Prompt Automation & Workflows

Workflows connect prompts with checks, code, and other services to make reliable systems.

Common building blocks:

• Orchestrator / Coordinator: a small program that calls prompts in order, applies business logic, and decides the next step.
• Validator: quick checks (regex, schema, or another model) that confirm outputs are correct before using them further.
• Normalizer: code that cleans and standardizes values (dates, names, currencies) so downstream prompts get tidy inputs.
• Retry & Fallback: try again with a stricter prompt or fall back to deterministic code if the model keeps failing.

Simple example workflow:

1. User submits text.
2. LLM extracts structured fields (title, date, summary).
3. Code validates and normalizes fields (check date format, trim long values).
4. LLM generates final content using the cleaned fields.
5. Validator checks the final output; if it fails, run a fallback or alert a human.

Practical tips:

• Keep each step small and testable — small steps are easier to debug.
• Cache results when possible to reduce cost for repeat requests.
• Make steps idempotent (safe to run multiple times) to simplify retries.
• Add observability: track how often validators fail and why.

These patterns let you blend the creativity of models with the safety and repeatability of code.