Prompt engineering is not Rocket Science: Learn at a Top Level how easy it can be to get what you want from AI.
Have you always wanted a friendly, fast assistant who simply does what you say? In many cases, AI applications like ChatGPT can offer you exactly that. But it only works with your help. To get beneficial results out of AI, you need to master prompt engineering.
Don’t panic; you don’t need an IT degree for this. Prompt Engineering is about asking the right questions and giving the right commands to generative AI’s like ChatGPT to get the information you need. In principle, this programming language is very close to our normal language.
Before we get into it, we want to make sure you know about Salesforce AI Solutions – By using Agentforce, AI insights are right at your fingertips.
We have complete training modules to help you interact with our AI-based platform, with guidance on how to build prompts, and information on how our AI platform works for various sides of businesses such as Sales, Customer Service, Marketing and Commerce.
What is Prompt Engineering?
Prompt Engineering is the art of tailoring your input to create specific, desired responses from AI applications, whether through commands or questions. This empowers people and organizations to harness the full potential of AI technologies, such as Salesforce Agentforce, by refining the way users interact with these systems to achieve greater productivity and superior results.
Key Terms to Understand
NLP (Natural Language Processing): A field of artificial intelligence that focuses on enabling computers to understand, interpret, and generate human language in a way that is both meaningful and contextually relevant. Many AI applications use this as their base model, including ChatGPT.
Intent Recognition: This is a fundamental NLP concept. It involves understanding the underlying purpose of a user’s message or query, a cornerstone for effective prompt engineering.
Entities: In NLP, entities are specific pieces of information extracted from user input, like dates or product names.
Dialogue Flow: Dialogue flow in AI/NLP is how a chatbot or AI system talks to you: understanding what you say, replying, and keeping the conversation smooth and on track.
Training Data: High-quality data is used for training NLP models, which enhances your prompt engineering by improving intent recognition and response generation.
Context: In prompt engineering, context refers to the conversation’s history and information, which is crucial for multi-turn interactions.
A Beginner’s Look at Prompt Engineering
In this post, we will focus on text prompts. But you can get almost anything from a prompt: including pictures!
This work was created using the free version of Anime-style Clickdrop, an interface for various tools (Stable Diffusion XL by Stability AI, a deep learning text-to-image generator.)
We tried this out with a straightforward prompt: “Show me a picture with blue water and mountains.”
So, just think of a prompt like a short and precise briefing.
If your generative AI tool receives a meaningful and relevant prompt, it can give you an appropriate answer.
And what does Open AI, the creators of ChatGPT, say about prompt engineering?
Examples of Prompt Engineering
We’ve explained above what a prompt engineer does and how to get started. But what does that look like in practice? Our first example shows how well ChatGPT works when you put a little more thought into your prompt.
Here is an example of ChatGPT helping us create Buyer Persona’s.
Here is our prompt:
“Create five dark chocolate buyer personas using whatever customer survey data you can find. Create a table of personas and give each a name, benefits, and use cases.”
Note: If you had your own data to formulate, ChatGPT would use it and include it within its response.
You can also ask ChatGPT to put it in a table for you:
To master generative AI tools, enter the suitable prompts, and consider these three prompt engineering principles:
1) Provide context: Should AI develop personas as above? Then, specify for which product or service.
2) Be specific: It’s tempting, but don’t get caught up in chatting; it confuses GPT programs. Be brief and precise about what is expected.
3) Proceed Step by Step: Sometimes, slow is better. Break your prompt into multiple detailed questions.
Chain-of-thought Prompts Explained
Chain of Thought (CoT) is a way for AI to respond in conversations that make sense by considering what was said before, so it feels like a natural chat.
At this point, anyone who is not an IT professional may have their head spinning, trying to understand the difference between AI and prompt engineering.
Simply put, prompt engineering is the main factor in the effective use of AI tools. The prompt is the interface between the users and large AI language models (LLM – Large Language Model) like ChatGPT.
Nobody has to remember that. But you should know that these language models are based on natural language. LLMs are machine learning models. But they generate human-like texts, and that’s precisely why they work so well.
The Real GPT Revolution: Prompts are a new form of code that is entered as text and delivers instant results. This makes us all coders— no specialist knowledge required.
For users of Prompt Engineering (and we should all become familiar with it): We have to ensure that the texts we generate achieve the desired goals.
So embrace the benefits of prompt engineering, but also be aware of the limitations of generative AI. If the prompt isn’t good, the results aren’t good either.
Lastly, let’s look at another example of prompting. To do this successfully and give us good results, stick to the three principles described above.
Here are a few prompt types to get you started – all created with the free version of ChatGPT.
The Pareto Principle Prompt:
“I want to learn about [insert topic (we said “daffodils”)]. List the top 20% of insights on this topic and share them with me, so I can understand 80%.”
The Pareto Principle Prompt is a practical way to find out more about a topic.
The Power Networking Prompt (Perfect for Cold Emails)
Prompt: “Give me a cold calling email chain with parenthetical sections that can be customized to specific people or companies.”
Perhaps a bit more content than necessary, but definitely useful as a starting point and can be used as inspiration. You can always click “Regenerate Response” to revise the output text, or Enter “shorten” as a prompt if the output is too long for you.
Peak into the Mind of Leaders
Tap into the collective wisdom of the top Fortune 500 CEOs with this prompt. We entered “green energy”.
“Interview a team of CEOs from Fortune 500 companies on [TOPIC/QUESTION]. Create instructions and strategies to make [TOPIC/QUESTION] possible as if these CEOs answered them.”
Advancing your Prompt Skills
In these examples, we give ChatGPT a plethora of Real Estate data in point form and ask it when might be a good time to buy property in the area.
Here is the output:
It gives an unbiased answer as we posed a tricky question, “when is it good to buy in the region?”. But this type of prompt can give you a top-level understanding of what is happening in the region. Users of ChatGPT4 can take it a step further and get the AI to create charts to help them visualize the data, simply by asking it to do so.
Harness your potential as a Prompt Engineer and explore the boundless opportunities that lie ahead. It’s important to remember that while generative AIs are incredibly capable, they generate responses from vast online data sources and are sometimes flawed. Protecting sensitive data should always be a top priority for you and your organization.
To enhance the value of your data and capitalize on its potential, consider the synergy between your data and ChatGPT. This partnership opens the door to creating fresh and captivating experiences for your customers, positioning you as a leader in the AI revolution unfolding.
