Resilient LLM Content Automation

A scheduled content engine engineered around the unglamorous reality of LLMs in production: overload, quotas, and malformed output — with no silent failures.

How it works

The problem

LLM-powered content jobs fail in production for boring reasons — provider overload (HTTP 529), quota limits, malformed responses — and a single unhandled failure can quietly break a scheduled job for days before anyone notices.

The approach

1. 1

   A multi-node LLM pipeline generates long-form content and matching imagery, then publishes to a CMS.

2. 2

   Reliability patterns on every model call: retry-with-backoff, an Opus→Sonnet fallback branch when the primary model stays overloaded, and a self-referencing error workflow that emails any failure with full execution context.

3. 3

   Secrets were moved out of node parameters into managed credentials — nothing hardcoded.

Highlights

• Built for unattended, scheduled operation with no silent failures.
• Graceful degradation: quality-first primary model, automatic fallback under load.
• Security-conscious: managed credentials, never hardcoded keys.

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