Prompt engineering is evolving fast, and while TAG and RISE are powerful tools, there are other frameworks that can help you get even better results from AI models. In this post, we’ll explore two lesser-known but super useful models: RTF and BAB.
🧠 Prompt RTF Framework
RTF stands for:
- Role: Define the AI’s persona or function.
- Task: Describe the task you want it to perform.
- Format: Specify the format of the output.
✅ Example:
Prompt: Act as a UX designer. Create a checklist for onboarding screens. Show me in bullet points.
- Role: UX designer
- Task: Create a checklist
- Format: Bullet points
This framework is great when you want clarity and structure in the output.
🔄 Prompt BAB Framework
BAB stands for:
- Before: Explain the current situation or problem.
- After: Describe the desired outcome.
- Bridge: Ask the AI to create a solution that connects the two.
✅ Example:
Prompt: Before: I struggle to stay focused while coding.
After: I want to work in 90-minute deep focus sessions.
Bridge: Suggest a daily routine and tools to help me get there.
BAB is perfect for problem-solving, goal setting, and behavioral change prompts.
🧭 When to Use RTF vs BAB?
| Use Case | RTF | BAB |
|---|---|---|
| Structured output | ✅ | ❌ |
| Role-based tasks | ✅ | ❌ |
| Personal development | ❌ | ✅ |
| Problem-solving | ❌ | ✅ |
| Creative formats | ✅ | ✅ |
💬 Final Thoughts
RTF and BAB are great additions to your prompt engineering toolkit. Whether you're building apps, writing content, or just trying to get better answers from ChatGPT, these frameworks help you guide the AI more effectively.
Try mixing them with other techniques like few-shot prompting or chain-of-thought reasoning for even better results.
Happy prompting! 🚀
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