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Role and Responsibilities

My Role

The project is founder-led and end-to-end. I own the product hypothesis, the architecture, and the implementation.

Work included:

  • product discovery and positioning, including the pivot from docs-as-code publisher and workspace ideas to a processing-layer / Compiler platform;
  • requirements definition and constraints (local-first, credits, no proprietary document store as the core);
  • solution architecture and system analysis: domain model, job lifecycle, identity, billing, and AI transformation boundaries;
  • UX and product workflow design for local rendering versus explicit server-side compilation;
  • AWS architecture: CloudFront / private S3, API Gateway, Lambda, DynamoDB, Cognito, and related serverless services;
  • Terraform infrastructure and GitHub Actions CI/CD with OIDC;
  • authentication and authorization design (Cognito; USER / ADMIN / SUPER_ADMIN);
  • billing and credit architecture (Paddle as merchant of record; credits as compute metering);
  • AI transformation architecture, prompt / contract design, and runtime versioning;
  • observability and quality strategy (transformation history, admin control plane, target Compiler Health);
  • privacy and cost trade-offs;
  • implementation, debugging, dogfooding, and roadmap prioritization.

AI assistants were used as a development accelerator for routine implementation. Architectural decisions, product direction, data boundaries, access model, review, and deployment remained under my control.

AI Usage

LLMs were used to accelerate routine implementation, generate boilerplate, and iterate quickly. They were not treated as authors or owners of the system.

Kept under manual control:

  • requirements interpretation and product positioning;
  • domain modeling;
  • architecture decisions;
  • privacy and cost boundaries;
  • access model;
  • prompt / contract design;
  • code review and debugging;
  • deployment decisions;
  • technical documentation.