What if talking to AI became as natural as talking to a teammate?
In March 2025, McKinsey reported that 71% of organisations now regularly use generative AI in at least one area of their business. The trend is clear: AI-assisted work isn’t just coming, it’s already here.
Today, the ability to give clear, effective instructions to tools like ChatGPT, Claude, and Gemini is quickly becoming a career-defining skill. And no, AI isn’t coming for your job. In fact, it’s coming to be your co-pilot.
As someone who’s seen firsthand how AI can supercharge both personal and professional productivity, I want to share a beginner-friendly guide to prompt engineering. Prompt engineering is a new kind of digital literacy of learning how to communicate effectively with AI so it gives you precise responses without endless back-and-forth.
Let’s get into it!
What is ‘Prompt Engineering’?
Simply put, prompt engineering is the practice of crafting effective instructions or questions to receive more meaningful responses from AI models. Think of it like learning to speak a new language fluently. When you first start conversing, you might say something like ‘I’m hungry’, but as you develop fluency, you can say ‘I’m hungry for salmon with a side of roasted vegetables, prepared on the grill with extra paprika and lemon.’ The AI understands both, but the detailed request gets you exactly what you’re looking for.
Just as language learners discover that tone, context and cultural nuances matter, prompt engineering teaches us that the way you frame a question dramatically affects the response. A beginner might ask an LLM to ‘write SQL to help with database analysis’, while someone more fluent might say ‘write a SQL query that finds all customers who haven’t placed an order in the past 6 months, include their contact information and optimise it for performance on a table with 2 million records’. Both prompts will output SQL code, but one delivers a response that gives you a closer solution to your problem.
At its core, prompt engineering combines creativity with systematic thinking. The following sections expand on the following concepts but, as an overview, it requires you to:
- Understand how AI models process information
- Structure your requests clearly and specifically
- Iterate and refine based on the results you receive
- Apply context and constraints that guide the AI toward your goals
Demystifying AI: Breaking Down the Barriers & Embracing Change
Mastering prompt engineering is really about mastering communication, a skill anyone can develop. But before diving deeper into techniques, let’s first address some common myths and misconceptions that might be holding you back from exploring AI’s potential.
Understanding AI’s Strengths and Limitations
Understanding that AI doesn’t truly ‘understand’ in the human sense is key to using it effectively. While AI can produce human-like responses, it works by recognising and combining patterns from its training data rather than through conscious reasoning. This means it’s both powerful – capable of making new connections and solving new problems – and limited by the scope and quality of what it learns during training. Because it operates through pattern recognition rather than true comprehension, your role as a meaningful prompter becomes crucial in providing clear direction and context for relevant outputs.
AI as an Amplifier, Not a Replacement
AI doesn’t replace creativity, intuition or empathy. It amplifies them. By handling repetitive or complex tasks, it frees us up to focus on strategy, storytelling and problem-solving, things machines can’t do alone. A marketer can test 10 headline variations in seconds, a data analyst can generate hypotheses and instantly test them with AI-generated code, and a founder can create landing page layouts without hiring a designer.
Breaking Down Technical Barriers
One of the biggest misconceptions is that AI is too complex for everyday professionals. The reality is different: traditional programming requires years of study to master specific coding languages, but prompt engineering democratises access to powerful tools by allowing you to communicate in natural language while achieving sophisticated results. This means professionals from marketing, finance, education, healthcare and countless other fields can leverage AI without extensive technical backgrounds.
The Practical Benefits
A McKinsey report found that generative AI could automate activities accounting for 60–70% of employees’ time, especially in data-heavy roles. Whether you need to draft emails, analyse spreadsheets or explain complex concepts, prompting can save hours of work. For career-switchers, industry-newbies and early-stage founders especially, AI becomes your co-pilot rather than competition as it can begin to level the playing field and reduce learning curves that previously required years of experience.
Practical Tips to Get Started
Use the C.R.E.A.T.E. Framework for Smarter Prompts
One method you can use to create effective prompts is by using the C.R.E.A.T.E. framework, a practical structure developed by AI consultant and author Dave Birss. It helps to build well-rounded prompts by speaking directly to the AI using ‘you’ to assign roles and context:
C – Character
- Define the role the AI should play.
- “You are a data analyst who specialises in customer retention and reporting”
R – Request
- Clearly state what you want the AI to do.
- “I want you to create a SQL query that shows monthly active users grouped by acquisition channel”
E – Examples
- Provide sample inputs, outputs or context.
- “The table is called user_events and contains columns for user_id, event_type, channel and event_date”
A – Additions
- Add specific preferences, e.g. style, voice, audience, constraints, etc.
- “Please ensure it’s compatible with BigQuery syntax”
T – Type of Output
- Clarify what format or structure you want.
- “Output the SQL in a code block with inline comments, no additional explanation needed”
E – Extras
- Include any additional info that might help.
- “Assume the analysis is for a weekly team dashboard used by marketing stakeholders”
Further Techniques for Better Results
Expanding from this framework, there are multiple advanced techniques we can learn to effectively communicate with AI, this includes:
Few-Shot Learning. Provide 2-3 examples of desired outputs to establish patterns and quality standards. Instead of asking ‘write a professional email’, show the AI an example of the tone and structure you prefer, then ask it to create something similar for your specific situation.
Chain-of-Thought Prompting. Guide the AI to complete tasks step-by-step, displaying each stage and result in order. This improves accuracy and transparency, especially for data analysis or problem-solving scenarios.
However, don’t overlook the essentials. While advanced techniques are powerful, they work best when built on solid foundations:
Start with a clear structure. Begin every prompt with at least three key elements: context (what background information does the AI need?), task (what specifically do you want accomplished?) and format (how should the output be structured?).
Be specific about constraints. Include important limitations in your prompts and specify word counts, target audiences, required elements or things to avoid. The more specific you are, the more useful your results will be.
Iterate and refine! Your first prompt rarely produces perfect results. Treat prompt engineering as a conversation, if the output isn’t quite right, explain what needs adjustment and ask the AI to revise accordingly.
The Measurable Impact
Studies consistently show that, when deployed systematically, generative AI delivers median productivity increases of 25% across various professional tasks. Users see faster content creation, improved analysis quality and better outcomes overall. The key difference: successful users communicate with AI systematically rather than using random prompts.
How to Start Prompting with Confidence
Beginning your prompt engineering journey may feel overwhelming, but confidence comes from practice and experimentation.
Start small, then build up. Practice writing prompts for simple and low-stake tasks, such as email drafting or spreadsheet functions. As you become comfortable with the basics, gradually tackle more complex professional challenges.
Join communities & learn from others. Connect with people and invite conversation on prompt-writing approaches. Online communities, workshops and courses provide opportunities to see how others tackle different challenges, as well as leaning on colleagues to learn from their experiences.
Keep a prompt library. Document prompts that work well for you. Build a personal collection of effective templates that you can adapt for different situations. This saves time and helps you recognise patterns in what makes prompts successful.
Embrace the learning process. Remember that prompt engineering is still an emerging field. Even experts are continuously learning and refining their approaches. Mistakes made along the way are learning opportunities, not failures.
Building on Personal Experience
From Humanities to Tech
My journey into tech began as a career-switcher with a humanities background, drawn to the idea that technology can open doors rather than close them. Through Data Analysis training with Code First Girls, I built the foundation that led to my current role as a Data Analyst at Tasman Analytics, a data consultancy that excels in turning disorganised data into actionable business insights across various industries. As both a CFG Ambassador and industry practitioner, I’ve seen firsthand how essential it is to adapt to new tools. In today’s fast-evolving landscape, the ability to communicate effectively with emerging technologies like AI is just as important as traditional analytical skills, and in turn, boosting both efficiency and impact.
Two Complementary Approaches
Code First Girls and Tasman Analytics represent two sides of the same mission: making advanced technology accessible and impactful. CFG empowers individuals to build confidence with new tools through inclusive and beginner-friendly learning environments, no programming background required. Meanwhile, Tasman Analytics shows how embracing emerging technologies translates into real business outcomes by helping clients tackle complex data challenges and build scalable solutions. Together, these approaches begin to bridge education and application, creating clear pathways for professionals to grow. Alongside this, learning how to effectively communicate with AI can augment human capability, accelerate problem-solving and unlock new forms of creativity across every industry.
Conclusion
Prompt engineering represents a fundamental shift in how we interact with AI. Whether you are looking to enhance your current role, explore new career possibilities or simply become more effective in your daily tasks, developing how to prompt effectively can unlock opportunities that didn’t exist just a few years ago.
The key? Start where you are. Every expert in prompt engineering started as a beginner who was willing to try, learn from the results, and iterate. Remember that AI is a powerful tool designed to amplify our creativity, not replace us. It is up to us to learn how to wield its power effectively or risk being left behind.
Ready to Begin?
- Expand your prompt power by reading articles by experts, completing online courses and bookmark this post to use as reference material.
- Explore Code First Girls’ Tech Taster classes to build foundational skills in a supportive environment designed for individuals without traditional technical backgrounds.
- Discover Tasman Analytics, an expert-led data analytics agency who help fast-growing companies turn emerging technologies into competitive advantages by clarifying data strategy, filling critical skill gaps and building internal capabilities for long-term independence.