- Large Language Model
- A predictive text assistant trained on vast data - like a sous chef trained in every recipe.
- You give it a prompt (your recipe) and it prepares a relevant, customized response (your dish).
- Language Generation: Can whip up clear, fluent responses across formats
- Pattern recognition: Synthesizes information like combining ingredients into something new
- Rapid Response: Instantly brainstorms, drafts, or ideates on cue
- Flexible use cases: Can support any station like marketing or legal or education.
- Hallucinations: May invent facts or substitute ingredients incorrectly
- No True Understanding: Predicts words but doesn't grasp meaning
- Limited Memory: Can forget earlier steps in a long recipe
- No Real-Time Awareness: Doesn't know what's in the fridge today unless you tell it
- Bias and Tone Drift: Can add seasoning you didn't ask for unless guided
- Hallucinations: Ask for sources or verify manually
- Missing context: Add background information or define the audience
- Off-brand tone: Include tone/style guidance in prompt
- Bias or sensitive content: Review critcally before sharing externally
- Outdated knowledge: Pair with real-time sources or apply human judgement
- Input: Supply the ingredients - words, context, instructions in the prompt
- Tokenization: The sous chef (LLM) breaks your prompt into smaller chunks, like chopping up ingredients into usable parts
- Encoding: The AI organizations those chunks and prepares the kitchen station - assigning numerical meaning
- Processing: The LLM processes everything by drawing on training to assemble a cohesive response.
- Output: Finally, your sous chef presents the finished dish tailored to your recipe (prompt).
- A prompt is the text or question you give to an AI model to guide its response.
- It is like a set of instructions, a creative brief, or a recipe.
- Prompting is the recipe, and the LLM is your sous chef.
- The better the recipe (prompt), the more effective the sous chef (LLM) can be in helping prepare the final dish (output).
- Clear: Precise language, avoid ambuguity
- Concise: Use just enough detail, don't overexplain
- Commanding: Use imperatives like "Explain", "List", "Compare"
- Contextual: Provide relevant background as needed
- As a role, your mission is to task.
- Deliver this as a format, writing in the style of tone.
- Focus on achieving objective, but don't restriction.
- Additionally, aim to incorporate desired skill/technique.
- Prompt Recipe -> LLM Sous Chef --> Output Dish.
- Summarize this product in one sentence....
- Summarize this product for a blurb on the product launch webpage, include a one sentence tagline, product description, and mockup a blog post too.
- This one needs a lot of structure, steps, and context.
- Light Appetizer: Summarize with quick bite-sized insights
- Side Dish: Compare and contrast to enhance understanding
- Hearty Starter: Explain and Analyze to warm up thinking
- Main Course: Strategy and Planning with rich layered decisions
- Chef's Special: Action-Oriented Practical Execution
- Dessert: Creative and Storytelling that is light, fun, or emotionally engaging
- Simple Lists
- Markdown Tables
- Freeform Text
- JavaScript Object Notation (JSON)