Home

A place to learn prompt engineering techniques and learn more about AI. 

Untitled

Welcome to Blaizing Academy Playground


A place to learn prompt engineering techniques and learn more about AI. 


Join our Slack Community Channel to interact with others to learn more about trends and new techniques..

[Join the Slack Community](https://join.slack.com/t/blaizing/shared_invite/zt-2zxdm7729-Bz4z5KraGCuEO3AxB67vIw)

Tools

Structured Prompt Design

What would...

LLMs

Blaizing Playground

PathFinder is your personalized career advisor, using insights from your personality and interests to help you discover fulfilling career paths while guiding you away from roles that may not suit you.

PathFinder

A guide to help users uncover the root causes of their challenges through structured dialogue and self-reflection.

The Problem Navigator

ImageMaker

Prompt Creator

Persona Maker

B-A-B (Before, After, Bridge)
Define the Before state (problem), specify the After state (desired outcome), and request the Bridge (steps).
Use Case: Problem-solving prompts, such as planning transitions from one state to another.

B-A-B (Before, After, Bridge)

R-T-F (Role, Task, Format)
Define a Role for the model to act as, specify the Task, and clarify the desired Format.
Use Case: When output needs to follow a specific style or role, e.g., a doctor explaining a diagnosis.

R T F  (Role, Task, Format)

T-A-G (Task, Action, Goal)
- Define the Task, specify the Action to take, and clarify the Goal of the task.
- Use Case: Goal-driven actions, such as providing step-by-step instructions.

T-A-G (Task, Action, Goal)

S-B-I (Situation, Behavior, Impact)
Meaning:
Situation: Provide the context or situation.
Behavior: Define the behavior or action being evaluated.
Impact: State the impact of that behavior.
Use Case: Feedback and evaluation prompts.

S-B-I (Situation, Behavior, Impact)

W-W-W (Who, What, Why)
Meaning:
Who: Who is involved or affected?
What: What is happening or what needs to be done?
Why: Why is this important or necessary?
Use Case: For concise prompts clarifying essential details.
Example:
Input: “Who: Marketing team. What: Develop a new campaign. Why: To target a younger audience.”
Output: “The marketing team should create a campaign focused on social media platforms popular with the younger demographic to capture their attention.”

W-W-W (Who, What, Why)

C-O-A (Challenge, Option, Action)
Meaning:
Challenge: What is the problem or challenge?
Option: Present available options or solutions.
Action: Request action or next steps based on those options.
Use Case: For decision-making scenarios.
Example:
Input: “Challenge: Sales are declining. Option: Increase advertising budget or launch a new product. Action: Which option should we choose?”

C-O-A (Challenge, Option, Action)

O-O-O (Objective, Obstacle, Outcome)
Define the Objective, identify the Obstacle, and state the desired Outcome.
Use Case: Best for goal-setting or troubleshooting scenarios.

O-O-O (Objective, Obstacle, Outcome)

P-A-S (Problem, Agitate, Solution)
Present a Problem, Agitate (explain why it’s a serious issue), and then offer a Solution.
Use Case: Often used in marketing or persuasive contexts.

P-A-S (Problem, Agitate, Solution)

R-I-S-E (Role, Input, Steps, Expectation)
Assign a Role, provide relevant Input, outline the Steps, and clarify the Expectation.
Use Case: Great for tasks that involve a clear role and require step-by-step guidance.

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

C-A-R-E (Context, Action, Result, Example)
Provide the Context, specify the Action, clarify the Result, and provide an Example.
Use Case: For instructional or process-driven tasks, often used in customer service or technical guidance.

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

Natural Language Agent

Blaizing Helper

LLM (GPT-4o)

User Car Agent

An expert on everything ever said on Ted Lasso and how Ted would approach any situation.