Frameworks

Maturity models and methodologies for product builders. Each framework provides a structured path for growth with tools, metrics, and practices.

6 Levels v1.1 · June 2026

DORA and SPACE in the AI Age

Measuring What Matters When AI Changes Everything

How traditional software delivery and developer productivity frameworks must adapt for AI-assisted development. Introducing AI-DORA and AI-SPACE: modified metrics for the era of AI product builders.

doraspaceai-nativemetricsproductivitydevops
6 Levels v1.0 · June 2026

LLM-as-a-Judge

Automated Code Review at Scale

A practitioner's guide to replacing human code review with LLM-based evaluation, multi-judge aggregation, and VEAL loop integration for continuous validation.

llm-as-a-judgecode-reviewevaluationmulti-agentVEALautomation
4 Levels v1.0 · June 2026

Loop Engineering

From Prompt Engineering to Autonomous Agent Loops

A practitioner's guide to designing self-running AI coding agents with Claude Code, Codex CLI, and the REAL/VEAL loop patterns for production multi-agent systems.

loop-engineeringagentsclaude-codecodexautonomousREALVEAL
7 Levels v1.0 · May 2026

Product Builder Maturity Model

Two Paths to End-to-End Product Ownership

A maturity model defining growth toward independent product ownership, with paths for both Product Managers and Engineers converging at the Product Builder level.

maturity-modelproduct-managementengineeringai-native
7 Levels v1.1 · May 2026

Software Delivery Autonomy Levels

From AI-Assisted to AI-Operated

A seven-level progression from traditional Agile teams to autonomous software delivery and operations, introducing ASDM for autonomous coding, review, validation, and operations.

maturity-modelasdmautonomousai-nativedevops
5 Levels v1.0 · June 2026

Spec-Driven Development

From Vibe Coding to Structured AI Execution

A comprehensive guide to spec-driven development (SDD) methodologies and tools for AI coding agents, including GitHub SpecKit, AWS Kiro, AI-DLC Workflows, OpenSpec, and VisionSpec.

spec-drivensddagentsspecificationsai-nativemethodology