The web is coming full circle.

We’ve been moving toward ‘Google Zero’ for years, where people get their answers directly from search results without ever clicking through to websites. Featured snippets, knowledge panels, instant answers. AI overviews are just the logical next step in this progression.

Are we seeing a return to the early web’s “answers upfront” approach? I’m thinking Yahoo’s curated portals, but with AI doing the curation automatically.

For the longest time we used “google us” as a verification that we were legit, and taught our users that that was the way to go. The problem was that the model got corrupted on the way. SEO spam and sponsored results meant you weren’t exploring authentic sources anymore.

AI overviews aren’t just about creators losing traffic. They’re a correction to a discovery system that had already broken.

Brand awareness becomes even more important. People need to know how to come to your site directly when they want your specific view of the story, not just the AI’s summary.

We obsess over metrics and minuscule shifts when the product market fit has not showed itself.

We focus on 2% shifts in conversion rates while our products have not found their long term audience.

The best communicators don’t hide behind complexity.

They cut through it.

They don’t use complex jargon.

They adapt their communication to the listener.

They explain complexity in simple ways.

AI struggles because human decision-making happens in the negative space.

The things we don’t do, the paths we don’t take, the features we don’t build.

Think about a senior developer looking at a junior’s code and saying “this works, but it’s doing too much.”

Or a designer choosing not to add that extra button because it would clutter the experience.

A product manager who says no to a feature request because it will dilute the core value proposition.

Those decisions to constrain, to say no, to leave things out. They’re often what separates good work from great work.

AI can generate endless possibilities, but it can’t feel the weight of choosing restraint.

The more I think about it, em dashes are the Sharknado of writing.

What 30 years ago would have been a crazy feat now feels like obvious special effects.

You know that moment in a movie when the CGI gets so obvious it breaks your immersion? That’s what’s happening with em dashes in 2025. We’ve developed “AI blindness” where our brains filter out patterns that feel artificial.

The real issue isn’t the punctuation itself. It’s the moment readers start questioning authenticity instead of engaging with ideas.

We’re creating an “authenticity uncanny valley.”

Meanwhile professional writers have been loving em dashes since long before ChatGPT existed. But now they’re second-guessing themselves, worried their natural style might trigger someone’s AI detector.

The same technique goes from impressive to eye-roll-inducing purely based on audience expectations, not because the thing itself has changed.

The feedback loop is absurd: the more people avoid certain patterns to seem “authentic,” the more those patterns become markers of inauthenticity.

Welcome to 2025, where even punctuation has an uncanny valley.

In Back to the Future Part II, Marty McFly walks into Cafe 80’s in 2015 and plays an old arcade game. He’s pretty good at it. But when he finishes, a couple of kids watching him are baffled: “You mean you have to use your hands? That’s like a baby’s toy!”

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Something big has changed in how we find information. Before, we searched Google, clicked through a bunch of links, and pieced everything together ourselves. Now we just ask a question and get an answer we can improve through conversation.

AI that can search isn’t just another tool. It’s a completely different way of working with information.

The Old Way: Search and Put It Together

This was the Google era. You got good at turning your questions into search terms, quickly scanning results, and opening way too many browser tabs. If you were really organized, you saved links for later.

Then you did the hard work of reading through different websites, figuring out what was useful, and putting it all together in your head to get your answer.

You learned to spot good sources. Not just the facts, but you could tell when a website was sketchy because it had more ads than actual content. You got better at seeing patterns across different articles.

The New Way: Ask and Check

Now that we’re in the conversation era, your main skill is asking good questions. Instead of hunting through search results and trying to avoid all the sponsored links at the top, you’re talking to an AI that can instantly pull together information from the entire internet, your own files, and your company’s data.

Your brain does completely different work now. Instead of collecting puzzle pieces, you’re checking whether the completed puzzle looks right. You need to quickly figure out if an answer is complete, correct, and actually helpful for what you need.

The question isn’t whether you’ll make this switch. It’s how quickly you’ll realize that how you work with information has changed forever.

Some say we are moving from information scarcity to information abundance. My view is that this transition has already happened.

What has changed with GenAI is the interaction model.

The previous model with search engines and knowledge bases was: search, filter, read, then synthesize. Now it’s: ask, receive a synthesized answer, then refine through conversation.

This is quite a shift in cognitive work.

Now you essentially have a conversation with the sum of human knowledge.

We’re moving from “search and synthesize” to “ask and evaluate.”

The true bottleneck now is the quality of your questions and your ability to recognize what is good.

As I heard my mom shout that it was time for bed, I screamed back “just one more level!”

That feeling I had as a kid that I was close to completing something, that I was getting closer to an end, was so super addictive.

I recall those memories with fond feelings as I now experience vibe coding in a similar matter.

As I sit late in the nights adding one more feature, prompt by prompt, and having one endorphin kick after another, my head starts prompting me “it’s time for bed.”

But I’m addicted…

“Just one more prompt.”

One thing we never fully embraced was digital collaboration. We treated it as temporary, a pandemic necessity rather than a new tool in our toolbox.

Suddenly we were on endless digital whiteboards trying to replicate physical spaces - the act of seeing multiple post-its on a wall, grabbing them and placing them somewhere else. And when the tools worked smoothly we got a sensation of watching others peoples cursors move and filter, sort and group it felt promising.

But since those years we have eagerly trying to return to our previous ways of working. Back in the rooms, not on screens.

Had we truly adapted one way of working to the digital medium, we might have had an additional tool and expanded our toolset.

The messy part of physical boards is the thing we have a hard time replicating. The badly handwritten notes that someone needed to explain for us to understand. The oddly sorted board that sparked new ideas since it was not just catagoriesed in the optimal AI way.

Maybe it is this imperfect human approach that the digital tools lack for us to make unexpected connections and innovation.

Instead focus on creating material that people actually interact with.

“Old” social media worked like mailing lists. More followers meant more people saw your posts.

“New” social media is all about engagement. An account with 10 followers can go viral with the right piece.

The algorithm favours interaction over audience size.

Good engaging work will find its people. What counts as “good” is another story.