Intent. Intelligence. Impact. / Creator Lab
Design lab · Build evidence pendingCreator Workbench
A two-day architecture lab. Crisis Cat brings the product vision. Wicked Spooky brings the cloud design. Together, they turn an ambitious one-person social media team into a buildable, measurable AWS specification.
The cast and the commission
Crisis Cat — product designer and client. Crisis Cat has designed the Creator Workbench: research, content, publishing, community, attribution, and a daily brief. The business starts with almost no money but expects thousands of subscribers if its marketing takes off.
Wicked Spooky — the solution architect. Wicked Spooky IT, also known as Second Act Sam, brings 30 years of IT experience and is studying AWS SAA-C03. In this scenario, Wicked Spooky takes responsibility for specifying the AWS environment Crisis Cat needs. “SAA” describes the architect's role and learning objective; it does not assert that the exam has already been passed.
WickedSpooky.ai hosts this training section inside its existing Amplify application. WickedSpookyIT.com is the delivery identity. The eventual creator.wickedspooky.ai product is a separate application outcome. These pages discuss and design that outcome; they do not operate it or provision its infrastructure.
Two days, one mission
| Lesson | The question | The design artifact |
|---|---|---|
| Day 1 — The Creator Workbench | What must the product do, and what is the simplest useful architecture? | Module specifications, human approval rules, local AI strategy, and Mermaid user journey |
| Day 2 — Wicked Spooky's architecture review | How do we deliver safely on today's budget and survive tomorrow's growth? | AWS feature review, alternatives, subscription guardrails, SAA mapping, and fail-forward plan |
Our product design method
We apply the method already defined on iLab: Discover → Plan → Execute → Certify → Impact. Governed Discovery clarifies intent and evidence. AI-Augmented Insight helps us examine choices. Certified Execution checks work against agreed requirements. Continuous Learning records failures and repairs. Trusted Impact connects measured outcomes to the original goal.
| Stage | What it means in this lab | Evidence we will retain |
|---|---|---|
| Discover | Translate Crisis Cat's pitch into requirements, constraints, unknowns, and authority | Product brief and prerequisite ledger |
| Plan | Compare architectures, assign ownership, and select the smallest credible design | Diagrams, decisions, cost model and acceptance criteria |
| Execute | Build bounded experiments when implementation labs begin | Versioned changes and reproducible test inputs |
| Certify | Verify approvals, tenant isolation, failure behavior, recovery and unit economics | Actual results, traces, cost measurements and restore records |
| Impact | Compare revenue, cost and useful outcomes; feed lessons into the next iteration | Daily brief, margin trend and fail-forward findings |
Method references: Discover, Plan, Execute, Certify, Impact. Here, Certify means internal acceptance; it does not mean third-party accreditation.
How to read the case study
Architecture choices are narrated as completed design decisions so this can guide a build from scratch. Resources, integrations, incidents and performance results are not claimed complete. Crisis Cat's assumption that infrastructure and integrations already exist is a scenario input; Day 2 turns it into a readiness checklist to verify before delivery.
The operations design case study holds the detailed cost model and all 14 SAA-C03 task statements. This training companion adds the client/architect story, the two-day discussion, and local-focused AI routing. It retains the human approval gate, headless event architecture, profitability floor, and evidence-first approach.
The promise we are designing for
One person can prepare a week of content and follow its commercial results without becoming a cloud operator. Nothing is published without approval of the exact version. Routine work uses deterministic processing or a small model where useful. Accepted jobs have visible outcomes. Growth changes throughput and paid usage within tested limits; it does not remove approvals, platform rules, or cost controls.
Start with Day 1 — The Creator Workbench.