Unlabelled AI profiles could also have their reach restricted
In a nutshell: There’s a huge number of accounts on Instagram that feature AI-generated characters, but identifying these as non-human isn’t always that simple. As such, the social media giant is changing its current “AI creator” label to the clearer “AI generated profile.” It will also limit the reach of any of these accounts that don’t use this designation.
It’s not just AI-generated slop content sweeping across Instagram these days. There are also countless personas that are entirely AI-generated – many of which appear to be influencer-style accounts – and not all of them make it clear that the person isn’t real.
Instagram previously allowed creators of these accounts to add an “AI creator” label, but it was optional and could still suggest that the persona is a real human who simply “creates” with AI.
The new “AI-generated profile” label is a lot clearer, and should help the many men who engage with AI-generated women on the site understand they’re not real.
Being optional means some account creators won’t add the disclaimer to their AI personas, of course. Instagram says that if it detects an unlabelled AI account in these cases, the account’s reach will be limited. That means non-followers won’t see the posts as recommendations in the Explore section or in Reels.
A lot of these personas are essentially influencers, selling products for legitimate brands. There are no specific rules requiring brands to tell consumers when advertising content has been created using AI, and many companies would rather go down this route than pay a real person to advertise their goods – they tend to be very defensive when they’re called out, too.
Instagram said it introduced the changes because its users “don’t like seeing a profile that seems human, only to find out later that the person featured is AI-generated.”
Unfortunately, Instagram is pretty specific about this applying only to profiles featuring an AI-generated person rather than a human. This won’t apply to the seemingly millions of accounts that pump out AI-generated content all day, every day, which Instagram pleasantly describes as “creators who simply use AI tools as part of their creative process.”
That type of AI content can still be labelled separately, though Meta’s system is hardly fool proof. Across Instagram, Facebook and Threads, the company adds an “AI info” label when an image, video, or piece of audio contains technical signals showing it was generated using AI, or when the uploader admits it. If AI was only used to edit something, the label is hidden in the post’s menu, while photorealistic images made using Meta AI are marked “Imagined with AI.”
Ultimately, both systems still depend on Meta detecting the content or the person behind an account being honest enough to label it themselves. The company admits that the technical markers it relies on can be removed, so it seems unlikely that every fake influencer is suddenly going to announce itself. But making these accounts easier to identify – and harder to push in front of unsuspecting users – is at least a start. Even if it won’t stop thousands of men from asking a collection of pixels whether she’s single.
Letting people see what you are learning and building can create real career capital.
When I first started posting on LinkedIn, my goal was pretty simple: I wanted to get hired.
I’d already been rejected from more than 700 job applications, so I knew the traditional route wasn’t exactly working for me. I started posting consistently because I wanted employers to see what they were getting before they even sat across from me in an interview. It worked.
Since graduating from university two years ago, I’ve received three full-time job offers—two of which I took: first as a marketing executive at a jewellery brand, and later as a marketing and community manager at a B2B startup, where I now lead growth. The third came from an agency helping students land jobs in the UK.
The interesting part wasn’t just that these opportunities came through LinkedIn. It was that I didn’t have to convince these employers to get to know me from scratch. They had already found me through my content—they knew what I did, what I cared about and how I thought.
In my most recent role, I was initially hired partly because the team wanted me to replicate what I’d built on LinkedIn for the company and its brand. The plans eventually changed, but my personal brand was a big part of why I was brought in.
That experience changed how I think about a CV.
A CV tells someone what you’ve done. Your content can show them how you think.
My LinkedIn presence has become a living portfolio. People can see what I think about marketing, the projects I’m working on, the side hustles I’m building, the things I’m learning and, occasionally, what I’m having for dinner. They get a sense of my personality—something a CV was never designed to capture.
It also changes who controls the first step of the career conversation.
The traditional job search is outbound: find an opportunity, apply, wait and try to convince someone you’re worth interviewing. Building in public creates another possibility: you build a body of work, people discover it, and opportunities can start coming to you.
That’s happened repeatedly in my own career. One of the opportunities I still find hard to believe is becoming a columnist for Inc. I never imagined that consistently posting on LinkedIn would eventually lead to writing for a publication I’d admired for years.
But perhaps the biggest misconception around personal branding is that it means becoming an influencer. I’ve built a community of more than 30,000 people while working full-time jobs. I wasn’t trying to become a full-time creator—I was documenting what I was already doing, learning and thinking about.
That’s the thing about creating content: you are the niche.
A coffee chat. An advertisement you noticed. An article you read. A customer conversation. A mistake at work. A side project you’re building. There is no shortage of things to talk about when you’re paying attention to your own life.
Over time, those observations become a body of work that shows people what you’re interested in, what you know and how you see the world.
That’s where personal branding becomes career capital.
We’re used to thinking about career capital as qualifications, experience, job titles and connections. But visibility can compound too–every post becomes another piece of proof, every conversation adds another relationship, and your audience becomes a network that exists beyond your current employer.
Your career doesn’t have to start and end with the organizations on your CV. You can build something that belongs to you.
For me, that something has become a community. I’ve made friendships through LinkedIn, found people who have supported me through major life changes and built relationships with people I’ve never met in person.
If someone offered me enough money to stop posting, I’d probably need a few million dollars to consider it—not because of the follower count, but because I’d be giving up the community I’ve built alongside.
That’s the part of personal branding that gets lost when we reduce it to followers, impressions and “influence.” The real asset isn’t attention. It’s trust.
And you don’t need 30,000 followers to build it. You don’t need to post every day or call yourself a creator. You just need to let people see what you’re already thinking, learning and doing. Being good at your job is only one part of building a career. The other is making it possible for the right people to know what you’re good at.
Reach is everything on social media. Post a thoughtful message that four people read and you might as well scream at the ocean. Recently, Instagram made a move to crack down on AI content by potentially limiting the reach of posts. That might actually work, and it could pave the way for at least addressing some of the AI slop issues we’ve been dealing with lately on social media.
As a quick summary, AI slop is the computer-generated content you might be seeing on your Instagram, X, Facebook and TikTok feeds. It looks ultra-realistic, mostly because AI content generators are now really good at making images and posts that look authentic.
The Instagram crackdown involves two seemingly minor changes. One is that AI creators, meaning the accounts that use an AI-generated profile and use AI content, must use a new label. Earlier this year, Instagram required using the label “AI creator”—the new label “AI-generated profile” is a way to identify the content more clearly.
However, it’s the second change that is the most surprising and potentially could help us all identify AI slop more easily. If an AI creator does not use the new label, Instagram can reduce the reach of posts.
According to the official statement: “Creators who proactively add the AI-generated profile label will not see a change to their profile’s reach. Creators who don’t appropriately label their AI-generated profiles may see limits to their profile’s reach.”
Why the Instagram crackdown is happening now
While a very recent Pew Research study looked at online content, it’s a good indicator of what is happening on social media as well. The study found that 10% of all content you see online is AI generated, and that’s a sharp increase since 2021 when AI slop accounted for only about 2% of all content.
As it happens, LinkedIn users are all over this change for Instagram users, and some have posted several insightful comments. In the posts I reviewed, most users are saying the Instagram change could help because the main reason people are using the bots is to increase reach, and this a notable penalty.
My own take on this is that Instagram has the best data on users and officials there know what works and doesn’t work. It is a balancing act, because as bots gain more reach and AI content looks more and more realistic, some of us could be fooled into thinking it’s real and that ultimately hurts the brand.
Reach is a tricky business. A post can go viral for the wrong reasons, but it can also go viral because we think fake content is legitimate and we connect on a personal level. Once we realize it’s AI generated content, we become just a bit less likely to keep clicking and sharing. It has a longterm impact on our engagement.
I feel this move by Instagram is a good step and will hopefully cause more human-generated content to surface as a way to avoid more Instagram AI slop. We’ll see in the coming months of it actually starts
Feature image credit: Photo by Robert Alexander/Getty Images
Gold stars, killer cats, and everything in between – here are the trends taking over the internet this month.
Trim down the time you spend on social media
Connor Gillvan, founder and owner of content agency TrioSEO, offers up four useful tips to reduce the time you spend managing socials, while maximising output:
Make content a part of your schedule – Gillivan recommends making it part of the schedule instead of allowing it to interrupt the entire week.
Repurpose strong ideas – Reduce your workload and get more value out of each piece of content by turning “one strong idea into several posts”.
Focus on useful, practical content – Rather than overly polished promotional posts, Gillivan says “useful, direct content usually performs better”.
While the temperature may be cooling, things are heating up on social media this September, with the new month bringing a batch of fresh online trends worth paying attention to.
From the inspirational and playful to the downright bizarre, social media marketing offers brands an organic way to reach their target customers – without shelling out a fortune on polished advertising.
However, even for the chronically online among us, spotting which formats are cutting through isn’t always an easy feat. To help you stay ahead of the curve, we’ve compiled a list of viral trends creating a buzz on social media this September.
1. Kinda chic
Audio: Steve Lacy – oh yeah?
Forget brat summer; a new trend is taking over, and it’s kinda chic.
In this format, creators overlay a butter-yellow font reading “kinda chic to” over a photo, video, or carousel, completing the phrase the average person wouldn’t normally consider chic. Think staying in on a Saturday night, wearing your hair natural, or.. being paid to write your nan’s Christmas cards for her.
This simple trend aims to romanticise the mundane, giving creators the chance to reframe the ordinary, unglamorous parts of their lives as something worth celebrating.
It’s already racked up over 100k hashtags on Instagram and has even been adopted by celebrities like Reece Witherspoon and Drew Barrymore, cementing its status as one of summer’s defining phrases.
For brands, it’s an easy trend to jump on without feeling forced. The format lets you showcase your brand’s values without being too polished or serious, whether you declare it’s “kinda chic” to still be figuring out things about your small business, or reply to customer emails yourself outside of work hours.
Source: jaymejo (TikTok)
Source: izzigshore (TikTok)
2. Gold star behaviour
Original audio
This photo trend gives creators and social media influencers the opportunity to share habits and choices they think deserve a gold star.
Creators choose a photo of a backdrop, add the “gold star behaviour” title with a playful or descriptive subtitle like “if I do say so myself”, then scatter a handful of gold stars around the image. Under the stars sits a different habit or opinion they want to praise, from outfit repeating to admitting when you’re wrong.
Rather than focusing on massive achievements, the trend rewards small, everyday wins that often go unnoticed. Lots of the habits also point to buying less, not more – a clear rebuttal against haul culture that dominated social media throughout the 2010s and early 2020s.
For brands, this is a chance to position your products or values as part of a good habit, rather than a hard sell. This could involve slotting your brand naturally into a list of feel-good behaviours, whether it be batch cooking, using your ingredients, or swapping fast fashion for well-made clothing that lasts.
Source: katrinawest (Instagram)
Source: blussomly (Instagram)
3. It was a bad dream
Original audio
This simple trend takes inspiration from the classic “it was all a dream” trope, bringing everyday objects to life and giving them their own fears for comedic effect.
It starts with a disastrous scenario: a product about to fall from a table, a phone about to fall into a sink. Then, before it hits the surface, the video cuts to the object tucked up in bed, waking up from a bad dream and looking around in confusion.
The beauty of this trend lies in its simplicity. No scripting, no dialogue, just a well-timed cut and a startled reaction.
It’s the perfect opportunity for brands selling products to hop in on. Just film the worst-case scenario your product dreads the most, whether it be dropped, left out in the rain, or broken, before cutting to it “waking up”, relieved it was just a bad dream.
Source: alinborodin.ugc (Instagram)
Source: nadiah.ugccreator (TikTok)
4. 10/10 habits
Original audio
Gen Z is locking in this September with this new 10/10 habits self-improvement trend. The format sees creators share habits designed to help followers unlock their potential, with each video kicking off with the line “10/10 habits to…”.
Most are offering advice on how to build extreme discipline or reduce screen time. From staring at a wall for ten minutes before studying to reset your dopamine levels, to deleting all social media apps for a month, the habits embrace being uncomfortable in order to reap longer-term rewards.
It’s a clear pushback for a generation raised on the infinite scroll. Instead of giving in to endless distractions, social media users are encouraging each other to stay accountable and self-disciplined when trying to achieve their goals.
For brands, the numbered list format is an easy one to co-opt. Just swap “discipline” for whatever aligns with the outcome of your product, from saving money to being more productive or being healthier.
Source: jessicawhitaker (YouTube Shorts)
Source: mekashantel (TikTok)
5. You can’t do that
Audio: Dance Till You’re Dead (Official Tram Remix) – Jaydon Lewis
Nothing screams main character energy like arguing with a hater who exists purely in your imagination.
The “you can’t do that” trend involves creators posting a video or image with the text “you can’t do that” layered over the top. It continues saying “of course I can…” followed by a deadpan comeback like ‘you whimsical loser, or you uncreative loser”.
In essence, the trend showcases confidence through exaggeration. The joke isn’t really about the insult, but about the creator refusing to let doubt have the last word.
Similar to the “kind of chic” trend, the format is self-empowering, letting creators flip criticism or self-doubt on its head, rather than letting it knock them down.
For brands, the trend is an opportunity to turn doubts or negative self-talk into a cheeky flex. The key is to keep it self-aware rather than boastful – the humour only lands if it feels like you’re on the joke.
Source: stephanie__allen (Instagram)
Source: laurenbrownconsulting (Instagram)
6. Cat in the hat
Audio: eerie ambient soundtrack
Now to the downright spooky. Fear has been spreading across social media after images of the Dr Seuss character Cat in the Hat prowling the streets of England went viral online.
Not helping to fight the “England is not a serious country” allegations, pictures of the figure based on Mike Myers’ 2003 adaptation have spawned from numerous accounts claiming to be the real deal, with some even organising phony “meet and greets” events in the woods to give fans the opportunity to meet the killer cat in person.
But those with a phobia of talking felines can rest assured – police authorities have dismissed the sightings as fake and confirmed the images are AI-generated. (Sigh of relief).
For brands brave enough to take on the trend, this is a chance to have a bit of fun with “sightings”. Whether you drop a comment on a viral video or post mock sightings near your workplace, it’s a low-cost way to claw your way into the conversation.
Source: realcatinthehatni (TikTok)
Source: invernesstouristboard (Instagram)
By Isobel O’Sullivan
Isobel O’Sullivan is a News Editor at Startups.co.uk with over five years of experience covering business and technology news. Since studying Digital Anthropology at University College London, she’s written for Tech.co, Expert Market, and Eco Experts, using her expertise to distil complex topics, and has had her work linked to in leading publications like the Financial Times and The Guardian.
Gen Alpha is often discussed as if brands can reach the generation by finding the right social platform, creator, or short-form video format.
The household data tells a more complicated story.
Amazon and Nike currently sit at the top among brands in U.S. households with Gen Alpha teenagers, according to early findings from the Gen Alpha Household Influence Study conducted by HarrisX and Allison Worldwide. McDonald’s ranks third with both teens and parents, while Walmart ranks fourth overall and performs particularly well with parents.
Those rankings are interesting, but they are not the most useful part of the research.
The bigger finding is that the purchase journey inside a Gen Alpha household does not move in one direction.
Parents shape what teenagers like. Teenagers shape what parents notice and buy. Different family members discover brands on different platforms. And the person creating demand is not necessarily the person completing the transaction.
For marketers, that changes the problem.
Gen Alpha Is Not Shopping Alone
There are roughly 67 million Gen Alpha children in the United States, including about 16 million between the ages of 13 and 16. Many of these teenagers are being raised by millennials, meaning both generations have grown up in environments where digital discovery, online shopping, social media, reviews, and algorithmic recommendations are normal parts of everyday buying.
But being digitally fluent does not make the teenager an independent buyer.
The study found that 80% of surveyed teens said their parents influence the brands they like.
The influence is even stronger in the opposite direction: 91% of surveyed parents said their teenagers influence the brands they like.
That makes the household less like a traditional parent-child purchasing hierarchy and more like a small recommendation network.
A teenager sees something on TikTok.
A parent checks the price.
Someone recognizes the brand from Amazon.
A sibling already owns something from it.
The purchase may happen at Walmart.
Trying to assign the entire conversion to the first platform in that chain misses much of what actually happened.
Attention and Purchasing Power Are Split
A lot of digital marketing is optimized around capturing the attention of one target customer and pushing that person toward conversion.
Gen Alpha households make that model harder to apply.
A teenager can create the demand without controlling the payment method.
That distinction becomes especially visible in beauty.
Nearly three-quarters of parent purchases involving Sephora and E.l.f. Cosmetics in the study were initiated by the teenager. Among the teenage girls surveyed, 60% said they would ask their parents for E.l.f. products. Teen girls were also more likely than boys to drive purchases made for them: 67% compared with 59%.
In situations like these, the teenager is doing work that marketers traditionally associated with the buyer.
They are discovering the product.
They may be choosing the specific brand.
They can introduce it to the household.
They can create the reason to purchase.
The parent may only enter later in the process.
That makes a simple question such as “Who is our customer?” less useful than it once was.
A better question may be: Who starts the purchase, who validates it, and who completes it?
Those can be three different people.
Mom Still Has More Influence Than TikTok
One of the more surprising findings has little to do with algorithms.
Among teenagers surveyed, 73% said their mothers influenced their brand preferences, compared with 58% who cited their fathers. According to the study, parental influence overall exceeded the influence attributed to social platforms, creators, or celebrities.
That does not mean social media has suddenly become unimportant.
It means discovery should not be confused with authority.
A creator might introduce a product. TikTok might create curiosity. YouTube might explain how something works.
A parent can still determine whether the product feels trustworthy, affordable, necessary, or worth buying.
This is particularly relevant for marketers who build an entire Gen Alpha strategy around youth-facing creative.
Getting the teenager interested may only solve the first part of the sale.
The parent still needs a reason not to say no.
There Is No Single Platform for the Gen Alpha Household
The media data makes the problem even less convenient.
Teen girls in the study leaned most heavily toward TikTok, at 42%, followed by Pinterest at 19%.
Teen boys were more likely to favour YouTube, at 35%.
YouTube also ranked first among dads, at 32%.
For moms, Facebook led at 24%.
A household can therefore contain several audiences occupying different parts of the internet at the same time.
That makes a “Gen Alpha platform strategy” a strange concept.
There may not be one.
A beauty product could first appear in front of a teenage girl on TikTok, become familiar through repeated exposure, get searched elsewhere by a parent, and eventually be purchased through a retailer that neither person originally used to discover it.
The media plan needs to survive that movement.
This is where marketers may need to think less about dominating one platform and more about making the brand recognizable when people encounter it again somewhere else.
The first impression gets attention.
The next impression may need to provide reassurance.
The final interaction needs to make purchasing easy.
Those jobs do not have to happen in the same feed.
Why Amazon and Nike Make Sense at the Top
Amazon and Nike occupying the leading positions is less surprising when viewed through this household lens.
Neither brand depends on one narrow cultural entry point.
Amazon is already deeply connected to how households search for, compare, order, replace, and discover products. A teen can want something without needing to create an entirely new purchasing behaviour for the parent.
Nike operates differently, but it also crosses generations.
It can exist simultaneously as sportswear, fashion, footwear, school clothing, identity, and a familiar household brand.
McDonald’s shows similar cross-generational strength, ranking third for both teenagers and parents in the study. Walmart, meanwhile, performs especially strongly with parents and ranks as the top brand among moms.
These brands are not simply attracting young consumers.
They already have infrastructure inside the household.
Recognition matters because Gen Alpha does not arrive at the purchase with a completely blank slate. Their parents already have years of experience with many of the same companies.
A brand can be new to the teenager while being old news to the person paying for it.
That familiarity can reduce friction.
Moms and Dads Do Not Play the Same Role Either
Treating “parents” as a single segment loses another part of the picture.
Walmart ranked highest with moms but third among dads. Wendy’s also performed particularly well with moms.
Among dads, Nike ranked first and McDonald’s second, with Adidas fourth and Samsung eighth.
There was another difference: 60% of dads in the survey said they introduced their teenagers to new brands, compared with 39% of moms.
So even within the parent side of the household, influence works differently.
One parent may be particularly important for purchase approval or routine household shopping.
Another may play a larger role in brand discovery.
The useful lesson is not that every campaign suddenly needs separate “mom ads” and “dad ads.” That would become mechanical very quickly.
It is that household roles should be investigated rather than assumed.
The Funnel Is Starting to Look More Like a Network
Traditional marketing funnels are convenient because they turn consumer behaviour into a sequence:
awareness, consideration, conversion.
Gen Alpha households do not necessarily behave that neatly.
Awareness might start with the teenager.
Consideration may move to a parent.
Then the parent encounters the brand independently.
The teenager brings it up again.
The family compares alternatives.
Another platform reinforces the choice.
Then somebody purchases it days later through a retailer.
Influence can travel backward and sideways.
For analytics teams, this creates an attribution problem. The last click can still be measured, but it may reveal surprisingly little about why the transaction occurred.
For brand teams, however, the situation is more interesting.
A company does not necessarily need to win every family member independently. It needs enough recognition, relevance, and trust to survive the handoff from one person to another.
What Marketers Should Take From the Data
The obvious response would be to add more channels.
That is probably too simple.
Running TikTok ads for teenagers, Facebook ads for moms, and YouTube ads for dads does not automatically create a household strategy. It can just create three disconnected campaigns.
The harder job is making those interactions support one another.
Youth-facing content can create curiosity without pretending teenagers have unlimited purchasing power.
Parent-facing information can answer practical concerns without feeling like an entirely different brand.
Retail availability can make it easy to act on demand that originated somewhere else.
And the message should remain recognizable enough that a parent understands which product their teenager is talking about when the brand moves from a screen into a real conversation.
That continuity may become more valuable as media consumption becomes more fragmented.
Gen Alpha Marketing May Really Be Household Marketing
The HarrisX and Allison Worldwide research was conducted from May 4 to May 12, 2026, using responses from 705 Gen Alpha teenagers aged 13 to 16 and 750 parents. Results were weighted across factors including age, region, gender, income, and race or ethnicity, with a reported margin of error of plus or minus 2.5%. The study is expected to continue quarterly.
It is one study, and brand rankings will change.
The underlying behaviour is more important.
Teenagers influence parents.
Parents influence teenagers.
Moms and dads do not necessarily play identical roles.
And those people are not consuming media in the same places.
For years, marketers have tried to understand younger consumers by asking which platform owns their attention.
Gen Alpha may force a different question.
Not where can we reach the teenager?
But how does an idea move through the household until someone finally buys it?
The brands that understand that movement may have a much better chance of becoming the Amazons, Nikes, and McDonald’s of Gen Alpha rather than simply becoming another brand that briefly appeared in their feed.
Source
Sara Karlovitch, “Amazon, Nike reign supreme with Gen Alpha teens: report,” Marketing Dive, published August 17, 2026. The article reports early findings from the HarrisX and Allison Worldwide Gen Alpha Household Influence Study.
Once upon a time, I was the editor-in-chief of a corrupt publication. I didn’t know it when I took the job, but within days of starting my new role, the secrets began pouring out: The product review articles were fake, the CEO didn’t care that his business practices were illegal, and the writers were all using ChatGPT.
In my opinion, large language models like ChatGPT are not inherently evil. AI can be an incredible tool for writers. I use it myself to brainstorm ideas, enhance clarity, streamline formatting, and polish my writing.
It’s also a sanity-saver when I can’t think of a particular word. (Pro-tip: Write your sentence, use an underscore as a placeholder, and ask ChatGPT to fill in the blank with the correct term.)
That said, there’s a huge difference between using AI as a supplement and abusing it to churn out content. The former boosts quality and efficiency. The latter insults the intelligence of your reader and causes your reputation to plummet.
The writers on my newly acquired team were using AI to generate entire articles, and it was painfully obvious. Their content was repetitive, boring, and poorly written, not to mention factually incorrect.
Because AI wants to answer your prompt but may not have the necessary data to do so, chatbots often produce “hallucinations,” or information that’s nonsensical and inaccurate. They may pull quotes, stats, or ideas out of thin air, and unless you fact-check your work, you’ll never know it. Misinformation was the first red flag, but AI-generated content also contains the same dead giveaway phrases over and over again.
People who obviously used ChatGPT almost always use these phrases:
“Treasure trove”
“Intricate tapestry”
“It’s important to note that”
“It’s essential to consider”
“While navigating the complexities of”
“A testament to”
“Furthermore”
“Consequently”
“In the world of”
“Let’s delve into”
“Look no further than”
“Whether you’re… or…”
“A plethora of”
“In conclusion”
What do most of these ChatGPT phrases have in common?
Ju Jae-young / Shutterstock
They’re low-effort transition phrases that don’t mean much of anything. They’re fluff. Placeholders. Wasted word count and bad writing. But why would ChatGPT spit out bad writing if language is supposed to be its specialty? Large language models like ChatGPT are primarily trained on publicly available text from the internet.
Yes, that includes some good writing — but for every high-quality piece, you’ll find hundreds of generic listicles, bad blog posts, spammy articles, keyword-stuffed nonsense, and amateur essays with no views.
Real writers use the above phrases, too, but that doesn’t mean they make for good writing
If you removed those phrases entirely, most of your sentences wouldn’t lose any meaning. But it would result in a clearer, more concise, and more confident article.
Beginners believe that fancy, wordy language impresses readers. Professionals know that writing is a form of communication, and communication should be as straightforward as possible.
A few of these phrases won’t make or break your work, but when most of them are present in the same article, it tells your editor two things: You used ChatGPT as a shortcut (not a springboard), and you have no interest in mastering your craft as a writer.
As for me? I got fired from that corrupt publication because I refused to let AI replace passionate, competent writers, and I wear that job termination like a badge of honor.
Maria Cassano is a writer, editor, and journalist whose work has appeared in HuffPost, NBC, Bustle, CNN, The Daily Beast, Food & Wine, and USA Today, among others. Her debut memoir (Numb, Party of One: A Memoir of Healing From Dissociation) is currently available for pre-order.
AI is already becoming a must-have for small businesses, but knowing how to use it well matters more than simply using it.
AI can move fast and be incredibly useful, but human judgment, oversight and ongoing learning are still essential.
It wasn’t that long ago that AI felt out of reach to many small business owners. Flash forward to today and AI is helping local businesses manage customer communications, create social media campaigns, schedule appointments, monitor inventory, and so much more.
AI adoption among SMBs increased from 55% in 2025 to 66% in 2026
70% report increased revenue
92% say AI saves time.
This data tells us that small business owners are embracing AI in large numbers and experiencing measurable benefits. But the survey surfaced a red flag: 70% of SMBs say they need more AI training.
It’s no longer really a question of whether small businesses are using AI. AI has quickly become table stakes. The bigger question now is whether business owners know how to use it effectively and, more importantly, how to use it in ways that actually make an impact on their business.
What’s interesting is that while seven in ten small business owners say they need more AI training, 86% say they’re already comfortable using AI. That suggests there’s an important gap between being comfortable with the technology and actually knowing how to use it well.
For many business owners, using AI might mean asking ChatGPT a question or generating a social media post. But there’s a lot more to using AI effectively. Understanding how to write better prompts, protect sensitive data, evaluate the quality of AI-generated content and integrate AI into existing workflows can make a significant difference in the results.
Marketing is a good example. A roofer can use AI to create a Google ad in a matter of seconds, but that doesn’t necessarily mean the ad will bring in more customers. If they don’t understand what matters to homeowners in their local market, what questions customers are asking or what drives local search performance for roofing businesses in their area, the final ad may sound polished while still missing the things that actually matter.
That’s the real opportunity (and challenge) with AI. It can help businesses move faster and get more done, but speed alone doesn’t guarantee better results. Without the right knowledge and oversight, it’s easy to trust AI too much and end up somewhere you never intended to go. The goal shouldn’t just be to use AI, but to understand how to use it strategically and make sure it’s working toward the outcomes that matter to the business.
Ad hoc AI education
When it comes to learning AI, most SMBs are figuring it out on their own:
YouTube and social media (57%)
Online resources and webinars (49%)
AI tools themselves (31%)
That DIY mindset fits the entrepreneurial spirit, but it can also lead to knowledge gaps.
For example, a florist might use AI to speed up customer responses, only to accidentally share incorrect promotion dates. The technology worked—the implementation didn’t.
The solution? Learn how to use AI effectively while putting the right safeguards in place. checks and balances.
Four ways small businesses can get smarter about AI
1. Start with a question specific to your business. Many businesses begin by asking an AI agent like ChatGPT, “How can I use ChatGPT to improve my business?” A better question: “What’s the most repetitive task in my business?”
A plumbing company admin can spend hours responding to after-hours inquiries. By implementing an AI-powered chat assistant trained on common service questions, the staffer arrives each morning with qualified leads already captured and ready to be followed up on.
2. Block out an ‘AI Learning Hour’ every week on your calendar. AI is evolving far too quickly to treat training as a “one and done” event. Put some discipline around how you and your employees approach AI training. Experiment with AI on real business tasks, participate in team sharing sessions, attend webinars or tutorials, learn new prompting techniques and explore new AI features in existing software.
An accounting firm designates Friday mornings for employees to test one new AI use case each week. Over six months, the team identifies several automations that reduce administrative work and improve client responsiveness.
Lesson: Small, consistent learning creates major gains over time.
3. Adopt a “Trust but Verify” mindset. Treat your AI tool like a talented intern, not an experienced decision-maker.
Always check and verify customer communications, financial information, legal language, and business recommendations. This process saves time and maintains accuracy.
Lesson: Human oversight is a “need to have” not a “nice to have.”
4. Turn to Your Business Peers. Resources like social media influencers can be helpful, but some of the most valuable AI lessons can come from other business owners who are facing the same challenges. Connecting with industry associations, local business groups, Chamber of Commerce events, or online communities related to your profession can give you practical insights and real-world examples of what’s actually working.
For example, a partner at a boutique law firm might attend a local Bar Association event focused on AI. After hearing how other firms are successfully using AI, they realize their efforts could go beyond blogging. Instead, they decide to focus on automating client intake and summarizing documents, creating more value for both the firm and its clients.
Lesson: Learn from businesses solving problems like yours. Real-world, industry-specific use cases often provide more value than generic AI tips.
Where small business owners can get AI-educated
There are many good options for business owners looking to elevate their AI literacy. The OpenAI Academy has built a dedicated Small Business learning track, and Anthropic offers an AI Fluency Framework & Foundations curriculum. The U.S. Chamber of Commerce has launched a free practical AI education program aimed specifically at SMBs. Local community colleges are another avenue, with many rapidly expanding their AI education through continuing education programs and AI literacy workshops.
Small businesses don’t need to become AI engineers. They need to become AI-literate. The good news is that AI education is more accessible than ever. The businesses that make learning a priority today will be the ones capturing the greatest value tomorrow.
Grant Freeman is President at Thryv, a global sales and marketing platform for small and medium-sized businesses. He ensures that Thryv’s innovative software and inspired customer teams create highly engaged and happy business owners.
Four Pillars Gin co-founder Matt Jones writes that, with the AI landscape moving rapidly, a risk lies in companies mistaking the race to adopt the technology as a strategy in itself. When everyone is using AI, what will remain distinctive is what one chooses to do with it.
Every month that goes by, the list of things AI is terrifyingly good at seems to grow.
For time-strapped and budget-poor leaders, the question is becoming less about whether AI matters and more about how to decide which AI priority to focus on first. And for many companies, their commitment to being the best at what they do in their category seems to have been replaced by simply trying to be the best at AI.
But that strikes me as a race only a handful of AI-first companies can ever win.
You know the FOMO is real when even the Deputy Prime Minister gets involved. Richard Marles is off to the US this week and AI is high on his agenda. According to Marles, getting this AI moment right for Australia represents the most critical moment for national self-reliance since World War II. And you thought your board’s scrutiny of your AI plans was tough.
The AI landscape is moving extraordinarily quickly, and there will inevitably be companies that move late and find themselves on the wrong side of the changes it brings.
But there’s another risk in moments like this.
When a technology becomes important and high-profile enough, the race to adopt it can start masquerading as strategy. The question shifts from ‘what problem are we trying to solve?’ to ‘how quickly can we do something, anything, with AI?’. Which brings me, somewhat reluctantly, to the second coming of brand purpose.
The fall of purpose
Yes, I know. ‘Purpose’ is a triggering word for survivors of the brand purpose wars of recent years. For a while, thanks in part to Simon Sinek and his useful but simplistic golden circle, brands didn’t merely make things or solve problems. They started with why. They stood for something. They were on a journey and inviting you to join them. Shampoo wanted to empower you, banks wanted to enable human flourishing and companies making sugary soft drinks proudly shared their peppy visions for social harmony-maxxing.
The author Matt Jones
The backlash was deserved. Mark Ritson and others spent years attacking the assumption that consumers needed the brands in their lives to possess some higher-order social purpose. Somewhere along the way, purpose had become shorthand for corporate virtue, usually expressed in advertising and bearing only a passing relationship to what the company actually did. It rarely meant anything or cost the company anything, all of which demonstrated it barely existed at all. The pity is that, in the process, we discredited a useful idea.
Purpose, at its best, was never about giving customers another reason to admire a brand. It was an internal tool for market orientation. It forced a business to stop staring lovingly at the product it wanted to sell and look instead at the people it hoped might buy it. Why does this thing need to exist in their lives? What problem does it solve? Why does that problem matter? Purpose, used correctly, helped shift the conversation from ‘what do we want to sell?’ to ‘why does anyone need us to exist?’
It’s not about you
This is how we used purpose at Four Pillars Gin. We wrote our purpose statement a year before we launched our first gin and never changed it. But we also never banged on to consumers or bartenders about it. It simply helped us make better, more focused decisions and kept us on course as growth, change and opportunity all inevitably tempted us with their various distractions.
For me, that’s always been the power of the ‘why’ question at the heart of purpose. Why will anyone care? Why would anyone mourn your business if you shut your doors tomorrow? These questions direct a company’s attention up from its own navel and out towards its customers.
Over time, organisations naturally become fascinated by their own capabilities and priorities. When you spend years developing a product, it’s understandable that the product becomes the centre of your universe. AI now gives us a bold new remix of that same old song. The inward-looking product obsessions of the past are becoming the inward-looking technology obsessions of the present. What can AI do for us? How many processes can we automate? Can we put an AI button on this before the investor presentation next week?
Leading with purpose helps to turn the telescope around and ask more meaningful questions. What problems do our customers rely on us to solve? Why do we matter to them? How is that changing? How can AI help us matter even more to them in the future? Will AI make the experience of working with us better, or is our obsession with AI at risk of distracting us from why we really exist?
The Canva case study
Consider Canva, much in the news last week after its valuation took a hit. Its original purpose was unusually easy to understand: democratise design. Take something that had largely required specialist skills and complicated professional software and make it accessible to almost anyone. That clarity helped turn an Australian start-up into one of the country’s great technology success stories.
Now Canva finds itself in the middle of an AI arms race. Its recent AI Vision event in Sydney showcased its own increasingly sophisticated AI capabilities alongside platform collaborators who may soon become competitors. OpenAI, Anthropic and others all sat on Canva’s impressive stage while simultaneously working to expand what ordinary people can create without the need for specialist tools like, well, Canva.
It would be foolish to conclude that Canva has somehow got AI wrong. It is investing heavily and has explicitly framed that investment around empowering people to design and create. But there is a strategic danger in accepting that the contest is now simply about whose AI is best. What happens if the great flattening takes place and the power of your AI model quickly becomes table stakes? Does the question then shift back to who has the best design workflow platform?
If Canva’s purpose remains democratising design for everyone from solopreneurs and students to enterprise teams, it doesn’t necessarily need to beat frontier AI companies at their own game. Perhaps it simply needs to use whatever technology is most relevant to deliver a design experience that is better than anyone else’s and be the world’s best place to manage design end-to-end, not just have the whizziest AI for bits of the process.
AI is not a strategy
Salesforce offers another timely example. News of the much-heralded “SaaS-pocalypse” has, for now at least, been exaggerated. Salesforce has reported record quarterly revenue and pointed to strong growth from Agentforce, its agentic AI offering. For decades,
Salesforce has operated around automating customer relationships, sales, service, data and the workflows connecting them. AI changes what Salesforce can do inside that world, potentially dramatically, but the centre of gravity remains recognisable. It has given Salesforce a new way to pursue and amplify the exact business it was already in.
Salesforce leader Marc Benioff has so far warded off the so-called “SaaS-pocalypse”
We’ve been here before, albeit on a smaller scale. Back in simpler times, businesses wanted a digital strategy, then a mobile strategy, before realising that nobody actually needed a mobile strategy. They just needed an overall business strategy that still made sense once every customer had a computer in their pocket.
AI is arguably broader and even more consequential than any of those shifts, but the tension is the same. And if AI develops anything like its advocates expect, being good at AI may eventually cease to be much of a differentiator anyway. Powerful models, agents and automation will become increasingly available to everyone. Saying your company “uses AI” could become about as revealing as announcing that your employees have email addresses.
Purpose matters for what it does
What will remain distinctive is what you choose to do with it. And that choice requires clarity about the business you’re actually in. The second coming of purpose doesn’t require another generation of lofty manifestos or brands explaining how they’re changing the world.
We’ve had quite enough of that. The great irony is that we spent years arguing about whether customers cared about our purpose. That was never really the point. Purpose mattered because it forced businesses to care more about their customers: to look beyond the thing they made and understand why it mattered in somebody else’s life.
AI makes that discipline useful all over again. When every organisation is asking how much AI it can deploy and how quickly, the more interesting questions remain stubbornly human: why do we exist, why do we matter to the people we serve, and can this extraordinary new technology help us matter to them even more?
Feature image credit: Cliff Obrecht, Melanie Perkins and and Cameron Adams at Canva Create 2026
By MATT JONES
Matt Jones has an eclectic background, combining economics, politics, brand experience and gin. To read more, see the biographical note at the end of his first column for Mumbrella on why SXSW Sydney failed.
For 30 years, the world wide web has run on a surprisingly profound social contract: most sites are free for search engines to access, but if you use their content you give credit by linking to the source.
Recently, that social contract has begun to collapse. Artificial intelligence (AI) tools are crawling sites not to link to them, but to train models and generate answers (which may or may not be accurate).
When you search for something, ChatGPT’s response or Google’s AI Overviews may still include links to sources, but they’re a kind of optional extra to the main answer.
This has triggered a bad dynamic for website owners, the public, and even AI companies themselves: as websites lose traffic (and revenue), many are beginning to block AI scraping tools, meaning AI results depend more on low-quality websites (many of which are also generated by AI). As a result, good information can be harder than ever to find.
How we got here
In the early days of the world wide web, search engines and content creators came to an agreement about crawling (the practice of technologically examining a site to index it, so it can be served up in search results). Content creators would provide access to their sites for free, and even allow search engines to reproduce small snippets of text.
In return, search engines provided links to the sites owned by content creators, who benefited from that web traffic. If content creators didn’t like the deal, they could prevent search engines from crawling their site with instructions in a file called robots.txt.
But if AI tools no longer provide web traffic, it cuts content creators out of the economic loop. There are also other costs associated with each visit to a website, so AI crawling can cost website providers money while not giving them any of the ad or other revenue that would come from human traffic. AI crawlers also crawl more deeply and more intensely than traditional web crawlers, magnifying that cost.
This change in traffic patterns isn’t a small or hypothetical problem. Cloudflare, a web hosting and service company that manages 30% or more of the top 10,000 sites on the internet, estimates over half of all web traffic is now AI bots.
Some of this will be AI agents supervised directly by people, but the majority will be crawlers. Site owners can use robots.txt to ask AI crawlers to stay off their sites – but some AI companies may ignore this polite request.
If the AI companies do honour the request, that can create a different problem. Sites containing misinformation are far less likely to ban AI crawlers, so the AI answers won’t be informed by high-quality sources.
What’s happening in the short term
On the horizon is an event dubbed “Google Zero” – the day when through-traffic from Google drops to nothing. While some greyhaired diehards (like one of the authors of this piece) might still click through to verify AI answers, this traffic is rapidly dwindling, as a direct result of AI summaries.
A study of Wikipedia confirms this, showing that traffic in the English language version of the site dropped off quickly with the launch of AI summaries on Google in English, and that the same pattern occurred in other languages as AI summaries were rolled out. Never having to click through to get an answer might seem great for information seekers, but the reality is more complex.
Many sites are now blocking AI crawlers altogether. Site owners who decide to block AI crawlers are less likely to be linked in AI Overviews answers, even when the AI tool can still access the content to ground its answers (using a technique called retrieval-augmented generation).
Alternative “pay to crawl” models have been suggested as a way to compensate content creators, but haven’t gained traction.
Come September 15, Cloudflare sites will block AI crawlers by default on pages that contain advertising (and therefore make money for content creators).
This means up to 30% of the world’s top sites will no longer appear in Google AI Overviews summaries. It also means that much of what AI is being trained on will itself be AI-generated text.
What it means for you
So what does this mean when you’re looking for information? The quality of AI summaries is likely to go down, at least in the short term, while the new economics of the web get sorted out.
This will happen for two reasons. The first is that high-quality content is less likely to go into those AI summaries – one recent study found that already, around 1 in 6 sources used by AI search tools is itself an AI-generated website.
The second reason is that, as AI models are trained on more AI text, their output may degrade (a phenomenon known as model collapse).
For now, whatever search engine you’re using, the best thing you can do is to scroll down and click on some actual search results. This benefits content creators, and is also more likely to give you more accurate information.
These tips can support your workflow, save time and make the AI assistant’s responses much better
Claude has become one of the AI tools I use most often, whether I’m brainstorming, planning something, vibe coding, researching a topic or simply trying to make sense of a complicated question. But using an AI chatbot every day doesn’t necessarily mean you’re using it well.
In fact, some of the habits that feel like they should make Claude better can have the opposite effect.
That’s what caught my attention when I came across a list of 27 Claude tips from AI consultant Ruben Hassid, who says he’s spent more than 1,800 hours using Anthropic’s chatbot.
Some of his advice goes against the way many of us have been taught to use AI. Keep everything organized in Projects? Maybe not. Keep correcting Claude until it understands what you want? That could actually make things worse. Spend 10 minutes crafting the perfect prompt? There may be a better approach.
Not every tip will make sense for every Claude user, and some of Hassid’s recommendations are based on his own experience rather than hard-and-fast rules. But several are worth trying if you use Claude regularly.
Here are five Claude habits worth breaking — and what to try instead.
1. Stop correcting Claude over and over
We’ve all had this conversation with an AI chatbot. You ask Claude for something. It gets it wrong and then you go back and forth trying to get the response you’re actually looking for — all while wasting your tokens in the meantime.
Even when you explain the problem in even more detail or add another layer of clarification, before long, you’re six messages deep trying to rescue an answer that wasn’t particularly good to begin with.
Hassid recommends doing something much simpler: go back and edit the original prompt. This is a feature that a lot of users overlook but it’s one of the best ways to avoid correcting every wrong answer, which in turn, keeps adding to the conversation.
That’s because every correction you add becomes part of the conversation Claude is working from. Instead of giving the model one clear instruction, you can end up with a growing trail of bad outputs, corrections and exceptions.
Editing the original prompt gives Claude another shot with cleaner instructions.
For example, imagine you asked:Plan a three-day trip to Boston.
Claude gives you an itinerary packed with museums, historical sites and early mornings. But what you really wanted was a relaxed weekend centered around food and neighborhoods.
You could spend several messages correcting the itinerary.
Or you could edit the original: Plan a relaxed three-day trip to Boston centered around great food and interesting neighborhoods. Include no more than one museum, avoid early mornings and leave plenty of unplanned time.
Same request. Much better context.
Try it: If Claude completely misses the mark, resist the urge to argue with it. Edit your previous prompt and regenerate the answer instead.
2. Stop keeping every conversation alive forever
(Image credit: Pexels / Eren Li)
This one is incredibly easy to do. Once Claude understands what you’re working on, abandoning that conversation can feel wasteful. So you keep going…and going!
Eventually the chat contains previous questions, rejected ideas, unrelated tangents, corrections and instructions that stopped being relevant 30 messages ago.
Hassid recommends starting fresh more often, arguing that very long conversations can eventually make Claude less effective.
There isn’t a magic number of messages where Claude suddenly becomes worse, and Claude’s context window is designed to handle a significant amount of information. But context isn’t the same thing as useful context.
Imagine using the same Claude conversation to plan a vacation for weeks. You’ve discussed five hotels, changed the dates twice, ruled out three destinations and completely changed your budget.
Claude may technically have all that information available, but you’re now asking it to distinguish between what you wanted two weeks ago and what you want today. Sometimes the clean slate is the advantage.
Try it: When a conversation starts feeling cluttered, ask Claude to summarize the important information and decisions you’ve made. Paste that summary into a fresh chat and continue from there.
3. Stop obsessing over the perfect prompt
The internet has spent the past few years convincing us that getting great AI results requires elaborate prompts. A few minutes on X or Instagram and you’ll be swamped with plenty of prompts.
But Hassid makes a compelling case for doing something considerably less polished: brain dumping.
Instead of spending several minutes turning an idea into the perfect prompt, simply tell Claude everything you’re thinking.
This works particularly well with voice input because we naturally provide more context when we’re talking. We mention what we’re trying to accomplish, what we’ve already tried, what we don’t like and the half-formed thoughts we might remove if we were carefully typing a prompt.
For example, instead of: Create a weekly meal plan for a family of four.
Try the prompt: I need dinners for the next five days. I don’t want anything that takes more than about 30 minutes, we’re trying to spend less on takeout, one person hates fish, I already have chicken and pasta in the house and Wednesday is going to be really busy, so that meal needs to be ridiculously easy. Help me figure this out.
The second prompt isn’t perfect, but it’s packed with useful information.
Try it: Open Claude and dictate your request as though you’re explaining the problem to a friend. Don’t organize it first. Let Claude organize it for you.
4. Stop telling Claude only what you want
(Image credit: The Motley Fool)
Quite often AI users will prompt an assistant with “Make this better.” “Give me something more interesting.” “Make this easier.” “Be more creative.”
And while they will probably give you answers, these instructions are incredibly subjective. Claude has to guess what “better” or “interesting” means to you.
Hassid recommends giving the model negative examples — showing Claude what you don’t want. Say you’re trying to come up with ideas for a 10-year-old’s birthday party.
Claude suggests a trampoline park, bowling, laser tag and an arcade.
Instead of responding: Give me more creative ideas.
Try the prompt: I don’t want trampoline parks, bowling, arcades, laser tag or other typical birthday-party venues. I’m looking for something the kids probably haven’t done at another birthday party this year.
Suddenly, “creative” has boundaries and it’s far more useful to Claude. The same technique works for recommendations, travel plans, recipes, gift ideas, schedules and almost anything else where personal taste matters.
Try it: When Claude gives you suggestions you dislike, tell it specifically what those options have in common and ask it to avoid that entire category.
5. Stop putting everything into Projects
Projects are one of Claude’s most useful features. They let you keep related chats, instructions and reference material together so you don’t have to repeatedly explain what you’re working on.
But that doesn’t mean every task belongs inside one. Hassid argues that fresh conversations can sometimes be better for creative work because accumulated context can steer Claude toward ideas and patterns you’ve already explored.
I’d treat this as a rule of thumb not something universal for Claude. Projects can be enormously useful when the model genuinely needs background information.
The question is whether that background is helping with the task you’re doing right now.
If you’re using Claude to help plan a major home renovation, for example, keeping your measurements, budget, preferences and previous decisions in one Project makes sense.
But if you suddenly want Claude to give you completely unexpected ideas for what to do with an empty room, you might get more variety by asking in a fresh chat without all those previous assumptions.
Otherwise, you risk asking Claude to surprise you while simultaneously surrounding it with everything you’ve already considered.
Try it: Use Projects when Claude needs context. Try a fresh chat when you want novelty. You can even give the same prompt to both and compare the results.
The takeaway
Sometimes the best thing you can give Claude is a clearer problem. So the next time Claude isn’t giving you what you want, don’t automatically add another paragraph of instructions. Try editing the prompt, start a new chat or tellit what you don’t want.
You may just find Claude understands you better when you give it less to untangle.
Amanda Caswell is the AI Editor at Tom’s Guide and one of today’s leading voices in AI and technology.
A celebrated contributor to various news outlets, her sharp insights and relatable storytelling have earned her a loyal readership. Amanda’s work has been recognized with prestigious honours, including outstanding contribution to media. Known for her ability to bring clarity to even the most complex topics, Amanda seamlessly blends innovation and creativity, inspiring readers to embrace the power of AI and emerging technologies. As a certified prompt engineer, she continues to push the boundaries of how humans and AI can work together. Beyond her journalism career, Amanda is a long-distance runner and mom of three. She lives in New Jersey.
