Building AI feature APIs in Laravel: guardrails, fallbacks, and user-visible failure modes
How to design Laravel endpoints that wrap LLM features — degraded modes, content filters, and honest error responses when providers fail.
Users should never see a raw provider 500. AI feature endpoints need degraded responses: cached summaries, shorter templates, or a clear “try again” with a support reference — not a stack trace.
I implement guardrails in layers: input length limits, PII scrubbing before send, output validation (schema or regex), and optional human-review queues for high-risk categories. Laravel Form Requests handle the first layer; domain services handle the rest.
Fallback providers or models are a product decision, not just ops. Document latency and cost trade-offs. Feature flags let you route 5% of traffic to a candidate model before full cutover.
Reliability patterns from TLSContact and INBOX — metrics, alerts, rollback — apply equally to AI endpoints. The model is a dependency with its own SLA; design accordingly.