Introduction

In prompt engineering, ChatGPT Prompt Frameworks are structured templates that help you communicate your request clearly to the AI. Instead of typing a vague question, you give ChatGPT a roadmap for the answer. Frameworks like R-T-F, T-A-G, B-A-B, C-A-R-E, and R-I-S-E are designed to help users get the most out of ChatGPT by providing clear instructions on roles, tasks, actions, and goals. This leads to more targeted, high-quality outputs for various purposes – from content creation and storytelling to problem-solving and strategy development. In this report, we break down each of these five frameworks, explain what they stand for, give practical examples (especially for YouTubers and content creators), and recommend when to use each.

R-T-F (Role – Task – Format)

Breakdown: The RTF framework stands for Role, Task, Format. It’s about specifying what you want ChatGPT to be, what to do, and how to deliver the answer. By clearly defining these three elements, you ensure the response comes from the right perspective and in the desired style. This framework is perfect for explicitly setting the AI’s persona, the job at hand, and the output structure.

Role: Define the persona or role you want ChatGPT to assume (e.g. a teacher, marketer, scriptwriter). This sets the perspective or voice of the response.

Task: State the specific task or question. What do you want the AI to do or solve? Clearly outlining the task guides ChatGPT’s focus.

Format: Describe the desired format or style of the answer (e.g. a list, a tweet, a formal report). This tells ChatGPT how to structure its output.

Purpose & Use: RTF is considered a “jack-of-all-trades” framework – it can be used for most scenarios to get clearer communication with ChatGPT. Use RTF whenever you have a specific role in mind for the AI or need the answer in a particular format. It’s great for content creation tasks where you want a certain tone or structure. For example, a YouTuber can use RTF to have ChatGPT act as an expert scriptwriter producing an outline in bullet points. By combining Role, Task, and Format, you effectively tell ChatGPT what persona to take, what to do, and what the output should look like.

Example Prompt:

> “You are an experienced YouTube scriptwriter (Role). Draft a video introduction for a vlog about travel budgeting (Task), and present it as a numbered list of key talking points (Format).”

In this example, the prompt assigns a clear role (an experienced scriptwriter), specifies the task (draft a video intro on travel budgeting), and requests a particular format (a numbered list). Using R-T-F in this way helps ensure the response is tailored: ChatGPT will answer as a seasoned scriptwriter and the output will be structured as requested.

When to Use R-T-F: Use RTF whenever you need a well-structured answer or when the context of who is speaking and how the answer is given matters. It’s especially helpful for creative content generation (scripts, articles, social posts) where adopting a specific voice or style is important. For a YouTuber, RTF can help generate ideas or scripts in a consistent format (like outlines, Q&A format, etc.), making the content more usable immediately.

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T-A-G (Task – Action – Goal)

Breakdown: The TAG framework stands for Task, Action, Goal. It focuses on breaking your prompt into what needs doing, how to approach it, and why (the end goal). This is ideal for prompts where you want a solution or plan to achieve a specific outcome.

Task: Define what needs to be done or the problem to tackle. This is the core request or objective (the “what”).

Action: Describe how to address the task – the steps or approach the AI (or the persona you’ve set) should take. This guides the method or process (the “how”).

Goal: State the desired outcome or result. What is the end goal you want to reach? This provides a clear purpose and success criterion for the task (the “why”).

Purpose & Use: TAG is ideal for problem-solving, planning, or brainstorming tasks where you have a clear objective in mind. By specifying Task, Action, and Goal, you ensure ChatGPT not only addresses the issue but also understands the context and what a good solution should achieve. For example, a content creator might use TAG to brainstorm strategies: the Task could be growing an audience, the Action might be exploring specific tactics, and the Goal would be the growth target. This framework is useful when you want step-by-step or structured advice aimed at a clear result.

Example Prompt:

> “Task: Increase viewer engagement on my cooking YouTube channel. Action: Suggest two creative strategies (like interactive video segments or community challenges) I can implement in upcoming videos. Goal: Boost my average view duration and subscriber interaction by 20%.”

In this prompt, we’ve broken the request into TAG: the task is improving viewer engagement; the action requested is two creative strategies detailing how to do that; the goal quantifies the desired outcome (20% improvement in metrics). ChatGPT, seeing this structure, would likely respond with a focused mini-plan – for instance, suggesting specific engagement tactics (actions) and keeping the stated goal in mind.

When to Use T-A-G: Use TAG when you have a specific objective and want ChatGPT’s help in figuring out how to get there. It’s great for planning content strategies, solving channel problems, or any scenario with a clear end goal (such as “increase subscribers by X” or “improve content quality”). For YouTubers, TAG can help generate action plans – for example, how to reach a subscriber milestone, where the Task is the area of improvement (content, engagement, etc.), the Action directs how to brainstorm or analyze, and the Goal define

s what success looks like. By making the goal explicit, you help ChatGPT tailor its advice or solution towards that outcome.

B-A-B (Before – After – Bridge)

Breakdown: The BAB framework stands for Before, After, Bridge. It’s a classic storytelling and persuasive writing formula. You describe the current state or problem (Before), the desired future state (After), and then request the Bridge – the solution or steps to get from before to after.

Before: Explain the current situation, challenge, or pain point. This sets the context by showing “where we are now” (often a problem state).

After: Describe the ideal outcome or how things look once the problem is solved. This is “where we want to be,” highlighting the benefits or improved state.

Bridge: Ask for the plan or solution that connects the two states. Essentially, how do we get from the “before” state to the “after” state?.

Purpose & Use: B-A-B shines in persuasive contexts, advertising, and storytelling. It works well when you want to motivate or convince the audience by first resonating with their problem, then showing a vision of improvement, and finally providing the solution. For content creators, this framework can help structure compelling narratives – for example, in a video script or an advertisement within a video, you might present a viewer’s problem, then show the solution’s payoff, and finally call them to action with how to achieve it. Using B-A-B in ChatGPT prompts means you can have the AI generate a piece that naturally flows through problem to solution.

Example Prompt:

> “We currently average only 100 views per video and few comments (before). We want to reach 1000 views per video and foster an active comment section (after). Draft a plan that bridges this gap – include content changes and promotional tactics to take us from 100 views to 1000 (bridge).”

In this example, the “before” is a YouTuber’s current struggle (low views and engagement), and the “after” is the goal (high views and active community). The prompt explicitly asks ChatGPT to provide the “bridge,” i.e., a detailed plan to get from point A to point B. This might lead to an output where ChatGPT suggests step-by-step strategies: improving video SEO, enhancing content quality, engaging with viewers, leveraging social media – all targeted at moving from the before-state to the after-state. The B-A-B structure ensures the answer stays focused on transformation: recognizing the problem, envisioning success, and mapping out how to achieve it.

When to Use B-A-B: Use B-A-B when you want to highlight a transformation or need a solution to a problem framed in terms of before/after. It’s especially useful for marketing copy, motivational storytelling, or any scenario where showing improvement is key. YouTubers might use B-A-B to script a segment that introduces a problem and then demonstrates how their content or a product solves it (great for sponsored content or tutorials). Because it naturally creates a narrative arc, B-A-B helps make the content more engaging and persuasive by taking the audience on a journey from problem to solution. Anytime you need ChatGPT to produce output that convinces or conveys progress (e.g. writing an ad, an inspirational story, or a case study), B-A-B is a go-to framework.

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C-A-R-E (Context – Action – Result – Example)

Breakdown: The CARE framework stands for Context, Action, Result, Example. It prompts you to set the stage with background, specify what needs to be done, state the expected outcome, and even give a reference example. This comprehensive approach ensures the AI has clarity and direction, which is excellent for analytical or strategic tasks.

Context: Provide background information or the scenario at hand. This is the context or situation that ChatGPT should understand before taking any action (the “where/when/why” background).

Action: Describe the action needed or the task to be done in this context. What do you want ChatGPT (or the assumed role) to do? This is the specific request or instruction (similar to the task element in other frameworks).

Result: State the expected outcome or the results you are looking for. What should happen if the action is done? This helps clarify the goal or intention behind the action.

Example: Provide an example or reference for clarity. This could be a real example, a hypothetical scenario, or a benchmark to guide the AI. Including an example helps ChatGPT better understand what you’re looking for by analogy or illustration.

Purpose & Use: CARE is great for evaluations, strategies, or instructional content where clarity is paramount. By giving context and an example, you reduce ambiguity, and by specifying action and result, you direct ChatGPT toward a concrete, desired outcome. This framework is very helpful when you want an analysis or recommendations. For instance, a YouTuber could use CARE to get ChatGPT to review their channel: provide context about the channel, ask for specific actions (like analysis of content or suggestions), state what result they expect (e.g. ways to improve engagement), and even give an example (“Channel X did this successfully”) to guide the style of recommendations. The inclusion of an example is a unique strength of CARE – it acts as a model or comparison, making the AI’s response more relevant and grounded.

Example Prompt:

> “Context: I run a tech review YouTube channel with 50k subscribers. Recently, view counts have dropped by 30%. Action: Analyze possible reasons for the decline and suggest actions to revive viewer interest. Result: I expect a set of recommendations to improve view counts and engagement. Example: For instance, if low video quality is a reason, recommend how to upgrade production, citing how another channel improved using better lighting or editing.”

In this prompt, we gave ChatGPT context (channel size and a problem: declining views), a clear task (analyze and suggest fixes), the expected result (recommendations to improve views), and even an example scenario (a hint that if quality is an issue, give a solution, with reference to another channel’s experience). A CARE-structured prompt like this leads to a thorough answer: ChatGPT might identify several factors (e.g. content relevance, upload frequency, production quality) and suggest specific improvements, possibly referencing the example (like how another channel’s change led to better results). The Example component ensures that the advice is concrete – by asking for a comparative illustration, we nudge the AI to be more specific, not just generic. Overall, CARE yields a response with clear analysis and actionable insights, which is why it’s suited for strategy or feedback-oriented queries.

When to Use C-A-R-E: Use CARE when clarity and completeness are critical, such as in performance evaluations, strategic planning, or teaching scenarios. It’s very useful if you want ChatGPT to consider a lot of detail: the framework ensures the AI takes into account context and provides a concrete result. For content creators, CARE can help in situations like evaluating why a particular video underperformed and how to improve it – you supply the context (video details, performance data), request actions (analysis/suggestions), state the result you want (e.g. ways to improve next time), and perhaps give an example (“compare it to a similar successful video”). CARE is also helpful beyond YouTube – for example, in project post-mortems, case studies, or planning documents where you want thoroughness and an example for illustration. Whenever you feel an answer could be too generic, adding an example in your prompt (using CARE) helps ground it in reality.

R-I-S-E (Role – Input – Steps – Expectation)

Breakdown: The RISE framework stands for Role, Input, Steps, Expectation. It is used to guide ChatGPT through a structured process: you assign a role, provide specific input/data, ask for a step-by-step solution, and state the expected outcome. RISE is particularly useful for instructional or planning prompts that require detail.

Role: Specify the role or persona the AI should adopt (similar to RTF’s Role). This could be an expert relevant to your task (e.g. “You are a data analyst” or “Act as a video marketing guru”).

Input: Give the information or data the AI should use. This is the specific input the AI needs to consider – for example, raw data, a scenario description, or any constraints (if you have no actual data to give, you can describe the kind of input, like audience demographics, that should be assumed).

Steps: Ask for a series of steps or a process. This prompts ChatGPT to break down its answer into an ordered list of actions or explanations – essentially a plan or how-to guide.

Expectation: State what outcome you expect or what goal these steps should achieve. This is the final result or the criteria for success, which helps the AI understand where the process should lead.

Purpose & Use: RISE is useful for detailed, step-by-step instructions or planning tasks. If you need a thorough solution broken into steps (like a tutorial, action plan, or timeline), RISE provides that structure. For a YouTuber or content creator, this can be handy when planning content strategy or technical how-tos. For instance, you might have ChatGPT act as a “content strategist” (Role), feed it some Input like your current content stats or a certain trend, and then ask for Steps to achieve a growth target (Expectation). The framework ensures the AI will produce a methodical response: considering the given input data and laying out steps toward the goal. It’s like asking for a recipe to reach a specific outcome, with the ingredients you have.

Example Prompt:

> “Role: You are a YouTube growth strategist. Input: Here are my channel’s last 6 months of metrics – growth has plateaued, with an average of 5k views per video and engagement dropping. Steps: Provide a step-by-step plan to reinvigorate channel growth (such as content adjustments, posting schedule changes, and audience outreach strategies). Expectation: The plan should aim to increase average views per video to 10k and boost engagement (comments/likes) by the end of the next 6 months.”

In this example, we explicitly set the role (YouTube growth strategist, so ChatGPT answers as an expert consultant), we provide input (a summary of the problem data – plateauing metrics), we request steps (a detailed plan with ordered actions), and we state the expectation (what the plan should achieve: double the views, etc.). A RISE-based prompt like this guides ChatGPT to produce a very structured answer – likely a numbered list of recommendations, each building on the given data, aimed at reaching the specified goal. You might see suggestions such as analyzing content types, experimenting with new formats, collaborating with other creators, promoting on other platforms, and so on, each step justified by the role’s expertise and the input data provided. RISE ensures the response is both thorough and goal-directed.

When to Use R-I-S-E: Use RISE when you want detailed guidance or a process, especially if you have some data or specifics to include. It’s the go-to framework for “how do I do this?” questions where the solution should be multi-step. Content creators might use RISE to get stepwise help on things like developing a content calendar, improving production workflow, or analyzing and acting on audience data. The Role ensures the advice comes from the right expert angle, Input grounds the advice in reality, Steps yield a clear plan, and Expectation makes sure those steps aim for a concrete goal. For example, if you have analytics data from your channel or blog, plugging it into a RISE prompt with a desired outcome can give you a tailored action plan from ChatGPT. Essentially, RISE is best whenever you need an AI-generated “strategy roadmap” or procedural answer – it keeps the output organized and aligned with a specific objective.

Conclusion

Prompt frameworks like R-T-F, T-A-G, B-A-B, C-A-R-E, and R-I-S-E are powerful tools for anyone looking to improve their interactions with ChatGPT. By using these frameworks, you transform a vague idea into a structured query that ChatGPT can follow easily, resulting in more relevant and high-quality outputs. Each framework has its strengths and ideal use cases: for example, R-T-F is a versatile all-rounder for defining roles and output format, T-A-G is great for goal-oriented planning, B-A-B works wonders for persuasive storytelling, C-A-R-E ensures thorough analysis with examples, and R-I-S-E gives you detailed step-by-step plans.

For a YouTuber script writer or content creator, these frameworks can be game-changers – they help you get tailored scripts, ideas, or strategies from ChatGPT in a format you can directly use or easily refine. The key is to choose the right framework for the right task (e.g. use B-A-B for an ad script vs. RISE for a content plan) and be specific in each part of the prompt. By clearly stating what you need (and how you need it), you guide the AI to deliver exactly what you’re looking for.

In summary, mastering these prompt frameworks will make your AI interactions more efficient and effective. Think of them as a formula: whenever you face a new content challenge or need inspiration, plug your scenario into one of these frameworks. You’ll quickly notice how much more focused and useful ChatGPT’s responses become. Happy prompting!

Shahid Rana

Community Manager

CREATE CAMP