CRITICAL GUIDELINES
Windows File Path Requirements
MANDATORY: Always Use Backslashes on Windows for File Paths
When using Edit or Write tools on Windows, you MUST use backslashes (\) in file paths, NOT forward slashes (/).
Examples:
- WRONG:
D:/repos/project/file.tsx - CORRECT:
D:\repos\project\file.tsx
This applies to:
- Edit tool file_path parameter
- Write tool file_path parameter
- All file operations on Windows systems
Documentation Guidelines
NEVER create new documentation files unless explicitly requested by the user.
- Priority: Update existing README.md files rather than creating new documentation
- Repository cleanliness: Keep repository root clean - only README.md unless user requests otherwise
- Style: Documentation should be concise, direct, and professional - avoid AI-generated tone
- User preference: Only create additional .md files when user specifically asks for documentation
Salesforce Data Cloud Integration Patterns (2025)
What is Salesforce Data Cloud?
Salesforce Data Cloud is a real-time customer data platform (CDP) that unifies data from any source to create a complete, actionable view of every customer. It powers AI, automation, and analytics across the entire Customer 360 platform.
Key Capabilities:
- Data Ingestion — Connect 200+ sources (Salesforce, external systems, data lakes)
- Data Harmonization — Map disparate data to unified data model
- Identity Resolution — Match and merge customer records across sources
- Real-Time Activation — Trigger actions based on streaming data
- Zero Copy Architecture — Query data in place without moving it
- AI/ML Ready — Powers Einstein, Agentforce, and predictive models
- Vector Database (GA March 2025) — Store and query unstructured data with semantic search
- Hybrid Search (Pilot 2025) — Combine semantic and keyword search for accuracy
Reference Map
Detailed material lives in references/. Load only what the current task needs.
| Topic | File | When to load |
|-------|------|--------------|
| Data ingestion (CDC streaming, batch API, Snowflake/Databricks Zero Copy) | references/ingestion-patterns.md | Configuring data sources, importing CSV/SFTP/S3 data, setting up Zero Copy to a warehouse |
| Identity resolution & authentication | references/identity-resolution.md | Defining match rules, reconciliation, custom matching, JWT Bearer auth |
| Real-time activation (Flow, Agentforce, Reverse ETL, calculated insights, segmentation, Data Cloud SQL) | references/activation-patterns.md | Triggering downstream actions, segmentation, Agentforce grounding, SQL queries |
| Vector Database & semantic/hybrid search | references/vector-database.md | Unstructured data indexing, semantic search, Einstein Copilot Search, multi-language search |
Data Cloud Architecture
┌──────────────────────────────────────────────────────────┐
│ Data Sources │
│ Salesforce CRM │ External Apps │ Data Warehouses │ APIs │
└────────┬─────────────────┬──────────────┬───────────┬────┘
│ │ │ │
┌────▼─────────────────▼──────────────▼───────────▼────┐
│ Data Cloud Connectors & Ingestion │
│ ├─ Real-time Streaming (Change Data Capture) │
│ ├─ Batch Import (scheduled/on-demand) │
│ └─ Zero Copy (Snowflake, Databricks, BigQuery) │
└────────────────────────┬─────────────────────────────┘
│
┌────────────────────────▼─────────────────────────────┐
│ Data Model & Harmonization │
│ ├─ Map to Common Data Model (DMO objects) │
│ ├─ Identity Resolution (match & merge) │
│ └─ Data Transformation (calculated insights) │
└────────────────────────┬─────────────────────────────┘
│
┌────────────────────────▼─────────────────────────────┐
│ Unified Customer Profile (360° View) │
│ ├─ Demographics, Transactions, Behavior, Events │
│ └─ Real-time Profile API for instant access │
└────────────────────────┬─────────────────────────────┘
│
┌────────────────────────▼─────────────────────────────┐
│ Activation & Actions │
│ ├─ Salesforce Flow (real-time automation) │
│ ├─ Marketing Cloud (segmentation/journeys) │
│ ├─ Agentforce (AI agents) │
│ ├─ Einstein AI (predictions/recommendations) │
│ └─ External Systems (reverse ETL) │
└──────────────────────────────────────────────────────┘
Core Workflow
- Identify use case — Ingestion, identity, segmentation, activation, or unstructured/AI search? Pick the matching reference.
- Map data sources — CRM CDC (real-time), external batch (S3/SFTP), or warehouse Zero Copy.
- Define DMOs and matching — Map source fields to Data Model Objects; configure identity resolution match + reconciliation rules.
- Build insights / segments — Calculated insights for KPIs (LTV, churn risk); segments for activation targets.
- Activate — Flow / Platform Events / Agentforce actions / Reverse ETL data actions.
- Validate — Use Data Cloud SQL workbench, check sync logs, monitor identity resolution metrics.
Best Practices
Performance
- Use Zero Copy for large datasets (>10M records)
- Batch imports outside business hours
- Index frequently queried fields in Data Cloud
- Limit real-time triggers to critical events
- Cache unified profiles when possible
Security
- Field-level security applies to Data Cloud queries from Salesforce
- Data masking for PII in non-production environments
- Encryption at rest and in transit (TLS 1.2+)
- Audit logging for all data access
- Role-based access control (RBAC) for Data Cloud users
Data Quality
- Data validation before ingestion
- Deduplication rules at source and in Data Cloud
- Data lineage tracking (know source of each field)
- Quality scores for unified profiles
- Regular data audits and cleansing
Resources
- Data Cloud Documentation: https://developer.salesforce.com/docs/data/data-cloud-int/guide
- Zero Copy Partner Network: https://www.salesforce.com/data/zero-copy/
- Data Cloud Pricing: Part of Customer 360 platform, usage-based pricing
- Trailhead: "Data Cloud Basics" and "Data Cloud for Developers"