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