Can prompt engineering, or command engineering, be considered a unique art form that emerged from and belongs to our age? The reason we liken prompt engineering to an art rather than a technical skill is this: every command given to artificial intelligence is not just about requesting information, but about shaping a way of thinking. Just as a painter creates emotion with colors and a lawyer creates persuasion with words, a good prompt engineer determines the AI's perspective, tone, and even "logic" by strategically selecting words. Therefore, using generative AI efficiently is the art of skillfully combining language, context, and intent rather than memorizing a technical formula. A good prompt builds not only the right answer but also the right thinking process, just like a lawyer directs a judge to the right question with a strong petition.

The use of artificial intelligence (especially generative AI) in the legal field has begun to increase rapidly today. Many lawyers and legal experts have experimented with generative AI tools and seen that this technology can provide groundbreaking benefits in tasks such as conducting legal research and preparing contract and petition drafts. For example, an international study conducted by LexisNexis in 2023 revealed that lawyers plan to use generative AI most frequently for purposes such as legal research and drafting legal documents. However, just as in traditional legal research, the quality of the results we obtain from AI tools is closely tied to the question we ask (i.e., the command we give). In other words, if we want to get correct and useful answers from AI, we need to carefully design what we ask and how we ask it. This is exactly where prompt engineering comes into play.

WHAT IS PROMPT ENGINEERING?

Prompt engineering is the process of carefully preparing and designing the commands we give to an AI model, i.e., prompts, to elicit the desired response or behavior. In other words, it is the art of carefully structuring our queries to get the most accurate, relevant, and useful answer from AI systems. This approach requires treating AI not as a magical "black box," but as if it were a junior lawyer or young colleague on your team. Just as you need to clearly explain to a junior lawyer what they should do and in what context when assigning them a task, you must also give AI clear instructions to produce the right output. A poorly expressed, vague prompt will likely result in an irrelevant or misleading answer. In contrast, a well-prepared prompt, like a clearly formulated question, narrows the AI's focus, defines terms, and directs it to the desired topic. Ultimately, since the outputs of AI models largely depend on how we ask them questions, prompt engineering skills have become an important and sought-after expertise in today's generative AI era.

WHY DO WE NEED PROMPT ENGINEERING?

We can consider the importance of preparing good prompts from several perspectives:

• More Accurate and Reliable Results: The clearer and richer the prompt the AI receives, the more purpose-appropriate the answer it produces, so instead of simple few-word commands, we should use comprehensive prompts that include context, purpose, and detail.

• Efficiency and Productivity: Well-designed prompts ensure that the AI understands you correctly, so you get targeted and accurate answers. This prevents wasting time with trial and error.

• Reducing Errors and "Hallucinations": Hallucination refers to AI making up non-existent or incorrect information. That is, AI can provide completely erroneous information in an extremely confident tone. Prompt engineering helps you minimize such risks by asking the right questions and controlling the process step by step.

• Control and Responsibility: In law, the final control should always be with the lawyer. Thanks to well-prepared prompts, the lawyer can maintain control over the text produced by AI. Getting responses in stages allows you to review the results at each step and make corrections if necessary. This way, you can position AI as an assistant whose output you supervise.

STEP-BY-STEP EFFECTIVE PROMPT WRITING

So since this "prompt engineering" is so important, how will we as lawyers use AI more effectively, how will we learn this art? Below, we will explain step by step with examples how you can use this structure in daily legal practice:

1. Specify the Legal Area and Context

Every legal analysis gains meaning within a specific framework. The same clarity must be presented to AI. At the beginning of the prompt, clearly state which branch of law the subject relates to: "rent increase limit under Contract Law," "conditions for justified termination under labor law," etc. This ensures the model thinks from the correct legislative perspective. When defining context, specifying the parties' positions, the basis of the event, and any local regulations also makes a big difference. For example, "Under what criteria is a mobbing claim evaluated when an employee at a technology company in Istanbul is subjected to constant demeaning emails?" Such a prepared context contains both temporal and spatial references and significantly increases the accuracy of the answer from AI.

Example Prompts:

• "Under Labor Law, explain the justified termination reasons for an employee working in the private sector in bullet points."

• "Within the framework of Family Law, evaluate the effect of a spouse's unauthorized use of private messages in a divorce case."

2. Give Active Verbs and Clear Instructions

Lawyers like clarity, and so does AI. Using verb-focused commands like "Evaluate," "Analyze," "Compare," "List," "Prepare a legal opinion" directly states what the model should do. Choosing words with strong action direction instead of vague verbs ("explain" or "mention") ensures that the output aligns with your request.

For example, "Analyze the admissibility of privately obtained private correspondence as evidence in a divorce case pursuant to TCC art.134 and support with Supreme Court decisions." Here the instructions "analyze" and "support" determine the model's direction.

Example Prompts:

• "Under Law No. 6502 on Consumer Protection art.11, explain the alternative rights that the consumer has due to defective goods and give examples from Supreme Court decisions for each right."

• "Comparatively list the employer's justified termination reasons and the employee's justified termination reasons under Labor Law No. 4857 art.25."

3. Show Foundation and Reference:

The better a prompt is grounded, the more reliable the response. Clearly tell AI which legal framework, law article, or case law it should think from. This ensures the model produces legal argumentation rather than just "general information."

For example, "Within the framework of Constitution art. 26, art.13 and ECHR art. 10, evaluate disciplinary penalties imposed due to social media posts in terms of freedom of expression." Thus, the model makes its interpretation based on the legislation you specified, not arbitrarily. "Showing foundation" is essential not only for accuracy but also for maintaining professional control.

Example Prompts:

• "Evaluate the conditions for applying the unjust provocation reduction in TCC art.29 together with the latest case law of the Supreme Court Criminal General Assembly."

• "Evaluate the presence of maturity difference in the invoice in light of TTC art.23 and Supreme Court IBCGA decisions."

4. Define an Active Role and Perspective:

Giving AI a "role" radically changes the tone, depth, and format of the answer. "Evaluate this event as a Supreme Court review judge." "As a tax lawyer, prepare a draft explanatory email to be sent to your client." "As a KVKK expert, summarize the administrative sanctions that can be applied in case of data breach." Such "persona" definitions determine the model's perspective. In areas with contextual density like law, "from whose eyes it is spoken" dramatically affects the quality of the answer. In short, defining a role positions AI as a "co-worker."

Example Prompts:

• "As an information law expert, analyze whether content produced by artificial intelligence falls under intellectual property protection within the framework of the Turkish Law on Intellectual and Artistic Works."

• "As a criminal judge, evaluate the applicability of the unjust provocation reduction in TCC art.29 in terms of whether the perpetrator's state of anger shows continuity in the event and write in the format of a reasoned decision draft."

5. Define the Format:

In law, the form of presentation is as important as the content. Instead of just requesting information from AI, also specify in what format you want it: "List in bullet points." "Summarize in table form." "Write in reasoned decision draft format." For example, if you say "Explain the mobbing proof criteria and the types of evidence sought by the Supreme Court for each criterion in table form," the model produces a ready document for you in terms of both information and format. This saves time especially in report and petition preparation processes.

Example Prompts:

• "Summarize the regulations on rent increase limit under Turkish Code of Obligations art.344 and the decisions given by the Supreme Court on this matter in table form."

• "Summarize the execution follow-up process in chronological timeline format."

6. Proceed Step by Step (Chain of Thought Technique):

Instead of giving AI a complex task all at once, guiding it step by step yields much more efficient results. This approach is called "Chain of Thought." For example, giving the command "List the criteria sought by the Supreme Court in the employee's mobbing claim" and after receiving the answer, giving a new command "Give a brief summary of 3 Supreme Court decisions that meet these criteria" pushes AI to think in chains. This method both reduces errors and allows you to see step by step how the answer is formed. In other words, you apply the Socratic method to AI.

Example Prompts

1. "Explain the liability principles of board members pursuant to Turkish Commercial Code art.553."

2. "Summarize three Supreme Court decisions in which board members were held liable for company damages."

3. "In light of these decisions, state in bullet points the preventive measures that can be taken to escape liability."

7. Have It Generate Counter-Arguments:

A good lawyer knows not only their own thesis but also the opposing party's thesis. You can ask the same from AI: "Now write the arguments of the plaintiff's attorney defending that this evidence is legal in three paragraphs." This method allows you to see possible counter-defenses in advance during case preparation. Using AI as an "opposing view simulator" strengthens your legal strategies.

Example Prompts:

• "You argued that WhatsApp correspondence obtained secretly in a divorce case would be considered illegal evidence. Now defend that this evidence should be accepted based on the principle of 'absence of other means of proof' from the plaintiff's attorney's perspective."

• "You found the employer's claim of not paying overtime unjust. Now evaluate the same event from the employee's attorney's perspective and explain the evidence that the employee can present to prove overtime work based on Supreme Court decisions."

8. Don't Forget Ethics, Privacy, and Verification

Technology may change, but the lawyer's responsibility does not. Never write real person, company, or case information openly to AI. Always use anonymized examples like "Plaintiff A," "Company X" in prompts. This is the digital extension of the confidentiality obligation in the Attorneys Act art.36. Also, always check the information the model provides. AI may occasionally "hallucinate"; that is, it may make up a non-existent law article or case law. If you encounter suspicious information, give a corrective additional prompt: "Check whether this decision actually exists and use only Supreme Court case law published in the Official Gazette." This protects you from both ethical risks and professional reputation loss.

Example Prompts:

• "Evaluate Company X's data processing activity towards its employee in terms of compliance with KVKK art.5."

• "Transform the text into an anonymized training example by hiding 'witness names' and 'event addresses' in criminal proceedings."

9. Continuously Improve

Prompt engineering is not a one-time skill; it's a habit. You may not get the perfect result on the first try, just like trying to draw or sing for the first time in your life. View interaction with AI as a dialogue: after each answer, clarify the question a bit more, remove unnecessary details, emphasize important points. This continuous improvement process makes you a "strategically thinking" user rather than a "question asker."

Example Prompts:

• "In your previous answer, you summarized Supreme Court decisions too generally. Please rewrite based on decisions from 2020 onwards."

• "Reorganize your answer in a shorter, client-oriented language."

In conclusion, prompt engineering is actually the digital version of a skill that lawyers already know very well: the art of asking the right question and supervising the answer. The steps we listed systematize this skill; the chain of thought technique deepens it; ethical principles draw safe boundaries. Ultimately, the issue is not to see AI as a magical box but to use it with a lawyer's reflex that can consciously direct it. Remember: asking the right question is the easiest way to reach the right information. Well, what if AI hallucinates, how will we know if its answer is correct? Until we discuss the problem of AI hallucination next week, farewell!

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