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Development timeline

YourSimulation was built in phases, each one a usable layer on top of the last: a rigorous engine first, then a visual editor, then experiments and storage, and finally analytics, optimization, and an AI companion. This page is the build story.

The story

Phase 1 — Engine

The foundation is a zero-dependency discrete-event simulation kernel: an event calendar, seeded RNG streams, the distributions, and the five node types. Correctness came first — the engine was validated against the closed-form results of M/M/1 and M/M/c queues, so its numbers can be trusted before any UI existed. See discrete-event simulation and queueing theory.

Phase 2 — Canvas editor

A React Flow drag-and-drop canvas for building models visually: drop sources, queues, resources, branches, and sinks, wire them with edges, and edit their parameters. See the architecture.

Phase 3 — Experiment mode & persistence

The engine moved into a Web Worker so long runs never freeze the UI. Run settings (horizon, warmup, replications, seed) became part of the model schema, and a KPI dashboard reported each metric as a mean with a 95% confidence interval. Firebase Auth + Firestore added sign-in and cloud model/experiment storage.

Phase 3.5 — Branding & design system

A light/dark token theme, a branded login screen, and a gradient wordmark — the visual identity layered over the working app.

Phase 4 — Watch mode & domain storytelling

A deterministic event recorder (recordRun) replays a single replication event-by-event, driving skinned animated playback. Domain themes (generic / airport / hospital / logistics / network) plus templates let the same generic engine tell a domain-specific story.

Phase 5 — Analytics & experiment design

Detailed statistics — percentiles, histograms, and time series — rendered as SVG charts, plus the ability to save experiments and compare them side-by-side.

Phase 6 — Cross-Entropy optimizer

optimize() and an Optimize tab: a Cross-Entropy search that finds the cheapest configuration meeting your service targets, instead of guessing. See Cross-Entropy optimization.

Phase 7 — AI companion

A provider-neutral, tool-using agent (Anthropic + Gemini, bring-your-own key) that can read and propose model edits; the user reviews and clicks Apply.

Add-on — JSON CLI + Claude Code skill

A JSON-in/JSON-out CLI (validate / run / optimize / record) over the engine, and a Claude Code skill that drives it from natural language. See the tutorial.

Add-on — Documentation & theory

This documentation site: theory pages, the tutorial, the glossary, this timeline, and the architecture map.

At a glance

PhaseThemeHighlights
1EngineZero-dep DES kernel; validated against M/M/1 & M/M/c
2Canvas editorReact Flow drag-and-drop model building
3Experiment & persistenceEngine in a Web Worker; run-settings schema; KPI dashboard (mean ± 95% CI); Firebase auth + Firestore
3.5Branding & design systemLight/dark token theme; branded login; gradient wordmark
4Watch mode & storytellingrecordRun recorder; animated playback; domain themes + templates
5Analytics & experiment designPercentiles, histograms, time series; SVG charts; saved-experiment comparison
6Cross-Entropy optimizeroptimize() + Optimize tab
7AI companionProvider-neutral tool-using agent (Anthropic + Gemini), propose → Apply
Add-onCLI + Claude Code skillvalidate/run/optimize/record + the skill
Add-onDocumentation & theoryThis site