🧭 Developer Blueprint

How to work on this platform β€” repo, internals, pipeline, tests, migration, docs, AI layer

Audience: Claude Code sessions and developers. Internal only. Content verified against the repo: 8 Jul 2026

1. Repo Structure & File Ownership

The monolith was split so parallel Claude sessions can build without overwriting each other. One feature, one file.

Golden rule: two sessions must never edit the same file at the same time. Shared files (js/config.js, js/shared.js, index.html, css/styles.css) are edited by ONE session, in the same session as the feature needing the change. Always git pull before starting, push promptly after committing.
FeatureEdit this fileNotes
Leadership Dashboard KPIsjs/dashboard.jsLoads the shared global data arrays for everyone
Cash flow / balance calculatorjs/cashflow.jsForecast, UC checks, what-if
Reconciliation enginejs/reconciliation.jsMatching, knowledge base, accuracy tracking; rate-limit pattern lives here
Invoicesjs/invoices.jsFetch, render, match, approve, pay
CFVs / rent statementsjs/cfv.jsOverdue rent detection, chase actions
Costs / transactions / income / P&Ljs/costs.js Β· js/transactions.js Β· js/income.js Β· js/pnl.jsFinance section tabs
Money Confidence / Wealthjs/money.js Β· js/wealth.jsPersonal finance layer
Arrearsjs/arrears.js Β· js/ar-variable.jsRent balance per tenancy
Fintable monitorjs/fintable.jsBank sync health
Site map & linksjs/sitemap.jsAlso SOP update requests
AI assistant paneljs/ai-assistant.jsContext blocks per tab live here
Skills / KPI sources / quick taskjs/skills.js Β· js/skills-data.js Β· js/kpi-sources.js Β· js/quick-task.js
Health barsjs/sync-bar.jsregisterSyncBar engine β€” shared, treat like shared.js
Operating Systems pagesos/*/index.htmltasks, operations, strategy, systemisation, team, business-plan-builder β€” loaded via iframe
Standalone iframe pagesfollow-up.html Β· compliance.html Β· ai-brain.htmlEach self-contained
Stylingcss/styles.css (consumes css/tokens.css)Whole-app look changes: tokens.css ONLY
Sidebar / tab shellindex.htmlProtected: OS sidebar items, OS iframe tab panels
Constants, table + field IDsjs/config.jsF, TABLES, INV, REC, PS, PAGE_REGISTRY, AI model IDs

2. JS Internals β€” Globals, Helpers, Conventions

All JS loads as plain <script> tags in one global scope. No bundler, no modules. Load order: config.js β†’ shared.js β†’ feature files.

3. Deploy Pipeline

The repo is the source of truth. Push to main β†’ GitHub Pages auto-deploys in 2-3 minutes β†’ confirm live before declaring done.

4. Testing & Quality Gates

Nothing ships unverified. Kevin never debugs β€” the session that builds it proves it works.

5. Supabase Migration β€” the Shadow Build

Airtable stays the system of record until per-module cutover. A parallel Supabase/Vercel build runs alongside via twins and shims. Spec: docs/supabase-schema-spec.md.

6. Docs & Specs Registry

Which document governs what. If it is not listed here, check STRUCTURE.md before creating a new one.

DocumentGovernsRule
MASTER-PLAN.mdTHE plan: every OD roadmap, launch task, priorityNever create another plan doc. Amendments via Β§13 holding pen, dated + sourced in the Changelog
STRUCTURE.mdWhere every file lives: repo, AI context layer, DriveRead before creating any file; update in the same commit if you add a new location
CLAUDE.mdSession rules: stack, workflow, quality gate, design system, concurrencyThe contract every session works under
PRODUCTISATION.mdDe-Kevining: D1-D9 decisions, tenant modelΒ§5 holds the decided outcomes
docs/supabase-schema-spec.mdTarget Postgres schema, RLS approachMigration source of truth
docs/agent-runtime-spec.mdHow agents execute (engine live since 3 Jul 2026)
docs/agentic-extraction-spec.mdLoom β†’ SOP β†’ agent pipeline (the core product engine)
docs/business-blueprint-spec.mdClient-facing Blueprint tab ("% of work run by AI")v1 = view over existing data
docs/client-profile-questionnaire.mdOnboarding interview that writes tenant_config
docs/airtable-cleanse-2026-07-07.mdRecord of the 7 Jul task cleanseHistorical

7. AI Layer

Everything AI-facing: model routing, prompts, skills, memory. The north star: AI agents execute up to 90% of repeatable operational work.