8.4 KiB
Google Cloud Product OS Technical Specification
Product-Centric IDE + SaaS Autopilot Platform
- 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.
- 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
-
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 │ └──────────────┘ -
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
- 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" }
- 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
- 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
- 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
- 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" }
- 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
- Supported Languages
TypeScript / Node
Python
No additional languages in v1.
- 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
- Non-Goals
The platform does NOT:
Replace VS Code generically
Support all frameworks
Support multi-cloud
Allow raw IAM editing
Execute cloud commands locally
-
Repository Structure /platform /client-ide /vscodium /extensions /backend /control-plane /executors /contracts /infra /docs
-
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
- 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.