AI Worker Examples
Examples are where the worker pattern becomes operational: a short problem statement, a worker spec, schemas, and how failures are handled.
All examples here are product-neutral. Treat them as starting points you can adapt to your own orchestrator, runtime, and model choices.
Examples#
- Email Summarization Worker — Summarize a thread and extract next actions under tight time and token limits.
- Code Review Worker — Review a diff and return actionable issues with a coarse risk rating.
- Data Validation Worker — Validate records against rules and schemas, returning structured errors.
- Web Scrape Worker — Fetch a page, extract fields, and return a normalized JSON payload.
- AWS Lambda Worker — A worker packaged as a Lambda function with explicit resource limits and logs.
- Queue-Based Worker — A worker that consumes messages with idempotency keys and backpressure.
- Validator Worker — A dedicated worker that checks another worker’s output before side effects.
- Aggregator Worker — Merge partial results into a single output contract, with conflict handling.
See also#
FAQ#
Are these examples tied to a specific vendor?
No. They describe contracts and operational behavior that you can implement anywhere.
Should I copy these schemas directly?
Use them as a baseline, then tailor fields to your runtime, tools, and observability conventions.
How many examples do I need in a real system?
Start with a handful of high-leverage workers (ingestion, validation, summarization) and expand as you identify stable capabilities.