Prompting and Prompt Engineering
What may the AI produce, what must it never decide, and what evidence lets a person approve the result? Invest in prompt structure when the task is consequential, repeated, ambiguous, or difficult to review.
What You Will Be Able to Decide
- Explain prompting and prompt engineering in product and business terms.
- Apply this decision: Invest in prompt structure when the task is consequential, repeated, ambiguous, or difficult to review.
- Recognise this material risk: the team repeatedly edits wording while leaving the task, evidence, and acceptance standard undefined.
- Use this review: Run one customer email through the intake tool with missing context, ambiguous intent, and a request that needs human approval.
A founder is deciding what to delegate to AI and what evidence to require before accepting the result. This lesson gives you a concrete question to take into a build brief, proposal review, or product decision.
What may the AI produce, what must it never decide, and what evidence lets a person approve the result? The course example is An AI assisted intake tool that turns customer emails into draft tasks; use it to decide what evidence would justify the choice before a builder implements it.
What Does Prompting and Prompt Engineering Mean for Your Product?
A founder is deciding what to delegate to AI and what evidence to require before accepting the result.
Use the illustrative service for this course (An AI assisted intake tool that turns customer emails into draft tasks) to make the choice concrete. What may the AI produce, what must it never decide, and what evidence lets a person approve the result?
Technical term
Prompting and Prompt Engineering
Prompting supplies an instruction; prompt engineering deliberately structures context, constraints, examples, tools, and evaluation for a repeatable result.
How Should a Founder Use Prompting and Prompt Engineering?
For an ai assisted intake tool that turns customer emails into draft tasks, ask what would happen if the team repeatedly edits wording while leaving the task, evidence, and acceptance standard undefined.
For this decision, the useful standard is that the output satisfies explicit constraints and survives review outside the conversation that produced it.
- Decision: Invest in prompt structure when the task is consequential, repeated, ambiguous, or difficult to review.
- Evidence to request: show that the output satisfies explicit constraints and survives review outside the conversation that produced it.
- Owner: name who will respond if the team repeatedly edits wording while leaving the task, evidence, and acceptance standard undefined.
- Record the result in the AI work brief, review record, and acceptance criteria.
- Practical review: Run one customer email through the intake tool with missing context, ambiguous intent, and a request that needs human approval.
How Do You Choose an Approach to Prompting and Prompt Engineering?
What may the AI produce, what must it never decide, and what evidence lets a person approve the result? Invest in prompt structure when the task is consequential, repeated, ambiguous, or difficult to review.
The risk is that the team repeatedly edits wording while leaving the task, evidence, and acceptance standard undefined. Compare a simpler option with the proposed one, including who will operate either choice.
- Describe the user or business outcome that must be protected.
- Identify the most credible failure and its consequence.
- Compare the simplest adequate approach with one realistic alternative.
- Set a review point for when the decision may need to change.
What Evidence Should You Accept for Prompting and Prompt Engineering?
What Warning Signs Should You Look For?
- The proposal does not address this risk: the team repeatedly edits wording while leaving the task, evidence, and acceptance standard undefined.
- Nobody can show whether the output satisfies explicit constraints and survives review outside the conversation that produced it.
- The decision has no named owner or review point.
What Should You Ask a Consultant?
- What changes for the user if we choose this approach to prompting and prompt engineering?
- How have we reduced or accepted this risk: the team repeatedly edits wording while leaving the task, evidence, and acceptance standard undefined.
- Can you demonstrate that the output satisfies explicit constraints and survives review outside the conversation that produced it?
- Who owns the result, and when will we reconsider it?
Key takeaway
Key Takeaway
Invest in prompt structure when the task is consequential, repeated, ambiguous, or difficult to review. Ask for evidence against the specific risk: the team repeatedly edits wording while leaving the task, evidence, and acceptance standard undefined.