AI Creator Foundations
Orientation to the AI creator landscape and the working setup everything else depends on. Covers business models and niche selection, disciplined use of ChatGPT and Claude, and how to assemble a repeatable studio workflow across image, voice, video and automation tools.
You can describe the opportunity you are pursuing, operate a configured AI workspace with a reusable prompt library, and run a documented studio workflow with a known monthly cost.
4 modules
The AI Creator Economy
How AI-native creator businesses are structured, where revenue comes from, and how to choose a niche and audience you can serve credibly, including the ethical and disclosure questions that come with synthetic media.
Deliverable: Opportunity, niche and monetisation brief
Topics covered (7)
- Landscape of AI-native creator businesses
- Business models and revenue streams
- Niche selection
- Audience definition
- Ethical positioning
- Disclosure practices
- Thirty-day roadmap
Mastering ChatGPT
Setting up a working ChatGPT environment: reusable context, prompt construction, research with verification, content and image workflows, and the quality-control habits that keep output usable.
Deliverable: Configured workspace and prompt library
Topics covered (9)
- Workspace and account setup
- Projects, memory and reusable context
- Prompt construction
- Research and fact-checking
- Strategy work
- Content workflows
- Image generation
- Prompt libraries
- Quality control and hallucination management
Mastering Claude
Using Claude for long-form and structural work: character and world specifications, brand documents, SOPs, product planning, and reviewing AI output critically. Includes when to reach for Claude, ChatGPT, or both.
Deliverable: Claude workspace and a structured character or brand specification
Topics covered (9)
- Projects and artifacts
- Long-form document work
- Character and world specifications
- Brand strategy documents
- SOPs and specifications
- Product and application planning
- Claude Code workflows
- Critiquing and improving AI output
- Choosing between tools
The AI Studio Workflow
Turning a pile of tools into a production system: which tool does which job, how files and assets are named and versioned, how work hands off between stages, and what the whole stack costs to run.
Deliverable: Studio map and operating budget
Topics covered (9)
- Mapping tools to jobs
- Model orchestration
- Image, voice, video, design and editing stack
- Automation tooling
- File organisation
- Asset naming
- Version control
- Production handoffs
- Cost planning and substitution options