Is the AI bubble about to burst? Apparently, AI prompt-to-code tools like Lovable and v0 have peaked and are on their way down.

Alistair Barr writing for Business Insider:

The drop-off raises tough questions for startups that flaunted exponential annual recurring revenue growth just months ago. Analysts wrote that much of that revenue comes from month-to-month subscribers who may churn as quickly as they signed up, putting the durability of those flashy numbers in doubt.

Barr interviewed Eric Simons, CEO of Bolt who said:

“This is the problem across all these companies right now. The churn rate for everyone is really high,” Simons said. “You have to build a retentive business.”

In an announcement to users this morning, Visual Electric said they were being acquired by Perplexity—or more accurately, the team that makes Visual Electric will be hired by Perplexity. The service will shut down in the next 90 days.

Today we’re sharing the next step in Visual Electric’s journey: we’ve been acquired by Perplexity. This is a milestone that marks both an exciting opportunity for our team and some big changes for our product.

Over the next 90 days we’ll be sunsetting Visual Electric, and our team will be forming a new Agent Experiences group at Perplexity.

While we’ve seen acquihires and shutdowns in either the AI infrastructure space (e.g., Scale AI) or coding space (e.g., Windsurf), I don’t believe we’ve seen one in the image or video gen AI space have an exit event like this yet. Obviously, The Browser Company announced their acquisition by Atlassian last month.

I believe building gen AI tools at this moment is incredibly competitive. I think it takes an even stronger stomached entrepreneur than in the pre-ChatGPT moment. So kudos for the folks at Visual Electric for having a good outcome and getting to continue to do their work at Perplexity. But I do think this is not the last that we’ll see consolidation in this space.

Tim Berners-Lee, the father of the web who gave away the technology for free, says that we are at an inflection point with data privacy and AI. But before he makes that point, he reminds us that we are the product:

Today, I look at my invention and I am forced to ask: is the web still free today? No, not all of it. We see a handful of large platforms harvesting users’ private data to share with commercial brokers or even repressive governments. We see ubiquitous algorithms that are addictive by design and damaging to our teenagers’ mental health. Trading personal data for use certainly does not fit with my vision for a free web.

On many platforms, we are no longer the customers, but instead have become the product. Our data, even if anonymised, is sold on to actors we never intended it to reach, who can then target us with content and advertising. This includes deliberately harmful content that leads to real-world violence, spreads misinformation, wreaks havoc on our psychological wellbeing and seeks to undermine social cohesion.

And about that fork in the road with AI:

In 2017, I wrote a thought experiment about an AI that works for you. I called it Charlie. Charlie works for you like your doctor or your lawyer, bound by law, regulation and codes of conduct. Why can’t the same frameworks be adopted for AI? We have learned from social media that power rests with the monopolies who control and harvest personal data. We can’t let the same thing happen with AI.

In my most recent post, I called out our design profession, for our part in developing these addictive products. Jeffrey Inscho, brings it back up to the tech industry at large and observes they’re actually publishers:

The executives at these companies will tell you they’re neutral platforms, that they don’t choose what content gets seen. This is a lie. Every algorithmic recommendation is an editorial decision. When YouTube’s algorithm suggests increasingly extreme political content to keep someone watching, that’s editorial. When Facebook’s algorithm amplifies posts that generate angry reactions, that’s editorial. When Twitter’s trending algorithms surface conspiracy theories, that’s editorial.

They are publishers. They have always been publishers. They just don’t want the responsibility that comes with being publishers.

His point is that if these social media platforms are sorting and promoting posts, it’s an editorial approach and they should be treated like newspapers. “It’s like a newspaper publisher claiming they’re not responsible for what appears on their front page because they didn’t write the articles themselves.”

The answer, Inscho argues, is regulation of the algorithms.

I’m happy that the conversation around the design talent crisis continues. Carly Ayres, writing for It’s Nice That picks up the torch and speaks to designers and educators about this topic. What struck me—and I think what adds to the dialogue—is the notion of the belief gap. Ayres spoke with Naheel Jawaid, founder of Silicon Valley School of Design, about it:

“A big part of what I do is just being a coach, helping someone see their potential when they don’t see it yet,” Naheel says. “I’ve had people tell me later that a single conversation changed how they saw themselves.”

In the past, belief capital came from senior designers taking juniors under their wing. Today, those same seniors are managing instability of their own. “It’s a bit of a ‘dog eat dog world’-type vibe,” Naheel says. “It’s really hard to get mentorship right now.”

The whole piece is great. Tighter than my sprawling three-parter. I do think there’s a piece missing though. While Ayres highlights the issue and offers suggestions from designer leaders, businesses need to step up and do something about the issue—i.e., hire more juniors. Us recognizing it is the first step.

Josh Miller, CEO, and Hursh Agrawal, CTO, of The Browser Company:

Today, The Browser Company of New York is entering into an agreement to be acquired by Atlassian in an all-cash transaction. We will operate independently, with Dia as our focus. Our objective is to bring Dia to the masses.

Super interesting acquisition here. There is zero overlap as far as I can tell. Atlassian’s move is out of left-field. Dia’s early users were college students. The Browser Company more recently opened it up to former Arc users. Is this bet for Atlassian—the company that makes tech-company-focused products like Jira and Confluence—around the future of work and collaboration? Is this their first move against Salesforce? 🤔

Simon Sherwood, writing in The Register:

Amazon Web Services CEO Matt Garman has suggested firing junior workers because AI can do their jobs is “the dumbest thing I’ve ever heard.”

Garman made that remark in conversation with AI investor Matthew Berman, during which he talked up AWS’s Kiro AI-assisted coding tool and said he’s encountered business leaders who think AI tools “can replace all of our junior people in our company.”

That notion led to the “dumbest thing I’ve ever heard” quote, followed by a justification that junior staff are “probably the least expensive employees you have” and also the most engaged with AI tools.

“How’s that going to work when ten years in the future you have no one that has learned anything,” he asked. “My view is you absolutely want to keep hiring kids out of college and teaching them the right ways to go build software and decompose problems and think about it, just as much as you ever have.”

Yup. I agree.

Jessica Davies reports that new publisher data suggests that some sites are getting 25% less traffic from Google than the previous year.

Writing in Digiday:

Organic search referral traffic from Google is declining broadly, with the majority of DCN member sites — spanning both news and entertainment — experiencing traffic losses from Google search between 1% and 25%. Twelve of the respondent companies were news brands, and seven were non-news.

Jason Kint, CEO of DCN, says that this is a “direct consequence of Google AI Overviews.”

I wrote previously about the changing economics of the web here, here, and here.

And related, Eric Mersch writes in a LinkedIn post that Monday.com’s stock fell 23% because co-CEO Roy Mann said, “We are seeing some softness in the market due to Google algorithm,” during their Q2 earnings call and the analysts just kept hammering him and the CFO about how the algo changes might affect customer acquisition.

Analysts continued to press the issue, which caught company management completely off guard. Matthew Bullock from Bank of America Merrill Lynch asked frankly, “And then help us understand, why call this out now? How did the influence of Google SEO disruption change this quarter versus 1Q, for example?” The CEO could only respond, “So look, I think like we said, we optimize in real-time. We just budget daily,” implying that they were not aware of the problem until they saw Q2 results.

This is the first public sign that the shift from Google to AI-powered searches is having an impact.

I enjoyed this interview with Notion’s CEO, Ivan Zhao over at the Decoder podcast, with substitute host, Casey Newton. What I didn’t quite get when I first used Notion was the “LEGO” aspect of it. Their vision is to build business software that is highly malleable and configurable to do all sorts of things. Here’s Zhao:

Well, because it didn’t quite exist with software. If you think about the last 15 years of [software-as-a-service], it’s largely people building vertical point solutions. For each buyer, for each point, that solution sort of makes sense. The way we describe it is that it’s like a hard plastic solution for your problem, but once you have 20 different hard plastic solutions, they sort of don’t fit well together. You cannot tinker with them. As an end user, you have to jump between half a dozen of them each day.

That’s not quite right, and we’re also inspired by the early computing pioneers who in the ‘60s and ‘70s thought that computing should be more LEGO-like rather than like hard plastic. That’s what got me started working on Notion a long time ago, when I was reading a computer science paper back in college.

From a user experience POV, Notion is both simple and exceedingly complicated. Taking notes is easy. Building the system for a workflow, not so much.

In the second half, Newton (gently) presses Zhao on the impact of AI on the workforce and how productivity software like Notion could replace headcount.

Newton: Do you think that AI and Notion will get to a point where executives will hire fewer people, because Notion will do it for them? Or are you more focused on just helping people do their existing jobs?

Zhao: We’re actually putting out a campaign about this, in the coming weeks or months. We want to push out a more amplifying, positive message about what Notion can do for you. So, imagine the billboard we’re putting out. It’s you in the center. Then, with a tool like Notion or other AI tools, you can have AI teammates. Imagine that you and I start a company. We’re two co-founders, we sign up for Notion, and all of a sudden, we’re supplemented by other AI teammates, some taking notes for us, some triaging, some doing research while we’re sleeping.

Zhao dodges the “hire fewer people” part of the question and instead, answers with “amplifying” people or making them more productive.

Yesterday, OpenAI launched GPT-5, their latest and greatest model that replaces the confusing assortment of GPT-4o, o3, o4-mini, etc. with just two options: GPT-5 and GPT-5 pro. The reasoning is built in and the new model is smart enough to know what to think harder, or when a quick answer suffices.

Simon Willison deep dives into GPT-5, exploring its mix of speed and deep reasoning, massive context limits, and competitive pricing. He sees it as a steady, reliable default for everyday work rather than a radical leap forward:

I’ve mainly explored full GPT-5. My verdict: it’s just good at stuff. It doesn’t feel like a dramatic leap ahead from other LLMs but it exudes competence—it rarely messes up, and frequently impresses me. I’ve found it to be a very sensible default for everything that I want to do. At no point have I found myself wanting to re-run a prompt against a different model to try and get a better result.

It’s a long technical read but interesting nonetheless.

Jay Hoffman, writing in his excellent The History of the Web website, reflects on Kevin Kelly’s 2005 Wired piece that celebrated the explosive growth of blogging—50 million blogs, one created every two seconds—and predicted a future powered by open participation and user-created content. Kelly was right about the power of audiences becoming creators, but he missed the crucial detail: 2005 would mark the peak of that open web participation before everyone moved into centralized platforms.

There are still a lot of blogs, 600 million by some accounts. But they have been supplanted over the years by social media networks. Commerce on the web has consolidated among fewer and fewer sites. Open source continues to be a major backbone to web technologies, but it is underfunded and powered almost entirely by the generosity of its contributors. Open API’s barely exist. Forums and comment sections are finding it harder and harder to beat back the spam. Users still participate in the web each and every day, but it increasingly feels like they do so in spite of the largest web platforms and sites, not because of them.

My blog—this website—is a direct response to the consolidation. This site and its content are owned and operated by me and not stuck behind a login or paywall to be monetized by Meta, Medium, Substack, or Elon Musk. That is the open web.

Hoffman goes on to say, “The web was created for participation, by its nature and by its design. It can’t be bottled up long.” He concludes with:

Independent journalists who create unique and authentic connections with their readers are now possible. Open social protocols that experts truly struggle to understand, is being powered by a community that talks to each other.

The web is just people. Lots of people, connected across global networks. In 2005, it was the audience that made the web. In 2025, it will be the audience again.

For the past year, CPG behemoth Unilever has been “working with marketing services group Brandtech to build up its Beauty AI Studio: a bespoke, in-house system inside its beauty and wellbeing business. Now in place across 18 different markets (the U.S. and U.K. among them), the studio is being used to make assets for paid social, programmatic display inventory and e-commerce usage across brands including Dove Intensive Repair, TRESemme Lamellar Shine and Vaseline Gluta Hya.”

Sam Bradley, writing in Digiday:

The system relies on Pencil Pro, a generative AI application developed by Brandtech Group. The tool draws on several large language models (LLMs), as well as API access to Meta and TikTok for effectiveness measurement. It’s already used by hearing-care brand Amplifon to rapidly produce text and image assets for digital ad channels.

In Unilever’s process, marketers use prompts and their own insights about target audiences to generate images and video based on 3D renders of each product, a practice sometimes referred to as “digital twinning.” Each brand in a given market is assigned a “BrandDNAi” — an AI tool that can retrieve information about brand guidelines and relevant regulations and that provides further limitations to the generative process.

So far, they haven’t used this system to generate AI humans. Yet.

In many ways, this excellent article by Kaustubh Saini for Final Round AI’s blog is a cousin to my essay on the design talent crisis. But it’s about what happens when people “become” developers and only know vibe coding.

The appeal is obvious, especially for newcomers facing a brutal job market. Why spend years learning complex programming languages when you can just describe what you want in plain English? The promise sounds amazing: no technical knowledge required, just explain your vision and watch the AI build it.

In other words, these folks don’t understand the code and, well, bad things can happen.

The most documented failure involves an indie developer who built a SaaS product entirely through vibe coding. Initially celebrating on social media that his “saas was built with Cursor, zero hand written code,” the story quickly turned dark.

Within weeks, disaster struck. The developer reported that “random things are happening, maxed out usage on api keys, people bypassing the subscription, creating random shit on db.” Being non-technical, he couldn’t debug the security breaches or understand what was going wrong. The application was eventually shut down permanently after he admitted “Cursor keeps breaking other parts of the code.”

This failure illustrates the core problem with vibe coding: it produces developers who can generate code but can’t understand, debug, or maintain it. When AI-generated code breaks, these developers are helpless.

I don’t foresee something this disastrous with design. I mean, a newbie designer wielding an AI-enabled Canva or Figma can’t tank a business alone because the client will have eyes on it and won’t let through something that doesn’t work. It could be a design atrocity, but it’ll likely be fine.

This *can *happen to a designer using vibe coding tools, however. Full disclosure: I’m one of them. This site is partially vibe-coded. My Severance fan project is entirely vibe-coded.

But back to the idea of a talent crisis. In the developer world, it’s already happening:

The fundamental problem is that vibe coding creates what experts call “pseudo-developers.” These are people who can generate code but can’t understand, debug, or maintain it. When AI-generated code breaks, these developers are helpless.

In other words, they don’t have the skills necessary to be developers because they can’t do the basics. They can’t debug, don’t understand architecture, have no code review skills, and basically have no fundamental knowledge of what it means to be a programmer. “They miss the foundation that allows developers to adapt to new technologies, understand trade-offs, and make architectural decisions.”

Again, assuming our junior designers have the requisite fundamental design skills, not having spent time developing their craft and strategic skills through experience will be detrimental to them and any org that hires them.

Sonos announced yesterday that interim CEO Tom Conrad was made permanent. From their press release:

Sonos has achieved notable progress under Mr. Conrad’s leadership as Interim CEO. This includes setting a new standard for the quality of Sonos’ software and product experience, clearing the path for a robust new product pipeline, and launching innovative new software enhancements to flagship products Sonos Ace and Arc Ultra.

Conrad surely navigated this landmine well after the disastrous app redesign that wiped almost $500 million from the company’s market value and cost CEO Patrick Spence his job. My sincere hope is that Conrad continues to rebuild Sonos’s reputation by continuing to improve their products.

From UX Magazine:

Copilots helped enterprises dip their toes into AI. But orchestration platforms and tools are where the real transformation begins — systems that can understand intent, break it down, distribute it, and deliver results with minimal hand-holding.

Think of orchestration as how “meta-agents” are conducting other agents.

The first iteration of AI in SaaS was copilots. They were like helpful interns eagerly awaiting your next command. Orchestration platforms are more like project managers. They break down big goals into smaller tasks, assign them to the right AI agents, and keep everything coordinated. This shift is changing how companies design software and user experiences, making things more seamless and less reliant on constant human input.

For designers and product teams, it means thinking about workflows that cross multiple tools, making sure users can trust and control what the AI is doing, and starting small with automation before scaling up.

In case you missed it, there’s been a major shift in the AI tool landscape.

On Friday, OpenAI’s $3 billion offer to acquire AI coding tool Windsurf expired. Windsurf is the Pepsi to Cursor’s Coke. They’re both IDEs, the programming desktop application that software developers use to code. Think of them as supercharged text editors but with AI built in.

On Friday evening, Google announced that it had hired Windsurf’s CEO Varun Mohan, co-founder Douglas Chen, and several key researchers for $2.4 billion.

On Monday, Cognition, the company behind Devin, the self-described “AI engineer” announced that it had acquired Windsurf for an undisclosed sum, but noting that its remaining 250 employees will “participate financially in this deal.”

Why does this matter to designers?

The AI tools market is changing very rapidly. With AI helping to write these applications, their numbers and features are always increasing—or in this case, maybe consolidating. Choose wisely before investing too deeply into one particular tool. The one piece of advice I would give here is to avoid lock-in. Don’t get tied to a vendor. Ensure that your tool of choice can export your work—the code.

Jason Lemkin has more on the business side of things and how it affects VC-backed startups.

This post has been swimming in my head since I read it. Elena Verna, who joined Lovable just over a month ago to lead marketing and growth, writing in her newsletter, observes that everyone at the company is an AI-native employee. “An AI-native employee isn’t someone who ‘uses AI.’ It’s someone who defaults to AI,” she says.

On how they ship product:

Here, when someone wants to build something (anything) - from internal tools, to marketing pages, to writing production code - they turn to AI and… build it. That’s it.

No headcount asks. No project briefs. No handoffs. Just action.

At Lovable, we’re mostly building with… Lovable. Our Shipped site is built on Lovable. I’m wrapping hackathon sponsorship intake form in Lovable as we speak. Internal tools like credit giveaways and influencer management? Also Lovable (soon to be shared in our community projects so ya’ll can remix them too). On top of that, engineering is using AI extensively to ship code fast (we don’t even really have Product Managers, so our engineers act as them).

I’ve been hearing about more and more companies operating this way. Crazy time to be alive.

More on this topic in a future long-form post.

Paul Worthington writing about the recent Cannes Festival of Creativity:

…nostalgia is rapidly becoming a major idea d’jour among marketers targeting that oh-so-desirable “Gen Z” demographic.

As a result, it should come as no surprise that if you were to walk around Cannes over the past month or so, you’d be forgiven for thinking brands no longer had any interest in the future: Lisa Frank notebooks. Tamagotchi cameos. Taglines from 1999. Brand after brand strapping itself to the past, seeking refuge in comfort. Instacart. Mattel. Burger King. Skoda. All treating relevance as if it were a rerun.

But along with nostalgia, another theme was present at Cannes—differentiation:

Cannes was also a parade of brands betting on something riskier. Something sharper. Something new. Liquid Death. Stripe. Tesla. Anduril. Companies building out from belief systems focused resolutely on what makes them unique. Making things you couldn’t have predicted because they weren’t remixes of the past—they were statements of the future.

Worthington argues that these two themes are diametrically opposed. Nostalgia brands are “fundamentally risk-averse” and feel safe. While differentiated brands are “risk-embracing,” betting that consumers are desperate for “something weird, sharp, and built from scratch.”

Here we go. Figma has just dropped their S-1, or their registration for an initial public offering (IPO).

Rollup of stats from Figma’s S-1.

While a lot of the risk factors are boilerplate—legalese to cover their bases—the one about AI is particularly interesting, “Competitive developments in AI and our inability to effectively respond to such developments could adversely affect our business, operating results, and financial condition.”

Developments in AI are already impacting the software industry significantly, and we expect this impact to be even greater in the future. AI has become more prevalent in the markets in which we operate and may result in significant changes in the demand for our platform, including, but not limited to, reducing the difficulty and cost for competitors to build and launch competitive products, altering how consumers and businesses interact with websites and apps and consume content in ways that may result in a reduction in the overall value of interface design, or by otherwise making aspects of our platform obsolete or decreasing the number of designers, developers, and other collaborators that utilize our platform. Any of these changes could, in turn, lead to a loss of revenue and adversely impact our business, operating results, and financial condition.

There’s a lot of uncertainty they’re highlighting:

• Could competitors use AI to build competing products?
• Could AI reduce the need for websites and apps which decreases the need for interfaces?
• Could companies reduce workforces, thus reducing the number of seats they buy?

These are all questions the greater tech industry is asking.

In a dual profile, Ben Blumenrose spotlights Phil Vander Broek—whose startup Dopt was acquired last year by Airtable—and Filip Skrzesinski—who is currently working on Subframe—in the Designer Founders newsletter.

One of the lessons Vander Broek learned was to not interview customers just to validate an idea. Interview them to get the idea first. In other words, discover the pain points:

They ran 60+ interviews in three waves. The first 20 conversations with product and growth leaders surfaced a shared pain point: driving user adoption was painfully hard, and existing tools felt bolted on. The next 20 calls helped shape a potential solution through mockups and prototypes—one engineer was so interested he volunteered for weekly co-design sessions. A final batch of 20 calls confirmed their ideal customer was engineers, not PMs.

As for Skrzesinski, he’s learning that being a startup founder isn’t about building the product—it’s about building a business:

But here’s Filip’s counterintuitive advice: “Don’t start a company because you love designing products. Do it in spite of that.”

“You won’t be designing in the traditional sense—you’ll be designing the company’s DNA,” he explains. “It’s the invisible work: how you organize, how you think, how you make decisions. How it feels to work there, to use what you’re making, to believe in it.”

Brian Balfour, writing for the Reforge blog:

Speed isn’t just about shipping faster, it’s about accelerating your entire learning metabolism. The critical metric isn’t feature velocity but rather your speed through the complete Insight → Act → Learn loop. This distinction separates products that compound advantages from those that compound technical debt.

The point being that now with AI, product teams are shipping faster. And those who aren’t might get lapped (to use an F1 phrase).