The 15 Most-Common AI Prompt Time Wasters
In professional settings, poorly structured AI prompts can lead to inefficiencies, such as increased billable time, extended deal cycles, and assumptions that compromise compliance reviews. Professionals must focus on crafting precise prompts to ensure…
In professional settings, poorly structured AI prompts can lead to inefficiencies, such as increased billable time, extended deal cycles, and assumptions that compromise compliance reviews. Professionals must focus on crafting precise prompts to ensure useful outputs, minimizing the need for rework.
Before utilizing AI, it is essential for professionals to comprehend the subject matter thoroughly. AI is a tool that can enhance existing competencies but also amplify gaps in knowledge. Familiarity with the topic allows for better evaluation of AI outputs, ensuring that critical information is not overlooked.
Ensure prompts are neutral and comprehensive. For example, instead of assuming enforceability, ask, "Is this contract enforceable under [law], and what damages might be available?"
Specify details like governing law and relevant roles. For instance, "Is this non-compete enforceable under California law for a software engineer earning $90K?"
Break down complex inquiries into separate prompts to ensure detailed analysis for each component.
Connect prompts to specific decisions, e.g., "Explain force majeure so I can assess whether our supplier’s claim triggers the clause in our 2022 agreement."
Include relevant documents and facts to ensure precise outputs. Abstract inputs will yield abstract outputs.
Frame prompts from a specific perspective, such as the defendant’s, to guide the AI's analysis.
Professionals must focus on crafting precise prompts to ensure useful outputs, minimizing the need for rework.
Define internal shorthand in a glossary to prevent misinterpretation.
Provide time-related details, such as applicable dates and deadlines, to anchor prompts in a specific timeframe.
Professional Habits That Generate Rework
9. Asking for Conclusions Instead of Reasoning
Request structured analysis rather than simple predictions to provide a comprehensive framework for decision-making.
10. Requesting Summaries When You Need Analysis
Specify that you require an analysis to understand implications rather than just a summary.
Customize inputs with jurisdiction, material terms, and other specifics to produce tailored outputs.
Request citations and sources to ensure outputs are verifiable and trustworthy.
Instruct the model to rank risks and propose mitigations for a prioritized action plan.
14. Blurring Obligations and Preferences
Clearly distinguish between regulatory requirements and optional preferences in prompts.
Integrate validation steps into prompts to verify claims against authoritative sources.
State your role. Provide your perspective and jurisdiction for accurate analysis. Supply the source material. Include all necessary contracts, data, or facts. Specify the deliverable. Clearly define the desired output. Define the purpose. Link output to a specific decision-making process. Set the format. Indicate the required format, such as a memo or risk matrix. Identify controlling sources. Reference relevant statutes or provisions. Require validation. Request citations and confirmation of recency.
Implementing this checklist saves time on rework and ensures more reliable AI outputs.
Effective use of AI is contingent upon the quality of input prompts. By refining prompt techniques, professionals can achieve decision-ready outputs and reduce verification efforts. Structured input has become an essential skill in leveraging AI effectively.
Michael Simon Baker is the principal at Michael S. Baker, P.C. ( NYBusiness.Law/ArtificialIntelligence.Lawyer ), specializing in business law and AI governance.
Based on reporting by TechBullion.