Frameworks, assessments, governance models, and operating playbooks for technology leadership.
This repository exists to help leadership teams align technology decisions with business outcomes. It is a practical operating playbook for CTO-level work: clarifying ownership, exposing tradeoffs, reducing risk, scaling teams, and communicating technology strategy in terms executives and boards can act on.
- CTO leadership
- AI strategy and governance
- Kubernetes and cloud-native platforms
- Cybersecurity and technology risk
- Technology due diligence
- Platform modernization
- Engineering organization scaling
- Executive and board communication
- Founders who need a clearer technology operating model
- CEOs who need technology leadership translated into business outcomes
- CTOs who want practical frameworks for assessment, execution, and communication
- PE firms evaluating technology risk and post-close priorities
- Boards that need concise visibility into technology posture
- Technology leaders scaling teams, platforms, governance, and delivery
Use this repository as a working CTO playbook, not as static reading material.
- Start with 100-Day CTO Plan when entering a new company, role, or turnaround.
- Use Technology Assessment and Engineering Org Review to establish current state.
- Use Technology Due Diligence Checklist for investment, acquisition, or board-level review.
- Use AI Governance Framework, AI Knowledge Governance Framework, Risk Register Template, and ADR Template to make governance concrete.
- AI Knowledge Governance Framework: classifies enterprise knowledge, defines RAG/private model decision patterns, and helps boards and CTOs protect sensitive IP while enabling AI adoption.
- AI Replicability Risk Framework: evaluates model dependency, proprietary data advantage, workflow advantage, knowledge advantage, operational maturity, and regulatory barriers.
- Use the fractional CTO templates to drive executive cadence, board reporting, and monthly operating reviews.
- Use the scaling templates to clarify roles, team structure, and hiring decisions.
- Use Operating Partner Technology Advisory Frameworks for the diligence, risk scoring, board brief, AI governance, portfolio review, and 100-day planning methodology that can be applied manually or automated in software.
Technology issues become business problems when leadership does not make ownership, tradeoffs, risk, and outcomes explicit.
The role of a CTO is not only to choose technologies. It is to create the operating clarity that lets the business make better decisions.
docs/ CTO plans, assessment frameworks, organization reviews, and roadmaps
governance/ AI governance, architecture decisions, and technology risk registers
due-diligence/ Investor and acquirer diligence frameworks
fractional-cto/ Fractional CTO operating cadence and executive reporting templates
operating-partner/ PE and CTO advisory methodology for diligence, board reporting, and post-close planning
scaling/ Engineering levels, team topology, and hiring frameworks
This repository contains operating frameworks, templates, and diligence methodology. Executive AI Advisor is the software platform that implements and demonstrates portions of these workflows:
https://github.com/serewicz/Executive-AI-Advisor
This repository is part of a broader Technology Leadership Portfolio: a practical system for assessing, operating, governing, implementing, and measuring technology organizations.
| Layer | Repository | Purpose |
|---|---|---|
| Methodology | CTO Operating System | Defines CTO, diligence, governance, board reporting, and operating partner frameworks |
| Assessment | Executive AI Advisor | Converts company documents into diligence reports, board briefs, CRA readiness assessments, AI governance assessments, and 100-day technology plans |
| Implementation | K8s Platform Blueprint | Provides implementation patterns for platform governance, FinOps, observability, policy controls, and compliance evidence |
| Measurement | Engineering Operating Metrics | Measures delivery flow, review quality, rework, engineering cost, AI usage cost, risk, and engineering governance |
This repository provides the methodology layer. See Technology Leadership Portfolio.
Timothy Serewicz is a CTO, technology executive, and fractional CTO based in Austin, Texas. He has 20+ years of experience across Kubernetes, Linux, AI, cybersecurity, cloud-native platforms, open source, and technology strategy. He helps leadership teams align technology decisions with business outcomes.
This repository is released under the MIT License. See LICENSE.