Webhooks (AI Context)

Why It Matters

AI operations often exceed typical HTTP timeout limits. Training jobs run for hours. Batch processing of thousands of documents takes significant time. Complex agent workflows may execute for minutes. Webhooks let you fire-and-forget these operations, then receive notification when they complete.

This pattern enables better architecture for AI applications. Instead of polling for completion or keeping connections open, your application submits work and moves on. The AI service calls your webhook when finished, delivering results or status. This decoupling allows horizontal scaling and fault tolerance.

For AI engineers building production systems, webhooks are essential for any async AI workflow. Whether you’re processing documents in bulk, running evaluation pipelines, or orchestrating multi-agent systems, webhooks provide the notification layer that ties asynchronous processing back to your application logic.

Implementation Basics

Implementing webhooks in AI applications involves several considerations:

Endpoint design defines your callback contract. Create a dedicated endpoint that receives webhook payloads. Include job identifiers so you can correlate completions with original requests. Use POST for data delivery.

Security prevents abuse. Verify webhook signatures if the sender provides them. Use secret tokens in headers. Validate that payloads match expected schemas. Consider IP allowlisting for critical workflows.

Idempotency handles retries gracefully. Webhook senders often retry on failure. Your endpoint should handle duplicate deliveries without processing the same job twice. Use unique job IDs and track processed events.

Reliability requires proper infrastructure. Return 2xx responses quickly. Acknowledge receipt before doing heavy processing. Queue received webhooks for async handling. Implement dead letter queues for failed processing.

Start by defining your webhook payload schema and endpoint. Add signature verification if your AI service supports it. Log all incoming webhooks for debugging. Build idempotency into your processing logic from the start. Retrofitting is much harder than designing it in.