Cross-Project Learning

Opt-in sharing of anonymized patterns and insights across the Bootspring community

Cross-Project Learning enables sharing anonymized development patterns and insights across the Bootspring community, improving recommendations for everyone.

Overview#

When enabled, Bootspring:

  • Anonymizes your development patterns
  • Contributes insights to the community pool
  • Receives aggregated learnings from other projects
  • Enhances your recommendations with community data

Privacy First#

All data is:

  • Opt-in only - Nothing shared without explicit consent
  • Fully anonymized - No identifying information
  • Aggregated - Individual data never exposed
  • Deletable - Right to be forgotten supported

What Gets Shared#

Patterns (if enabled)#

  • Development workflow patterns
  • Successful code patterns
  • Error resolution patterns

Decisions (if enabled)#

  • Decision types (not content)
  • Outcome success rates
  • Impact scores

Workflows (if enabled)#

  • Workflow completion rates
  • Phase durations
  • Success metrics

What's Never Shared#

  • Project names or identifiers
  • File paths or code content
  • User information
  • API keys or secrets
  • Business logic
  • Any identifying information

Enabling Cross-Project Learning#

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Community Insights#

Viewing Insights#

Access aggregated community learnings via CLI:

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Community insights include pattern data (e.g., "Using database migrations reduces deployment failures by 85%"), decision outcomes (e.g., "OAuth providers reduce auth support tickets by 70%"), and workflow metrics (e.g., "Feature development workflow average completion: 4.2 days").

Insights automatically enhance Bootspring's recommendations for your project.

Viewing Your Contributions#

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Data Transparency#

Export Your Data#

See exactly what has been shared:

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Delete Your Data#

Exercise your right to be forgotten:

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After revoking:

  • No new data will be shared
  • Previous contributions are deleted
  • You can still view public community insights

How Anonymization Works#

Path Anonymization#

File paths are stripped of identifying information. For example, /Users/john/projects/my-secret-app/src/auth/login.ts becomes [PROJECT]/auth/anon_a7b3c9d2.ts.

Field Removal#

Sensitive fields are automatically removed:

  • email, password, secret, key, token
  • api_key, auth, credential, private
  • phone, address, name, username

Identifier Hashing#

Remaining identifiers are hashed into anonymous tokens (e.g., user_12345 becomes anon_8f4d2e6a9b1c).