AI Coding Governance with Spec-Driven Prompts
Govern AI-assisted coding with spec-driven prompts: define scope, boundaries, evidence, and audit trails before generated code reaches review.
Spec Coding Blog
Paginated browsing for the full Spec Coding article archive. These pages keep long lists readable while preserving direct links.
AI Coding PR Review with Acceptance Criteria
Review AI-generated pull requests against acceptance criteria: inspect the diff, run evidence checks, and catch failures a quick skim misses.
AI Coding Risk Register Before Merge
Use a pre-merge risk register for AI-generated code: flag auth, data, contract, migration, rollback, and observability risks.
AI Coding with Test-Evidence Gates
Use test-evidence gates for AI-generated code: require meaningful tests before merge and catch hallucinated implementations before release.
API Change Management for AI-Generated Clients
Manage API changes for AI-generated clients with structured changelogs, announcement channels, compatibility rules, and CI gates.
API Error Taxonomy for AI-Assisted Integrations
Design API error taxonomies AI-generated clients can use, with stable codes, retry categories, and machine-readable details.
API Schema Diff Review Before Release
How to run an API schema diff review before every release: what diff tools catch, what they miss, and the human checks that still matter for OpenAPI and GraphQL.
Designing API Specs for Agentic Clients
Design API specs for LLM-powered agentic clients with discoverable fields, idempotency, dry-runs, semantic descriptions, and safe destructive actions.
Contract Testing Plan: From OpenAPI to CI
Add contract testing from OpenAPI to CI with generated tests, provider checks, consumer expectations, and reliable fixtures.
Data Sync Between Services: Spec Guide
Specify cross-service data sync with ordering guarantees, conflict handling, backfill plans, and event-driven or pull-based tradeoffs.
Designing Idempotent Workflows with Specs
How to specify idempotency keys, deduplication windows, and state-machine transitions so retries and partial failures don't double-charge or corrupt data.
Event-Driven Systems: Specification Patterns
Specification patterns for event-driven systems: schema versioning, command vs fact events, orchestration choices, idempotent handlers, and replay safety.
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