ai-dlcAI-Driven Development Life Cycle (AI-DLC) adaptive workflow for software development. Use when: starting a new project, new feature, bug fix, refactoring, mi...
Install via ClawdBot CLI:
clawdbot install sydpz/ai-dlcGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Calls external URL not in known-safe list
http://localhost:8080Audited Apr 18, 2026 · audit v1.0
Generated May 8, 2026
A startup wants to build a new SaaS platform for project management. Using AI-DLC, the AI guides from workspace detection to code generation, ensuring all phases are followed with human approval gates. The methodology adapts to the greenfield nature, focusing on full inception and construction phases.
A large enterprise needs to fix a critical bug in an existing legacy system. AI-DLC's brownfield detection triggers reverse engineering to analyze the codebase, then minimal requirements analysis captures the bug description, followed by targeted workflow planning and per-unit construction for the fix.
An e-commerce company wants to add a new recommendation engine feature. AI-DLC generates user stories for the new functionality, designs the application architecture, and iterates per-unit loops for code generation and testing, with approval gates after each step.
A mobile app company plans to migrate its backend to a cloud-native architecture. AI-DLC's reverse engineering phase documents existing components, then comprehensive requirements analysis captures migration constraints, followed by infrastructure design and code generation for new cloud services.
A manufacturing firm needs an internal tool for inventory tracking. AI-DLC treats it as a greenfield project, executing a streamlined workflow with minimal requirements, workflow planning, and code generation to quickly deliver a working prototype with audit trails.
Offer AI-DLC as a methodology to consulting clients for software projects, charging per project or per month. Consultants use the process to accelerate delivery while maintaining quality through human oversight.
Integrate AI-DLC into a SaaS development platform, providing tools that guide users through the methodology. Revenue from platform subscriptions, with premium tiers for advanced features like reverse engineering and multi-unit loops.
Develop training courses and certifications for development teams to adopt AI-DLC. Generate revenue from course fees, certification exams, and corporate training packages.
💬 Integration Tip
Integrate AI-DLC with existing CI/CD pipelines by mapping the OERATIONS phase to deployment tools like Jenkins or GitHub Actions, and use the audit.md file for compliance logging.
Scored Jun 20, 2026
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