Introduction: Cultivating ‘Prompt Engineering for Colleagues’ Through Dialogue with AI
In this modern age where dialogue with AI has become a part of our daily lives, we are honing a new skill called ‘prompt engineering’ every day. Did you know that this technique of accurately conveying intentions to AI and eliciting desired responses can actually be surprisingly applied to human-to-human communication, especially in building relationships with colleagues?
‘Collaboration with colleagues isn’t going well,’ ‘There are many disagreements,’ ‘Team productivity isn’t increasing’… If you are harboring such worries, it might be because your ‘prompts’ to your colleagues are not appropriate.
In this blog post, we will explain groundbreaking methods to apply the prompt engineering techniques cultivated through dialogue with AI to building and improving relationships with colleagues. We will provide practical tips to make your relationship with your colleagues better and smoother, and as a result, improve the performance of the entire team.
Why is prompt engineering necessary for relationships with colleagues now?
Colleagues are partners with whom we advance daily work and are indispensable for achieving team goals. However, communication with colleagues who have different values and work styles can sometimes create friction. Lack of information sharing, misalignment of perceptions, and conflicts of opinion are often causes of reduced team productivity.
Prompt engineering in relationships with colleagues becomes a powerful framework for building deeper understanding and trust, and eliciting desired cooperation by understanding the colleague’s ‘thought process,’ ‘work style,’ and ‘expectations,’ and designing ‘optimal questions’ and ‘ways of conveying’ tailored to them.
If you acquire this knowledge, your communication with colleagues will evolve from a mere means of information transmission into a ‘value creation process‘ that builds trust, deepens cooperation, and achieves goals together. Now, let’s explore the profound world of prompt engineering for colleagues together and maximize the potential of your relationship with your colleagues!
1. Replacing the basic concepts of prompt engineering with ‘dialogue with colleagues’
The basic principles of prompt engineering used in dialogue with AI are also very effective in communication with colleagues. Here, we will explain those key concepts by replacing them with dialogue with colleagues.
1-1. ‘Clear instructions’ and ‘sharing context’
Just as you give clear instructions to AI, it is important to convey your intentions and requests specifically when making requests or sharing information with colleagues. Also, by concisely sharing background information (context) so that colleagues can understand the situation, you can prevent misunderstandings and promote smooth cooperation.
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AI: ‘Please summarize the following about XX in 300 characters.’
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Prompt to a colleague: ‘Mr./Ms. XX, I have a consultation regarding the YY project currently in progress. Currently, a problem with ZZ has occurred, and I would like to proceed with Plan A, but I would like to hear your opinion.’
1-2. ‘Specifying roles’ and ‘clarifying expectations’
Just as you give a role to AI by saying ‘Please answer as an expert in XX,’ by clearly conveying what role you expect from your colleague (information provider, collaborator, reviewer, etc.) and what you are seeking when making a request to a colleague, it becomes easier for the colleague to respond with peace of mind.
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AI: ‘As an experienced marketer, please propose a catchphrase for this new product.’
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Prompt to a colleague: ‘Mr./Ms. XX, I came to consult with you because I would like to receive advice based on your extensive experience regarding this matter. In particular, I would like to hear your opinion on how to convey this to the customer.’
1-3. ‘Setting constraints’ and ‘presenting options’
Just as you give constraints to AI such as ‘Please propose 3 items in bullet points,’ by presenting the scope of thinking or options to your colleague when making a proposal, it becomes easier for the colleague to think, and it is easier to lead to constructive discussion. For busy colleagues, reducing the burden of thinking from scratch is extremely important.
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AI: “Please create an article with a positive tone that includes the following three points.”
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Prompt for a colleague: “[Name], I have prepared two options, Plan A and Plan B, regarding this matter. I have summarized the pros and cons of each in the document. If you have any other good ideas, I would love to hear them as well.”
1-4. ‘Providing Concrete Examples’ and ‘Utilizing Feedback’
Just as you provide concrete examples to an AI by saying ‘Please answer in this format,’ you can help colleagues understand your intentions more deeply by providing specific examples or sharing past success stories when reporting or making proposals. Furthermore, just as you evaluate AI-generated results to encourage improvement, actively seeking feedback from colleagues and applying it to the next step builds trust.
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AI: “The previous answer was a bit abstract. Please explain it with more concrete examples.”
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Prompt for a colleague: “[Name], following your feedback the other day, I have improved the points regarding [Topic]. Specifically, I added data on [Topic] and made it easier to understand visually with a graph. Does this meet your expectations? I would appreciate it if you could let me know if there are any other areas for improvement.”
2. Designing ‘Prompts’ for Colleagues: A Psychological Approach
Just as prompt engineering for AI maximizes its performance, designing ‘prompts’ for colleagues is essential for unlocking their potential and building better relationships. Here, we will explain how to design effective ‘prompts for colleagues’ by incorporating psychological perspectives.
2-1. Understanding Colleagues’ ‘Thinking Styles’ and ‘Work Styles’ (Empathy and Persona Setting)
Just as you adjust prompts by understanding the characteristics of AI, it is important in relationships with colleagues to understand their thinking styles (e.g., whether they are logical, focus on the big picture, or pay attention to details) and work styles (e.g., whether they prefer individual work, value cooperation, prioritize speed, or prioritize thoroughness). This is the task of imagining the colleague’s ‘inner persona’.
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Questioning: What information is the colleague interested in right now? What kind of language would make it easiest for the colleague to understand?
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Example: For a logical colleague, start by conveying the conclusion, then present the supporting data or facts. ‘[Name], to start with the conclusion, Plan A is the best. There are three reasons for this.’
2-2. Prompts Based on ‘Positive Intent’ (Adlerian Psychology: Teleology)
Adlerian psychology posits that ‘every human action has a purpose.’ By inferring the positive intent behind a colleague’s actions and designing prompts based on that premise, colleagues are less likely to feel attacked, which leads to more constructive dialogue.
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Bad example: “Why don’t you ever listen to my opinions, [Name]?”
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Good example: “I understand that you are cautious about this matter because you are prioritizing the success of the entire project. I believe my proposal can contribute to that success, but if you have any concerns, could you please share them with me?”
2-3. Drawing Out Information from Colleagues with ‘Open-Ended Questions’ (NLP: Meta-Model)
Just as you use open-ended questions to elicit detailed information from AI, using open-ended questions that cannot be answered with ‘yes’ or ‘no’ in conversations with colleagues allows you to deeply draw out their thoughts, feelings, and specific situations. The NLP (Neuro-Linguistic Programming) meta-model provides questioning techniques to fill in these ‘missing pieces of information’.
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Bad example: “Is this policy okay?”
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Good example: “[Name], what are the points you are particularly emphasizing regarding this new policy? Also, how do you see this policy affecting the team?”
2-4. Encouraging Action with ‘Future-Oriented’ Prompts (Solution-Focused Approach)
Just as you give AI future-oriented prompts like ‘Please suggest concrete steps to improve X,’ you can use similar prompts in conversations with colleagues. By focusing on future solutions and goals rather than blaming them for past problems, you make it easier to encourage behavioral change and constructive cooperation.
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Bad Example: ‘Because of you, we made another mistake.’
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Good Example: ‘Colleague, regarding this matter, I feel there is room for improvement in terms of △△. To prevent similar mistakes in the future, how about we introduce a verification process like □□? I would like to hear your thoughts.’
3. Practice! Examples of Using Prompt Engineering to Dramatically Change Relationships with Colleagues
Beyond theory, let’s experience the power of prompt engineering for colleagues through practical application examples. Here, we introduce examples of use in common business scenarios.
3-1. Improving the Quality of Cooperation Requests and Information Sharing
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Situation: Even when asking a colleague for cooperation, they don’t move easily. Information sharing does not go smoothly.
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Bad Prompt: ‘Hey, can you help me with that?’ (The point is unclear, one-sided)
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Good Prompt: ‘I’m sorry to bother you while you’re busy, but I have a request for your cooperation regarding the □□ task for the △△ project. Currently, a problem with 〇〇 has occurred in the part I am in charge of, and your expertise is essential. Could you spare about 15 minutes? Specifically, I would like to ask for your help with creating document A and analyzing data B.’
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Point: By first conveying the purpose of the ‘cooperation request’ and then clearly presenting the ‘current issue’ and ‘the reason why the colleague’s expertise is needed,’ the colleague can understand the importance of the request and feel the significance of cooperating. By communicating the specific content of the request and the time required, you reduce the burden on the colleague.
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3-2. Resolving Disagreements Constructively
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Situation: Opinions differ from a colleague, and discussions tend to go in parallel.
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Bad Prompt: ‘Your opinion is wrong.’ (One-sided denial)
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Good prompt: “[Name], regarding [Topic], I would like to align our perspectives, could you spare a moment? My view is A, but I also understand that your view, B, is very important from the perspective of [Context]. I would like to find a better solution while leveraging the strengths of both our opinions; what do you think?”
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Point: By starting with respecting the other person’s opinion and acknowledging its positive aspects, it becomes easier for them to listen to your feedback. It is important to present a common goal (a better solution) and show a cooperative attitude.
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3-3. Facilitating feedback within the team
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Situation: It is difficult to give feedback to a colleague, or no improvement is seen even after giving feedback.
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Bad prompt: “[Name]’s document is hard to understand.” (Abstract, critical)
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Good prompt: “[Name], regarding the [Topic] document you created the other day, may I provide some feedback to enhance its effectiveness? Specifically, regarding the [Context] graph, if you were to change it like [Suggestion], the data might stand out more and make your intent easier for the recipient to grasp. What do you think?”
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Point: By framing the purpose of the feedback as ‘improvement,’ pointing out specific areas, and proposing concrete suggestions, it becomes easier for the other person to accept it constructively. Asking for their opinion creates an opportunity for dialogue.
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3-4. Collaboration during difficult situations or when problems arise
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Situation: A problem has occurred at work, and it is difficult to ask a colleague for help.
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Bad prompt: “[Name], I’m in trouble…” (Vague SOS)
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Good Prompt: “[Name], I am very sorry, but I have an urgent request for advice regarding [Project]. Currently, a problem has occurred with [Issue], and there is a possibility that we may not meet the deadline for [Project] if things continue this way. Based on your experience, I would like to ask for your opinion on whether approach A or approach B is more appropriate, or if there is another better way. Could you spare about 5 minutes?”
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Key Point: By apologizing first and then concisely conveying the ‘current situation,’ ‘impact,’ ‘specific problem,’ and ‘requested cooperation,’ your colleague can quickly grasp the situation and calmly consider how to respond. By presenting specific options, it also makes it easier for your colleague to provide advice.
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These application examples are just one possibility. The important thing is to strive to deeply understand the situation and emotions of the colleague in front of you, as well as the goals of the entire team, and consciously design the ‘optimal prompt’ tailored to them. By repeating this practice, your relationship with your colleagues will improve dramatically, which will in turn lead to an increase in the overall productivity of the team.
Conclusion: Build the best teamwork with the ‘best prompt’ for your colleagues
In this article, we proposed a new concept called ‘Prompt Engineering for Colleagues,’ which applies the techniques of prompt engineering cultivated through dialogue with AI to focus on relationships with colleagues, and explained its specific methods and application examples.
The relationship with your colleagues is not just a ‘professional association.’ It can become a ‘powerful engine‘ that enhances the quality of your work, attracts new opportunities, accelerates your self-growth, and influences the success of the entire team. And the fuel to maximize that engine is an effective ‘prompt for colleagues.’
Starting today, please consciously practice the prompt engineering mindset introduced here. Your every word and every question will become the ‘best prompt‘ that deepens your colleagues’ understanding, builds trust, and pushes the performance of the entire team to the next stage.
I sincerely hope that your relationships with your colleagues will become richer and that you will build the best teamwork. Now, let’s follow the lead of ‘prompt engineering’ in your communication and grasp your ideal team!
