Leadership Playbook

EngineeringFrameworks

Battle-tested methodologies for building software in the age of AI agents. These are the frameworks I bring into fractional CTO engagements — the artifacts boards ask for and teams actually use.

The Library

Six frameworks, one operating model.

Each framework answers a specific question I hear from engineering leaders. Read them standalone — or use them together as the backbone of an AI transformation.

Available

Spec-Driven Development

Bring intentionality to an AI-accelerated SDLC

When agents can generate thousands of lines of code in seconds, the spec becomes the control plane. A methodology for making specification — not implementation — the center of delivery.

For: Engineering orgs rolling out AI coding agents

Read the framework

Coming Soon

AI Governance Framework

Policy, risk, and compliance that enables velocity

A board-ready governance model covering usage policy, model approval, data boundaries, vendor risk, and incident response. Pair with the public governance checklist to assess current state.

For: Leaders facing audit, compliance, or board questions

Coming Soon

Build vs. Buy Decision Matrix

The #1 question on every CTO's desk

A structured decision framework for evaluating AI tooling, platforms, and foundation models — weighing switching cost, lock-in, data sovereignty, and time-to-value against internal capability.

For: CTOs navigating vendor sprawl and foundation-model choice

Coming Soon

AI Architecture Decision Records

Auditable decisions for AI-native systems

An ADR template tuned for AI architecture: model selection, retrieval strategy, evaluation harness, guardrails, and observability. Decisions that survive team turnover and post-incident reviews.

For: Platform teams standardizing AI infrastructure patterns

Coming Soon

LLM Cost & Evaluation Framework

Answer "what is this actually costing us?"

A unit-economics and evaluation model for production AI — per-request cost, eval coverage, regression gates, and model-swap decisions. The numbers a board expects you to have.

For: Teams operating LLM features at meaningful scale

Coming Soon

Team Enablement Ladder

From AI-curious to AI-native in 90 days

A capability ladder for engineering teams adopting AI-assisted workflows — skills, artifacts, and rituals by level. How to move 200+ engineers without burning trust or quality.

For: VPs of Engineering driving org-wide AI adoption

Stay Current

New frameworks ship to the newsletter first

Subscribe to get each framework as it's published, plus the field notes behind it — real engagements, real tradeoffs.

Subscribe for Updates

Put it to work

Need a hand rolling these out?

I bring these frameworks into fractional CTO engagements — adapting them to your stack, org, and stage. From design to team rollout.

Book a Strategy Call