I am a technology executive who can lead technology internally and represent it externally. I help leadership teams understand what emerging technologies actually change, decide where to invest, and turn complex technical choices into business results.
My experience combines internal technology leadership with external representation to customers, partners, boards, investors, governments, and technical communities. My strongest contribution is bridging technical depth and executive decision-making: working credibly with architects and engineering teams, testing assumptions, identifying business consequences, and communicating decisions clearly.
I am a former Vice President of Education at The Linux Foundation. I led approximately 60 employees and contractors, including nine direct reports and three managers, and influenced approximately $8 million in annual investment. My work has included AI-enabled products, platform modernization, acquisition integration, governance, organizational transformation, and open-source ecosystem leadership.
- Website: serewicz.com
- LinkedIn: linkedin.com/in/serewicz
- Schedule a Conversation: calendar.app.google/2KmjiyNZjh3FSQUy7
- Enterprise technology and product strategy
- AI adoption, governance, and operating models
- Customer-facing technical strategy and executive briefings
- Technology diligence and value-creation planning
- Open-source, developer, and partner ecosystems
- Platform modernization
- Cybersecurity and board reporting
- Organizational transformation and engineering leadership
| Subject | Executive decision or business consequence |
|---|---|
| Kubernetes and platform modernization | Decide whether modernization reduces operating risk and cost or merely relocates complexity. I stopped a high-risk Kubernetes migration at a global semiconductor company that could have created multimillion-dollar cost and operating exposure. |
| Enterprise AI adoption | Select use cases where data readiness, workflow ownership, evaluation, and governance can produce measurable value rather than isolated pilots. |
| AI replicability | Determine whether an AI capability creates defensible business advantage or can be reproduced quickly by competitors using the same models and tooling. |
| Cybersecurity and cryptographic readiness | Translate security controls, cryptographic inventory, and post-quantum exposure into investment priorities, accountability, and board-level risk decisions. |
| Architecture and technical debt | Identify when complexity constrains delivery, margin, resilience, or strategic options. I simplified a financial-services architecture from approximately 8,000 nodes to 10-15 manageable clusters, and recommended retaining colocated infrastructure for a quantitative trading organization where latency created business advantage. |
- Enterprise AI strategy, RAG, evaluation, knowledge governance, and responsible adoption
- Linux kernel, enterprise Linux, UNIX, and mission-critical infrastructure
- Kubernetes, distributed platforms, cloud architecture, and platform engineering
- Cybersecurity, cryptographic inventory, and post-quantum readiness
- RISC-V and open-source hardware ecosystem engagement
- Open-source business, governance, education, and developer ecosystems
- Quantum technology communication for executives and governments
I do not position myself as the deepest implementer in every domain. My value is understanding complex technologies deeply enough to challenge assumptions, work effectively with specialists, recognize business consequences, and guide executive decisions.
- Approximately 900 multi-day technical courses delivered
- 40-50 talks and presentations worldwide
- Executive and technical quantum courses developed for the World Bank
- Audiences including engineers, executives, enterprise customers, governments, military organizations, and global technology communities
Recommended starting point: Executive AI Advisor - see how technical evidence becomes cited risk assessments, board briefs, and accountable 100-day plans.
| Order | Repository | What it demonstrates |
|---|---|---|
| 1 | Executive AI Advisor | Evidence-based technology diligence, executive decision support, AI governance, board briefs, and 100-day plans |
| 2 | CTO Operating System | CTO, governance, diligence, board reporting, and operating frameworks |
| 3 | Technology Leadership Portfolio | How assessment, governance, implementation, and measurement connect as an executive operating model |
| 4 | K8s Platform Blueprint | Platform modernization, FinOps, observability, policy controls, and compliance evidence |
| 5 | Engineering Operating Metrics | Delivery flow, review quality, rework, cost, risk, and engineering governance metrics |
| 6 | HarvestGuard | Local-first cryptographic asset inventory and evidence collection for diligence and post-quantum migration planning |
Together, these repositories show a consistent leadership approach: test technical assumptions, translate findings into business consequences, define accountable action, and measure whether execution improves.
Representative examples of technology leadership, executive advisory work, platform transformation, and AI-enabled decision support: