From generation to control
Part 2 made the main problem clear: the code needed to understand slide structure before filling text into a template.
Part 3 moved to the next product-level question. Generating a deck is useful, but a real user also needs to edit the result, preview it, and export it through a repeatable deployment path.
New direction
The project split into two tracks:
- an editable web app for controlling generated slide content
- an operational path for deploying the app with Docker, Caddy, Lightsail, and Terraform
This changed the project from an experiment into a tool shape.
Web app structure
The editable layer needed to keep the generated slide model and rendered output close enough that user edits would make sense.
The main requirement was not visual perfection. It was control:
- users can review generated text
- users can edit fields before export
- the app can rerender after changes
- the final PPTX output follows the same structure
Deployment structure
The deployment side focused on repeatability. Docker provided the runtime package. Lightsail gave a simple hosting target. Caddy handled web serving and TLS-friendly routing. Terraform documented infrastructure setup.
Takeaway
The key shift was from “AI creates slides” to “the user controls a generated artifact.” That is a better product boundary. AI can draft, but the app needs editing, preview, export, and deployment discipline to be usable.
