EXPLAINME.adoc

Candy Crash — EXPLAINME

This file maps README.adoc claims to their implementation evidence for sceptical developers.

Table of Contents

• "Total Pervasive Ambient Computing for Vehicle Operator Training"
• "Environmental intervention that makes the boundaries between training and living dissolve"
• "Rust core + ReScript UI + SPARK/Ada verification"
• Dogfooded Across The Account
• Known Gaps

"Total Pervasive Ambient Computing for Vehicle Operator Training"

Candy Crash is a framework for training humans to operate vehicles—cars, motorbikes, aircraft, watercraft—through pervasive ambient computing.

— README.adoc

How this is implemented

As of the current state, Candy Crash is a design-stage project with a detailed conceptual framework documented in the README. The src/ directory contains the initial project scaffold. The README makes clear that "the repository currently contains remnants of an earlier approach — a conventional LMS for driving theory" which "must be rebuilt from first principles." The design documentation in ROADMAP.adoc defines five phases (Phase 0: conceptual foundation through Phase 5: validation).

Caveat

No ambient computing infrastructure (sensor mesh, actuator mesh, training intelligence) is implemented yet. Phase 0 (conceptual foundation) is in progress. The project is honest about being pre-implementation.

"Environmental intervention that makes the boundaries between training and living dissolve"

This is not an LMS. This is not e-learning. This is not a course. This is an environmental intervention.

— README.adoc

How this is implemented

The README documents a coherent theoretical framework rooted in embodied cognition (Gibson, Varela et al.), situated learning (Lave & Wenger), and ubiquitous computing (Weiser). The Human Factors Constraints section applies Cognitive Load Theory (Sweller), vigilance decrement research, and Endsley’s three-level situation awareness model as hard design constraints — preventing the system from over-claiming ambient training’s effectiveness.

Caveat

The theoretical framework is documented but not yet translated into running code. References cite peer-reviewed literature (Endsley 1995, Sweller 1988, Mark et al. 2008) rather than unpublished assertions.

"Rust core + ReScript UI + SPARK/Ada verification"

Core Runtime: Rust. User Interfaces: ReScript. Formal Verification: SPARK/Ada.

— README.adoc

How this is implemented

The technology direction is declared in the README’s "Technology Direction" section with explicit rationale: Rust for real-time sensor/actuator loops, ReScript for type-safe UI, SPARK/Ada for aviation-adjacent safety requirements. The ROADMAP.adoc maps these to implementation phases. Cargo.toml confirms Rust as the build system.

Caveat

None of the language implementations are complete yet — this is the declared direction, not a done state. The earlier Rails/Ruby codebase in the repository represents the wrong paradigm and is scheduled for removal.

Dogfooded Across The Account

Technology / Pattern	Used here	Also used in
Embodied cognition / pervasive computing theory	Design framework for ambient training	heterogenous-mobile-computing (similar ambient AI routing concept)
Rust/SPARK architecture	Planned for safety-critical sensor loops	launch-scaffolder, ephapax
TPCF contributor framework	Contribution governance model	boj-server
ReScript for UI	Planned for configuration and monitoring	gossamer, panll

Known Gaps

Caution

The repository contains remnant Rails/Ruby code from an earlier LMS approach. The CLAUDE.md for this repo bans Ruby/Rails explicitly. That code should be removed before any Phase 1 implementation begins.

Caution

No empirical validation of transfer effects exists yet — the README correctly flags this as a design implication ("do not assume ambient training transfers to vehicle operation without evidence"). Effectiveness claims require Phase 5 validation studies.