IMPACT
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Friday, October 23, 2026
Your AI-Generated Flyers Look Terrible. Here Are 100 Prompts to Fix Them in Seconds
My daughter’s school is putting on a Halloween bake sale and the PTA sent home a flyer this week nudging parents to contribute cookies. The relevant dates and details were included. There was a cheerful Jack-o-lantern and autumnal accents. It did the job.
Still, looking at it made my soul hurt. And not just because it was obviously made with AI.
I’m a busy working mom too. I don’t begrudge whichever volunteer saved herself a few minutes with technology here. But if you put every other Halloween school flyer ever made in the history of the world into a blender, this would have been the result. The blandness was aggressive. I longed for handmade weirdness. Or even machine made weirdness. Please just some evidence of personality or aesthetic judgement to relieve the cheerful mediocrity.
On the scale of life problems complaints, bad AI poster design ranks extremely low. But it is increasingly common. Social media is full of cranky complaints about the hideousness and repetition of everyday flyers, posters, and signs made with AI.
Some businesses are even getting blowback from fed up customers. Walmart recently had to ban employees from using AI to freelance in-store graphic design. Delis have been ridiculed for menus dubbed “AI monstrosities.” Competent but uncanny AI signage is bad for our souls. But it can also be bad for business.
And according to one fellow finicky design enthusiast at least it is entirely avoidable.
Use good AI prompting to beat bad AI design
Like me, John Hartnup has noticed a sudden repetitiveness in the everyday ads, menus, and posters surrounding him in the UK.
“The problem with these is not so much that they’re bad. They’re OK, I don’t love them. The problem is that once you’ve seen that style 20 times it starts to irritate just from the sheer repetition,” he wrote on his personal site.
But unlike me, Hartnup moved beyond grumbling to actually do something about this scourge of same-y same-y signs. His inspiration was to use AI tirelessness to defeat AI blandness. He asked ChatGPT to identify the design style behind so many offending posters and then to generate a long list of alternate visual styles.
With the entire history of human design at its disposal, the AI cheerfully compiled. Eventually producing no less than 100 alternatives that don’t involve the usual bubbly letters in primary colors and plasticky cartoon accents.
100 options for every occasion
If you find that an impressive number of styles to choose from, so do I. And they span the gamut from clean and modern to edgy and unexpected. Here’s a small sample of what ChatGPT spat back at Hartnup:
Bauhaus / Modernist
Geometric shapes, primary colours, strong type
Feels cultural / design-led
Swiss Style
strict grid, lots of whitespace
Black/white + one accent colour
Very “information design”, almost institutional
Contemporary Editorial (Magazine-style)
Big headline, elegant serif + sans mix
Think weekend supplement or gallery leaflet
Could feel surprisingly premium
Cut Paper / Collage (Matisse-inspired)
Inspired by Henri Matisse cut-outs
Organic shapes, bold colour blocks
Very striking from a distance
Botanical Scientific Illustration (Modernised)
Clean line drawings of plants, labelled or diagram-like
Monochrome + one highlight colour
Quietly distinctive, slightly academic
90s Rave Flyer / Acid Graphics
Neon colours, warped type, energetic layout
Could echo the samba/dhol energy
Surprisingly effective if done with restraint
Japanese Minimal Poster
Very restrained layout, lots of empty space
One strong graphic element
Elegant, calm, and unusual in this context
And on and on and on. If you’re curious what these look like in practice, Hartnup applied several of them to an identical request for a summer fair flyer on his site.
Now, there’s no excuse for slop signage
Are the results great works of art that will one day hang in the Louvre? Absolutely not. Are they vastly more interesting and varied than the autumnal mediocrity advertising my kid’s bake sale or the grotesque menus so offending deli patrons? Absolutely yes.
And best of all, they are easy to generate as standard slop signage thanks to Hartnup.
He’s generously posted prompts for all 100 design styles, along with a sample poster in each style, for free to his site. Just browse, select, and pop them into your image generator of choice. There are even detailed instructions on how to get the most out of the prompts.
“You don’t have to ask AI for posters as images that can’t be edited,” Hartnup reminds readers with design skills. “Claude and Gemini can generate HTML, PNG, PDF, where the text is real text, layers are real layers, you can change fonts, move things around, edit the text.”
Raising the bar for business owners
The whole site is an act of generosity towards all of us tormented by the tsunami of blah design AI has unleashed upon the world. It is also a challenge to business owners.
If it’s this easy to use AI to make a poster that’s actually distinctive and appealing, you really shouldn’t settle for slop signage that offends your customers’ eyeballs ever again.
EXPERT OPINION BY JESSICA STILLMAN
Wednesday, October 21, 2026
5 Factors That Decide Whether AI Recommends Your Business
Open ChatGPT or Claude and ask either one to recommend the best company in your category. Then read the answer.
If you’re not in it, you already know the feeling. You have happy customers, a good website, and maybe even some great media features. But the tool your buyers now turn to for recommendations doesn’t seem to know you exist.
Here’s what changed. AI search tools are becoming the new front door of the internet. People don’t “Google” things the way they used to, sifting through pages of links to find the one that’s relevant. They ask, get an answer with recommendations, and decide.
AI tools pull those answers from third-party, trusted, credible sources. Not your ads or your social posts, but the stories a journalist chose to write because it was interesting and credible.
The umbrella term for all of this is generative engine optimization, or GEO. Think “the new SEO.” If it helps, picture it like a recipe: press coverage is the protein, but you still need the rest of the ingredients.
Here are the five layers that help AI models decide which brands to recommend:
1. Earned media
AI tools treat editorial coverage in high-authority outlets the way we used to treat word of mouth: as credible information. A journalist chose to write about you, and that carries weight no ad or social post can replicate.
Your coverage should hit three things: recent, relevant, and reputable.
Ask yourself: How much coverage have you landed in the last 12 months? Is it tiny blogs, or real mid-tier and top-tier outlets? And when you show up, are you quoted as an expert or just named in passing? Those aren’t the same value to an AI answer engine.
2. Digital footprint consistency
This one trips people up more than you’d expect. Your website calls you a wellness entrepreneur. Your LinkedIn says certified nutritionist and speaker. Your press bio says nutrition expert and author. None of those are wrong, but to an AI model trying to build a clear picture of you, it’s confusing.
Think of it like everyone reading from the same one-page bio. When your story is told the same way across your website, LinkedIn, press, and social, AI can describe you confidently. When it’s inconsistent, AI gets tentative, and a tentative model doesn’t recommend you.
Your tone can shift from platform to platform, but your positioning can’t. Keep your bio and byline consistent everywhere you show up.
3. Reviews and community presence
AI reads Reddit, forum threads, Google reviews, and it’s checking whether what the media says about you matches what regular people say in their own words.
Land a great feature but let your Google reviews go stale, and that’s fighting your messaging. The fix isn’t glamorous: Ask new customers for reviews so the old ones get diluted and pushed down.
4. Topical authority
Ask ChatGPT to provide a list of the top gut health experts. It surfaces the people cited repeatedly, across multiple sources, on that exact topic.
This is what we’ve always called thought leadership. What’s new is that it’s now measurable.
So, pick your thing. One brand I work with makes breast pumps, and their entire promise is more milk in less time. It’s the tagline, the blog positioning, and most of their press coverage. AI has started recommending them that way when breastfeeding moms ask for the most powerful pump.
The test: If AI read everything published about you, would it land on a clear sense of what you’re known for, or a muddy picture of someone featured 10 different ways?
5. Freshness and structure
AI favors recent information. If your last press hit was two years ago and your blog’s been quiet for three, AI isn’t seeing you.
Structure gets technical, but you don’t need to become a developer. Just know AI reads your website differently than people do. It wants clear, direct language that answers real questions. A beautiful site full of vague brand-speak is harder to parse than a plain one.
“We empower visionaries to unlock their potential” tells AI nothing. Say who you help, how, and why you’re qualified.
Why you can’t wait for the analytics
Someone asks ChatGPT for the best moisturizer for dry skin, gets a recommendation, makes up their mind. Then they close the window, Google the brand name, and buy. Your analytics logs that as “direct traffic” or “branded search.” Nobody sees the AI in the middle of it. The industry calls this dark search, dark AI, and the attribution gap.
Pew Research Center found that once a Google AI summary appears, people click a search result only eight percent of the time (down from the standard 15 percent) and click a link inside the summary just one percent of the time. The answer is now the search term.
So set a baseline this week. Block half an hour and run an AI visibility audit on your brand with these five steps:
1. Open an AI tool you want to appear in and ask the questions your customers would.
2. Ask the models what it says about you.
3. Screenshot what comes up.
4. Note anything inaccurate, missing, or surprising.
5. Work the five layers.
The effort you put in now builds groundwork you can’t see yet. Document your baseline now, so you can prove the movement later.
BY JENNIFER BERSON, FOUNDER @JENERATIONPR
Monday, October 19, 2026
Even LinkedIn is getting tired of your AI-written posts
Bland, AI-generated posts have made LinkedIn the butt of many an internet joke this year. The platform has heard its users’ complaints about lengthy, generic missives never touched by human hands loud and clear.
As AI has made it easier than ever to create huge volumes of content cheaply and easily, that “slop” has flooded the internet. YouTube, Pinterest, Spotify and other platforms have all sought to limit the amount of spammy, AI-generated content their users see.
But LinkedIn has been hit especially hard. Scrolling through the professional networking site earlier this year could mean being bombarded by bullet-pointed lists accented by emojis, references to “B2B sales,” and asks for a follow or comment for more.
A report published in July by Pangram, a research firm that tracks AI content online, found that more than 40% of long-form posts on the platform were AI-generated, compared to around 30% on X and Medium and a smaller percentage on Reddit and Substack.
So now, LinkedIn is upping its fight against slop.
“I know you think you’re doing the right thing with your perfectly bulleted list and your hook at the top, and you followed all the advice from LinkedIn advisors across the internet,” LinkedIn Editor-in-Chief Dan Roth, who leads the platform’s content strategy, told CNN in an interview. “But what works is being human.”
There is some irony in this, given that LinkedIn is owned by Microsoft. The tech giant has pushed for people to adopt its AI tools for everything from writing to coding, and it is up against steep competition from the likes of OpenAI and Anthropic. LinkedIn previously offered AI tools to edit or rewrite posts, although it recently scaled the offerings back.
But low-quality AI posts are a business problem for LinkedIn. They all start to sound the same, Roth said.
If users see too many generic AI posts, instead of content that really teaches them something or gives them a deeper understanding of a professional connection, LinkedIn risks losing them to other platforms.
Fighting AI slop
In August, LinkedIn rolled out a button letting users flag when a post “seems like AI slop,” which was clicked more than 1 million times within its first two weeks. Now, the company is trying to use its own AI systems to help weed out AI slop on the platform and to remind LinkedIn users how to post like humans.
The company built a team largely made up of former journalists and social media experts who have an eye for recognizing generic, sloppy content. These experts help train LinkedIn’s AI model on what authentic, useful posts look like. If the model flags a post as low-quality, AI-generated content, it’ll be less likely to be distributed beyond that user’s direct connections.
Also key to the strategy is a creator management team that acts as “content therapists” for executives, subject matter experts and other LinkedIn users, many of whom have gotten accustomed to the convenience of using AI to write what, on the surface, appear to be polished posts, Roth said.
“A lot of times now today, they’ll run it through Claude or Gemini or wherever, they’ll post it on LinkedIn and it will perform poorly. And then they come to the team and they’re like, ‘Why did this do badly?’” Roth said. “And the best thing you can do is give it back to them and be like, ‘Did you enjoy reading this? Do you see yourself in this?”
Instead, the team encourages users to embrace imperfection in their posts — to make videos by leaning a phone up against a coffee mug, rather than shooting in an expensive studio, or to dash off a post to start a conversation, even if it isn’t a complete thought.
The efforts are showing early signs of success. Improvements to LinkedIn’s detection systems have resulted in a 40% decline in views of content classified as AI slop, the platform said last month.
That’s not to say LinkedIn is entirely opposed to AI, Roth said, adding that “not everyone is a born communicator.” But failing to edit or personalize content means it’s less likely to reach a wide audience on the platform.
“We just try to push people to be more human,” he said. “That is what is required to be able to cut through the noise.”
By Clare Duffy
Friday, October 16, 2026
AI Has a New Name: Super Intelligence. Why You Should Start Using SI Right Now
An executive order directing federal agencies to use “Super Intelligence” and “SI” in place of “Artificial Intelligence” and “AI” has big implications. A new Super Intelligence Force was also announced last week to coordinate the federal response.
This all makes SI more than a slogan. As I’ve written about before, language is a critical leadership lever that can shift mindsets and mobilize action.
With SI now the official language of the U.S. executive branch, business leaders need to understand what changed and why, including the implications for leadership, innovation, and organizational transformation.
The Definition of Super Intelligence
SI is currently defined using the same basic definition as AI, while allowing 60 days for the Assistant to the President for Science and Technology to propose a formal federal definition.
The concept of SI has been around for a while. In 1998, Nick Bostrom from Oxford University introduced the idea that superintelligence is intelligence that is much smarter than the best human minds in every field. Depending on your perspective, we might already have achieved this.
For business leaders, SI works best as a strategic term. AI has become a catchall for chatbots, automation, and applications. SI raises the conversation to the level CEOs and boards should address: how a dramatic increase in intelligence could—and should—reshape the way a company makes decisions, operates, and competes.
The SI Summit that created a word that will stick
The White House summit assembled leaders from chipmakers, data centers, cloud platforms, and frontier model companies. David Sacks, chair of the President’s Council of Advisors on Science and Technology, called it the first gathering of the critical players across the industry’s full stack. Many were competitors. Some had deep disagreements. They still produced an agreement.
Six companies signed the White House Accord on Super Intelligence. It calls for internal controls, an internal team to verify them, outside audits, and an independent board committee. Specifically:
Implement robust internal controls to monitor the capabilities and alignment of its models during training and deployment around areas like cybersecurity, biosecurity, and chemical threats, and to ensure that its models do not hack or access technical systems in unintended ways.
Empower an internal team to ensure all of the controls, monitoring, and detection are operating as intended, and that any issues are remediated.
Partner with an independent external auditor or evaluator to carry out independent assessments of whether the controls, monitoring, and detection are operating as intended.
Designate an independent committee of the board of directors to oversee and receive reports from the teams operating the controls and the internal and external auditors and evaluators, as well as to ensure any issues identified are remediated.
The summit’s most useful lesson came from who was included. Anthropic CEO Dario Amodei attended despite sharp disagreements with many others in the room. All the key players who needed to sign up for voluntary controls on the future of AI (now SI) were present. That’s been a fundamental principle of change management. Engagement is key for buy-in and ultimately implementation.
The new federal task force extends that pattern. Its leaders come from intelligence, the Federal Trade Commission, the Pentagon, and the Office of Personnel Management. It also plans outreach to consumers, public interest groups, religious organizations, infrastructure providers, and technology companies.
Build Your Own Super Intelligence War Room
Most businesses will never train a frontier model. But every business, small and large, will face choices about where these systems are used in strategy, innovation, operations, and more. And also what data they give access to the SI to use, and who carries the risk when things fail.
The idea of “superintelligence” can be a forcing function to elevate AI from chatbot discussions to truly taking a look at the implications for business strategy.
For example, a small company can bring together the owner, the salesperson closest to customers, the operations lead, and outside technology or legal advisers. A large company needs the leaders responsible for technology, business strategy, workforce decisions, customer experience, security, legal risk, and operations. Include at least one informed skeptic as well.
Start with one important use case tied to the business strategy of the company. For example: how you develop new products, identify emerging competitors, monetize your business model, or anything else that’s mission-critical. Describe how a new “super intelligent system” could provide you with a step change in innovation and value, whether saving money or generating new revenue streams. Also explore what a system like this would ideally do on its own and where a person must review its work to help minimize risks.
This is basically a strategic brainstorm, but anchored in real value creation and a recognition that SI might be here to stay – and play a critical role in business strategy.
Names Matter
Names matter. Use specific technical terms like chatbot, data center, open-weight model, or application to “declutter” the concept of artificial intelligence (e.g., making it more descriptive while simplifying what it means).
Use “Super Intelligence” in strategy conversations to signal that the company is making choices about a new source of capability with consequences across the business.
The first test of any SI strategy is simple: what will you do or create with real super intelligence?
EXPERT OPINION BY SOREN KAPLAN, WSJ BESTSELLING AUTHOR, KEYNOTE SPEAKER, AND LEADERSHIP STRATEGY ADVISOR
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