In partnership with

An Entire Month of Videos Before Lunch

Tired of the post-every-day grind?

Syllaby.io automates your entire content workflow. All you need is a topic—our AI does the rest.

✅ Get daily viral content ideas
✅ Auto-generate scripts tailored to your niche
✅ Instantly create faceless videos
✅ Bulk schedule across all your platforms

Syllaby is perfect for coaches, creators, and marketers who want to grow without showing their face or spending hours editing.

Try Free for 7 Days

Stay ahead with the most recent breakthroughs—here’s what’s new and making waves in AI-powered productivity:

• Aquant Agentic AI Platform: Lets service-focused companies build, deploy, and integrate custom AI agents for process automation and smarter field service.

• Google NotebookLM: An AI app for researchers and professionals that automatically summarizes and connects insights across your documents for streamlined project management.

• Reclaim.ai: Smart calendar and booking automation to optimize schedules without human effort.

• Wispr Flow: Voice-to-text app that seamlessly works across platforms for hands-free productivity.

• GrammarlyGO: Now a full writing copilot offering tone, editing, and message drafting with AI.

• Otter.ai: Upgraded real-time transcription and multilingual note support.

• Google Gemini (Scheduled Actions): Business professionals can now automate recurring tasks with natural language instructions.

Feature Article: Aquant’s Agentic AI Platform

The Next Generation of Service Productivity

Aquant has just launched its Agentic AI Platform—an evolution in enterprise automation that’s uniquely designed for organizations specializing in field service, equipment maintenance, and complex operations. Unlike off-the-shelf tools, Aquant empowers businesses to build custom AI agents infused with their own domain expertise.

• Create smart agents tailored to specific machines, error codes, and workflows.

• Rapidly deploy new automations and integrate with CRM, ERP, and collaboration systems.

• Use real-world terminology across voice, text, and offline channels.

• Focus responses and recommendations on actionable outcomes tied to KPIs.

Key Results:

• Field service teams using Aquant’s AI report up to 39% faster issue resolution.

• The agentic reasoning adapts in real time, helping technicians and customer service reps solve cases smarter and quicker.

Who Benefits?

• Industrial, Medical device, Food equipment, Electronics, and Manufacturing companies who need purpose-built AI automation for high uptime, remote resolutions, and deep knowledge capture.

Find out how Aquant is reshaping service automation.

How to Talk to AI

Why Prompting Matters

In the olden days (i.e., a year or so ago), you had to be exact in your input to computers. You couldn’t say, “Maybe output this as a Word document… or maybe as a CSV.” You had to tell it exactly what you wanted, and it would do only exactly that. If you were even one character off in typing a command, it would have no idea what you wanted.

Now, you can talk to computers like you would a person. It will even do its best to get you results if you misspell things or use bad grammar. It will take vague instructions and make an attempt at it.

But, like with a person, it’s not fair to be unclear about what you want and expect good results. So, to get the best out of AI, you need to work on your prompts – your instructions to the AI. And whether you’re writing an email, summing up a report, debugging code, brainstorming ideas, or just asking a question, a well-made prompt can make all the difference.

Prompting Basics: General Best Practices

Before diving into specific uses, let’s cover some prompting basics that apply to any scenario. Getting good answers is much easier when you follow these guidelines:

• Be clear and specific: Don’t be shy about spelling out exactly what you need. Provide enough detail and context for the AI to understand your request. Ambiguous or overly general prompts (“Tell me about this”) often lead to irrelevant or vague answers. Instead, specify your goal and any particulars: for example, mention the format, style, or audience you have in mind. The more precisely you describe the task, the more consistent and useful the output becomes.
  

• Give context or examples if needed: If your question depends on background info, include it in your prompt. You can even show a quick example of the kind of answer you want. Providing 1-3 examples (a technique called “few-shot prompting”) can teach the model the pattern or format you expect. For instance, rather than asking “Translate this sentence” generically, you might add an example: “Translate: Bonjour → Hello. Merci → ...” to guide the style.
  

• Define a role or tone: You can ask the AI to adopt a role or persona relevant to your task. This sets the context and tone in one go. Start your prompt with something like “You are a friendly history teacher...” or “Act as a professional resume editor...”. This helps the model answer with the appropriate level of detail, terminology, or formality. For example, “You are an expert travel guide. Give me a friendly and engaging rundown of things to do in Paris.” will tune ChatGPT’s tone accordingly (the words “friendly and engaging” guide the style).
  

• Specify the output format: If you know how you want the answer, say so! Want a list of bullet points, a step-by-step explanation, or JSON data? Just include that instruction. For example: “Give the answer in three bullet points.” or “Output as JSON.” Models follow format instructions well when you make them explicit. This is super handy to avoid wading through a long paragraph when you’d prefer a concise list of key points.
  

• Ask for step-by-step reasoning on tough problems: For complex questions (like a math problem or a tricky decision), it helps to have the AI explain its thinking. You can prompt with “Let’s think this through step by step” or “Explain your reasoning before giving the final answer.” This chain-of-thought approach often improves accuracy on logic-heavy tasks and reduces mistakes, since the model will show you its thought process. It’s like watching it work through the problem out loud, which both guides it and lets you catch any errors. This is usually an automatic feature, though, of reasoning models.
  

• Iterate and refine: Treat your conversation with the AI as just that – a conversation. If the first answer isn’t exactly what you wanted, don’t fret. You can refine your prompt or follow up with additional instructions. For example, “Thanks, now could you make that summary shorter?” or “Actually, explain it in simpler terms.” Iterative prompting is normal and expected. Even experts tweak their prompts multiple times to get the best result. There’s no one magic prompt that works every time; getting great output is often a matter of refining your ask based on the AI’s last response.
  

• Mind the model’s limits: Even though today’s models have huge capacities, they’re not infinite. Most have a context limit (how much text they can handle at once). The latest models like GPT-5 and Claude 4 can take in tens or even hundreds of thousands of words, but if you exceed the limit, the model might ignore the overflow or get confused. For very long texts or chats, consider summarizing or breaking the input into smaller chunks. Also, remember that models might not know events after their training cutoff (unless they have browsing or updates), so they could be unaware of very recent news. Always double-check critical factual answers from an AI – they sometimes sound confident but can be wrong (don’t worry, it’s not you, it’s them). If accuracy is crucial, you can even ask something like, “Can you provide sources for that information?”, although not all chatbots can cite sources on demand.
  

Finally, focus on guiding the AI rather than tricking it. Modern AI models have guardrails for safety, so trying to “jailbreak” or fool them with sneaky prompts isn’t useful for a beginner (and often won’t work). Instead, you’ll get the best results by writing clear, honest instructions. Remember, there’s no secret cheat code – just clear communication and a bit of patience to refine your prompt!

With those principles in mind, let’s look at tips for specific common use cases.

Writing Assistance: Your AI Co-writer and Editor

One of the most popular uses of ChatGPT/Claude is helping with writing tasks – from drafting emails and blog posts to editing and polishing your text. The key here is to tell the AI exactly what you need written and how. A few strategies for writing assistance:

• Set the scene: If you need a particular tone or style, mention it. For example: “Write a polite apology email to a customer in a professional tone.” or “Draft a witty two-paragraph blog intro about winter travel.” By specifying the style (professional, witty) and format (email, two-paragraph intro), you guide the model’s writing voice and length. Likewise, stating the audience or purpose helps; writing “Explain this concept as if I’m a 5th grader” yields a simpler, clearer explanation than just “Explain this concept.”
  
  

• Use personas for style consistency: As mentioned earlier, role prompts can be powerful. If you want the AI to mimic a certain perspective or expertise, start with a role. For instance, “You are an experienced copywriter. Write a product description for a new coffee mug...”. The output will likely include the persuasive, polished touches a copywriter might use. This trick also works for creative writing: “Act as a Shakespearean poet and write a sonnet about cheese.” can produce a surprisingly on-theme verse, just for fun.
  

• Provide outlines or templates: If you have a structure in mind, give the AI a skeleton to fill in. For example: “Help me write a cover letter. Start with a greeting, then 1) an intro about my background in teaching, 2) a paragraph on why I’m passionate about the school, 3) a closing.” By laying out the sections, you’re less likely to get a rambly one-size-fits-all paragraph. Business teams often use this approach – providing an annotated template or bullet points, and letting the AI expand them into full text. It’s a great way to maintain control over the content.
  

• Iterate for polish: Once the AI drafts something, you can ask it to refine or edit. For example, “Now make it more concise and add a friendly joke in the intro.” Don’t hesitate to direct the bot to adjust wording, tone, or length. It’s truly like working with an assistant: give feedback and watch it improve the piece. If the first attempt isn’t perfect, your clarifications in a follow-up prompt can get it just right.
  

Also, if you have a chunk of writing you want improved, you can paste it in and say something like “Proofread and enhance the clarity of the following text. Keep the tone formal.” By explicitly stating what kind of edits you want (grammar fixes, clearer wording, maintain formal tone), the AI can act as a helpful editor or proofreader.

Summarization: Getting to the Gist

Have a long article, report, or conversation that you need condensed? AIs are quite good at summarization. The trick is to guide what the summary should focus on and how it’s presented. Here are some tips for prompting summaries:

• State the format and focus: Simply saying “Summarize this” might work, but it’s hit-or-miss – the model could produce a too-brief blurb or include irrelevant details, because “summarize” is vague. It helps a lot to specify the key points or format you want. For example, “Summarize the following meeting transcript in 3 bullet points, focusing on (1) decisions made and (2) action items.” Now the AI knows you want bullet points and exactly which aspects to highlight. Another example: instead of “Summarize this article,” say “Summarize this article in three concise bullet points. Each bullet should capture one major finding, and use no more than 15 words.” This kind of prompt yields a far clearer, more useful summary.
  

• Mention the audience if relevant: Summaries can differ if they’re for experts vs. laypersons. If you want a simple summary for a beginner, you could prompt, “Summarize the below text for a general audience with no jargon.” Conversely, “Summarize the below technical paper for an AI research team” might include more specific terminology. Setting an audience or purpose ensures the summary is at the right depth and complexity.
  

• Use hierarchy for long texts: If you’re dealing with very long content (say, a full novel or a huge report) that even a big-context model struggles with, consider a hierarchical approach: first ask for a summary of each section or chapter, then summarize those summaries. You can literally prompt, “First, list the main sections of this report. Then for each section, give a 1-2 sentence summary.” This stepwise summarization breaks the task down. Modern models with large context windows can handle a lot (OpenAI and Anthropic models can digest book-length inputs), but it’s still wise to structure the prompt in digestible parts if you hit a limit.
  

• Double-check for accuracy: Summaries are only useful if they’re faithful. AIs sometimes hallucinate (make up things) in summaries by accident – especially if the text was complex. If the stakes are high (e.g., summarizing a legal document), it can be good to ask the AI to double-check its summary: “Does this miss any important point from the original text?” Or you can cross-verify by asking questions about the text to ensure the summary didn’t omit something critical. Generally, though, if you clearly instruct what to focus on, the summaries tend to be on point and save you a ton of reading time.
  

Example: “Summarize the following customer support chat in three bullet points, focusing on the issue, customer sentiment, and resolution. Use clear, concise language.” A prompt like this tells the AI exactly what the reader cares about (the problem, how the customer felt, and how it was resolved) and the desired format. The result will be a neat little trio of bullets that gives you the story at a glance.

Coding Help: Debugging and Generating Code with AI

AIs can act as pair programmers or tutors, helping you write code, explain algorithms, or squash bugs. If you’re a beginner in prompting (or coding), here’s how to get the most from an AI on programming tasks:

• Be specific about the language and goal: Always mention the programming language and what you’re trying to do. Instead of “How do I sort a list?” say “How do I sort a list in Python?” or better, “In Python, how can I sort a list of dictionaries by the ‘age’ field?”. The extra detail ensures the AI gives you a relevant code snippet or function in the right language. AIs have seen a lot of coding scenarios, so the more you can describe your particular scenario, the more precise their answer will be.
  

• Include code and error messages: If you have code that’s not working, paste the snippet and any error message into your prompt. For example: “I have the following JavaScript code (...), and it throws an error ‘X is undefined’ on line 12. What’s wrong and how can I fix it?”. By giving the full context – code and the error – you make it much easier for the AI to debug. Think of it as showing your work to a teacher; the more context they have, the better they can help.
  

• Ask for an explanation if learning: If you’re using an AI to learn (not just get answers), prompt it to explain the code. For instance, “Explain what this function does, line by line.” or “Why is quicksort algorithm O(n log n) on average? Explain in simple terms.” You can even combine this with code generation: “Write a Python function to reverse a string and explain the code step-by-step in comments.” This way, you get the code plus an explanation.
  

• Use role-play for expertise: Just as with writing tasks, setting a role can help in coding assistance. Starting your prompt with “You are a senior software engineer experienced in C++” or “Act as a Python programming tutor” can influence the detail and tone of the answer. The former might lead to more efficient, robust code, while the latter might lead to a more educational, commented solution.
  

• Format your request for clarity: When dealing with code, proper formatting is essential. Use markdown triple backticks ``` to encapsulate code in your prompt or ask the AI to do so in its answer. For example: “Provide the code in a single Python code block.” This ensures the response is clean and easy to copy. Also, if you want just the code, you can say, “Give only the code solution, no explanation.” Conversely, if you want a walkthrough, say “Explain the solution step-by-step.” Being explicit about the format helps avoid confusion.
  

• Stay patient and iterate: Debugging can be iterative. If the solution the AI gives doesn’t immediately solve your issue, describe what happened when you tried it, and ask another question. You might say, “I tried that, but now a different error comes up: ...” This back-and-forth is normal, much like talking to a human colleague. Each iteration, the AI has more information about the problem, increasing the chances it will get it right. Also, if the AI’s answer seems off, you can nudge it: “That doesn’t seem correct because X. Can you think of another approach?” Treat it as a collaborator who occasionally needs a little guidance or correction. AI can often act confident when it’s on the wrong path, so make sure to shepherd it.
  

One more tip: remember that AI-generated code might not be perfect. Always test and review it. Often, the suggestions are solid (and can save you time searching through docs), but it’s good practice to make sure the code actually runs and does what you intended. Think of AI as a super helpful assistant that can still make human-like mistakes on code – double-checking will save you some debugging down the road.

Ideation & Brainstorming: Sparking Creative Ideas

Whether you’re brainstorming marketing slogans, startup ideas, writing prompts, or solutions to a tricky problem, AIs can generate a flurry of ideas. The challenge is avoiding too many similar or generic suggestions. Here are some ways to prompt more creatively:

• Ask for multiple options (and lots of them): By default, a model might give you a single idea or a short list that’s fairly obvious. To get creative ideas, explicitly request a bunch. For example: “Give me 10 creative social media post ideas for a bakery launching a new cake flavor.” The first few ideas might be predictable, but as the list goes on, the model will often venture into more unique territory. So, don’t stop at one or two ideas – push for quantity to increase the variety.
  

• Demand diversity: If you find the suggestions are too similar, tweak your prompt to encourage diversity. For instance, “List 5 completely different uses for a retired smartphone, each from a unique perspective (e.g., artist, engineer, teacher, etc.).” Or if you’re looking for travel destinations, you might add, “Make sure they’re in different parts of the country.” Simply telling the bot “give me ideas that are vastly different from each other” can prompt it to avoid the same-old answers. You can also specify a format like “brainstorm ideas in a table with two columns: conventional idea vs. out-of-the-box idea.” Forcing that contrast can yield a spread of normal and wacky suggestions.
  

• **Use the “yes, and…” technique (iterative prompting): Treat brainstorming with AI like improv – build on what it gives. You can start with a basic prompt to get some ideas, then refine in follow-ups. For example, “Give me startup ideas involving renewable energy.” Once you have a list, you might say, “These are okay, but they’re a bit boring – can you make them bolder and more unusual?” or “Combine ideas 3 and 5 and see if something cool comes out.”. The AI can take the initial seeds and morph them. You can even instruct it in one go: “Generate 8 ideas, then pick the most promising 2 and expand those further with catchy details.” This chain-of-thought style prompt has the model brainstorm, then critique or build on its own ideas. It’s a powerful way to simulate a creative back-and-forth process.
  

• Role-play for creativity: A fun and effective trick is to assign the AI a creative role. For example, “Imagine you are a comedian brainstorming movie premises – give me 5 absurd movie plot ideas.” Or “You’re an advertising genius from the 1950s – suggest some classic tagline ideas for a modern electric car.” By role-playing, the AI can tap into a more specific creative voice or angle. Another approach: turn the tables and have the AI ask you questions to spur ideas. You might prompt, “I need to come up with a new mobile app concept, but I’m not sure where to start. Ask me five questions to get me thinking.” This way, the AI helps you explore the space by interviewing you, which can clarify your own requirements or spark inspiration.
  

• Refine and filter: Once you have a bunch of raw ideas, you can use the AI to help evaluate or refine them. For example, “Here are 10 ideas I have (list…). Which two seem most promising for a small budget, and why?” or “Take idea #4 and give me a catchy tagline for it.” The AI can act as a sounding board, a critic, or a creative director to polish the brainstorm results. You can even ask it to highlight any potential flaws or downsides in an idea (a bit of self-critical thinking). This ensures that by the end of the session, you not only have lots of ideas but also some sense of which ones might be gems.
  

Brainstorming with AI is like having an enthusiastic, tireless collaborator on call. The best results come when you encourage it to push past the obvious. By requesting a large number of ideas and steering it to vary them or play pretend roles, you’ll get a richer set of suggestions than with a generic prompt. And of course, feel free to mix in your own judgment and creativity – use the AI’s ideas as a springboard and build from there!

General Q&A: Getting Factual or Helpful Answers

Sometimes you just have a straightforward question: it might be factual (“What’s the capital of X?”), advice (“How do I improve my sleep habits?”), or anything in between. AIs are trained on vast knowledge, but how you phrase your question can still affect the quality of the answer. Here are a few tips for general Q&A prompts:

• Keep it specific and unambiguous: Much like earlier advice, a well-specified question yields a better answer. If your question is too broad (“Tell me about Toledo”), the answer could be an overwhelming info-dump. Narrow it down: “What are the top places to visit in Toledo?”. Now you’re likely to get a focused answer. Similarly, if you want an answer in a certain style or length, say so: “Give a brief answer (2-3 sentences) suitable for a beginner.”
  
  

• Ask for an explanation or an example: If you suspect an answer might be complex, you can build the explanation into your prompt. For instance, “What is quantum computing? Explain like I’m 12 years old, with an example.” This not only tells the AI to simplify the answer, but also to include an example to aid understanding. Models are quite good at tailoring their answer to a requested level of detail or age group when prompted clearly. Don’t hesitate to add “and give an analogy” or “and then quiz me on it” if you’re learning – the AI can accommodate these extra requests in one go.
  

• Break down multi-part questions: If you have a question that has several parts, you might get a clearer result by breaking it into separate asks or explicitly numbering the parts. For example: “1) What are the benefits of solar energy? 2) What are the drawbacks? Answer each separately.” The AI will then structure its response to address each point in turn, which is easier to read. You could also instruct, “Answer in a structured way: first give a definition, then pros, then cons.” Clarity in structure helps the model not to miss anything.
  

• Verify and refine for factual queries: While AIs can provide a lot of factual info, they do not have an internal guarantee of truth. They might occasionally present outdated or incorrect information, especially if the topic is very recent or niche. A good practice is to ask the AI to double-check itself: “Are there any assumptions in your answer that might be wrong? If so, correct them.” You’d be surprised – sometimes the model will willingly point out a possible mistake or uncertainty it has. Additionally, for critical facts (like medical, legal, or historical details), it’s wise to cross-verify with a trusted source. You can also frame your question to encourage accuracy, e.g., “According to reputable sources, what is the population of X as of 2025?”. Some advanced prompt patterns even ask for citations, but note that some models might format something like a citation that looks real yet isn’t verifiable. Use those with caution unless you’re using a tool that actually provides source links.
  

• Use the conversation: If the answer you get is not what you wanted, follow up. For example, “That isn’t what I was looking for – I meant X, not Y. Could you address that?” or “Can you expand on the second point you made?”. One of the joys of these AI assistants is that you can have a back-and-forth. They remember the context of your conversation (up to their memory limit), so you can clarify or ask for more detail without starting from scratch. This iterative approach often leads to a great answer in a couple of turns if the first wasn’t perfect. Think of it as digging for the answer together: each prompt-response cycle hones in closer to what you need.
  

And don’t forget, if you’re ever unsure, you can always ask the AI to clarify its own answer. It sounds funny, but “Can you explain that answer in a different way?” or “Why do you say that?” can turn a dry answer into a more insightful one.

Practice Makes Perfect

Prompting is partly art, partly science – and you’ll get better at it the more you chat with these models. And they keep getting more user-friendly so that it takes less expertise to use them well. The best advice is to just jump in there and try them out on different tasks and see what they’re good at. And when you have some good prompts that help get the results you want, make sure to save them again for future use.

Most importantly, have fun with it! We finally have computers you can chat with, and you don’t need exacting language to operate them. Enjoy this modern miracle, and just apply a little bit of patience and thought to use it well.

Happy prompting!

Partner Spotlight: IT Agent

Elevate your business efficiency.

IT Agent is your trusted partner in business automation and tech support, specializing in deploying and customizing AI assistants for organizations of all sizes.

• Supercharge your IT Management with AI.

• IT Agent provides state-of-the-art remote access, automated patching, and intelligent task automation so your Admins can do more.

Whether you’re upgrading your organization’s capabilities or launching new initiatives, IT Agent ensures your team stays ahead with remote access that fits your needs.

Learn more at: itagent.com.

Stay productive, stay curious—see you next week with more AI breakthroughs!