681 lines
7.6 KiB
Markdown
681 lines
7.6 KiB
Markdown
Google Cloud Product OS
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Product-Centric IDE + SaaS Autopilot Platform (Requirements & Architecture)
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Vision
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Build a Product-Centric IDE and Automation Platform dedicated exclusively to:
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Launching, growing, and operating SaaS products on Google Cloud
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This is NOT a general-purpose IDE.
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This is a Product Operating System (Product OS) designed to unify:
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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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AI-driven automation
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into one coherent platform.
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It delivers:
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A Cursor-like experience
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Without Cursor cost
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Powered by Gemini (Vertex AI)
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Optimized specifically for Google Cloud
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Focused exclusively on building & automating products
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Core Product Principles
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1. Product-Centric, Not Code-Centric
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This platform optimizes for:
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Shipping, launching, growing, and optimizing products, not just writing code.
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2. Opinionated for Google Cloud
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This system is:
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Cloud Run-first
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Firestore / Cloud SQL-native
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BigQuery-native
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Cloud Build-native
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Gemini-native
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No AWS, no Azure, no multi-cloud abstraction.
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3. Automation First
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Everything is:
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Automatable
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Observable
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Auditable
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Optimizable
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4. AI as a Product Operator
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The AI is not just a coding assistant.
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It is a:
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Product Operator AI
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capable of coordinating marketing, growth, support, analytics, and code.
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IDE Structure: Product-Centric Layout
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Instead of a traditional IDE layout, the system 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 first-class and AI-assisted.
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Section Requirements
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1. Code Section
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Purpose:
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Build and deploy product services
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Must support:
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Cloud Run services
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Cloud SQL / Firestore integration
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Secrets management
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Logs & traces
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Rollbacks
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Service templates
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Not required:
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Arbitrary framework support
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Every programming language
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Optimized languages:
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TypeScript / Node
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Python
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2. Marketing Section
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Purpose:
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Automate go-to-market and content execution
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Must support:
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Campaign generation
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Social scheduling (Missinglettr)
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Blog generation & updates
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Landing page updates
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Brand voice control
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Product update → campaign pipeline
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AI must:
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Convert product changes into launch content
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Adapt content to brand style
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3. Analytics Section
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Purpose:
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Understand product performance and causality
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Must support:
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Funnels
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Retention
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Activation
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Cohorts
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LTV
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Causal drivers
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Experiment results
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NOT a SQL editor.
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This is a Product Intelligence Interface.
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AI must answer:
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“Why did conversion change?”
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“What caused activation to drop?”
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“What should we test next?”
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4. Growth Section
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Purpose:
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Optimize onboarding and conversion
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Must support:
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Funnel definitions
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Onboarding flows
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Growth experiments
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A/B tests
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Nudge systems
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Conversion optimization
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AI must:
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Detect drop-offs
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Recommend experiments
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Evaluate uplift
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5. Support Section
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Purpose:
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Integrate customer feedback and product health
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Must support:
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Ticket ingestion
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AI-assisted replies
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Knowledge base generation
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Product issue detection
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Feedback loops into product & marketing
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6. Experiments Section
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Purpose:
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Enable continuous product optimization
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Must support:
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Hypothesis creation
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Experiment creation
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Assignment
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Result analysis
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Causal impact estimation
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Recommendation engine
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7. Infrastructure Section
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Purpose:
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Hide GCP complexity behind product workflows
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Must support:
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Cloud Run provisioning
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Pub/Sub
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Cloud SQL / Firestore
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IAM abstraction
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Deploy / rollback
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Resource health
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No raw IAM or Terraform exposure by default.
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Everything should be expressed as product-level actions.
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AI System Design
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Supervisor AI (Product Operator)
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This is NOT a coding agent.
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It is a:
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Product Operator AI
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capable of coordinating decisions across:
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Marketing
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Growth
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Product
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Support
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Analytics
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Experiments
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Responsibilities:
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Interpret product goals
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Prioritize actions
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Dispatch tasks to tools
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Enforce policies
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Learn from outcomes
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Tool Execution Model (Critical Design Decision)
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Backend Tool Execution (Option 1)
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All tools execute on the backend.
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The IDE:
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NEVER runs gcloud
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NEVER holds cloud credentials
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NEVER touches databases directly
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Instead:
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IDE / Agent → Control Plane API → Executors → GCP Services
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Benefits:
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Security
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Auditing
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Shared automation with SaaS autopilot
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Centralized policy enforcement
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No local cloud configuration
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Control Plane Architecture
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Control Plane API
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A Cloud Run service responsible for:
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Authentication
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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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Core endpoints:
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POST /tools/invoke
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GET /runs/{id}
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GET /runs/{id}/logs
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GET /tools
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GET /artifacts/{run_id}
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Tool Registry
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All actions are formalized as tools.
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Example:
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cloudrun.deploy_service
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analytics.get_funnel_summary
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firestore.update_company_brain
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missinglettr.publish_campaign
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experiments.create_ab_test
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Each tool defines:
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Input schema
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Output schema
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Risk level
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Executor mapping
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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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Executors (Domain Services)
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Each executor is a Cloud Run service with scoped permissions.
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Deploy Executor
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Cloud Build
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Cloud Run
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Artifact Registry
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Analytics Executor
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BigQuery
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Causality modeling
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Funnel analysis
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Firestore Executor
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Company Brain
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Styles
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Configs
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SQL Executor
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Summaries from Cloud SQL
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Read-heavy
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Missinglettr Executor
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Campaign publishing
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Scheduling
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Data Layer
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Firestore
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Company Brain
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Style profiles
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Tool registry
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Policy configs
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Run metadata
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GCS
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Logs
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Artifacts
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AI outputs
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Generated patches
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Trace data
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BigQuery
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Events
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Causality models
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Experiments
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Analytics warehouse
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AI Code Editing Strategy
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We do NOT build a new editor.
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We use:
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VS Code APIs
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Patch-based updates
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Flow:
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AI generates structured diffs
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IDE previews changes
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User approves
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IDE applies locally
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Backend executes deploy/test
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Later:
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Backend can open PRs automatically
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IDE Base Technology
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Editor Base
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✅ VSCodium
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Not Code-OSS directly.
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Reasons:
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Open source
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OpenVSX marketplace
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Low maintenance
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Redistributable
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Fast to ship
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Language Strategy
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We support only:
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TypeScript / Node
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Python
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This allows:
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Better templates
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Better debugging
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Better automation
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Faster AI alignment
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IAM Strategy
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Users
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OAuth only
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No GCP IAM exposure
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Backend Service Accounts
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Least privilege
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Per-executor roles
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No key files
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Workload identity only
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Product vs General IDE: Explicit Non-Goals
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This platform is NOT:
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A general code editor
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A multi-cloud IDE
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A framework playground
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A replacement for VS Code for all use cases
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It IS:
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A Product Operating System
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A SaaS automation platform
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A GCP-native product launcher
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An AI-driven product operator
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Target Users
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Solo founders
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Indie hackers
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Startup teams
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AI-first SaaS companies
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Product-led growth teams
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Strategic Differentiation
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You are not competing with:
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VS Code
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Cursor
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JetBrains
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You are competing with:
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10+ disconnected tools:
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Segment
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HubSpot
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Mixpanel
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Amplitude
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Intercom
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Zapier
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Notion
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Google Cloud Console
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Marketing schedulers
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Experiment platforms
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You replace them with:
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One Product Operating System
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Build Roadmap
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Phase 1: Core Platform
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Control Plane API
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Deploy Executor
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VSCodium Extension (Deploy + Logs)
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Gemini integration
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Phase 2: Product Intelligence
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Firestore Executor (Company Brain)
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Analytics Executor
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Funnel + driver tools
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Phase 3: Automation
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Marketing Executor
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Growth + Experimentation
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Supervisor AI
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Phase 4: Full Autopilot
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Approval workflows
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PR automation
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Continuous optimization
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Multi-tenant SaaS
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Final Statement
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This platform exists to enable:
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One-click product launch, AI-driven growth, and autonomous SaaS operation on Google Cloud.
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It is:
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A Product OS
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An AI Product Operator
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A Cursor-like experience
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A GCP-native automation platform |