Google Cloud Product OS Technical Specification Product-Centric IDE + SaaS Autopilot Platform 1. Purpose This document defines the technical architecture, components, interfaces, and implementation plan for building a: Google Cloud–native, Gemini-powered Product Operating System (Product OS) The platform unifies: Code development Product launch Marketing automation Analytics and causality Growth optimization Support automation Experimentation Infrastructure management into a single product-centric IDE and automation system. This is not a general-purpose IDE. It is a Product OS for launching and operating SaaS products on Google Cloud. 2. Core Design Principles 2.1 Product-Centric Orientation The platform optimizes for: Shipping products Launching features Running marketing Optimizing growth Operating infrastructure Automating decisions Not for: Arbitrary coding workflows Multi-cloud portability Framework experimentation 2.2 Opinionated for Google Cloud The platform is single-cloud and deeply integrated with: Cloud Run Cloud Build Artifact Registry Firestore Cloud SQL BigQuery Pub/Sub Vertex AI (Gemini) No AWS or Azure abstraction layers are supported. 2.3 Backend Tool Execution (Security Model) All automation executes on the backend. The IDE: Never runs gcloud Never runs Terraform Never holds GCP credentials Never touches databases directly Instead: IDE / Supervisor AI ↓ Control Plane API ↓ Executors ↓ GCP Services 2.4 AI as a Product Operator The AI is not a coding assistant. It is a: Product Operator AI Responsibilities: Interpret product goals Read analytics and insights Decide actions Dispatch tools Enforce policies Learn from outcomes 3. High-Level Architecture ┌─────────────────────────────┐ │ VSCodium IDE Client │ │ (Product-Centric UI Shell) │ └──────────────┬──────────────┘ │ ▼ ┌──────────────────────────┐ │ Control Plane API │ │ (Tool Router + Policy) │ └──────────────┬───────────┘ │ ┌──────────────┬───────────┼─────────────┬──────────────┐ ▼ ▼ ▼ ▼ ▼ Deploy Executor Analytics Exec Firestore Exec SQL Exec Missinglettr Exec Cloud Build+Run BigQuery Firestore Cloud SQL Social Posting │ ┌──────▼───────┐ │ GCS Store │ │ Artifacts │ └──────────────┘ 4. IDE Client Architecture 4.1 Base Editor VSCodium distribution OpenVSX marketplace Preinstalled extensions Preconfigured settings Custom UI panels 4.2 Product-Centric Navigation The IDE must expose: Product OS ├── Code ├── Marketing ├── Analytics ├── Growth ├── Support ├── Experiments └── Infrastructure Each section is: First-class AI-assisted Connected to backend tools 4.3 IDE Responsibilities The IDE handles: File editing Patch preview & application Project context collection Tool invocation UI Artifact viewing Logs & traces display The IDE does NOT: Execute cloud commands Store secrets Perform deployments Perform database queries 5. Control Plane API 5.1 Purpose The Control Plane is the central orchestration backend. Responsibilities: Auth Tool registry Tool invocation routing Policy enforcement Run tracking Artifact storage (GCS) Gemini proxy 5.2 Core Endpoints POST /tools/invoke GET /runs/{run_id} GET /runs/{run_id}/logs GET /tools GET /artifacts/{run_id} 5.3 Tool Invocation Contract Request { "tool": "cloudrun.deploy_service", "tenant_id": "t_123", "workspace_id": "w_456", "input": { "service_name": "marketing-gateway", "repo": "github.com/org/repo", "ref": "main", "env": "prod" }, "dry_run": false } Response { "run_id": "run_20260119_abc", "status": "queued" } 6. Tool Registry All executable actions are declared as tools. 6.1 Tool Schema tools: cloudrun.deploy_service: description: Deploy a Cloud Run service input_schema: service_name: string repo: string ref: string env: string output_schema: service_url: string risk: medium executor: deploy-executor 6.2 Registry Responsibilities Input validation Output validation Risk classification Executor routing Used by: IDE Supervisor AI Web dashboard 7. Executors (Domain Services) Each executor is a Cloud Run service with its own service account. 7.1 Deploy Executor Purpose: Build and deploy services Tools: cloudrun.deploy_service cloudrun.tail_logs cloudrun.rollback GCP APIs: Cloud Build Cloud Run Artifact Registry IAM: roles/cloudbuild.builds.editor roles/run.admin (scoped) roles/artifactregistry.writer 7.2 Analytics Executor (OpsOS) Purpose: Product intelligence and causality Tools: analytics.get_funnel_summary analytics.get_top_drivers analytics.get_anomalies GCP APIs: BigQuery BigQuery ML IAM: roles/bigquery.dataViewer roles/bigquery.jobUser 7.3 Firestore Executor Purpose: Company Brain + configs Tools: firestore.get_company_brain firestore.update_company_brain GCP APIs: Firestore IAM: roles/datastore.user 7.4 SQL Executor Purpose: Transactional summaries Tools: sql.get_subscription_summary sql.get_user_metrics GCP APIs: Cloud SQL IAM: roles/cloudsql.client DB-level users 7.5 Missinglettr Executor Purpose: Social publishing Tools: missinglettr.publish_campaign missinglettr.get_campaign_status Secrets: Missinglettr API tokens IAM: roles/secretmanager.secretAccessor 8. Data Storage 8.1 Firestore Used for: Company Brain Tool registry Policy configs Style profiles Run metadata 8.2 GCS Used for: Logs AI outputs Generated patches Deployment artifacts Prompt snapshots 8.3 BigQuery Used for: Event warehouse Funnels Causality models Experiment results 9. AI Integration 9.1 Gemini Proxy All AI calls go through Control Plane. Responsibilities: Auth Rate limiting Prompt registry Logging Cost controls 9.2 AI Patch Contract Gemini must return: { "files": [ { "path": "src/main.ts", "diff": "@@ -1,3 +1,6 @@ ..." } ], "commands": [ "npm test" ], "summary": "Add logging middleware" } 10. IAM Strategy 10.1 Users OAuth only No GCP IAM No key files 10.2 Backend Workload identity No long-lived keys Least privilege Per-executor roles 11. Supported Languages TypeScript / Node Python No additional languages in v1. 12. SaaS Autopilot Layer A Supervisor AI Agent runs in Vertex AI Agent Designer. It calls the same tools as the IDE. Supervisor AI → Control Plane → Executors 13. Non-Goals The platform does NOT: Replace VS Code generically Support all frameworks Support multi-cloud Allow raw IAM editing Execute cloud commands locally 14. Repository Structure /platform /client-ide /vscodium /extensions /backend /control-plane /executors /contracts /infra /docs 15. Implementation Phases Phase 1 – Core Control Plane API Deploy Executor Gemini Proxy IDE Deploy UI Phase 2 – Intelligence Firestore Executor Analytics Executor Funnel + driver tools Phase 3 – Automation Missinglettr Executor Growth + Experiments Supervisor AI 16. Final Statement This system is a: Google Cloud–native Product Operating System for launching, growing, and automating SaaS products using Gemini and backend-controlled automation. Optional Next Steps Generate Control Plane API scaffold Generate Tool Registry schema Generate VSCodium extension skeleton Generate Terraform base If you want, I can next generate: The Control Plane API OpenAPI spec The Tool Registry schema file The First Executor service skeleton The VSCodium extension skeleton Tell me which one you want first.