Frameworks
Maturity models and methodologies for product builders. Each framework provides a structured path for growth with tools, metrics, and practices.
The frameworks form one system. The two-loop operating model is the architecture: the Product Loop decides what to build and verifies it worked; the Builder Loop implements and verifies it’s built right. The PBMM grows the person who runs both loops; the autonomy levels grade how much of the Builder Loop runs without humans.
The Product Loop & Builder Loop
The Two-Loop Operating Model for AI-Native Product Development
AI-DLC, Spec-Kit, and OpenSpec run a single engineering loop: the task arrives from outside, and verification means the code matches the task. The two-loop model adds the missing Product Loop — originating what to build and verifying it worked — the same move Scrum@Scale made for Scrum.
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.
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.
The Five Ps
The 5-P Product Stage Model — Preparation to Profit
When building is cheap, only results are scarce. The Five Ps stage a product from Preparation to Profit, and answer the question the maturity models don't: not how good are you, but how far did the product get.
AI-Native Product Manager Metrics
Measuring PM Effectiveness When AI Accelerates Everything
Input and output metrics for AI-Native Product Managers focused on customer request velocity. How to measure PM effectiveness when the goal is shrinking delivery time from years to 30 days.
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.
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.
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.
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.