Artificial intelligence tools are now a regular part of academic and administrative work — yet many of us have experienced the frustration of AI responses that miss the mark: too vague, poorly toned or simply not useful.
The difference often comes down to how the prompt is written. One practical framework is RTCF — Relevance, Tone, Clarity and Format. Applying these four principles helps faculty and staff get dramatically better results from AI tools.
Relevance: Give the AI What it Needs to Know
AI tools work best when they understand the context of your request. Before writing a prompt, ask yourself: What background information does the AI need to produce a useful response?
Rather than asking, “Write an email about the deadline,” try: “Write an email to undergraduate students reminding them that the drop/add deadline is this Friday, and that they should consult their academic advisor if they have questions.”
The more relevant context you provide — your role, your audience, the purpose of the task — the more targeted and accurate the output will be.
Tone: Tell the AI How It Should Sound
AI tools can write in many registers — formal, conversational, empathetic, authoritative — but they need guidance. Left to default, outputs can feel generic or misaligned with your institutional voice.
Be explicit. Phrases like “use a professional but warm tone,” “write formally as appropriate for a faculty senate memo,” or “keep the language accessible for first-generation students” give the AI clear direction. This is especially important for sensitive communications — such as messages about academic standing, policy changes, or student support — where tone carries as much weight as content.
Clarity: Be Specific About What You Want
Vague prompts produce vague results. Clarity means stating your request precisely, including any constraints or requirements the output must meet.
Compare these two prompts:
- Vague: “Summarize this report.”
- Clear: “Summarize this accreditation report in three bullet points, focusing on the key findings related to student outcomes. The summary will be shared with the department chairs.”
Specific prompts reduce the need for back-and-forth revisions and save time. If your request has multiple parts, list them. If there are things the AI should avoid, say so explicitly.
Format: Specify How the Output Should Be Structured
Format is the most overlooked element of prompt writing, yet it has an immediate impact on usability. Should the response be a bulleted list, a paragraph, a table, a numbered checklist or a formal letter? How long should it be?
Without guidance, AI tools will make their own formatting choices — which may not suit your needs. Stating “provide the response as a two-paragraph summary” or “format this as a professional agenda with time allocations” ensures the output is ready to use with minimal editing.
Putting It All Together
Here is an example of an RTCF-informed prompt in practice:
“I am an academic department coordinator writing to faculty about an upcoming curriculum review meeting. Using a professional and collegial tone, draft a 150-word email invitation that clearly states the meeting date (Thursday, May 22 at 2 p.m.), the agenda items (program learning outcomes and assessment data review), and asks recipients to confirm attendance by end of day Monday. Format it as a ready-to-send email with a subject line.”
This single prompt incorporates all four elements: relevant context, specified tone, clear requirements and explicit format. The result will be far more usable than a generic request.
A Skill Worth Developing
As AI tools become more embedded in higher education workflows, communicating effectively with them is an increasingly valuable professional skill. The RTCF framework offers a simple, memorable structure for anyone looking to get more out of these tools — whether you are a seasoned user or just getting started.
For any questions, please contact Richard Plott by email or on Teams.