
Gilad Foyer developed and enhanced automation and backend features across port-labs/port-docs and port-labs/terraform-provider-port-labs, focusing on workflow reliability and advanced data handling. He implemented an AI-assisted GitHub Actions workflow in Go and YAML to automate documentation reviews, streamlining CI/CD for the Claude docs pipeline. In Terraform provider development, Gilad resolved complex schema mismatches and value conversion bugs, enabling deeper nested dataset rules and improving state stability for policy-as-code workflows. His work demonstrated depth in Go, Terraform, and API integration, with careful attention to recursive data structures, robust testing, and schema evolution, resulting in more reliable and expressive infrastructure automation.
February 2026 — Key deliverable: a critical fix to the dataset rule schema in port-labs/terraform-provider-port-labs to support deeper nesting of dataset rules and remove a blocking schema mismatch. Implemented by increasing datasetRuleSchema depth from 2 to 10, enabling up to 10 levels of nested rules in actions. This eliminates the 'Struct defines fields not found in object: rules' error for 3+ levels, stabilizing policy-as-code workflows and reducing plan/apply failures. The change is tracked in commit 30e10876613e62171d1f822f15fa7ab7a6435e6c. Technologies: Go, Terraform Plugin SDK, schema handling, and thorough regression checks. Business value: higher expressiveness for complex policies, smoother Terraform operations, and improved reliability for customers using advanced dataset rules.
February 2026 — Key deliverable: a critical fix to the dataset rule schema in port-labs/terraform-provider-port-labs to support deeper nesting of dataset rules and remove a blocking schema mismatch. Implemented by increasing datasetRuleSchema depth from 2 to 10, enabling up to 10 levels of nested rules in actions. This eliminates the 'Struct defines fields not found in object: rules' error for 3+ levels, stabilizing policy-as-code workflows and reducing plan/apply failures. The change is tracked in commit 30e10876613e62171d1f822f15fa7ab7a6435e6c. Technologies: Go, Terraform Plugin SDK, schema handling, and thorough regression checks. Business value: higher expressiveness for complex policies, smoother Terraform operations, and improved reliability for customers using advanced dataset rules.
January 2026 focused on hardening dynamic filtering in self-service actions and enabling advanced, nested dataset filtering for the Port API integration. Key work delivered improves correctness of dynamic expressions, increases filtering flexibility, and strengthens test coverage for complex scenarios.
January 2026 focused on hardening dynamic filtering in self-service actions and enabling advanced, nested dataset filtering for the Port API integration. Key work delivered improves correctness of dynamic expressions, increases filtering flexibility, and strengthens test coverage for complex scenarios.
December 2025 monthly summary for port-labs/terraform-provider-port-labs: Delivered a critical value-conversion bug fix for Terraform resources (array_props.object_items.default). The change ensures default values are written to the API in the expected path (property.Default) and fixes the read path to convert API responses to List[Map[String]] instead of List[String], eliminating a type mismatch and state drift during plan/apply.
December 2025 monthly summary for port-labs/terraform-provider-port-labs: Delivered a critical value-conversion bug fix for Terraform resources (array_props.object_items.default). The change ensures default values are written to the API in the expected path (property.Default) and fixes the read path to convert API responses to List[Map[String]] instead of List[String], eliminating a type mismatch and state drift during plan/apply.
Month: 2025-08 — Port Docs team delivered AI-assisted PR workflow and CI enhancements for the Claude docs pipeline in port-labs/port-docs. Implemented a new GitHub Actions workflow to automate documentation reviews using Claude AI on PRs, with CI refinements to trigger rules, checkout behavior, and ongoing documentation maintenance for the Claude docs pipeline. These changes stabilize the docs workflow, shorten review cycles, and improve consistency and quality of documentation.
Month: 2025-08 — Port Docs team delivered AI-assisted PR workflow and CI enhancements for the Claude docs pipeline in port-labs/port-docs. Implemented a new GitHub Actions workflow to automate documentation reviews using Claude AI on PRs, with CI refinements to trigger rules, checkout behavior, and ongoing documentation maintenance for the Claude docs pipeline. These changes stabilize the docs workflow, shorten review cycles, and improve consistency and quality of documentation.

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