Brand guidelines have always been a compromise. You document the rules—colors, typography, spacing, logo usage—and hope people follow them. They don’t, or they follow the letter while missing the spirit. Every designer who’s inherited a brand system knows the drift: assets that are technically on-brand but feel wrong, or interpretations that stretch “flexibility” past recognition.

Luke Wroblewski is pointing at something different:

Design projects used to end when “final” assets were sent over to a client. If more assets were needed, the client would work with the same designer again or use brand guidelines to guide the work of others. But with today’s AI software development tools, there’s a third option: custom tools that create assets on demand, with brand guidelines encoded directly in.

The key word is encoded. Not documented. Not explained in a PDF that someone skims once. Built into software that enforces the rules automatically.

Wroblewski again:

So instead of handing over static assets and static guidelines, designers can deliver custom software. Tools that let clients create their own on-brand assets whenever they need them.

That is a super interesting way of looking at it.

He built a proof of concept—the LukeW Character Maker—where an LLM rewrites user requests to align with brand style before the image model generates anything. The guidelines aren’t a reference document; they’re guardrails in the code.

This isn’t purely theoretical. When Pentagram designed Performance.gov in 2024, they delivered a library of 1,500 AI-generated icons that any federal agency could use going forward. Paula Scher defended the approach by calling it “self-sustaining”—the deliverable wasn’t a fixed set of illustrations but a system that could produce more:

The problem that’s plagued government publishing is the inability to put together a program because of the interference of different people with different ideas. This solved that.

I think this is an interesting glimpse into the future. Brand guidelines might have software with them. I can even see a day where AI can generate new design system components based on guidelines.

I spent all of last week linking to articles that say designers need to be more strategic. I still stand by that. But that doesn’t mean we shouldn’t understand the technical side of things.

Benhur Senabathi, writing for UX Collective, shipped 3 apps and 15+ working prototypes in 2025 using Claude Code and Cursor. His takeaway:

I didn’t learn to code this year. I learned to orchestrate. The difference matters. Coding is about syntax. Orchestration is about intent, systems, and knowing what ‘done’ looks like. Designers have been doing that for years. The tools finally caught up.

The skills that make someone good at design—defining outcomes, anticipating edge cases, communicating intent to people who don’t share your context—are exactly what AI-assisted building requires.

Senabathi again:

Prompting well isn’t about knowing to code. It’s about articulating the ‘what’ and ‘why’ clearly enough that the AI can handle the ‘how.’

This echoes how Boris Cherny uses Claude Code. Cherny runs 10-15 parallel sessions, treating AI as capacity to orchestrate rather than a tool to use. Same insight, different vantage point: Cherny from engineering, Senabathi from design.

When I managed over 40 creatives at a digital agency, the hardest part wasn’t the work itself—it was resource allocation. Who’s got bandwidth? Who’s blocked waiting on feedback? Who’s deep in something and shouldn’t be interrupted? You learn to think of your team not as individuals you assign tasks to, but as capacity you orchestrate.

I was reminded of that when I read about Boris Cherny’s approach to Claude Code. Cherny is a Staff Engineer at Anthropic who helped build Claude Code. Karo Zieminski, writing in her Product with Attitude Substack, breaks down how Cherny actually uses his own tool:

He keeps ~10–15 concurrent Claude Code sessions alive: 5 in terminal (tabbed, numbered, with OS notifications). 5–10 in the browser. Plus mobile sessions he starts in the morning and checks in on later. He hands off sessions between environments and sometimes teleports them back and forth.

Zieminski’s analysis is sharp:

Boris doesn’t see AI as a tool you use, but as a capacity you schedule. He’s distributing cognition like compute: allocate it, queue it, keep it hot, switch contexts only when value is ready. The bottleneck isn’t generation; it’s attention allocation.

Most people treat AI assistants like a single very smart coworker. You give it a task, wait for the answer, evaluate, iterate. Cherny treats Claude like a team—multiple parallel workers, each holding different context, each making progress while he’s focused elsewhere.

Zieminski again:

Each session is a separate worker with its own context, not a single assistant that must hold everything. The “fleet” approach is basically: don’t make one brain do all jobs; run many partial brains.

I’ve been using Claude Code for months, but mostly one session at a time. Reading this, I realize I’ve been thinking too small. The parallel session model is about working efficiently. Start a research task in one session, let it run while you code in another, check back when it’s ready.

Looks like the new skill on the block is orchestration.

The data from Lenny’s Newsletter’s AI productivity survey showed PMs ranking prototyping as their #2 use case for AI, ahead of designers. Here’s what that looks like in practice.

Figma is now teaching PMs to build prototypes instead of writing PRDs. Using Figma Make, product managers can go from idea to interactive prototype without waiting on design. Emma Webster writing in Figma’s blog:

By turning early directions into interactive, high-fidelity prototypes, you can more easily explore multiple concepts and take ideas further. Instead of spending time writing documentation that may not capture the nuances of a product, prototypes enable you to show, rather than tell.

The piece walks through how Figma’s own PMs use Make for exploration, validation, and decision-making. One PM prototyped a feature flow and ran five user interviews—all within two days. Another used it to workshop scrolling behavior options that were “almost impossible to describe” in words.

The closing is direct about what this means for roles:

In this new landscape, the PMs who thrive will be those who embrace real-time iteration, moving fluidly across traditional role boundaries.

“Traditional role boundaries” being design’s territory.

This isn’t a threat if designers are already operating upstream—defining what to build, not just how it looks. But if your value proposition is “I make the mockups,” PMs now have tools to do that themselves.

The optimistic case for designers in an AI-driven world is that design becomes strategy—defining what to build, not just how it looks. But are designers actually making that shift?

Noam Segal and Lenny Rachitsky, writing for Lenny’s Newsletter, share results from a survey of 1,750 tech workers. The headline is that AI is “overdelivering”—55% say it exceeded expectations, and most report saving at least half a day per week. But the findings by role tell a different story for designers:

Designers are seeing the fewest benefits. Only 45% report a positive ROI (compared with 78% of founders), and 31% report that AI has fallen below expectations, triple the rate among founders.

Meanwhile, founders are using AI to think—for decision support, product ideation, and strategy. They treat it as a thought partner, not a production tool. And product managers are building prototypes themselves:

Compare prototyping: PMs have it at #2 (19.8%), while designers have it at #4 (13.2%). AI is unlocking skills for PMs outside of their core work, whereas designers aren’t seeing the marginal improvement benefits from AI doing their core work.

The survey found that AI helps designers with work around design—research synthesis, copy, ideation—but visual design ranks #8 at just 3.3%. As Segal puts it:

AI is helping designers with everything around design, but pushing pixels remains stubbornly human.

This is the gap. The strategic future is available, but designers aren’t capturing it at the same rate as other roles. The question is why—and what to do about it.

Almost a year ago, I linked to Lee Robinson’s essay “Personal Software” and later explored why we need a HyperCard for the AI era. The thesis: people would stop searching the App Store and start building what they need. Disposable tools for personal problems.

That future is arriving. Dominic-Madori Davis, writing for TechCrunch, documents the trend:

It is a new era of app creation that is sometimes called micro apps, personal apps, or fleeting apps because they are intended to be used only by the creator (or the creator plus a select few other people) and only for as long as the creator wants to keep the app. They are not intended for wide distribution or sale.

What I find compelling here is the word “fleeting.” We’ve been conditioned to think of software as permanent infrastructure—something you buy, maintain, and eventually migrate away from. But these micro apps are disposable by design. One founder built a gaming app for his family to play over the holidays, then shut it down when vacation ended. That’s not a failed product. That’s software that did exactly what it needed to do.

Howard University professor Legand L. Burge III frames it well:

It’s similar to how trends on social media appear and then fade away. But now, [it’s] software itself.

The examples in the piece range from practical (an allergy tracker, a parking ticket auto-payer) to whimsical (a “vice tracker” for monitoring weekend hookah consumption). But the one that stuck with me was the software engineer who built his friend a heart palpitation logger so she could show her doctor her symptoms. That’s software as a favor. Software as care.

Christina Melas-Kyriazi from Bain Capital Ventures offers what I think is the most useful framing:

It’s really going to fill the gap between the spreadsheet and a full-fledged product.

This is exactly right. For years, spreadsheets have been the place where non-developers build their own tools—janky, functional, held together with VLOOKUP formulas and conditional formatting. Micro apps are the evolution of that impulse, but with real interfaces and actual logic.

The quality concerns are real—bugs, security flaws, apps that only their creator can debug. But for personal tools that handle personal problems, “good enough for one” is genuinely good enough.

Last December, Cursor announced their visual editor—a way to edit UI directly in the browser. Karri Saarinen, the designer who co-founded Linear, saw it and called it a trap. Ryo Lu, the head of design at Cursor, pushed back. The Twitter back-and-forth went on for a couple days until they conceded they mostly agreed. Tommy Geoco digs into what the debate actually surfaced.

The traditional way we talk about design tools is floor versus ceiling—does the tool make good design more accessible, or does it push what’s possible? Geoco argues the Saarinen/Lu exchange revealed a second axis: unconstrained exploration versus material exploration. Sketching on napkins versus building in code.

Saarinen’s concern:

Whenever a designer becomes more of a builder, some idealism and creativity dies. It’s not because building is bad, but because you start introducing constraints earlier in the process than you should.

Lu’s counter:

The truth only reveals itself once you start to build. Not when you think about building, not when you sketch possibilities in a protected space, but when you actually make the thing real and let reality talk back.

Both are right, and Geoco’s reframing is useful:

The question is not should designers code. It’s are you using the new speed to explore more territory or just arriving at the same destination faster?

That’s the question I keep asking myself. When I use AI tools, am I discovering ideas I wouldn’t have found otherwise, or am I just getting to obvious ideas faster? The tools make iteration cheap, but cheap iteration on the same territory isn’t progress.

I think about it this way—back when I was starting out, sketching thumbnails was the technique I used. It was very quick and easy to sketch out dozens of ideas in a sketchbook, especially when they were logo or poster ideas. When sketching interaction ideas, the technique is closer to a storyboard—connected thumbnails. But for me, once I get into a high-fidelity design or prototype, there is tremendous pull to just keep tweaking the design rather than coming up with multiple options. In other words, convergence is happening rather than continued divergence.

This is a fascinating watch. Ryo Lu, Head of Design at Cursor builds a retro Mac calculator using Cursor agents while being interviewed. Lu’s personal website is an homage to Mac OX X, complete with Aqua-style UI elements. He runs multiple local background agents without stepping on each other, fixes bugs live, and themes UI to match system styles so it feels designed—not “purple AI slop,” as he calls it.

Lu, as interview by Peter Yang, on how engineers and designers work together at Cursor (lightly edited for clarity):

So at Cursor, the roles between designers, PM, and engineers are really muddy. We kind of do the part [that is] our unique strength. We use the agent to tie everything. And when we need help, we can assemble people together to work on the thing.

Maybe some of [us] focus more on the visuals or interactions. Some focus more on the infrastructure side of things, where you design really robust architecture to scale the thing. So yeah, there is a lot less separation between roles and teams or even tools that we use. So for doing designs…we will maybe just prototype in Cursor, because that lets us really interact with the live states of the app. It just feels a lot more real than some pictures in Figma.

And surprisingly, they don’t have official product managers at Cursor. Yang asks, “Did you actually actually hire a PM because last time I talked to Lee [Robinson] there was like no PMs.”

Lu again, and edited lightly for clarity:

So we did not hire a PM yet, but we do have an engineer who used to be a founder. He took a lot more of the PM-y side of the job, and then became the first PM of the company. But I would still say a lot of the PM jobs are kind of spread across the builders in the team.

That mostly makes sense because it’s engineers building tools for engineers. You are your audience, which is rare.

It’s always interesting for me to read how other designers use AI to vibe code their projects. I think using Figma Make to conjure a prototype is one thing, but vibe coding something in production is entirely different. Personally, I’ve been through it a couple of times that I’ve already detailed here and here.

Anton Sten recently wrote about his process. Like me, he starts in Figma:

This might be the most important part: I don’t start by talking to AI. I start in Figma.

I know Figma. I can move fast there. So I sketch out the scaffolding first—general theme, grids, typography, color. Maybe one or two pages. Nothing polished, just enough to know what I’m building.

Why does this matter? Because AI will happily design the wrong thing for you. If you open Claude Code with a vague prompt and no direction, you’ll get something—but it probably won’t be what you needed. AI is a builder, not an architect. You still have to be the architect.

I appreciate Sten’s conclusion to not let the AI do all of it for you, echoing Dr. Maya Ackerman’s sentiment of humble creative machines:

But—and this is important—you still need design thinking and systems thinking. AI handles the syntax, but you need to know what you’re building, why you’re building it, and how the pieces fit together. The hard part was never the code. The hard part is the decisions.

This episode of Design of AI with Dr. Maya Ackerman is wonderful. She echoed a lot of what I’ve been thinking about recently—how AI can augment what we as designers and creatives can do. There’s a ton of content out there that hypes up AI that can replace jobs—“Type this prompt and instantly get a marketing plan!” or “Type this prompt and get an entire website!”

Ackerman, as interviewed by Arpy Dragffy-Guerrero:

I have a model I developed which is called humble creative machines which is idea that we are inherently much smarter than the AI. We have not reached even 10% of our capacity as creative human beings. And the role of AI in this ecosystem is not to become better than us but to help elevate us. That applies to people who design AI, of course, because a lot of the ways that AI is designed these days, you can tell you’re cut out of the loop. But on the other hand, some of the most creative people, those who are using AI in the most beneficial way, take this attitude themselves. They fight to stay in charge. They find ways to have the AI serve their purposes instead of treating it like an all-knowing oracle. So really, it’s sort of the audacity, the guts to believe that you are smarter than this so-called oracle, right? It’s this confidence to lead, to demand that things go your way when you’re using AI.

Her stance is that those who use AI best are those that wield it and shape its output to match their sensibilities. And so, as we’ve been hearing ad nauseam, our taste and judgement as designers really matters right now.

I’ve been playing a lot with ComfyUI recently—I’m working on a personal project that I’ll share if/when I finish it. But it made me realize that prompting a visual to get it to match what I have in my mind’s eye is not easy. This recent Instagram reel from famed designer Jessica Walsh captures my thoughts well:

I would say most AI output is shitty. People just assumed, “Oh, you rendered that an AI.” “That must have been super easy.” But what they don’t realize is that it took an entire day of some of our most creative people working and pushing the different prompts and trying different tools out and experimenting and refining. And you need a good eye to understand how to curate and pick what the best outputs are. Without that right now, AI is still pretty worthless.

It takes a ton of time to get AI output to look great, beyond prompting: inpainting, control nets, and even Photoshopping. What most non-professionals do is they take the first output from an LLM or image generator and present it as great. But it’s really not.

So I like what Dr. Ackerman mentioned in her episode: we should be in control of the humble machines, not the other way around.

When Figma acquired Weavy last month, I wrote a little bit about node-based UIs and ComfyUI. Looks like Adobe has been exploring this user interface paradigm as well.

Daniel John writes in Creative Bloq:

Project Graph is capable of turning complex workflows into user-friendly UIs (or ‘capsules’), and can access tools from across the Creative Cloud suite, including Photoshop, Illustrator and Premiere Pro – making it a potentially game-changing tool for creative pros.

But it isn’t just Adobe’s own tools that Project Graph is able to tap into. It also has access to the multitude of third party AI models Adobe recently announced partnerships with, including those made by Google, OpenAI and many more.

These tools can be used to build a node-based workflow, which can then be packaged into a streamlined tool with a deceptively simple interface.

And from Adobe’s blog post about Project Graph:

Project Graph is a new creative system that gives artists and designers real control and customization over their workflows at scale. It blends the best AI models with the capabilities of Adobe’s creative tools, such as Photoshop, inside a visual, node-based editor so you can design, explore, and refine ideas in a way that feels tactile and expressive, while still supporting the precision and reliability creative pros expect.

I’ve been playing around with ComfyUI a lot recently (more about this in a future post), so I’m very excited to see how this kind of UI can fit into Adobe’s products.

Website screenshot SaaS company Urlbox created a fun project called One Million Screenshots, with, yup, over a million screenshots of the top one million websites. You navigate the page like Google Maps, by zooming in and panning around.

Why? From the FAQ page:

We wanted to celebrate Urlbox taking over 100 million screenshots for customers in 2023… so we thought it would be fun to take an extra 1,048,576 screenshots evey month… did we mention we’re really into screenshots.

(h/t Brad Frost)

Ryan Feigenbaum created a fun Teenage Engineering-inspired color palette generator he calls “ColorPalette Pro.” Back in 2023, he was experimenting with programatic palette generation. But he didn’t like his work, calling the resulting palettes “gross, with luminosity all over the place, clashing colors, and garish combinations.”

So Feigenbaum went back to the drawing board:

That set off a deep dive into color theory, reading various articles and books like Josef Albers’ Interaction of Color (1963), understanding color space better, all of which coincided with an explosion of new color methods and technical support on the web.

These frustrations and browser improvements culminated in a realization and an app.

Here he is, demoing his app:

He told me his CEO - who’s never written a line of code - was running their company from an AI code editor.

I almost fell out of my chair.

OF COURSE. WHY HAD I NOT THOUGHT OF THAT.

I’ve since gotten rid of almost all of my productivity tools.

ChatGPT, Notion, Todoist, Airtable, Google Keep, Perplexity, my CRM. All gone.

That’s the lede for a piece by Derek Larson on running everything from Claude Code. I’ve covered how Claude Code is pretty brilliant and there are dozens more use cases than just coding.

But getting rid of everything and using just text files and the terminal window? Seems extreme.

Larson uses a skill in Claude Code called “/weekly” to do a weekly review.

1. Claude looks at every file change since last week
2. Claude evaluates the state of projects, tasks, and the roadmap
3. We have a conversation to dig deeper, and make decisions
4. Claude generates a document summarizing the week and plan we agreed on

Then Claude finds items he’s missed or procrastinating on, and “creates a space to dump everything” on his mind.

Chris Butler wrestles with a generations-old problem in his latest piece: new technologies shortcut the old ways of doing things and therefore quality takes a nosedive. But is it different this time with the tools available to us today?

While design is more accessible than ever, with Adobe experimenting with chat interfaces and Canva offering pro-level design apps for free, putting a tool into the hands of someone doesn’t mean they’ll know how to wield it.

Anyone can now create something that looks professional, that uses modern layouts and typography, that feels designed. But producing something that feels designed does not mean that any design has happened. Most tools don’t ask you what you want someone to do. They don’t force you to make hard choices about hierarchy and priority. They offer you options, and if you don’t already understand the fundamentals of how design guides attention and serves purpose, you’ll end up using too many of them to no end.

Butler concludes that as designers, we’re in a bind because “the pace of change is only accelerating, and it is a serious challenge to designers to determine how much time to spend keeping up.”

You can’t build foundational knowledge while chasing the new. But you can’t ignore the new entirely, or you’ll fall behind. So you split your time, and both efforts can suffer. The fundamentals remain elusive because you’re too busy keeping up. The tools remain half-learned because you’re too busy teaching [design fundamentals to clients].

Butler—nor I—know if there’s a good solution to this problem. Like I said at the start, this is an age-old problem. Friction is a feature, not a bug.

This is just the reality of working in a field that sits at the intersection of human behavior and technological change. Both move, but at different speeds. Human attention, cognition, emotion — these things change slowly, if at all. Technology changes constantly. Design has to navigate both.

And while Butler’s essay never explicitly mentions AI or AI tools, it’s strongly implied. Developers using AI tools to code miss out on the fundamentals of building software. Designers (or their clients) using AI to design face the issues brought up here. Those who use AI to accelerate what they already know, that seems to be The Way.

I’ve been a big fan of node-based UIs since I first experimented with Shake in the early 2000s. It’s kind of weird to wrap your head around, especially if you’re used to layers in Photoshop or Figma. The easiest way to think about nodes is to rotate the layer stack 90-degrees. Each node has inputs on the left, a distinct process that it does to the input, and outputs stuff on the right. You connect up multiple nodes to process assets to form your final composition. Popular apps with node-based workflows today include Unreal Engine (Blueprints), DaVinci Resolve (Fusion and Color), and n8n.

ComfyUI is another open source tool that uses the same node graph architecture. Made in 2023 to add some UI to the visual generative AI models like Stable Diffusion appearing around that time, it’s become popular among artists to wield the plethora of image and video gen AI models.

Fast-forward to last week, when Figma announced they had acquired Weavy, a much friendlier and cloud-based version of ComfyUI.

Weavy brings the world’s leading AI models together with professional editing tools on a single, browser-based canvas. With Weavy, you can choose the model you want for a task (e.g. Seedance, Sora, and Veo for cinematic video; Flux and Ideogram for realism; and Nano-Banana or Seedream for precision) and compose powerful primitives using generative AI outputs and hands-on edits (e.g. adjusting lighting, masking an object, color grading a shot). The end result is an inspiring environment for creative exploration and a flexible media pipeline where every output feeds the next.

This node-based approach brings a new level of craft and control to AI generation. Outputs can be branched, remixed, and refined, combining creative exploration with precision and craft. The Weavy team has inspired us with the balance they’ve struck between simplicity, approachability, and power. They’ve also created a tool that’s just a joy to use.

I must admit I had not heard about Weavy before the announcement. I had high hopes for Visual Electric, but it never quite lived up to its ambitions. I proceeded to watch all the official tutorial videos on YouTube and love it. Seems so much easier to use than ComfyUI. Let’s see what Figma does with the product.

In graphic design news, a new version of the Affinity suite dropped last week, and it’s free. Canva purchased Serif, the company behind the Affinity products, last year. After about a year of engineering, they have combined all the products into a single product to offer maximum flexibility. And they made it free.

Of course then, that sparks debate.

Joe Foley, writing for Creative Bloq explains:

…A natural suspicion of big corporations is causing some to worry about what the new Affinity will become. What’s in it for Canva?

Theories abound. Some think the app will start to show adverts like many free mobile apps do. Others think it will be used to train AI (something Canva denies). Some wonder if Canva’s just doing it to spite Adobe. “Their objective was to undermine Adobe, not provide for paying customers. Revenge instead of progress,” one person thinks.

Others fear Affinity’s tools will be left to stagnate. “If you depend on a software for your design work it needs to be regularly updated and developed. Free software never has that pressure and priority to be kept top notch,” one person writes.

AI features are gated behind paid Canva premium subscription plans. This makes sense as AI features have inference costs. As Adobe is going all out with its AI features, gen AI is now table stakes for creative and design programs.

I’ve been on the receiving end of Layer 1226 before and it’s not fun. While I’m pretty good with my layer naming hygiene, I’m not perfect. So I welcome anything that can help rename my layers. Apparently, when Adobe showed off this new AI feature at their Adobe MAX user conference last week, it drew a big round of applause. (Figma’s had this feature since June 2024.)

There’s more than just renaming layers though. Adobe is leaning into conversational UI for editing too. For new users coming to editing tools, this makes a lot of sense because the learning curve for Photoshop is very steep. But as I’ve always said, professionals will also need fine-grained controls.

Writing for CNET, Katelyn Chedraoui:

Renaming layers is just one of many things Adobe’s new AI assistants will be able to do. These chatbot-like tools will be added to Photoshop and Express. They have an emphasis on “conversational, agentic” experiences — meaning you can ask the chatbot to make edits, and it can independently handle them.

…

Express’s AI assistant is similar to using a chatbot. Once you toggle on the tool in the upper left corner, a conversation window pops up. You can ask the AI to change the color of an object or remove an obtrusive element. While pro users might be comfortable making those edits manually, the AI assistant might be more appealing to its less experienced users and folks working under a time crunch.

A peek into Adobe’s future reveals more agentic experiences:

Also announced on Tuesday is Project Moonlight, a new platform in beta on Adobe’s AI hub, Firefly. It’s a new tool that hopes to act as a creative partner. With your permission, it uses your data from Adobe platforms and social media accounts to help you create content. For example, you can ask it to come up with 20 ideas for what to do with your newest Lightroom photos based on your most successful Instagram posts in the past. 

These AI efforts represent a range of what conversational editing can look like, Mike Polner, Adobe Firefly’s vice president of product marketing for creators said in an interview. 

“One end of the spectrum is [to] type in a prompt and say, ‘Make my hat blue.’ That’s very simplistic,” said Polner. “With Project Moonlight, it can understand your context, explore and help you come up with new ideas and then help you analyze the content that you already have,” Polner said.

It’s interesting to me that Figma had to have a separate conference and set of announcements focused on design systems. In some sense it’s an indicator of how big and mature this part of design has become.

A few highlights from my point-of-view…

Slots seems to solve one of those small UX paper cuts—those niggly inconveniences that we just lived with. But this is a big deal. You’ll be able to add layers within component instances without breaking the connection to your design system. No more pre-building hidden list items or forcing designers to detach components. Pretty advanced stuff.

On the code front, they’re making Code Connect actually approachable with a new UI that connects directly to GitHub and uses AI to map components. The Figma MCP server is out of beta and now supports design system guidelines—meaning your agentic coding tools can actually respect your design standards. Can’t wait to try these.

For teams like mine that are using Make, you’ll be able to pull in design systems through two routes: Make kits (generate React and CSS from Figma libraries) or npm package imports (bring in your existing code components). This is the part where AI-assisted design doesn’t have to mean throwing pixelcraft out the window.

Design systems have always been about maintaining quality at scale. These updates are very welcomed.

With Cursor and Lovable as the darlings of AI coding tools, don’t sleep on Claude Code. Personally, I’ve been splitting my time between Claude Code and Cursor. While Claude Code’s primary persona is coders and tinkerers, it can be used for so much more.

Lenny Rachitsky calls it “the most underrated AI tool for non-technical people.”

The key is to forget that it’s called Claude Code and instead think of it as Claude Local or Claude Agent. It’s essentially a super-intelligent AI running locally, able to do stuff directly on your computer—from organizing your files and folders to enhancing image quality, brainstorming domain names, summarizing customer calls, creating Linear tickets, and, as you’ll see below, so much more.

Since it’s running locally, it can handle huge files, run much longer than the cloud-based Claude/ChatGPT/Gemini chatbots, and it’s fast and versatile. Claude Code is basically Claude with even more powers.

Rachitsky shares 50 of his “favorite and most creative ways non-technical people are using Claude Code in their work and life.”

Noah Davis writing in Web Designer Depot, says aloud what I’d thought—but never wrote down—before AI, templates started to kill creativity in web design.

If you’re wondering why the web feels dead, lifeless, or like you’re stuck in a scrolling Groundhog Day of “hero image, tagline, three icons, CTA,” it’s not because AI hallucinated its way into the design department.

It’s because we templatified creativity into submission!

We used to design websites like we were crafting digital homes—custom woodwork, strange hallways, surprise color choices, even weird sound effects if you dared. Each one had quirks. A personality. A soul.

When I was coming up as a designer in the late 1990s and early 2000s, one of my favorite projects was designing Pixar.com. The animation studio’s soul—and by extension the soul I’d imbue into the website—was story. The way this manifest was a linear approach to the site, similar to a slideshow, to tell the story of each of their films.

And as the web design industry grew, and everyone needed and wanted a website, from Fortune 500s to the local barber shop, access to well-designed websites was made possible via templates.

Let’s be real: clients aren’t asking for design anymore. They’re asking for “a site like this.” You know the one. It looks clean. It has animations. It scrolls smoothly. It’s “modern.” Which, in 2025, is just a euphemism for “I want what everyone else has so I don’t have to think.”

Templates didn’t just streamline web development. They rewired what people expect a website to be.

Why hire a designer when you can drop your brand colors into a no-code template, plug in some Lottie files, and call it a day? The end result isn’t bad. It’s worse than bad. It’s forgettable.

Davis ends his rant with a call to action: “If you want design to live, stop feeding the template machine. Build weird stuff. Ugly stuff. Confusing stuff. Human stuff.”