Automation prep: prompts as pseudo-steps

Automation prep: prompts as pseudo-steps

Why it matters: Automation works when prompts become explicit pseudo-steps with inputs and outputs.

Goals

• Write prompts as pseudo-steps.
• Define inputs/outputs per step.
• Add error handling rules.

Key definitions

• Pseudo-steps: A sequence of instructions that a human or system can execute repeatedly.
• Input validation: Rules that ensure required fields exist and are in the right shape.
• Error handling: What to do when the model is uncertain or output fails QA.

Workflow (step-by-step)

1. Write the workflow as numbered steps with input/output contracts.
2. Add required fields and defaults.
3. Add failure rules (ask questions, stop, or escalate).
4. Add a QA step that checks criteria.
5. Test with 2 real inputs, including one messy input.

Example (good vs bad)

✅ Good: A prompt that can be automated because steps and contracts are explicit.

❌ Bad: A vague prompt that depends on hidden context and breaks in automation.

Checklist

• Inputs defined.
• Outputs structured.
• Failure rules exist.
• QA step exists.

Metrics / criteria

• Automation readiness: step-by-step, no missing inputs.
• Measurable: You can say whether the output is correct/complete (pass/fail or a score).
• Effort: You can produce the result in 15–30 minutes using the workflow.
• Clarity: Another person can run your prompt and get a similar outcome.

Common mistakes + fixes

• Pitfall: Automating an unstable prompt. Fix: Stabilize with a checklist and tests first.
• Pitfall: Vague instructions. Fix: Add constraints, examples, and a success checklist.
• Pitfall: One-shot prompting. Fix: Iterate: draft → critique → revise → verify.
• Pitfall: No validation. Fix: Add QA steps, tests, and explicit “what counts as done”.

Student tasks

1. Apply the workflow to one real work task related to automation prep: prompts as pseudo-steps.
2. Create a small artifact: prompt, checklist, rubric, table, draft, or decision note.
3. Run one quality check and record what changed after the check.
4. Write a 3-sentence reflection: what worked, what failed, and what you will reuse.

Useful external sources

• OpenAI prompt engineering guide: https://platform.openai.com/docs/guides/prompt-engineering — Prompt structure, iteration, constraints, and evaluation habits.
• NIST AI Risk Management Framework: https://www.nist.gov/itl/ai-risk-management-framework — Risk framing, governance language, and verification mindset.
• OWASP Top 10 for Large Language Model Applications: https://owasp.org/www-project-top-10-for-large-language-model-applications/ — Practical AI safety risks such as prompt injection, leakage, and insecure output handling.
• Google People + AI Guidebook: https://pair.withgoogle.com/guidebook/ — Human-centered AI design, user control, feedback, and failure modes.

Bibliography

• OpenAI prompt engineering guide. https://platform.openai.com/docs/guides/prompt-engineering
• NIST AI Risk Management Framework. https://www.nist.gov/itl/ai-risk-management-framework
• OWASP Top 10 for Large Language Model Applications. https://owasp.org/www-project-top-10-for-large-language-model-applications/
• Google People + AI Guidebook. https://pair.withgoogle.com/guidebook/