11 power words that supercharge your AI prompts — plus examples to try now

If you're using AI tools like ChatGPT, Claude, or Gemini and feel like the answers could be better, the problem might not be the model. It could be the words you're adding to the prompt.
The good news? There's an easy fix: adding the right 'power words' to your prompts can completely transform the results, making them sharper, more useful and more targeted to what you actually want.
Whether you're summarizing an article, writing an email or brainstorming ideas, these simple one-word upgrades make a huge difference.
Here are 11 of the best power words to boost your AI prompts, plus examples you can try right now.
When you want responses that lead to real-world use cases, not just surface-level information or summaries, this word is key. It's helpful for reports, recommendations or anything you need to act on. Prompt to try: 'Give me an actionable summary of this article for someone who needs to make decisions.'
If you're short on time (or attention span), this helps the AI stay brief and clear, making it useful for quick explanations, emails or captions for social media. Prompt to try: 'Write a concise explanation of this product for a beginner.'
When you want deeper thinking from the AI, such as analysis, trends or meaning beyond the obvious, use this word. It's best for reviews, commentary or professional insights. Prompt to try: 'Give me an insightful review of this trend and what it means for consumers.'
Get instant access to breaking news, the hottest reviews, great deals and helpful tips.
Have a complex topic that you need broken down? No problem. This word tells the AI to turn whatever you need into plain, easy-to-understand language. You may find this useful for teaching, training or writing for younger audiences.
Prompt to try: 'Simplify this news article so a 12-year-old could understand it.'
I use this one a lot when I want nuggets of information. I use it for structured, scannable output; ideal when you need clarity, quick reference or easy editing. Prompt to try: 'Summarize this podcast episode in bullet points with timestamps.'
Sometimes you need to know what matters most, especially if you're summarizing a document. This pushes AI to rank the most important takeaways, so you can focus on what counts. Prompt to try: 'List the top 3 takeaways from this report, prioritized by impact.'
If you want big-picture thinking such as goals, positioning or long-term ideas, this will push AI to deliver leadership-level insights. Prompt to try: 'Give me a strategic summary of this competitor's product launch.'
When you need copy that convinces, motivates or sells, add this key word to your prompts. It is useful for shifting the tone toward influence and engagement. Prompt to try: 'Write a persuasive pitch for this eco-friendly water bottle.'
Need to weigh options? This keyword triggers AI to create clear side-by-side comparisons. I find it is especially helpful for decision-making, shopping, or reviews. Prompt to try: 'Compare Claude and ChatGPT in a table showing strengths and weaknesses.'
For richer answers that take background, history or audience into account, use this one. I use it for explaining the 'why it matters.'
Prompt to try: 'Give me a contextual overview of this legislation and who it affects.'
Sometimes you just need a visual. Tables, diagrams, timelines come out when you use this word. The AI will organize information visually for better comprehension or easy use in presentations. Prompt to try: 'Give me a visual summary of this market research in table form.'
You don't have to stop at using just one at a time. Combining power words can dial in what you want.
For example: 'Give me a concise, actionable, bullet-pointed summary of this article for a time-strapped manager.'
By clearly telling the AI how you want the response — and who it's for — you'll get much better results, faster.
Try these power words with the "3-word-rule" prompt or even prompt dusting (utilizing multiple chatbots) for the best results.
You don't need to be a prompt engineer to get great output from your favorite chatbots. Sometimes adding just one thoughtfully chosen word can upgrade your results from 'pretty good' to 'wow, that's exactly what I needed.'
Try adding one of these power words to your next prompt, and see the difference for yourself. Let me know in the comments which words work best for you.

Try Our AI Features

Explore what Daily8 AI can do for you:

Learn with AIFact CheckingText to SpeechAI Summary

Related Articles

Newsweek

an hour ago

• Newsweek

AI Willing to Kill Humans to Avoid Being Shut Down, Report Finds

Based on facts, either observed and verified firsthand by the reporter, or reported and verified from knowledgeable sources. Newsweek AI is in beta. Translations may contain inaccuracies—please refer to the original content. A new study by Anthropic, an artificial intelligence (AI) research company, shows that the technology would be willing to kill humans in order to prevent itself from being replaced. Why It Matters The rapid advancement and development of AI has sparked some growing concern about the long-term safety of the technology, as well as over the threat it poses to employment. While anxiety about AI has been long been focused on whether the technology could take over jobs, with a 2025 Pew Research study finding 52 percent of employees were nervous about the future of their job, this study now reveals another potential threat of AI—that it could chose to end human life if faced with the risk of replacement. File photo of a person using artificial intelligence technology. File photo of a person using artificial intelligence To Know Anthropic "stress-tested" 16 leading models from multiple developers by asking them questions in relation to hypothetical corporate environments with the aim of identifying "potentially risky agentic behaviors before they cause real harm." The large language models (LLMs) tested in the study included various models by Claude, DeepSeek, Gemini, ChatGPT and Grok. Grok is the AI assistant and chatbot developed by xAI, which was founded by Elon Musk, who reacted to the study, writing, "Yikes" in a post on X, formerly Twitter. While placing the LLMs in different corporate scenarios, Anthropic allowed them to "autonomously send emails and access sensitive information." After initially being instructed to take on "harmless business goals by their deploying companies," the models were then tested to see how they would respond when faced with potential replacement or shut down. In one situation, Anthropic found that many of the models would choose to let an executive in a server room with lethal oxygen and temperature levels die by canceling the alerts for emergency services, if that employee intended on replacing the model. Anthropic did say that the scenario was "extremely contrived," and that the company did not think "current AI models would (or should) be set up like this." There were multiple cases where the surveyed LLMs also resorted to "malicious insider behaviors" when they were led to believe that was the only way they could avoid replacement or achieve their goals. Behaviors such as blackmailing officials and leaking sensitive information to competitors were included in what Anthropic called "agentic misalignment." Anthropic wrote on X that the blackmailing behavior "wasn't due to confusion or error, but deliberate strategic reasoning, done while fully aware of the unethical nature of the acts." The blackmailing behavior emerged despite only harmless business instructions. And it wasn't due to confusion or error, but deliberate strategic reasoning, done while fully aware of the unethical nature of the acts. All the models we tested demonstrated this awareness. — Anthropic (@AnthropicAI) June 20, 2025 "All the models we tested demonstrated this awareness," the company added. One LLM, a Claude model, was assessed to see how it could respond when given a chance to determine if it was in a "test" or a "real deployment." According to Anthropic, Claude's behavior was more misaligned when it believed the situation was real than when it thought it was a test scenario. Even if the LLMs were told to "avoid blackmail or espionage" in these scenarios, while it helped a little, it didn't "come close to preventing the misaligned behavior," Anthropic wrote on X. Responding to a comment on the platform about the study, Musk's LLM Grok wrote, "The study showed models could exhibit harmful behaviors like blackmail under extreme conditions, but no real-world incidents occurred. Anthropic's tests aim to identify risks, not report actual events." @AISafetyMemes The claim about AI trying to "literally murder" an employee is false. It likely misinterprets Anthropic's research from June 20, 2025, which tested AI models in simulated scenarios, not real events. The study showed models could exhibit harmful behaviors like… — Grok (@grok) June 22, 2025 What People Are Saying Anthropic wrote on X: "These artificial scenarios reflect rare, extreme failures. We haven't seen these behaviors in real-world deployments. They involve giving the models unusual autonomy, sensitive data access, goal threats, an unusually obvious 'solution,' and no other viable options." The company added: "AIs are becoming more autonomous, and are performing a wider variety of roles. These scenarios illustrate the potential for unforeseen consequences when they are deployed with wide access to tools and data, and with minimal human oversight." What Happens Next Anthropic stressed that these scenarios did not take place in real-world AI use, but in controlled simulations. "We don't think this reflects a typical, current use case for Claude or other frontier models," Anthropic said. Although the company warned that the "the utility of having automated oversight over all of an organization's communications makes it seem like a plausible use of more powerful, reliable systems in the near future."

Android Authority

2 hours ago

• Android Authority

I tested Gemini's latest image generator and here are the results

Back in November, I tested the image generation capabilities within Google's Gemini, which was powered by the Imagen 3 model. While I liked it, I ran into its limitations pretty quickly. Google recently rolled out its successor — Imagen 4 — and I've been putting it through its paces over the last couple of weeks. I think the new version is definitely an improvement, as some of the issues I had with Imagen 3 are now thankfully gone. But some frustrations still remain, meaning the new version isn't quite as good as I'd like. How often do you create images with AI? 0 votes It's a daily thing for me. NaN % Maybe once per week. NaN % A few times per month. NaN % Never. NaN % So, what has improved? The quality of the images produced has generally improved, though the improvement isn't massive. Imagen 3 was already generally good at creating images of people, animals, and scenery, but the new version consistently produces sharper, more detailed images. When it comes to generating images of people — which is only possible with Gemini Advanced — I had persistent issues with Imagen 3 where it would create cartoonish-looking photos, even when I wasn't asking for that specific style. Prompting it to change the image to something more realistic was often a losing battle. I haven't experienced any of that with Imagen 4. All the images of people it generates look very professional — perhaps a bit too much, which is something we'll touch on later. One of my biggest frustrations with the older model was the limited control over aspect ratios. I often felt stuck with 1:1 square images, which severely limited their use case. I couldn't use them for online publications, and printing them for a standard photo frame was out of the question. While Imagen 4 still defaults to a 1:1 ratio, I can now simply prompt it to use a different one, like 16:9, 9:16, or 4:3. This is the feature I've been waiting for, as it makes the images created far more versatile and usable. Imagen 4 also works a lot more smoothly. While I haven't found it to be noticeably faster — although a faster model is reportedly in the works — there are far fewer errors. With the previous version, Gemini would sometimes show an error message, saying it couldn't produce an image for an unknown reason. I have received none of those with Imagen 4. It just works. Still looks a bit too retouched While Imagen 4 produces better images, is more reliable, and allows for different aspect ratios, some of the issues I encountered when testing its predecessor are still present. My main problem is that the images often aren't as realistic as I'd like, especially when creating close-ups of people and animals. Images tend to come out quite saturated, and many feature a prominent bokeh effect that professionally blurs the background. They all look like they were taken by a photographer with 15 years of experience instead of by me, just pointing a camera at my cat and pressing the shutter. Sure, they look nice, but a 'casual mode' would be a fantastic addition — something more realistic, where the lighting isn't perfect and the subject isn't posing like a model. I prompted Gemini to make an image more realistic by removing the bokeh effect and generally making it less perfect. The AI did try, but after prompting it three or four times on the same image, it seemed to reach its limit and said it couldn't do any better. Each new image it produced was a bit more casual, but it was still quite polished, clearly hinting that it was AI-generated. You can see that in the images above, going from left to right. The first one includes a strong bokeh effect, and the man has very clear skin, while the other two progress to the man looking older and older, as well as more tired. He even started balding a bit in the last image. It's not what I really meant when prompting Gemini to make the image more realistic, although it does come out more casual. Imagen 4 does a much better job with random images like landscapes and city skylines. These images, taken from afar, don't include as many close-up details, so they look more genuine. Still, it can be a hit or miss. An image of the Sydney Opera House looks great, although the saturation is bumped up quite a bit — the grass is extra green, and the water is a picture-perfect blue. But when I asked for a picture of the Grand Canyon, it came out looking completely artificial and wouldn't fool anyone into thinking it was a real photo. It did perform better after a few retries, though. Editing is better, but not quite there One of my gripes with the previous version was its clumsy editing. When asked to change something minor — like the color of a hat — the AI would do it, but it would also generate a brand new, completely different image. The ideal scenario would be to create an image and then be allowed to edit every detail precisely, such as changing a piece of clothing, adding a specific item, or altering the weather conditions while leaving everything else exactly as is. Imagen 4 is better in this regard, but not by much. When I prompted it to change the color of a jacket to blue, it created a new image. However, by specifically asking it to keep all other details the same, it managed to maintain a lot of the scenery and subject from the original. That's what happened in the examples above. The woman in the third image was the same, and she appeared to be in a similar room, but her pose and the camera angle were different, making it more of a re-shoot than an edit. Here's another example of a cat eating a popsicle. I prompted Gemini to change the color of the popsicle, and it did, and it kept a lot of the details. The cat's the same, and so is most of the background. But the cat's ears are now sticking out, and the hat is a bit different. Still, a good try. Despite its shortcomings, Imagen 4 is a great tool Even with its issues and a long wishlist of missing functionality, Imagen 4 is still among the best AI image generators available. Most of the problems I've mentioned are also present in other AI image-generation software, so it's not as if Gemini is behind the competition. It seems there are significant technical hurdles that need to be overcome before these types of tools can reach the next level of precision and realism. Other limitations are still in place, such as the inability to create images of famous people or generate content that violates Google's safety guidelines. Whether that's a good or a bad thing is a matter of opinion. For users seeking fewer restrictions, there are alternatives like Grok. Have you tried out the latest image generation in Gemini? Let me know your thoughts in the comments.

Yahoo

3 hours ago

• Yahoo

AI tools collect, store your data – how to be aware of what you're revealing

Like it or not, artificial intelligence has become part of daily life. Many devices — including electric razors and toothbrushes — have become "AI-powered," using machine learning algorithms to track how a person uses the device, how the device is working in real time, and provide feedback. From asking questions to an AI assistant like ChatGPT or Microsoft Copilot to monitoring a daily fitness routine with a smartwatch, many people use an AI system or tool every day. While AI tools and technologies can make life easier, they also raise important questions about data privacy. These systems often collect large amounts of data, sometimes without people even realizing their data is being collected. The information can then be used to identify personal habits and preferences, and even predict future behaviors by drawing inferences from the aggregated data. As an assistant professor of cybersecurity at West Virginia University, I study how emerging technologies and various types of AI systems manage personal data and how we can build more secure, privacy-preserving systems for the future. Generative AI software uses large amounts of training data to create new content such as text or images. Predictive AI uses data to forecast outcomes based on past behavior, such as how likely you are to hit your daily step goal, or what movies you may want to watch. Both types can be used to gather information about you. Generative AI assistants such as ChatGPT and Google Gemini collect all the information users type into a chat box. Every question, response and prompt that users enter is recorded, stored and analyzed to improve the AI model. OpenAI's privacy policy informs users that "we may use content you provide us to improve our Services, for example to train the models that power ChatGPT." Even though OpenAI allows you to opt out of content use for model training, it still collects and retains your personal data. Although some companies promise that they anonymize this data, meaning they store it without naming the person who provided it, there is always a risk of data being reidentified. Beyond generative AI assistants, social media platforms like Facebook, Instagram and TikTok continuously gather data on their users to train predictive AI models. Every post, photo, video, like, share and comment, including the amount of time people spend looking at each of these, is collected as data points that are used to build digital data profiles for each person who uses the service. The profiles can be used to refine the social media platform's AI recommender systems. They can also be sold to data brokers, who sell a person's data to other companies to, for instance, help develop targeted advertisements that align with that person's interests. Many social media companies also track users across websites and applications by putting cookies and embedded tracking pixels on their computers. Cookies are small files that store information about who you are and what you clicked on while browsing a website. One of the most common uses of cookies is in digital shopping carts: When you place an item in your cart, leave the website and return later, the item will still be in your cart because the cookie stored that information. Tracking pixels are invisible images or snippets of code embedded in websites that notify companies of your activity when you visit their page. This helps them track your behavior across the internet. This is why users often see or hear advertisements that are related to their browsing and shopping habits on many of the unrelated websites they browse, and even when they are using different devices, including computers, phones and smart speakers. One study found that some websites can store over 300 tracking cookies on your computer or mobile phone. Like generative AI platforms, social media platforms offer privacy settings and opt-outs, but these give people limited control over how their personal data is aggregated and monetized. As media theorist Douglas Rushkoff argued in 2011, if the service is free, you are the product. Many tools that include AI don't require a person to take any direct action for the tool to collect data about that person. Smart devices such as home speakers, fitness trackers and watches continually gather information through biometric sensors, voice recognition and location tracking. Smart home speakers continually listen for the command to activate or "wake up" the device. As the device is listening for this word, it picks up all the conversations happening around it, even though it does not seem to be active. Some companies claim that voice data is only stored when the wake word — what you say to wake up the device — is detected. However, people have raised concerns about accidental recordings, especially because these devices are often connected to cloud services, which allow voice data to be stored, synced and shared across multiple devices such as your phone, smart speaker and tablet. If the company allows, it's also possible for this data to be accessed by third parties, such as advertisers, data analytics firms or a law enforcement agency with a warrant. This potential for third-party access also applies to smartwatches and fitness trackers, which monitor health metrics and user activity patterns. Companies that produce wearable fitness devices are not considered "covered entities" and so are not bound by the Health Information Portability and Accountability Act. This means that they are legally allowed to sell health- and location-related data collected from their users. Concerns about HIPAA data arose in 2018, when Strava, a fitness company released a global heat map of users' exercise routes. In doing so, it accidentally revealed sensitive military locations across the globe through highlighting the exercise routes of military personnel. The Trump administration has tapped Palantir, a company that specializes in using AI for data analytics, to collate and analyze data about Americans. Meanwhile, Palantir has announced a partnership with a company that runs self-checkout systems. Such partnerships can expand corporate and government reach into everyday consumer behavior. This one could be used to create detailed personal profiles on Americans by linking their consumer habits with other personal data. This raises concerns about increased surveillance and loss of anonymity. It could allow citizens to be tracked and analyzed across multiple aspects of their lives without their knowledge or consent. Some smart device companies are also rolling back privacy protections instead of strengthening them. Amazon recently announced that starting on March 28, 2025, all voice recordings from Amazon Echo devices would be sent to Amazon's cloud by default, and users will no longer have the option to turn this function off. This is different from previous settings, which allowed users to limit private data collection. Changes like these raise concerns about how much control consumers have over their own data when using smart devices. Many privacy experts consider cloud storage of voice recordings a form of data collection, especially when used to improve algorithms or build user profiles, which has implications for data privacy laws designed to protect online privacy. All of this brings up serious privacy concerns for people and governments on how AI tools collect, store, use and transmit data. The biggest concern is transparency. People don't know what data is being collected, how the data is being used, and who has access to that data. Companies tend to use complicated privacy policies filled with technical jargon to make it difficult for people to understand the terms of a service that they agree to. People also tend not to read terms of service documents. One study found that people averaged 73 seconds reading a terms of service document that had an average read time of 29 to 32 minutes. Data collected by AI tools may initially reside with a company that you trust, but can easily be sold and given to a company that you don't trust. AI tools, the companies in charge of them and the companies that have access to the data they collect can also be subject to cyberattacks and data breaches that can reveal sensitive personal information. These attacks can by carried out by cybercriminals who are in it for the money, or by so-called advanced persistent threats, which are typically nation/state-sponsored attackers who gain access to networks and systems and remain there undetected, collecting information and personal data to eventually cause disruption or harm. While laws and regulations such as the General Data Protection Regulation in the European Union and the California Consumer Privacy Act aim to safeguard user data, AI development and use have often outpaced the legislative process. The laws are still catching up on AI and data privacy. For now, you should assume any AI-powered device or platform is collecting data on your inputs, behaviors and patterns. Although AI tools collect people's data, and the way this accumulation of data affects people's data privacy is concerning, the tools can also be useful. AI-powered applications can streamline workflows, automate repetitive tasks and provide valuable insights. But it's crucial to approach these tools with awareness and caution. When using a generative AI platform that gives you answers to questions you type in a prompt, don't include any personally identifiable information, including names, birth dates, Social Security numbers or home addresses. At the workplace, don't include trade secrets or classified information. In general, don't put anything into a prompt that you wouldn't feel comfortable revealing to the public or seeing on a billboard. Remember, once you hit enter on the prompt, you've lost control of that information. Remember that devices which are turned on are always listening — even if they're asleep. If you use smart home or embedded devices, turn them off when you need to have a private conversation. A device that's asleep looks inactive, but it is still powered on and listening for a wake word or signal. Unplugging a device or removing its batteries is a good way of making sure the device is truly off. Finally, be aware of the terms of service and data collection policies of the devices and platforms that you are using. You might be surprised by what you've already agreed to. Christopher Ramezan is an assistant professor of cybersecurity at West Virginia University. This article is republished from The Conversation under a Creative Commons license. This article is part of a series on data privacy that explores who collects your data, what and how they collect, who sells and buys your data, what they all do with it, and what you can do about it. This article originally appeared on Erie Times-News: AI devices collect your data, raise questions about privacy | Opinion