10 prompt engineering examples and techniques for early-stage startups

If you’ve ever used ChatGPT before or any other generative AI model (and chances are that you have - because they’ve been everywhere the past two years), you're likely no stranger to the concept of prompt engineering. 

However, you might not have known that what you are doing (adjusting your prompts to get the answers that you want) was even called prompt engineering. 

There’s more to it, though. A whole process and relatively new but promising discipline of making AI do your bidding. As an early-stage startup with limited resources, this might be a great and cost-efficient way to perform lots of tasks beneficial for your business. 

Do you want to know how? Read on and learn AI prompt engineering examples and techniques best suited for you.

Main concepts of prompt engineering for startups

In simple terms, prompt engineering is the art of crafting instructions that elicit specific responses from AI models. It's about understanding how to communicate effectively with machines and how to get them to produce the results you need.

The basics of prompt engineering

A prompt is essentially a short instruction that tells an AI model what to do. It's a way of providing context, setting parameters, and guiding the model toward a specific outcome.

Think of it like giving directions to a team member. You need to be clear, concise, and specific about what you want them to achieve. The same applies to AI models. The better your instructions, the better the outcome.

Breaking down a prompt

All the prompt engineering examples ChatGPT, Claude, Gemini, Llama, etc., they all have something in common - crafting a good prompt is of the essence here. Garbage in, garbage out, right? Spend time refining your prompts – it's an investment that pays off. Here’s how to structure a prompt that gets results:

• Agenda. Set the scene. Give the AI context. For example: "Imagine you're a seasoned VC evaluating a pitch deck."
• Instruction. Tell the AI exactly what you want. Be specific! Example: "Give me three potential weaknesses in this business model."
• Trigger. Provide concrete examples for the AI to work with. Example: "Given this pitch deck focused on a subscription box for ready-made meals, what are the key metrics I should be looking at?"
• Format. Specify the output you want. Bullet points? A paragraph? Code? Example: "List the metrics in a bulleted list."

The anatomy of a prompt

As your prompts get more complex, it's helpful to recognize their different parts. Here's how you might structure them:

1. Task context. Assign a role to the AI and outline the general task it's expected to perform.
2. Tone context. Set the desired tone for the interaction.
3. Background information. Provide any necessary documents or data the AI needs.
4. Detailed instructions and rules. Lay out specific guidelines for how the AI should interact.
5. Examples. Offer sample solutions for the AI to learn from.
6. Conversation History. Include any prior exchanges that are relevant.
7. Immediate task description. State the specific task you want done right now.
8. Think step-by-step. If needed, encourage the AI to reason through the problem.
9. Output formatting. Tell the AI how you'd like the response formatted.
10. Prefilled response. If it helps, start the AI off with a template or partial answer.

Prompt engineering examples and benefits: what’s in it for startups?

As a founder, you're resource-strapped, time-poor, and need every advantage. Prompt engineering is that advantage. Market reports project crazy growth in this area – Grand View Research estimates a 32.8% CAGR from 2024 to 2030. That’s not hype, that’s opportunity.

Here are some more details. 

Practical applications

NLP tasks. Need to summarize lots of market research? Prompt engineering helps AI condense information quickly and accurately. Think instant summaries of news articles, competitor analysis, or even translating documents.

Chatbots and assistants. Tired of clunky customer service? Train your chatbot with sharp prompts, pulling real-time data from your systems. Give customers quick answers, recommendations, and 24/7 support.

Content creation. Blog posts, marketing copy, and even creative writing – prompt engineering can help generate content that matches your brand voice.

Q&A systems. Building a knowledge base? Use prompt engineering so tha your AI can accurately and efficiently answer user questions. No more sifting through FAQs.

Recommendation systems. Use AI and prompt engineering to analyze user data and offer more personalized product recommendations that will boost your sales and customer loyalty.

Data analysis and insights. Prompt engineering also helps extract meaningful insights from your data, even without a huge data science team.

Why this matters – bottom line benefits

Accuracy. Clear prompts = accurate results. Less time fixing mistakes, more time building your business.

Time savings. Automate tasks, get answers fast and free up your team to focus on what matters.

Creativity boost. Use AI to generate new ideas and explore innovative solutions you might not have thought of.

Resource optimization. AI works even with limited data or a small team. Level the playing field against bigger competitors.

Consistency. Standardize outputs and maintain quality across all your AI-powered processes.

Top 10 best prompt engineering examples and techniques

Now, we’ve selected the ten best prompt engineering examples and techniques for startups based on our own experience.

1. Zero-shot prompting 

Zero-shot prompting is when you ask the AI to perform a task without providing any examples. It's a quick way to test the AI's general knowledge and get instant insights without much setup.

Example prompt: 

"What are the key factors to consider when developing a startup business plan?"

Why or when to use it:

Great for when you're in a hurry and need broad information fast.

2. One-shot prompting

Sometimes the AI needs a little nudge to understand the context or format you want. One-shot prompting involves giving one example alongside your prompt.

Example prompt: 

"Describe the importance of a business model in a startup. Example: A business model helps outline revenue streams and cost structure." 

Why or when to use it:

Useful when you need responses in a specific format or style.

3. Few-shot prompting

If one example isn't enough, a few might do the trick. Few-shot prompting means you give the AI several examples to help it grasp the pattern or style you're aiming for.

Example prompt: 

"List the steps involved in developing a startup business plan. Example 1: Conduct market research. Example 2: Define your target audience."

Why or when to use it:

Ideal for more complex tasks where the AI needs to understand a specific sequence or structure. 

4. Chain-of-thought prompting

For complex problems, ask the AI to think out loud. Chain-of-thought prompting gets the AI to break down its reasoning process, which can lead to more accurate and insightful answers.

Example prompt: 

"Explain how to validate a startup idea." 

Example answer:

"First, identify a problem that needs solving. Next, conduct market research to see if there's demand. Then, create a minimum viable product (MVP) to test your concept. Finally, gather feedback and iterate based on user responses."

Why or when to use it:

Helps when you need detailed explanations or solutions that require multiple steps.

5. Iterative prompting

Sometimes you won't get the perfect answer on the first try. Iterative prompting involves refining your questions based on the AI's previous responses to guide it toward the desired outcome.

Example prompt: 

• Initial prompt: "I'm researching fraud prevention in travel. Can you outline key areas to focus on?"
• Follow-up prompt: "Could you detail identity verification methods for travel?"
• Next prompt: "How can transaction monitoring be effectively implemented?

Why or when to use it:

To dive deeper into a topic by narrowing down your questions step by step.

6. Instruction prompting

Don't assume the AI knows exactly what you want. Providing detailed and explicit instructions ensures the AI understands your expectations.

Example prompt: 

"Write a mission statement for a startup focused on eco-friendly products. The mission statement should be concise, inspirational, and reflect the company's commitment to sustainability."

Why or when to use it:

When you want to get responses that meet specific criteria or guidelines.

7. Contextual prompting

Providing background information helps the AI generate more accurate and relevant answers. If context matters, include it.

Example prompt: 

"Considering the increasing importance of sustainability, what strategies can a startup implement to become more eco-friendly?"

Why or when to use it:

Useful when the AI needs to consider specific factors or external information.

8. Interleaved prompting 

When you have multifaceted questions, interleaved prompting lets you address them simultaneously.

Example prompt: 

"List the steps to develop a startup business plan and summarize why financial planning is crucial."

Why or when to use it:

Efficient for getting comprehensive answers that cover multiple aspects.

9. Template-based prompting 

Templates guide the AI to produce responses in a specific format, ensuring consistency across outputs.

Example prompt: 

"Describe a unique selling proposition (USP) for a startup. Template: 'Our startup offers [unique feature] that [benefit].'" 

Why or when to use it:

Ideal for creating uniform content, like product descriptions or mission statements.

10. Prompt chaining 

For more involved tasks, prompt chaining connects multiple prompts in a sequence. The output from one prompt becomes the input for the next.

Example prompt: 

• First prompt: "Generate a list of essential components for a startup pitch deck."Output: "1. Introduction 2. Problem Statement 3. Solution 4. Market Opportunity 5. Business Model 6. Financial Projections 7. Team 8. Roadmap"
• Second prompt: "Write the problem statement section for a startup developing a new productivity app."

Why or when to use it:

Useful for workflows that require multiple steps or stages to complete.

Conclusion

Ultimately, prompt engineering is all about clear communication, but this time - with AI. In some ways it resembles our communication with other fellow humans - we have to be specific and brief to avoid confusion. 

The direction is simple - keep your prompts focused on your goals, and guide the conversation from general ideas to detailed points. 

Be sure to also allow some flexibility to discover unexpected insights and clearly state your intent to stay on track. Be ready to adjust your prompts as needed, and don't hesitate to try different approaches based on the AI's responses. 

As an agency that integrates AI into various startup operations, we know how important it is to use it well. If you need help, we're here to support you with our prompt engineering services to make the most of these powerful tools.