I hadn’t been to a WordCamp Europe in a couple of years, and walking into the venue in Kraków on June 4 reminded me exactly what I’d been missing. I was giddy about catching up with everyone I already knew as much as I was about learning something new.
I’ve been going to WordCamps since 2010, and I wrote down almost this exact feeling after my first WordCamp Europe a few years back. The conclusion then came down to three words: it’s the people. The friends you reconnect with, the people you finally meet in person after years of only knowing them online, the strangers you fall into conversation with in the queue for coffee. A lot of conferences later, I still haven’t found the thing that beats it.
But let me stop waxing poetic about the value of community (will probably get back to that later) and tell you what I found insightful and the thoughts that came after I finished applauding each speaker.
My turn came on Saturday
I was proud to be part of this year’s speaker line-up with a talk I care a lot about, on what I call the expertise-visibility gap.
The argument, in short: a remarkable number of genuinely brilliant people stay the best-kept secret in their field, because being great at the work isn’t enough to be seen for it. Closing that gap comes down to three things: standing for one thing; finding the angles only you can speak to; and building a system that keeps you visible without burning you out. AI is part of all this in the role of a sparring partner that sharpens your thinking while the writing and the judgment stay yours.
I won’t spend more of this post on my own session, because I already wrote the whole thing up, resources included. So let me point you toward the other talks that stayed with me. Every WCEU session is recorded, so you can watch the full program yourself. What follows is a quick tour of the ones I loved, and why.
When AI makes everything a little bit beige
The strongest stretch of the whole event, for me, came on day two: a run of talks on business and product marketing, an all-women lineup, and I had the slightly terrifying honor of closing it out. Three of those talks stacked into a single argument about how to stand out, even though none of the speakers planned it that way.
AI won’t save your marketing (but it might save your time and money)
Monika Dimitrova opened on the problem the rest of us are all dealing with. AI, she argued, is raising the floor on quality and lowering the ceiling at the same time because it averages out distinctiveness. Everything gets a little more polished, a little more competent, and a little more identical. All of our content becomes more beige.
AI lifts everyone to the same floor and erases the differences that mattered.
Monika Dimitrova
Her way out of it came in three moves:
- Talk to real people. Read the support tickets, comb the public reviews, or just call a few customers, until you actually know what they care about and what job they’re hiring you to do.
- Solve a real problem. Find and focus your marketing on the human pain sitting behind the feature rather than the feature itself.
- Have a real opinion. Put a stake in the ground and say what you stand for, even if it costs you a slice of the market. She was careful here, and so am I. A real opinion is something you believe in enough to defend over the long run. No hot take required, and no need to get counter-narrative for the sake of being counter-narrative.
She closed on a point that bridges into everything else. AI is a multiplier, which means a lean solo operator or a small, decisive team can now outpace a big organization whose every post crawls through legal, brand, and three rounds of sign-off from the highest-paid person in the room.
If you want AI to genuinely work for you, the thing to streamline is how you make decisions.
Stop positioning into obscurity to unlock growth
Liza Bogatyrev took that same fight one level down, from how you sound to how the product itself gets positioned.
Her starting observation will be familiar to anyone who’s worked in a marketing team: we write careful, detailed positioning, and then it goes off to live in a deck nobody opens, while sales improvises its own version on every call. The positioning we labored over never makes it into the actual go-to-market motion. Her question was simply how to get everyone aligned and telling the same story.
Her answer came as four hurdles to clear:
Start problem-first, with product marketing and product management agreeing on the one problem you solve better than anyone, drawing on both the product view and a real understanding of the ideal customer. Define who you serve by behavior rather than demographics, by the pain they feel and the job they’re trying to get done, so you can tell quickly whether someone is a fit. Then, even inside a narrow market, go for volume: people rarely buy the first time they see you, so you need enough visibility to stay top of mind and to meet them where they actually are in the buying journey. And make the messaging about outcomes and solutions, in plain language a business decision-maker understands, not only for the technical buyer.
My favorite thing she said works for anyone selling something you can’t physically hold, services and software included. Borrow the test from retail packaging and ask whether your product would stand out “on a shelf”—or, rather, within the consideration set of your potential buyer. Is it instantly clear what it is? And is it obviously different from the thing sitting next to it?
Three levels of atomic product-market fit
Debbie Levitt pushed the thread one level deeper still, past positioning and into the product itself.
Most of us, she pointed out, only ever talk about product-market fit at the macro level: the big match between the problems we solve and a market that finds those problems urgent. But she made the case for two more levels we tend to ignore. The meso level is how well your features and services actually serve your audience’s needs. The micro level is every individual touchpoint, digital or human, and how each one feeds into the whole experience.
Once you look at fit across all three levels, differentiation stops being a single thing. In software we reach for “fast” by default, but fast is only one option on a long list that also holds other considerations that may be important for your users. The work is figuring out which of those matters most to the people you serve, then making sure every small interaction, every micro moment, carries that promise home.
No matter what you think you sell, you actually sell value, desirability, trust, accessibility, usefulness, good usability, and quality. When everyone is “fast,” you’ll compete based on these.
Debbie Levitt
Getting into the room in the first place
All of that differentiation rests on one unspoken assumption: that someone finds you at all. In an AI-mediated web, can you still take that for granted? Two more of my favorite sessions were about earning that discovery, for human readers and machines alike.
The clarity dividend: accessibility as an SEO strategy
Accessibility is a topic I’ve cared about since a WordCamp Europe in Berlin back in 2019, where it first really clicked for me. So Anne-Mieke Bovelett‘s talk, built around what she called the clarity dividend, was always going to land. Her core argument is one I wish more teams heard: accessibility is a sound business decision, with the conversion and visibility numbers to back it up.
Every time a user returns to Google within seconds because they couldn’t find what they came for, abandons a form because the error message is confusing, or gives up because a page is cognitively overwhelming, Google records it as a failure signal.
Anne-Mieke Bovelett
Search engines increasingly weigh behavior signals—how easily people can read, navigate, and use your site—as success signals. So a clear, easy site is more visible, not only kinder. And it reaches further than that: AI crawlers move through the web using many of the same cues as people relying on assistive tech. Build for the humans who need clarity most, and you’re building your AI visibility at the same time.
What I appreciated most, as someone who regularly has to sell this kind of work to stakeholders, is that she came armed with numbers. One figure she cited, from Deloitte: a 0.1 second improvement in load time correlated with an 8.5% lift in retail conversions. She shared a whole set of resources and the proof you need to walk into a management meeting and make the case for an accessibility overhaul and get buy-in.
The AI-first WordPress site: crawler to citation
Alain Schlesser‘s session went more technical than I’d normally pick, which is exactly why I’m glad I sat in. He walked through how to build a WordPress site that AI systems can actually read and cite, from robots.txt to structured data to the content patterns that earn citations, and how to measure whether any of it is working. He gave us non-technical folks a great look at what we need to do. I didn’t even know you have to treat AI bots in different ways:
Ignore this layer and you go invisible at the exact moment that counts: when someone’s AI assistant is building a shortlist of who to consider, and your name never comes up. All the positioning and differentiation in the world can’t help you if you’re not even in the room where the decision happens. This groundwork is what earns you a seat at that table, so your message gets the chance to do its job.
This is the one I’m taking home for myself as technical homework. I have a WordPress site of my own to look after, and AI optimization is going straight to the top of the list. Alain was generous enough to share a full checklist, so you can start too.
Scaling without losing the human
The last two talks I want to flag share a question that sits under everything above: once AI is part of how you work, how do you scale what you produce without scaling the sameness? Both answered it well, one from the vantage point of an enormous organization, the other from the level of a single decision.
Two Worlds Collide: WordPress at CERN
The science geek in me was always going to love a CERN keynote. CERN is CERN. But the story of how such a massive organization moved from Drupal to WordPress gave me far more than a fan moment. As Joachim Valdemar Yde & Francisco Borges Aurindo Barros were guiding us through a behind-the-scenes look of this massive migration, two ideas stuck.
The first was a line that went straight into my notes: the website is the focal point, the first thing people looking to get to know you go to.
CERN websites serve as crucial channels for achieving the Organization’s strategic objectives and communications goals. They enable meaningful stakeholder engagement and represent CERN to all audiences — both internal and external — making them vital to our long-term mission and an essential component of our broader communication strategy.
Joachim Valdemar Yde
A good reminder that even now, with AI overviews often the first stop, the people who genuinely want to understand you still come to the source. Talk of the brand website’s death feels premature to me, and a little out of step with how humans actually work. We still want to hear it from you, in your own words.
The second was the sheer scale of this operation. I gasped when they said that due to lack of resources the team focused on their top 800 sites. Eight hundred, as the short list! That number still feels otherworldly, and it makes the case for content governance. They’ve reached a point where any scientist can publish, freely, for the whole community, while the organization still sounds and looks like one organization. The way you hold those two things together is guardrails: a ready-made library of vetted plugins people can pull from, for instance, so they get freedom and a safety net in the same move.
That’s almost exactly how I approach AI governance in content work. You give people approved skills with the quality standards built in, plus shared context blocks (the brand, the audiences, the messaging pillars, the voice) so everyone is creating freely but still pointed at the same people and the same core messages.
Human in the loop means something
If CERN was about the systems, Tammie Lister‘s talk was about what those systems must never automate away. “Human in the loop” has become a box people tick, and her whole argument was that it should mean something, for real.
She had a very clear take on how to split the work in true human-AI collaboration. Hand AI what it’s genuinely good at: scaling, pattern recognition, speed, consistency. Keep for the humans what only humans bring: the implicit and explicit knowledge of a subject, a real point of view beyond the easily-googled facts, the judgment to read a situation, the context that stops the output from sliding back to the average. And above all, accountability. A machine can’t feel remorse, or shame, or empathy, which is why the decisions that carry real weight have to stay with a person.
It would be easy to assume this matters for engineering but not for something as “soft” as content. I’d argue the opposite. Content is human-to-human, which makes it precisely where misdirection, manipulation, and dark patterns can slip in unnoticed. Someone has to be answerable for it.
The detail I loved most was how she practiced what she preached. Her slides were built with AI, but from illustrations she’d drawn herself, by hand. She kept the human in the loop in the most literal sense I saw all weekend.
What I actually flew home with
Put the two days together and a shape appears. Get the technical foundations right, and an AI assistant can find you and pass your name along. Say something only you would say, and you stay out of the beige. Build the systems and the governance underneath, and you can do all of it at scale without sounding like a machine wrote it. Genuinely useful, all of it. I cam back with a notebook full of notes on how to do that.
And yet the part that matters most, for an event like WordCamp, is the part that never makes it onto a slide or a summary note: who you meet, and what happens in the hallway.
I’d forgotten how much I missed it until I was back in it. The friends I only see once a year, picking up a conversation mid-sentence as if we’d paused it the day before. The people I’d known only as avatars, suddenly real over a coffee. The new faces who, by the end of the second day, weren’t strangers anymore. Wendie Huis in ‘t Veld called it “the WCEU fever,” the high you keep riding for a week once you’re home. I agree, I’m still riding it.
That warmth has hard business logic under it, too: community is the part no feature comparison captures, and it’s what holds up best as AI gets better at everything else. I dug into the business side of it on LinkedIn.
So I’m already counting down to the next stop on the WordCamp calendar. I want the next round of talks like these, the ones that send me home rethinking how I work. And just as much, I want the hallway again, the conversations with friends that leave me feeling connected and part of something far bigger than my own corner of the work.
