Disciplines, not technologies.
Each capability area is a way of thinking about a class of problem. The technologies that show up are a consequence of that thinking — not the other way around.
Cloud Infrastructure
Designing and operating cloud systems that scale predictably and fail gracefully.
- AWS architecture and cost optimization
- Deployment pipelines (CI/CD) on Vercel, Railway, and self-hosted runners
- Containerization and orchestration with Docker
- Observability — logs, metrics, traces
Infrastructure is a product decision, not a checklist. The right shape comes from how the business actually grows, not from a reference architecture diagram.
- — Push-to-deploy pipelines — this site auto-ships to Vercel on every commit
- — Static-first architecture that stays fast under load without hand-tuning
- — Infrastructure sized to how the product actually grows, not a reference diagram
Software Engineering
Building production software the way engineering organizations build it — typed, tested, and maintainable.
- Full-stack web — Nuxt, Vue, Next.js, React
- API design — REST, GraphQL, internal service contracts
- Database modeling with PostgreSQL and Prisma
- TypeScript-first codebases that survive team growth
The best code is the code a stranger can change six months from now. Clarity beats cleverness; types are documentation that runs.
- — Strict-typed TypeScript end to end — this site, CookyChef, and FarMight
- — Production apps shipped solo and in teams, from MVP to investor pitch
- — Code a stranger can change six months later — clarity over cleverness
Automation
Removing manual work that does not deserve human attention — quietly, durably, and observably.
- Python tooling — scrapers, ETL pipelines, internal utilities
- Workflow orchestration and scheduled jobs
- Scripting for data movement, reporting, and integration glue
- AI-assisted workflows where the leverage is real
Automation that nobody trusts gets ignored. The hard part is not writing the script — it is making the script boring enough that the team forgets it exists.
- — AI-assisted delivery when the leverage is real — 5 products in 5 weeks
- — Python tooling for the glue work: scraping, ETL, scheduled jobs
- — Automation boring enough the team forgets it's running
Security Foundations
Treating security as an architectural concern from day one — not as a final review.
- Networking and Linux fundamentals
- System hardening for production workloads
- Secrets management and credential hygiene
- OWASP-aware web application practices
Most breaches do not come from sophisticated attacks. They come from defaults nobody changed and assumptions nobody questioned. Security maturity starts with the boring parts.
- — Posture measured, not assumed — Sentinel grades headers, cookies, email/DNS, and TLS from outside the perimeter
- — Secrets in env, never in git — enforced on this site and every client build
- — OWASP-aware defaults: input validation at the boundary, least privilege
Engineering Operations
The unglamorous craft of keeping engineering organizations productive over time.
- Debugging across the stack — frontend, backend, infrastructure
- CI/CD pipeline design and maintenance
- Technical documentation that engineers actually read
- Systems analysis and reliability reviews
A team that cannot find the cause of yesterday's bug will not ship next quarter's feature. Operational discipline is the foundation everything else stands on.
- — Reliability recovered through structured debugging and root-cause analysis
- — Cross-stack debugging — frontend, backend, and infra in one head
- — Documentation engineers actually read, because it stays close to the code
Need these capabilities on your team?
If one of these disciplines maps to a problem you're facing, let's talk it through.