Blog

Systems Over Surfaces

In 2025 we need to start building systems for content consumption and input instead of focusing only on apps, websites, SEO and other surface level tactics. Too many people get caught up in trying to learn how to design liquid glass or chat UI design patterns, which drives me mad. Unless you are working for Apple designing their UI, there is no need for you to learn how to design glass. You would not use it for anything of your own. You will use their glass UI when you have to, but otherwise your designs should reflect your brand’s CI, not Apple’s visual language.

The same applies to chat UI patterns. These exist for the platforms that use them, so unless you are designing for those platforms there is little point in spending time creating patterns like this. These are surface decisions. Your focus should be on your client’s needs, on how they are going to distribute information and instruction for consumption, and on how you will get engagement through input and interaction. That means building systems that work across multiple contexts and not being distracted by trends that exist only at the surface.

Learning from others is valuable, but the goal should be to centralise all of your content so it is consistent and avoids unnecessary repetition. Once the content foundation is in place, you need a way to capture input, whether that comes through text, voice, gestures or interactions that result in a response, action and reaction. This is where systems thinking pays off because a strong system can adapt to many different surfaces without being redesigned each time.

When we talk about content consumption in this context, we are not talking about endlessly scrolling through a feed on Instagram or TikTok. We are talking about business and visibility. Every company should have a central resource where its content can be stored and distributed no matter how or where it is consumed. That might be on mobile, on desktop websites, inside apps, through Google search or via ChatGPT. It might be read or listened to, presented in words or in visuals. It might need a rich interface, or it might not need one at all. Whatever the format, it needs to be consistent, accessible, and able to adapt to different environments without losing clarity or impact.

Once you have addressed how content will be consumed, you must think about how people will interact with it. What will the input look like, and how will that input influence what is consumed or how the user engages? Will they add a product to a cart, submit a form, leave a review, or trigger a specific action in a system? These are system level decisions that must work across many surfaces. The possibilities for capturing and responding to input are countless and they change depending on where, when and how the interaction happens.

This is the new frontier and it is still largely unknown. I am not offering fixed solutions because there is no single interface any more. We have to design for many possible environments and sometimes we will be designing for no interface at all. With the promise of non screen devices becoming a reality, and with the likelihood of limited visual opportunities such as subtle metrics or visual cues in something like meta glasses, we need to start preparing for a completely different type of interactive experience. That is only possible if we think in systems, not in surfaces.

Which is why it makes no sense to waste time learning how to make liquid glass effects or trendy chat UI patterns unless you are specifically designing for the companies and platforms that use them. Instead, invest your time in understanding how content will be seen, how it will be distributed, and what people are actually going to interact with in the context of your brand or your client’s business. Build systems that can adapt to any surface because in the years ahead those surfaces will keep changing and the systems you create now will decide whether you can keep up.

Create the Future of Design

It’s an exciting time to be a designer. Now is the time to elevate the work, using your passion, experience, and judgement to take your craft to a new level. The future of design is open to those who are willing to cut through the noise and lead it.

The machines have already learned everything ever designed, which means the highest standards are now available to anyone. What once took years of experience to master can now be generated. If you still have a passion for design, now is the time to learn these tools and move beyond what has already been produced.

You should be looking at the tools that are now being used to perform the tasks you once did. Figure out how they can remove the repetitive work and create more space for you to design a better, more thoughtful product experience. Use these tools to save time, and combine them with craft, good taste, and sound decisions to move your work forward.

Below are just a few tools to start with. Learn them if you want to stay competitive in the market, and once they are second nature, build on them. Use them to push the quality and ambition of your work further than before.

In early discovery, AI enables speed. Perplexity can help you explore markets, identify behavioural patterns, and review competitive products more efficiently. ChatGPT is useful for drafting briefs from loose inputs or assembling initial documents that outline direction. Notion AI supports the organisation of ideas into clearer formats. Tome enables those ideas to be presented in a coherent, visual structure without unnecessary time spent formatting. These platforms reduce friction in the early stages of thinking.

That said, choosing which signals to trust, what problems to address, and where to challenge assumptions still comes down to experience. Tools help you see more. They do not decide what is relevant.

During research, Dovetail and AskViable increase coverage by helping you transcribe sessions, extract sentiment, and cluster findings quickly. These efficiencies matter, especially in time-sensitive settings. But no system can detect hesitation in a participant’s tone, catch inconsistencies in their responses, or understand what they chose not to say. The task of interpreting meaning still belongs to the person doing the work.

For workshop preparation, FigJam AI, Whimsical, and Miro AI offer ready-made canvases, templates, and content generation. They allow you to plan collaborative sessions in far less time. Real-time synthesis features help condense insights while the session is running. But leading a workshop requires skill. You still need to follow the discussion, redirect focus if needed, and manage the energy in the room. No tool can substitute for effective facilitation.

In concept development, Galileo, Uizard, and Visily convert inputs into interface options with minimal delay. This allows for faster exploration of alternatives. You can quickly scan multiple directions, discard those that feel generic, and continue developing stronger approaches. These tools are useful for moving beyond the first idea, but they do not resolve what should be built or why. That decision still rests on purpose, not convenience.

In visual execution, Diagram and Figma’s native AI features provide layout suggestions, help with spacing, and manage repetitive actions like component creation. When used alongside a solid design system, they reduce effort and enforce consistency. But they do not account for how something feels, or whether the visual language supports the intent of the product. Assessing whether a design communicates effectively still requires human judgment.

Design systems benefit from platforms like Supernova, Locofy, and UXPin Merge, which streamline documentation, validate consistency, and translate components into code. These help close the gap between design and engineering. Even so, systems need curation. Knowing what to keep, what to remove, and how to evolve a framework requires clear ownership and ongoing input. The system reflects product priorities. Tools do not make those decisions for you.

In prototyping, tools like Framer, Anima, Locofy, and Quest AI enable designers to produce functional models with little or no handoff. This can increase alignment with engineers and help teams validate ideas earlier. But fidelity alone does not explain how an idea works. A prototype should demonstrate logic, explore edge cases, and help answer specific questions. Producing output is not the goal. Communicating purpose is.

As handoff becomes more automated, tools like Zeplin, Specify, and Relay help translate decisions into usable files while tracking updates. Code generation now includes components with production-grade formatting. But alignment with engineering depends on trust, mutual understanding, and conversation. Those relationships are not managed by software.

Testing is increasingly efficient. Maze and Useberry support unmoderated tests, collect interaction data, and surface usability issues quickly. ChatGPT helps write test scripts, group insights, and structure follow-up questions. These improvements make it easier to run tests more often. Still, observing how someone interacts with a feature, where they get stuck, or when they become disengaged tells you more than any metric. Analysis remains a human task.

In marketing, Jasper and Copy.ai create headline variants, body copy, and microtext at scale. This speeds up iteration and removes friction when trying different tones. But context still matters. Effective content reflects the product’s purpose and the audience’s expectations. Matching tone to intent is not something AI can do without direction.

You do not need to learn every tool in depth. But you should understand what they offer, where they apply, and which ones support your workflow. Choosing a reliable set of tools gives you a base to build from. Once that is established, your focus should return to the problems that need solving.

This shift expands the space in which you can apply your craft. With less time spent on repetitive production, you gain more room for exploration, clearer framing, and stronger decisions. Designers who integrate these tools effectively will not just increase their speed. They will raise the quality of their work. The machines become partners that amplify your ability and support the creation of new standards in design that you will lead.

Building my site with AI

I built my website using AI. Not a site builder or a drag-and-drop interface, but actual HTML, CSS, JavaScript, and a custom WordPress theme, written and structured with the help of AI tools.

When I lost my job last year, I needed to pull together my portfolio quickly. I tried a bunch of tools like Squarespace for ease of use so I could just focus on my case studies, and Framer to build something modern with no-code tools, but I thought using AI would make for a more interesting experiment. At first I just used AI to help me generate some ideas using HTML, CSS and JS, but I knew I had to use a CMS and ended up using WordPress. I had not built a theme in a while and the last time was before the block editor was in use. This part was fairly easy, simple prompts in both ChatGPT and Claude gave me all the foundational templates I needed to start from. I was really impressed with the ease at which this could be done so I kept going.

I wrote a list of features I wanted my site to have based on ideas I had played around with before, and I used Claude, Perplexity and ChatGPT. None of them alone could output consistently enough to build what I wanted. At first things were really frustrating because I was prompting and making headway and then out of the blue the AIs would hallucinate or just forget everything and stop working sensibly. It drove me mad and I rediscovered what I consider as close to road rage as I had ever experienced, I would never speak to a human the way I furiously typed my distaste for the AIs messing things up.

There are limits to how much AI can output. There is also only so much you can do in a session before things start to collapse. Often AI forced me to take a time-out. I was making good progress and then out of nowhere it would break something that was working perfectly or introduce some random failure. One of the most infuriating behaviours is when it decides to delete huge chunks of code without telling you, entire features just vanish. You only notice much later when you are too far into a new flow to remember what was lost and that one flaw nearly broke me.

I still do a lot of the coding myself. I lean on AI to give me structure, clean things up, check my logic and handle the grunt work. But AI does not do the thinking. I still have to understand the problem, design the solution and make judgment calls. It is not a replacement for my own skills, it is a faster way to scaffold, clean up and iterate, but the mental heavy lifting still needs me.

But it was me who had to learn a valuable lesson. If nothing else let this be the ultimate takeaway from this article, you need to break up tasks like you would if you were building or designing something yourself. One thing at a time. AI cannot handle large prompts even well structured ones without dropping parts. I had to learn to break everything down. That does not mean I was not outraged again. No all the AIs were excellent at fixing one thing and breaking a few others and it got infuriating. I am certain my neighbours must have been terrified of me. I even took a trip to Bali while working on the site and I am sure that while I kept my composure in coffee shops my typing might have scared some of the nomads sipping on their coconuts in the co-working space. But I persisted and chipped away until I had something close to what I have now. I recently did an update aligned to my new branding. But here are some of the features of the site.

I went with a mobile-first approach and scaled up accordingly. WordPress adds some nuances I am still working through but mostly it works.

Snap to scroll and full width and height for content unless the content is longer than that area and then it allows natural scrolling. It is not perfect. Something I do not understand is making it not nearly as smooth as I would like.

The sections throughout the site change colour on scroll. Instead of having solid background blocks, each section smoothly fades from one shade to the next. It adds a more dynamic and polished feel to the scrolling experience.

I’m a huge performance nut, so I rely on CSS variables to reduce redundant code and system fonts to minimise load time. On Apple devices the site uses San Francisco fonts, which feel native and sharp. Android users also get a clean and legible experience thanks to optimised system fonts.

I also implement viewport-aware background images. These automatically adjust based on device size to maintain visual impact without wasting bandwidth. After a recent hosting migration I lost some of these image files, so I’m in the process of re-rendering and re-optimising them now.

The sections have bite-size amounts of information because lets be honest who reads. There is a bunch of scripts for time of day, day of the week, random case studies on the homepage etc.

I originally had different themes load based on time of day but now that I am introducing my brand colours I have only one theme with different colours based on the section you are in.

I am now spending more time refining the content for AI search results and it is challenging every day I learn something new and have to adjust.

I still add features but Ive learned to break them up. A big one I want to work on after all the recent bug fixes is animation. I had some but found it caused browser lag. I used js frameworks but they seem so bloated for me, so looking at an alternative approach.

I am also considering a new navigation which is still my typical floating on the top right on desktop and bottom on mobile I think there might be something fresher I could add. Feel free to share any new user friendly options you might have seen.

Working with AI is not easy. I’ve also tried Bolt, Lovable and a few others, as I’m constantly bombarded with builders, but honestly none of them offer the refinement I can get with just ChatGPT and similar tools when I keep things simple and focus on one task at a time.

A personal site is never truly finished. It grows as your skills grow. For me, building this version with AI wasn’t just a way to ship something fast. It pushed me in ways I never expected despite frustrating me so badly. But I have gotten used to this being the way I work now.

P.S. I am aware there are some bugs, I’ve recently changed servers and I’m updating the content on my site.

The Writings on the Wall

Words have always mattered. But now, writing has become a superpower.

In a world where AI can produce passable paragraphs in seconds, it is no surprise that many writers feel threatened. I do not blame them. Every time a new design tool comes along claiming that anyone can now be a designer, a little part of me dies as well. But any experienced designer knows it takes far more than arranging elements on a screen to create something that works. There are users to consider, best practices to apply, styles to refine, and context to respect. An AI-generated design might look neat in isolation, but it rarely holds up in the real world.

The same truth applies to writing.

AI has opened up writing to everyone. Almost anyone can improve clarity, spelling, and tone with the right prompt. But keeping writing on brand and developing a distinctive, consistent voice still relies on the taste makers and the most cunning of linguists. This is where skill and experience make all the difference.

More than your website’s design, your content is the thing to focus on. Design and build are simply the structure. What you say and how you say it will shape how people experience your brand. It will also determine how your words are surfaced and used by new technologies. As AI-powered tools become the default way people search and interact, old content strategies will no longer be enough.

Some of the sharpest writers I know work in advertising, which has always felt like the Formula One of writing. They can craft that perfect combination of words to drive a message home, punchy and perfectly timed, often clever or funny. This kind of writing hits harder than anything else, but it is only one part of a brand’s voice.

There are many other opportunities emerging.

Content is no longer limited to campaigns, websites, or social media. It is becoming the backbone of how customers discover, query, and engage with businesses. When interfaces start to disappear and people rely on voice commands and AI answers, the words themselves will be the brand experience.

Every touchpoint should feel like your brand.

This includes your ads, your product copy, your customer support responses, your frequently asked questions, your packaging, your legal disclaimers, and every other place language shows up. Even the voice and tone of your AI assistants can and should be unique.

If you are going to invest in this, it makes sense to build a writing system as thoughtfully as you would create a design system. You will need guidelines, examples, and tools that help teams stay consistent without losing creativity.

Imagine your AI sounding recognisably yours, in the same way you hear a voice in a film and know exactly who it is. Think about how a single sound can stamp a brand into memory, like the PlayStation or a OS startup chime. Your language should work the same way.

This is the time to find your voice and write words that resonate with people no matter where they meet you. Because in the end, when all the screens and buttons fade into the background, it is the words that will remain.

Agencies need to learn to surf the AI tsunami

There is a shift happening, and it is bigger than anything the industry has faced before.

Elon Musk said something like, it does not really matter how clean the beach is if there is a thousand-foot tsunami heading for shore. That captures the moment we are in. Most agencies are still tidying up their decks, adjusting workflows and revisiting templates while a wave is forming that could wipe out anyone who has not already started adapting.

I believe in the talent sitting in agencies. I have seen it, I have worked with them, and the quality of the work has never been the issue. The problem is that traditional agency structures are too slow for what is coming. While big agencies reorganise, the brave ones have gone out on their own or started micro-agencies with like-minded talent, and it is working. This small-agency model is already proving they can deliver work that rivals the behemoths but with the speed and agility clients now demand.

Why fighting it won’t work

Too many agencies jump to building their own AI tools, but that is not innovation, that is misdirection. The real shift is understanding and adopting what already works. You cannot have your PMs doing design work, and you cannot use we are experimenting as an excuse for delivering mediocre results. The one thing you still have is quality, so do not compromise it.

It might seem appealing for clients to go in-house, but most internal teams struggle because they inherit the worst parts of corporate structure and lose the creative edge in the process. Eventually, clients will return to the agencies that adapted, not the ones that folded under their own stubbornness.

What smart agencies do now

The smartest move you can make now is to invest in your people. That does not mean forcing them to learn new tools on their own dime. It means easing their current workload so they have time to experiment. Let them see what these platforms can do. Help them understand how something that once took a team of ten can now be prototyped in an afternoon. Once they experience that shift, they will start pushing boundaries on their own.

Give them unlimited access and buy as many tokens as needed so they can explore freely. Stop throttling their exposure. This is how you increase output by enabling their creativity with what they already know how to do.

When your teams start working with AI instead of against it, something fundamental shifts. They will spend more time shaping ideas and pushing creative boundaries in ways they probably could not imagine before. Instead of briefing others and throwing things over the wall, they will stay close to the work, control the details, and achieve the standard they have always aspired to.

This is where the real competitive advantage emerges against those nimble micro-agencies. They may be fast, but you have something they do not. Deep brand knowledge, established client relationships, and teams that can now move with the same speed but at greater scale.

Price and time will not really matter anymore because both are going to flatten. What will matter is the value and impact of the work. If you can show what your work does and how it affects a client’s business, no one will argue with that. They will invest in results, not just output.

Their boldest ideas, once limited by time, tools or cost, will now be easier to express, easier to test, and more compelling than ever before.

This is how we move forward. Not by resisting change, but by mastering it. The tsunami is coming. The question is not whether it will hit, it is whether you will be ready to ride the wave.

Beyond Design Systems

Design systems have become standard practice across most modern teams. Ask anyone what a design system is and you’ll hear the same few things: a centralised repository of components, visual styles, documentation, and usage rules. It’s a way to speed up production, drive consistency, and align teams working on digital products. Most of the time, that means some UI kits in Figma and a coded library of reusable front-end components. Useful, but often treated as a fixed asset library rather than a foundation for creative thinking.

Depending on who you speak to, design systems are either a lifesaver or a creative constraint. Designers might feel boxed in by too much rigidity. Engineers may appreciate the efficiency. Brand teams enjoy the consistency. All of these perspectives are valid. They come from different needs. The real value isn’t the assets themselves. It’s the system-level thinking that enables teams to work from the same foundation while still leaving space for interpretation and originality when it’s appropriate.

Systems Create Trust

When design systems are done well, they drive trust. Not just with the customer, but inside the organisation too. Everyone is working from the same visual and behavioural playbook. Patterns are predictable. Teams aren’t reinventing basic components every week. This makes everything smoother, particularly at scale. There’s no need for twelve versions of the same button, each with a different hover state. As long as the system leaves space to go beyond the default when needed, it works. The value comes from shared standards, not enforced uniformity.

Design systems should also carry the rationale behind every component. Why a card looks the way it does. What behaviour is expected from a modal. What principles guide these decisions. A strong system communicates this context clearly. It’s not just documentation, it’s design leadership at scale.

Extend the System Beyond the Interface

Visual components are only one layer of the system. There’s no reason to stop there. Voice and tone are just as critical to brand coherence as colour and typography. Yet they’re often treated as secondary, or worse, left undocumented entirely.

A robust system should provide clear guidance on language. Not just grammar and phrasing, but the intent behind it. What the brand sounds like. What words should be used. Which ones should be avoided. This is especially valuable for teams producing interface copy, marketing materials, and legal content. If a brand’s look is tightly governed but its language is all over the place, trust erodes. Customers notice the disconnect.

Even better is when the system supports the production process itself. Legal disclaimers, product descriptions, and error messages are often repeated, tweaked, and reviewed under pressure. Having templates, tone guidelines, and an approval system in place dramatically improves both quality and speed. A writing system is just as important as a visual one. Most brands don’t have one.

Production Environments Need Structure Too

In high-pressure production environments such as internal creative teams, in-house agencies, or large-scale marketing teams, efficiency is non-negotiable. Yet these teams are often operating with scattered resources. Brand guides are handed out in PDF format. Visual assets are dumped into folders. Nobody knows what’s approved, what’s current, or what’s been deprecated.

These brand environments need their own system. Not just asset storage, but proper organisation. Marketing asset creation often lacks the same level of care applied to digital product design. A system for social templates, video formats, typography rules, and usage dos and don’ts is not hard to set up, but it’s rarely done with intention. Instead, teams scramble under deadline pressure, redoing work that should have been templated.

When I worked in an in-house agency, I kept thinking how much smoother things would be if we’d defined our formats in advance. Not just the look, but the production specs. That way we wouldn’t lose hours figuring it out every time. It’s basic design ops. Yet many brands haven’t taken ownership of this foundational layer.

Design Systems as Internal Products

When working in agency environments, the default suggestion was often to adopt an off-the-shelf design framework. While helpful for some, they often came with a steep learning curve and felt too abstract or generic. Instead, we built our own design systems tailored to the work we actually did. Not as a replacement for creativity, but as a baseline to launch from.

These weren’t complex design systems. They were smart templates for components we used frequently. They helped us move faster, produce more consistently, and freed up time to focus on the more complex or unique aspects of a brief. That’s the point. Systems aren’t just about constraints. They serve as multipliers. They let people spend less time re-solving solved problems and more time doing the work that adds real value.

It’s not about sameness. It’s about structure. And that structure can be a huge enabler for creativity, especially when it’s flexible enough to evolve.

Systems Beyond the Screen

Interfaces are no longer limited to screens. Design systems must evolve accordingly. As interaction moves beyond desktop, tablet, and mobile into voice, wearables, and emerging input formats, the system has to do more than standardise pixels. It has to define sound, behaviour, intent, and tone across multiple modalities.

Auditory and conversational interfaces are already part of the experience. AI assistants, voice UIs, and LLM-powered tools are becoming more common in product and service delivery. This demands a new kind of system thinking. The golden thread is no longer just the visual language. It’s the consistent application of a brand’s voice, structure, and intent across every touchpoint, in every format.

To make this work, brands will need systems that train AI models in how to speak, what to prioritise, and how to uphold the values and tone of the company. GPT-style tools will need structure, not just input. A prompt library, content hierarchy, tone calibration, and dialogue frameworks all become part of the system. These help maintain clarity, intent, and identity at scale.

An AI agent operating on behalf of a brand must know when to offer help, when to stay silent, how to escalate, and what not to say. If these models are to become extensions of a brand, then the system must give them a framework to act within. That turns the design system into something closer to an operating system. One that powers intelligent branded experiences instead of static UIs.

Ownership of this work will vary. Some companies may form new roles and teams to manage it. Others will rely on cross-functional collaboration between design, content, brand, product, and legal. Agencies may build the foundation. AI tools may help evolve it. Regardless of who maintains it, these systems must move beyond visuals to remain useful in the years ahead.

Keep the System Flexible

The challenge going forward is balance. A good system creates consistency, but not at the cost of creativity. A loose system invites interpretation, but can lead to chaos. Somewhere in between is a system that scales with the organisation, evolves with the work, and supports its use across both human and machine-driven interactions.

The best systems are not rigid rulebooks or chaotic archives. They are structured foundations that support better thinking, clearer communication, and more meaningful experiences, wherever and however they are delivered.

The Invisible Interface

We are entering a phase where the interface is no longer visual, but conversational. It is not about screens anymore. It is about systems. And right now, ChatGPT feels like the front door to everything.

What started as a clever assistant is quietly becoming an operating system. The recent integrations with Gmail, Docs, Calendar and other tools are not just features. They are signals. ChatGPT is no longer just something we talk to. It is becoming the layer we work through.

You could call it ChatGPT OS. And it changes everything.

From UI to AI
Traditional UI has felt stagnant for a while now. Add a few micro-animations, optimise a flow, reuse the same component library. It is useful, but it rarely feels new.

Now imagine skipping the UI entirely. Just say what you need. Pull data from one place, summarise it, draft a reply, send it. All within a single thread. The GPT becomes the interface.

This does not mean design becomes irrelevant. It means design moves deeper. We need to think about intent, memory, context, and connection. We are not designing buttons. We are designing inputs, integrations, and trust.

Voice, screens, and discomfort
Voice feels like the most obvious interface. Yet it still feels awkward in practice. Not because it is a bad idea, but because the execution is not there yet. These systems do not understand when to pause, when to interrupt, or when you are thinking.

And personally, I do not want to speak to my computer in public. I do not like the idea of people hearing my commands, or listening to my conversations. It feels exposed. It feels unsafe.

So while we wait for something like Jony Ive and Sam Altman’s mystery device, we are left with screens. Which brings me to a very practical frustration.

Why is the ChatGPT editing experience so cramped?
When working on longer content, the side-by-side view becomes messy. It forces output into places that do not make sense, and it decides on the layout for you. Claude gets this right with a clearer layout. But ChatGPT still struggles with space.

If we are serious about this being an OS, then it needs an environment. Imagine a widescreen mode with two clear panels. One for conversation. One for output. Nothing overlapping. Nothing shifting. Just enough space to breathe.

Building the invisible layer
The most exciting part of all this is the invisible layer of integration. What happens when you can say, ‘Add my Gmail here,’ and it just works?

Or will it require onboarding? Authentication steps? A smart way to manage permissions inside the conversation?

This is where the work gets interesting. It is no longer just product design. It is system design. We are building experiences across layers of intent, security, and automation.

That is the side of AI I want to be on. Not the prompt-generated visuals. Not the surface-level gimmicks. But the deeper work that shapes how we engage, how we connect, and how we build trust.

It feels like a natural progression. We started with how things looked. Then came the shift to why they mattered. Visual design gave way to design thinking. Over time, we embraced storytelling, systems thinking and service design. The work expanded beyond screens to include entire experiences and ecosystems.

Now we are entering a new phase. One where the interface disappears and the challenge becomes architectural. We are designing logic, flow and context inside systems that respond, adapt and learn. Every day brings a new interaction to define, a new constraint to navigate, and a new opportunity to shape how people work with technology, not just through it.

This is not the end of design. It is the next surface we design for.

Are you ready to build it?

Clowns to the Left of Me, Jokers to the Right

Scroll for more than a few swipes and you land in the middle of a mess. One side tells you if you are not AI ready, you are out. The other side claims they can spot a ChatGPT-written post a mile off. If you use AI, your work is shit. Everyone is shouting. Few are making sense. It’s as baseless as UX vs the world.

Job descriptions now expect you to be an AI expert in your field. As if that means anything. AI has not been around long enough for anyone to truly become one. At best, there are early adopters, power users, and curious creatives. While the rest of us are dipping in and out, most of the noise is either panic or performance. Some posts are crying out to protect the craft. Others are blindly embracing whatever feels new. In the middle, there are a lot of people just trying to keep the lights on.

Let’s be clear. You are not an expert. Neither am I. Maybe you are ahead of the curve. Maybe you use AI tools more than others. That is fine. But calling yourself an expert just because you have been playing around with prompts for a few months is not helping anyone. Expertise takes time. It takes failures. It takes patience and perspective.

I still laugh when I see AI Creative Director on a job post. Not because I feel threatened. Because it is nonsense. I think Rodd Chant ®️©️ came up with the rather funny Creaitive Director, or at least owns the domain. A lot of Creative Directors earned that title the slow way over decades. Through work. Leading teams. Solving problems and lessons learned.

Then comes the sting. The uncomfortable feeling when people who could never write suddenly sound better than you. When people who never designed are getting decent UI out of thin air. Developers are seeing AI spit out code. Video editors are watching automation creep into their timeline. The tools are getting smarter. And it is rattling the people who built their careers without them.

This is how it goes. The shift always feels like a threat. Until it becomes the norm.

You do not need to panic. You do not need to start calling yourself something you are not. Or have AI in your title just to be relevant. You do not have to be an expert. You can just be a user. Exploring the tools. Trying things. Stay grounded. Be curious. That is enough.

Storytelling is not better because it was co-written with AI. A perfect sentence means nothing if the message is empty. Nobody cares if you used a semicolon correctly, unless the emphasis really matters. AI has not made me a better writer. But it has helped me stop pretending to be a perfect one. Being myself is what sets me apart. Always has been.

I use the tools. I test new things. I rely on the foundations I spent years building. And I try to stay kind through it all. No judgment. Just forward motion.

I am still figuring it out. Still navigating the noise. But I refuse to be dragged to the extremes. I do not want to be the loudest voice in the room. I just want to keep showing up, doing what I can, and staying open to where it all leads.

Maybe that’s what we all need to focus on right now, not picking sides in the AI wars, but finding our own path through the chaos.

Where do you sit in all of this?

Invisible AI, Visible Impact

AI is integrated into how people work. It’s being used to write posts, design assets, generate code, and automate tasks that used to take hours. It’s changing day-to-day behaviour in ways most companies aren’t paying attention to. The focus is still on delivery, cost-cutting, and being able to say they’ve added an AI feature, even when it offers no real benefit. While companies posture to appear current, they’re missing how users are using AI to access information, complete tasks, and make decisions. That shift is already changing how products are found, evaluated, and expected to perform.

Make your content discoverable by AI
Search behaviour is changing. People are no longer clicking through pages of results. They are asking questions and receiving one answer, generated by the AI tool they trust. That answer is built from available information. If your content is unclear or inaccessible, your product will be left out.

Most websites were designed for search engines. They rely on ranking and brand recognition to get clicks. But AI tools don’t send users to your site. They pull information directly and generate a summary. If the structure is unclear or the content lacks detail, your product gets misrepresented or left out entirely.

Make sure your content is structured in a way AI tools can interpret. There are many things you could do like using clear hierarchy, writing in a question and answer format, and adding schema markup. Content now needs to be designed for how AI tools find, interpret and present information.

Stop building AI features that don’t solve anything
The market is full of shallow AI features. Most exist to give the impression of progress. Companies are launching tools that look progressive but don’t improve anything. Some of them just add the letters AI onto their product without delivering anything of value.

Users are already using AI to navigate work, find answers, and complete tasks. They rely on it to summarise, compare, interpret, and recommend. They’re not waiting for your AI feature. They’re already using their own tools to evaluate and interact with what you offer.

Responding to this starts with research. Understand how AI is becoming part of how people work, think, and interact. You don’t need to add AI to your product. You need to make sure your product can be accessed, understood, and used through the AI tools people already rely on. Some companies will need to integrate into those environments. Others will need to expose information in a more structured way. The goal is not to look innovative. It’s to make your product usable in the workflows that already exist.

Use AI to improve performance, not perception
Companies continue to use AI as a way to appear forward-thinking. They announce new features, add visible AI elements to the interface, and use the label to drive attention. But these changes rarely improve how the product actually works.

The friction is still there. Users get stuck, slowed down, or lost in the same places. Tasks take too long. Onboarding is confusing. Support is overwhelmed. The AI doesn’t fix any of it. It just gives the impression that something has changed.

AI should be applied where it improves performance. It can make the product faster, more accessible, and easier to navigate. It can personalise content, reduce support, automate repetitive steps, and improve how systems respond behind the scenes. These changes don’t need to be visible. They need to make the experience better.

Companies are using AI to increase speed, reduce effort, and look innovative. But users are already using AI to evaluate, decide, and act. If your product is not discoverable through their tools, useful in their workflows, or improved by what AI can offer, you are falling behind.

Make your content accessible. Build features that reflect real behaviour. Apply AI where it makes things better, not louder.

The businesses that remain visible in this new environment will not be the ones talking about AI. They will be the ones using it to be found, to be useful, and to perform better throughout the entire experience.

P.S. Are you seeing ROI from AI?

What I Want AI to Do for Me

It’s easy to feel frustrated with how artificial intelligence is being used right now. We’ve all seen the gimmicky trends — AI-generated action figures, lazy artwork, or quick-fix content that floods our feeds and undercuts real creative work.

But instead of ranting about how AI is being abused, I want to flip the script.

Let’s talk about what I actually want AI to do for me.

A personal AI that knows me

Imagine having a personal AI — let’s call it myAI — that is securely and biometrically linked to you. It knows your basic health data: your blood type, height, weight, and age. Nothing shocking there.

But now imagine it goes further. Your myAI updates in real time with your blood test results, what you’ve eaten, where you’ve been, how you’ve slept, and how you’ve trained. It knows when you’ve had too much caffeine, or if you’re low on magnesium. It knows your habits and patterns because it’s tracking them for you.

The data stays with you. You control it. You choose who gets access, and when.

This kind of AI could give you quick, clear access to the information that normally takes too long to find. And in an emergency? You could grant medical practitioners temporary access to key information — the kind of data that could save your life or help them make faster, more informed decisions.

It’s not about being tracked. It’s about being supported — by something built for you, not the algorithm.

AI that makes me better, not irrelevant

Now let’s talk about AI for designers.

No, I don’t want AI to create my work for me. I don’t want it to generate logos or layouts or try to guess what looks “cool.” That’s not help — that’s replacement.

What I do want is a personal AI assistant that stays up to date with legal standards and best practices. Things like the Privacy Act, WCAG accessibility guidelines, and ethical design frameworks. I want an AI tool that supports my work by highlighting areas where I can improve — not creatively, but structurally and responsibly.

For example:

“This form field might not meet accessibility standards for screen readers.”
“This layout could be improved for colour contrast and legibility.”
“This data collection method may breach new privacy regulations in your region.”

Give me guidance. Give me guardrails. Let AI handle the compliance, so I can focus on the craft.

The future of AI is personal and ethical

I don’t need AI to replace me. I want AI to respect me.

That means tools that are personalised, useful, and transparent — not mass-market shortcuts that try to fake creativity. We need AI systems that empower individuals, not just businesses looking to cut corners or jump on trends.

We can build a better future for AI. But only if we stop chasing hype, and start focusing on usefulness.

That’s the version of AI I want in my life.

Not as a replacement.
As a sidekick.