Product & Technology Stack
The layers behind the work.
A practical view of the product, operations, data, engineering, and infrastructure layers behind my technical product management and marketing operations systems work.
Product and Decision Layer
Where problems, options, requirements, and product decisions become explicit.
Miro
- Role
- Discovery and systems mapping
- Why chosen
- It makes problem spaces, journeys, and system relationships visible before implementation.
- Where used
- Used for discovery workshops, flow mapping, and decision framing.
Markdown + MDX
- Role
- Product and decision documentation
- Why chosen
- Requirements and decisions stay reviewable and close to version history.
- Where used
- Used for briefs, specifications, decision records, case studies, and release notes.
Project and Operations Layer
Where ownership, delivery, risk, and recurring operations are coordinated.
ClickUp
- Role
- Operations and delivery workspace
- Why chosen
- It connects tasks, owners, statuses, dependencies, and recurring execution.
- Where used
- Used for marketing operations, delivery planning, and operating workflows.
Jira
- Role
- Structured technical delivery
- Why chosen
- It supports backlog, issue, sprint, and release coordination when engineering work needs a formal delivery model.
- Where used
- Used where product and engineering delivery require issue-level traceability.
Data and Systems Layer
Where operational information becomes a maintainable source of truth.
Airtable
- Role
- Operations data layer
- Why chosen
- It combines relational structure with an interface that operations teams can maintain.
- Where used
- Used for workflow sources of truth, capacity, vendor, finance, and reporting systems.
Automation and Integration Layer
Where repeatable work becomes an observable, owned workflow.
n8n
- Role
- Automation and integration engine
- Why chosen
- It supports inspectable API orchestration, branching, retries, and operational handoffs.
- Where used
- Used for synchronization, reporting, alerts, and tool-to-tool workflows.
AI workflow design
- Role
- Applied automation capability
- Why chosen
- AI is useful when inputs, review gates, failure behavior, and ownership are designed as part of the system.
- Where used
- Used selectively for structured analysis, drafting, classification, and execution support.
Engineering and Delivery Layer
Where product intent becomes versioned, tested, and reviewable output.
GitHub
- Role
- Change and delivery management
- Why chosen
- Code, documentation, review, CI, and releases share one inspectable history.
- Where used
- Used for public products, site delivery, validation, and release workflows.
Astro + TypeScript
- Role
- Static product and content delivery
- Why chosen
- The combination keeps public interfaces fast, typed, and testable.
- Where used
- Used for xhesam.com and static-first public products.
Infrastructure Layer
Where hosting, edge behavior, deployment evidence, and response policy are managed.
Cloudflare
- Role
- Hosting and edge runtime
- Why chosen
- It supports static delivery, narrow functions, preview deployments, and response controls.
- Where used
- Used for Pages, Functions, redirects, and deployment verification.