TECHNOFILE
Real-world examples : The good , and the bad .
Example 1 : Planning an office party
Vague prompt : “ Help me plan an office party ” Result : Generic party planning checklist that could be found anywhere online . Refined prompt : “ I need to plan a retirement party for our company ’ s beloved office manager of 25 years . Budget is $ 500 , attendance expected around 40 people , in our office space next month . Please suggest unique ways to celebrate her love of gardening and mystery novels , while keeping it professional . Include decoration ideas , catering suggestions , and a rough timeline .” Result : Detailed , personalised plan with creative touches like mysterythemed decorations and succulent party catering .
Advanced prompting techniques Try the ‘ Layer Cake Method ’. Think of prompting like building a cake – layer by layer : Start with your base request , add specifications , request a first draft , then review and refine with follow-up prompts . For example :
Layer 1 : “ Help me create a monthly newsletter template .” Layer 2 : “ Make it suitable for a law firm ’ s internal communications .” Layer 3 : “ Include sections for case wins , new hires , and industry updates .” Layer 4 : “ Now , add specific formatting for Outlook email distribution .”
Best practices beyond prompting Using AI in this regard is a game of education . Common users talk of “ training ” the AI . The same is true for anyone new to using AI . As such , here ’ s a few tips for early adopters :
w Keep a prompt library . Create a document of your most successful prompts . Think of it as your personal AI phrasebook . w Use temperature control . When available , adjust the AI ’ s
“ temperature ” setting . You can actually instruct the AI to apply different temperatures in the prompt . IBM says different temperature settings essentially introduce different levels of randomness in the output . It allows the user to adjust the text to better suit different real-world applications of text generation . Use lower temperature ( around 0.3 ) for factual tasks , higher ( 0.7-0.9 ) for creative work . w Fact-check important information . Always remember that AI can make mistakes , and ‘ hallucinations ’ are a real thing , where the AI can actually manufacture information that has no factual basis , or is drawn from associated information that isn ’ t relevant to the task . Always verify crucial details , especially numbers and dates . w Be aware of the context window . AI has limits on how much it can “ remember ” in one conversation . For complex tasks , break them into manageable chunks .
Common pitfalls to avoid w The Kitchen Sink Approach . Throwing every possible detail into a prompt isn ’ t helpful . Stay focused on what ’ s relevant . w The One-Word Wonder . Singleword prompts rarely yield useful results . “ Newsletter ?” isn ’ t going to get you what you want . “ Create a one-page monthly newsletter template focusing on employee achievements and company updates ” more likely will . w The Assumption Avalanche . Don ’ t assume the AI knows your industry jargon or company-specific terms . Define acronyms and specialised terms . w The Human Touch . While mastering AI prompting can revolutionise your workflow , remember that it ’ s a tool , not a replacement for human judgment . AI is like having a brilliant intern who needs clear direction but can produce amazing work when guided properly .
As AI technology evolves , prompting techniques will too . The key is to stay curious and experimental while maintaining professional standards . Remember , the goal isn ’ t to create more work for yourself but to make your existing work more efficient and effective .
The multi-model approach : knowing which AI to use when Finally , one of the most overlooked aspects of working with AI is choosing the right tool for the job . Just as you wouldn ’ t use Excel to write a novel or PowerPoint to manage your budget , different AI models excel at different tasks .
Large language models like GPT are excellent for writing and editing , research summaries , creative brainstorming , document analysis and email composition but are not recommended for image creation or editing , real-time data analysis , or handling sensitive personal information .
Barbara Wong , Operations Director at TechFlow Solutions , shares her workflow : “ I use different AI tools like I use different applications . One for creative writing , another for data analysis , and a third for image generation . Understanding these distinctions has transformed how I approach each task .”
Remember , the goal isn ’ t to become an AI expert – it ’ s to be an expert at using AI to enhance your existing expertise . As Rachel Goldman , a veteran executive assistant , puts it : “ I ’ m not in the AI business , I ’ m in the getting-thingsdone business . AI is just one of the most powerful tools in my arsenal .” S
THE EXPERT
Tech expert Tim is the technology writer for Executive PA Media . He can be heard on talk radio in Australia and is a tech presenter who speaks at conferences and trade shows about technology ’ s impact on work and lifestyle .
Autumn Issue 2025 | Executive PA 35