Photo of author Joao Carlos da Silva Junior

“With coworkers, you don’t just blurt out a task and hope they get it. You give context, you clarify, you refine. You talk. That’s how you should approach prompting.” – Valentin Despa (Software Developer, Udemy Instructor)

Graphic showing a brain with an overlay of various nodes

Artificial Intelligence (AI) is no longer a buzzword, it’s infrastructure. It’s changing how we teach, sell, write, and even think. At the heart of this transformation is one simple, yet powerful skill: prompt engineering.

And no, it’s not about talking to robots. It’s about understanding how language unlocks intelligence.

Prompt engineering is the practice of creating well-structured inputs—like text, images, or other data—to help the AI understand the task and generate relevant, high-quality outputs. In short, it serves as the bridge between human intent and machine response.

Understanding Prompt Engineering

At its core, prompt engineering is the art (and science) of crafting effective instructions to get the best outcomes from large language models (LLMs) like ChatGPT, Claude, or Gemini. Think of it as talking to an extremely talented intern: brilliant, fast, but easily confused if your ask isn’t clear.

But it goes far beyond simple Q&A. Prompt engineers design the way models reason, write, summarize, analyze, and even “think creatively” all by shaping the prompt.

Basic questions ask for simple facts, such as “When did Taylor Swift release her first album?” More advanced prompts ask for creativity or in-depth research, such as “List all of Taylor Swift’s albums and their overall rating from major reviews” and “Write a 500-word short story about a witch who gets lost in the forest and can’t speak her own name.”

The most complicated queries ask the model to research, generate, or summarize long passages with multiple specifications, including “Redact all names from the list” or “Don’t exceed 2,000 words.”

Common types of prompts include:

Despite their advancements, LLMs may struggle with certain tasks, such as solving math problems, answering trick questions, staying on topic, analyzing large amounts of text, and providing factually accurate responses. As a result of these shortcomings, businesses could receive false or misleading information. Prompt crafting teaches AI models to overcome these challenges and become a reliable source of data, summaries, and creative text.

Once you’ve engineered an LLM, the model can assist with a variety of tasks, including product development, content generation, and research workflows. This convenience could save your employer thousands of dollars each year.

Prompt Engineering ≠ Basic Question Asking

Prompting isn’t about “asking a chatbot stuff.” It’s about leveraging the model’s probabilistic reasoning to:

Prompt chaining is essential for reducing hallucinations—confident but incorrect or fabricated outputs—in multi-layered tasks. It involves breaking a complex task into a sequence of smaller, structured prompts, where the output of one step becomes the input for the next. This step-by-step approach helps improve accuracy and is one of the most underrated techniques in business workflows today.

To learn more about effective prompt creation, check out The Complete Prompt Engineering for AI Bootcamp. This comprehensive course teaches you to work with a variety of models, including Midjourney, GitHub, Stable Diffusion, ChatGPT, and more. You’ll also learn about Python coding and complete projects you can add to your resume.

Prompt Engineering Misconceptions with Valentin Despa (Software Developer, Udemy Instructor)

What are some common misconceptions people have when they first begin learning prompt engineering?

One of the biggest misconceptions is that prompt engineering is hard—something only for tech experts or advanced users. And sure, in some edge cases, it can get complex. But for most real-world uses, that’s simply not true.

In fact, you can learn a few simple techniques in minutes that dramatically improve the quality of your outputs—sometimes by 10x.

Here’s what often happens: many people start using tools like ChatGPT the same way they use Google. They type in a question or statement and expect an answer. Maybe the prompts are a bit longer, but the mental model stays the same. And honestly, for many tasks, that works just fine.

But when it doesn’t—when the output misses the mark—it’s easy to think “I need to learn prompt engineering from scratch.” While deepening your skills over time is great, you already have what you need to get started.

What’s missing isn’t a toolkit—it’s a mindset shift.

“Don’t treat ChatGPT like a smarter Google. Treat it like a helpful coworker.”

With coworkers, you don’t just blurt out a task and hope they get it. You give context, you clarify, you refine. You talk. That’s how you should approach prompting.

Here’s one powerful tip: Use the AI to help you write better prompts for AI. That’s right—just ask it directly.

For example: “Help me craft a better prompt for this task.”

Or simply add this to any prompt:

“Ask me follow-up questions before giving your answer.”

This one shift—seeing the AI as a collaborator, not a search box—can unlock a whole new level of results.

Courses by Valentin Despa

DeepSeek AI for Developers
Valentin Despa
4.7 (163)
초보자를 위한 Postman 및 API 테스트 빠른 입문
Valentin Despa, Valentin Despa – Support
4.9 (9)
Jenkins: Jobs, Pipelines, CI/CD and DevOps for Beginners
Valentin Despa, Valentin Despa – Support
4.6 (1,560)
Bestseller
Custom GPTs: Create a Custom ChatGPT with Your Data
Valentin Despa
4.6 (743)
Bestseller
Performance Testing: Introduction to k6 for Beginners
Valentin Despa, Valentin Despa – Support
4.7 (1,750)
Bestseller
Introduction to OpenAI API & ChatGPT API for Developers
Valentin Despa, Valentin Despa – Support
4.5 (60,449)
Postman: The Complete Guide – REST API Testing
Valentin Despa, Valentin Despa – Support
4.7 (21,364)
Bestseller
Introduction to Git for GitLab projects
Valentin Despa, Valentin Despa – Support
4.5 (6,006)
Highest Rated
Introduction Agile & Scrum for Product Owner Certification
Valentin Despa, Valentin Despa – Support
4.7 (8,825)

Courses by Valentin Despa

What Is Prompt Engineering Used For?

Prompt engineering is used for everything from global LLMs to company-specific models. On a broad scale, prompt crafting helps popular LLMs, such as ChatGPT, answer millions of questions in a quick, efficient, and reliable manner. For businesses, prompt engineering teaches models to automate certain tasks, integrate with software, and develop content workflows.

This field also helps marketers develop effective advertising campaigns. Many bots struggle to understand the subtleties of marketing, such as grabbing the audience’s attention, entertaining them with humor, and tapping into subconscious desires. With prompt building, LLMs can generate better marketing materials and boost each client’s return on their investment.

Prompt building is particularly valuable in education, where clear, relevant, and factual information is essential. As an engineer, you’ll teach models to stick to the facts, cite their sources, and avoid repeating unverified opinions. This helps teachers conduct research and develop effective lesson plans.

Contrary to popular belief, you don’t have to be a programmer to understand prompt engineering. Some coding knowledge helps, but prompt builders aren’t developing software —they’re crafting prompts to refine existing models. Whether you’re in a technical or nontechnical field, prompt crafting is probably relevant to your industry.

To learn more, check out our prompt engineering courses. These classes teach you how to write your own prompts and provide example questions you can use as a starting point. Once you’ve completed a course, you’ll have the skills to unlock your model’s full potential.

Why Prompt Engineering Is Business-Critical (Not Just Techy)

Yes, LLMs can generate. But they can also mislead, hallucinate, or skip steps  especially under vague instructions. That’s why prompt engineering isn’t a gimmick,  it’s risk mitigation.

Businesses deploying AI at scale need repeatable, auditable, human-guided interactions with these models.

Fact check: The claim that prompt engineering “makes LLMs more accurate” is misleading. Accuracy depends on the model’s training data and reasoning abilities. Prompting only optimizes the output from existing capabilities: it doesn’t “fix” flawed models.

The future isn’t just about prompt engineers. It’s about AI-literate professionals who can think, adapt, and guide intelligent systems with clarity and empathy.

How Prompt Engineering Skills Enhance Career Opportunities

AI is becoming a major player in hundreds of industries, including education, health care, fashion, marketing, music, retail, and food service. When you know how to craft effective prompts, you’ll become a valuable asset for employers who use LLMs every day.

Growing Demand for AI and Prompt Engineering Skills

AI-related jobs have experienced significant growth in recent years, with job openings increasing by 42% from 2022 to 2024[1]. On a global scale, AI job ads have increased by 68% since 2022[2].

Prompt engineer salaries can very greatly, with compensation for most prompt engineering roles falling somewhere between $32,500 and $159,000[3,4]. However, top earners can see salaries of $200,000 or more.

Integration Across Various Roles and Industries

If you enjoy working with AI but prefer different fields, you don’t have to stick with the technology industry. Prominent builders can find jobs in marketing, retail, education, government, and numerous other sectors. Even writers, artists, and musicians use LLMs for inspiration and rough drafts.

Corporate Investment in AI Training

As AI usage increases, many corporations are making LLMs an essential part of the workday. For example, since 2019, JPMorgan Chase has required asset and wealth management employees to undergo 500% more training hours[5], which includes prompt building courses. The bank also utilizes in-house LLMs and places a $1.5 billion value on its AI use cases[6].

Career Advancement Through Prompt Engineering

With prompt crafting on your resume, you show employers that you’re ahead of the curve and ready to enter this new world of technology. You’re prepared to stay on top of the latest trends, make their tools more efficient, and solve problems with logic and reasoning. Taking a few classes and gaining experience gives you an edge over your fellow applicants.

Mastering Prompt Engineering Techniques

Zero-shot prompts are the most common query. These prompts ask a question or make a request without including examples. Your zero-shot prompts might look like this:

Few-shot prompts offer examples that help the model answer the question. These prompts test the LLM’s ability to interpret content and use reasoning skills. Examples of few-shot prompts include:

Prompt chaining involves breaking a task into separate prompts to make it easier for the model to handle. If you submit the entire task at once, the LLM could struggle to process the information and make significant errors. However, a prompt chain allows the model to focus on each step individually. This is an example of a prompt chain:

If you need accurate information, you’ll typically have to perform a fact check to ensure accuracy. This involves checking the LLM’s claims against verified sources, such as university and government websites. Without fact-checking, you could accidentally prompt a model to produce false data.

To learn more about writing queries, check out this ChatGPT Prompt Engineering course. This free course shows you how to write questions and includes vibrant examples.

The Future of Prompt Engineering

Since LLMs are a relatively new development, prompt crafting is still in the early stages. However, new advancements are helping engineers take their projects to the next level.

From Manual Prompts to Automated Systems

When AI models first hit the market in 2023, prompt engineers had to come up with their own questions and rely on their intuition. This was a lengthy but rewarding process that relied heavily on trial and error. Sometimes, they’d enter the same prompt dozens of times with slight rephrasings to nudge the model in the right direction.

Today, businesses are offering templates and prompt libraries that give engineers a starting point. These pre-written prompts are challenging and designed to push the LLM to its limits. You can use them for inspiration or send them directly to the model to see how it reacts.

Prompt engineers also have tools at their disposal, such as LangChain and Semantic Kernel, that help them generate prompts and train AI bots. Some businesses have incorporated these tools into their software, so you won’t have to pay for them separately. You could also experiment with a free version to get experience.

Where Prompt Engineering Is Headed

AI isn’t just the driving force behind chatbots — you can also find it in software, web interfaces, apps, and search results. As businesses continue to integrate AI into their products, prompt engineering might become essential for the software you use every day, such as Google Workspace and Microsoft Word. When you ask these tools to complete a task, an LLM might operate in the background.

Eventually, models might start generating their own prompts. Currently, they rely on reinforcement learning with human feedback (RLHF). However, when they’ve completed enough training, they could teach themselves by writing and refining complex queries.

Once prompt building becomes obsolete, you may transition to a role as a prompt orchestrator who writes complicated prompt chains that require elaborate analysis and research. Your employer could also entrust you with multiple LLMs that work together to create an efficient workplace.

Why It Still Matters

No matter how advanced AI becomes, employers will still need people to write complex, challenging, and unusual prompts with a human touch. They’ll need professionals to teach LLMs to respond without bias, understand nuance, and provide up-to-date information. Over time, prompt engineers could help programmers create some of the world’s most sophisticated models.

Learn Prompt Engineering With Udemy

You don’t have to depend on trial and error to succeed. We offer dozens of courses that teach you how to write a variety of prompts, refine your queries, push the model’s boundaries, and work with the world’s biggest LLMs.

The structured learning paths give you a strong foundation before introducing more advanced topics. You’ll also complete hands-on projects that put your abilities to the test.

To start, browse our Prompt Engineering courses. You’ll learn all about prompt writing, machine learning, deep learning, ChatGPT usage, and advanced prompt-writing techniques.

Prompt Engineering Project Ideas for Your Resume with Valentin Despa (Software Developer, Udemy Instructor)

Which projects can learners complete to highlight and showcase their prompt engineering skills to potential employers?

Showcasing prompt-engineering talent takes more than posting a prompt template—you need a working example that makes people say “wow.” The simplest path is to build a tiny AI-powered app that fixes a real-life headache you’ve felt yourself. Because the pain is yours, you’ll keep iterating the prompts until the result shines.

That mini app can be something as simple as a Custom GPT within ChatGPT or a standalone web app.

Today’s rise of AI-assisted coding—sometimes called “vibe coding”—makes that build step beginner-friendly. Tools like Cursor, Windsurf, or Lovable generate most of the boilerplate, so you can pour your energy into refining prompts.

So turn your best prompt into a mini-app—a great prompt is a feature, not a file.

To build your own customized version of ChatGPT, a project that can help fill out your portfolio, enroll in Valentin’s Custom GPTs course.

Final Thoughts

Prompting isn’t just a skill. It’s a bridge between human intention and machine execution. And in a world being rebuilt by AI, knowing how to guide intelligence: clearly, ethically, and effectively, might just be the most human skill of all.

Build your prompt engineering skills with Udemy today.

[1] https://www.forbes.com/sites/jackkelly/2024/03/06/the-hot-new-high-paying-career-is-an-ai-prompt-engineer/

[2] https://www.linkedin.com/pulse/demand-ai-talent-2024-2025-global-tech-job-market-analysis-rathi-s82jc/

[3] https://www.ziprecruiter.com/Salaries/Prompt-Engineering-Salary

[4] https://www.glassdoor.com/Salaries/prompt-engineer-salary-SRCH_KO0,15.htm

[5] https://www.ciodive.com/news/jpmorgan-chase-ai-training-strategy-prompt-engineering-/717273/

[6] https://www.linkedin.com/pulse/jpmorgan-mandates-ai-training-every-new-employee-blockchaincouncil-hbfdc/

Page Last Updated: June 2025