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Agent Development Lifecycle

v3.7.3·37 Agents·125 Skills·141 Commands·37 Hooks·SOC2 + APRA

Govern AI agents in regulated industries. Reduce cloud costs. Ship with confidence.

AI agents build governed & Humans ship trusted. 80% autonomy & 100% accountability.
Get StartedView on GitHub

Powered by Claude Code (Anthropic) · 7 ADLC Principles · Open Source

Why ADLC?

AI agents edit code without review, claim completion without evidence, and push changes without audit trails. In regulated industries, this is unacceptable.

ADLC adds principled governance — deterministic hooks block unsafe actions, rules guide behavior. AI agents build governed & Humans ship trusted. 80% autonomy & 100% accountability.

Enforced by 22 hooks. Principle I · Claude Code Hooks.

Cost Down

FOCUS 1.2+ FinOps across AWS + Azure. Persona reports for CFO, CTO, CloudOps.

Compliance

22 hooks enforce governance. APRA CPS 234, SOC2, ISO 27001 alignment.

Time-to-Value Up

37 AI agents + 141 commands automate CDK, Terraform, K8s, FinOps workflows.

How We Run the Lifecycle

One platform. Three lenses. Pick the one that maps to your role.

Built with ADLC

Digital products built and governed by the ADLC framework

Golden Paths

End-to-end research questions validated by 6-agent PDCA scoring

Each path maps agents, commands, skills, hooks, and MCPs with why/what-if/value/purpose

Ready to govern your AI agents?

Open-source. Local-first. Hybrid-cloud.

Get StartedGitHub
PyPI: runbooksTerraform ModulesCloudOps DocsDevOps DocsF2T2EA CycleClaude Code
PersonasLimitationsIndustriesMarketplaceDocumentationComponent Telemetry
ADLC Framework v3.7.3 · Apache 2.0