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Anthropic just released Claude-mythos-5 .
While many people are focused on benchmarks and model rankings, I think the bigger lesson is something else.
Every new generation of AI is reducing the gap between having an idea and building a solution.
A few years ago, creating a product required a larger team, more time, and specialized skills across multiple areas.
Today, a single person can research, design, code, test, document, and launch faster than ever before.
Technology is no longer the biggest obstacle.
The real advantage comes from identifying meaningful problems, making good decisions, and taking consistent action.
AI continues to increase the speed of execution, but it cannot replace curiosity, ownership, and persistence.
The people who learn how to work effectively with AI will not simply become more productive. They will be able to create opportunities that were previously out of reach.
In the future, success may depend less on how much work you can do yourself and more on how well you can direct intelligent tools toward solving real problems.
Tools will continue to improve.
The question is whether we are improving with them.
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The network for creativity
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Been using AI a lot lately to prototype ideas early, show the direction, and make sure we’re aligned before jumping into the actual build.
Such a good time saver.
The abstract linework gives the avatar a distinct character without leaning on a face—especially like how the data labels make the concept feel functional.
Your website is no longer just being read by people.
AI search engines are reading it too and they understand your website in ways surprisingly similar to how a good UX designer evaluates it.
@Framer's latest AEO guide highlights a few things that matter:
1. Clarity beats cleverness - If a page jumps between ideas, uses vague language, or assumes too much context, AI systems have a harder time understanding what the page actually means.
2. Structure matters - Clear headings, sections, summaries, definitions, and FAQs help AI break content into usable chunks. That is essentially good information architecture.
3. Context > Keywords - AI search is not simply matching keywords. It is trying to understand relationships between ideas, anticipate follow-up questions, and determine whether a page provides enough context to answer them.
This changes how I think about AEO.
You don't need to "write for AI." You need to build websites that are genuinely easy to understand.
For humans first. And increasingly, for machines too.
That means website strategy, content architecture, UX, SEO, and AI discoverability are becoming much more connected.
The interesting part?
Good UX is starting to become good AI optimization.
If your website is struggling with poor AEO results, book a free discovery call today!
