Walkaround— typed explainers with progressive playback.
Walkaround turns a question, concept or code change into a streamed interactive artifact: structured scenes, narration, generated media, pointer choreography and learning interactions. The model authors a constrained presentation format rather than unrestricted markup or a long chat response.
- Node.js ESM
- MCP SDK
- Azure Speech
- Zod
- Playwright
- typed visual recipes
- progressive rendering
Stack
Engineering evolution
Reconstructed from commit history, current source and design specifications. The sequence is evidence-led; explanatory rationale is condensed rather than presented as a literal design diary.
The first architectural constraint was a scene/document format the player could validate and render. That made partial validity, progressive playback and later visual QA possible.
Silence trimming, playback speed, cadence, native timing and pooled synthesis were added because audio latency directly changes the perceived responsiveness of the entire experience.
As the recipe catalog grew, visual-mix auditing was added to limit layout, animation and image density. Variety without constraints produced inconsistent explanatory structure.
Pointer movement became target-aware and narration-aware. Technical content required precise anchors so motion communicates current focus rather than adding generic animation.
Format, energy, depth, visual density and delivery became separable dimensions while automated selection remains the default. The system stays controllable without turning every request into a configuration form.
Reduced motion, high contrast, semantic dialogs, image attribution and pull-request walkthrough modes moved the renderer toward a reusable presentation runtime rather than a single demo flow.
Interaction architecture
System shape
Current constraint
The engine can continue expanding its feature surface, but further complexity is no longer the primary objective. The next constraint is product validation: identify a repeatable explanation workflow with measurable return usage and let that evidence determine which system capabilities deserve further investment.