4

E-Commerce Product Catalog

Build a product catalog with incremental unit-by-unit development, testing, and validation

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Workshop 5

Brownfield E-Commerce

Modernize a sample e-commerce app — AI-DLC Workflow auto-analyzes the codebase, then you pick what to build

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AI-DLC Adaptive Workflows

Open-source workflow scaffolds that bring AI-DLC principles to life

Transform your development process with adaptive workflows that intelligently select stages, modulate depth, and embed human oversight at every critical decision point.

Key Features:
  • Adaptive Decisioning: Workflows conform to your problem's shape
  • Transparent Checkpoints: Human approvals embedded at every decision gate
  • End-to-End Traceability: Complete audit trail of reasoning and decisions
Workspace Detection

AI-DLC workflows automatically analyze your workspace and adapt the workflow. For greenfield projects, it proceeds to Requirements Analysis. For brownfield projects, it performs Reverse Engineering first. This demonstrates the truly adaptive nature of AI-DLC workflows.

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Adaptive AI-DLC Workflow