Put Any HTML File On Your Own Site Just By Talking To AI | Practical AI Ep 45

Practical AI: Episode 45

Put Any HTML File On Your Own Site Just By Talking To AI

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Published: June 12, 2026

TL;DR

  • Web design changed again. Anthropic released Fable 5 and Mythos 5 on June 9 — but only Fable 5 is public. The hosts showed a Fable-designed yoga site that shifts its lighting from dawn to dusk as you scroll, the kind of creative design that used to need the best designer you ever met.
  • The smartest models are getting locked down. Mythos 5 — the more cyber-capable twin — is not public. It’s restricted to vetted partners in Project Glasswing. The lesson the hosts kept hammering: don’t get locked into one model.
  • Agents moved into real operating work. AWS shipped a FinOps Agent that watches your cloud bill and files report tickets. Not a chatbot — a worker. ChatGPT learned to “dream,” refreshing its memory of you in the background.
  • Your website now has a second customer that isn’t human. The deep dive (built on Greg Isenberg’s piece) lays out how AI agents discover, evaluate, and buy — and why the businesses that become “agent-operable” win first.
  • The demo: Olga published a finished HTML file straight onto her own live site just by talking to AI through the PageMotor MCP — no admin panel, no code — so every asset she makes compounds her AI-search footprint instead of dying on someone else’s server.

This Week’s Materials

Table of Contents

About This Show

Practical AI is a weekly live show (Fridays 11am CT) hosted by Olga Pechnenko and Chris Pearson that cuts through AI hype to deliver news, trends, and hands-on tips for builders and founders. Unlike technical AI podcasts, Practical AI focuses on business applications and ROI — what actually works, what’s hype, and what you can implement Monday morning.

What You’ll Gain

  • Understand the new split in AI models. The public gets the safer model; the most capable versions are moving behind locked, vetted programs. Knowing which way that’s going changes what you build on.
  • See what AI design can do now. A Fable-generated site that animates its own light from dawn to dusk shows the creative ceiling just jumped — and what that means for anyone who owns a website.
  • Learn why your website now has two customers. One is human and wants to be persuaded; one is an AI agent that wants structured capability and trust. Most sites are built for only one of them.
  • Discover how to make your content compound. Publishing your assets onto your own domain — not a rented host — is what turns one-off files into a living archive that AI engines keep citing.
  • Know which businesses get reshaped first. Bookings, ordering, real estate, and anything procedural get captured by agents before enterprise does. Being early is the whole advantage.

Biggest Takeaway to Implement: Pick one repetitive job in your business and write it down as a job description — that’s your first agent. Then ask the new question that matters: is my website ready for an AI agent to find, trust, and act on? If it’s not, getting it ready now is the first-mover move.

Frequently Asked Questions

Did Anthropic release Mythos 5 to the public?

No. On June 9 Anthropic released two configs of the same model class — Claude Fable 5 is the public, generally-available one, while Claude Mythos 5 is NOT public. Mythos is “limited to approved customers in Project Glasswing,” the vetted program for cyber defenders and critical infrastructure. Read more below.

What makes Fable 5 different?

Early feedback points to better creativity, not just better reasoning — which is why the hosts showed a Fable-designed yoga site that animates its own lighting through the day. It’s the public, safer twin: it cuts off high-risk domains like bio-health, cryptography, and security questions. Read more below.

What is the AWS FinOps Agent?

An agent AWS put into public preview on June 9 that watches your AWS bill, investigates a cost spike, traces the cause, and files a report ticket into Slack or Jira. It’s AWS-only, US East region in preview, and it’s the cleanest example yet of an agent doing real, recurring operating work instead of chatting. Read more below.

What does “the internet’s new customer isn’t human” mean?

For the whole history of the web, the user was a person you persuaded. Now AI agents act on people’s behalf — discovering, evaluating, paying, and renewing. Your business needs to be machine-usable, not just pretty. The agent wants structured capability, permission, and trust. Read more below.

How did Olga put an HTML file on her own website by talking to AI?

Her Claude is connected to the pagemotor.com MCP server. She pointed it at a finished HTML file and said “publish this,” it read PageMotor’s API docs, asked clarifying questions, showed her the URL slug to approve, and folded the page into her live site — schema, title tags, and analytics included — without her ever opening an admin panel. Read more below.

Was the Apple Siri prediction right?

No — it resolved as a MISS. Chris called Apple going “bring your own model” at the OS layer. At WWDC on June 8 Apple did the opposite: a locked, unified Siri with no model choice, custom-built in collaboration with Google’s Gemini models (confirmed by Apple’s own newsroom). Read more below.

Practical AI: Put Any HTML File On Your Own Site Just By Talking To AI

Key Definitions

What is Project Glasswing?

Anthropic’s vetted-partner program for its most cyber-capable model. When Anthropic shipped Mythos 5, it kept it out of general release — “not generally available… limited to approved customers in Project Glasswing,” aimed at cyber defenders and critical-infrastructure operators. It’s the mechanism that keeps the more powerful twin out of the public’s hands.

What is an agent (in the “second customer” sense)?

An AI acting on someone’s behalf to get a job done — finding a tool, reading the docs and pricing, checking policies, and sometimes paying. Unlike a human visitor, it doesn’t care about your hero video. It wants structured capability, identity and permission, and trust signals it can verify. It’s a new kind of customer your site has to serve.

What is an MCP?

A Model Context Protocol — in plain terms, a bridge that connects an AI to a website and hands it a menu of commands it’s allowed to run. Olga’s Claude is connected to PageMotor’s MCP, which is how it can read the site’s documentation and publish or edit pages directly, without anyone touching an admin dashboard.

What is GEO (Generative Engine Optimization)?

The practice of making your content the source AI engines quote inside their answers. Publishing your assets onto your own domain — rather than letting them live on a rented host or a local machine — is what lets that content compound into a living archive that ChatGPT, Perplexity, and Google’s AI Overviews can keep citing.

Quotable Moments

It was the internet that changed last week. Now it’s web design. I’ve been doing this over 20 years, and this week my mind got warped a little bit. I don’t see things the same way anymore.

— Chris Pearson on the pace of change

The whole point of Mythos not being available to humans is very interesting. More than ever right now it’s important to not be locked in with any particular model, because you never know how they’re going to decide what’s available to you and what’s not.

— Olga Pechnenko on model lock-in

It’s not a chatbot, it’s a worker. Most of you don’t manage an AWS bill, and that’s fine. But watch this as the clearest example yet of where AI is going.

— Olga Pechnenko on the AWS FinOps Agent

I want all the content I create to live on my site. I’m very greedy. I just want to talk to my site and convert my HTML file as a page on my site without touching anything. And that’s what I did.

— Olga Pechnenko on the demo

I have to operate like I am five years old and I don’t know anything about the world, and ask the craziest questions — because somehow AI can either figure out a way to make it happen, or at least tell me I’m crazy.

— Olga Pechnenko on the mindset shift

0:00 Why web design just changed again

The hosts opened on a simple claim: last week it was the internet that changed; this week it’s web design. Chris, a 20-year veteran, said his mind got warped — he doesn’t see things the same way anymore. The promise of the episode: catch you up on the week’s AI news so you’re the most interesting person at dinner tonight, then go deep on the website of the future — what it needs to be, and how you can now build and run it just by talking to AI.

1:11 Fable 5 is here, and why Mythos stays locked away

Two Models, One Public

On June 9, Anthropic released Fable 5 and Mythos 5. Fable 5 is the public, generally-available model (1M-token context, always-on adaptive thinking, stronger safeguards in high-risk domains). Mythos 5 is NOT public — “limited to approved customers in Project Glasswing.”

This resolved a running prediction. Chris had called Mythos going public by the end of May; Olga said it wouldn’t. Neither was fully right: Anthropic did ship on June 9, but only Fable 5 reached the public. Mythos 5 — the more cyber-capable twin — stayed gated behind Project Glasswing, the vetted program for cyber defenders and critical infrastructure. Fable is the padded-room version: it cuts you off on bio-health, cryptography, and security questions so you can’t do damage with it.

Verify-everything moment: The hosts flagged on air that the AI summary used to prep this segment wrongly said Mythos went public. It didn’t, and still hasn’t. Checked against Anthropic’s own announcement and system card — Fable 5 public, Mythos 5 Glasswing-only. That’s why every claim gets verified before it reaches you.

4:17 Watch Fable 5 design a yoga site that moves with the sun

The early read on Fable 5 is that the leap is in creativity, not just reasoning — and that’s the more useful upgrade for anyone who builds. To show it, the hosts pulled up a design Ken (a PageMotor beta participant) generated with Fable: a site for a fictional company that runs three yoga studios in California. The design motif is the lighting of a single day. As you scroll, the page moves from dawn through late day to dusk, the light shifting with it.

The Creative Ceiling Just Jumped

The price opt-in sits at the most golden part of the page — it literally lands at golden hour on the scroll. The classes page uses little SVGs to show the time of day and where the sun is. As Chris put it: the best designer you’ve ever met would have come up with something like this.

Olga’s takeaway: she’s excited to play with the design side of Fable, because better creativity opens possibilities that the relentless pursuit of raw intelligence doesn’t.

8:09 The real reason the smartest models are getting locked down

Andrej Karpathy’s verified post on Fable 5 pulled 2.48M views, 25K likes, and 6.3K bookmarks — a strong signal that the people who actually build on these models reacted hard, and that the praise isn’t just hype. But the conversation shifted to what it means that Mythos stays gated. Olga framed it as the beginning of AI’s tiering: the most capable, no-limit models go to whoever pays the most — pharma, big enterprise — while normal users get the safe version.

Chris’s read, offered as conjecture: Mythos specifically censoring hardcore bio-health research isn’t only about safety. It’s about incumbents — the companies sitting on trillion-dollar drug horizons — not wanting the general public competing to create breakthroughs. Both hosts landed on the same survival rule, quoting Chamath: more than ever, don’t get locked in with one model. If you build everything on a single model, you’re exposed to whatever that company decides to restrict next.

11:38 ChatGPT now remembers you on its own

OpenAI began rolling out a new ChatGPT memory system it calls “Dreaming” — announced June 4 and rolling out through the week, Plus and Pro in the US first. Instead of a manual list of saved facts, it runs in the background and synthesizes what it knows about you across your whole history.

Why it matters: This automates what every power user already does by hand — keeping a memory file updated so each new session doesn’t start from zero. The difference between a tool you re-explain yourself to every time and an assistant that actually knows your context. For real work, it compounds.

The flip side, which Olga felt sharply: a memory that edits itself is a memory you don’t fully control. If 60% of your inputs are about one topic, it may start treating you as only that, and stop surfacing anything new. Her practical tip — become your own auditor. Regularly ask ChatGPT (and Claude) “what do you remember about me and my work?” and read the notes like a new hire’s, keeping what’s right and correcting what’s stale.

15:28 AWS built an agent that works your cloud bill

On June 9, AWS put its FinOps Agent into public preview — for AWS customers, on their own AWS bill (US East region in preview, free during preview). FinOps is the tedious art of deciphering cloud billing. This isn’t a chatbot giving advice; it’s a digital worker that watches your costs, investigates a spike, traces the cause, and files a report ticket into Slack or Jira.

Key Takeaway: Most viewers don’t manage an AWS bill, and that’s fine — watch it as the clearest example yet of where AI is going. Not a chatbot, a worker. Any repetitive “watch this number and flag the weird one” job in your business is the next candidate to hand to an agent.

Olga read it as a high-trust move — “let me help you pay less” — and noted there’s not a lot of hard data on it yet (no published savings figures or customer counts), so she’s watching it as a pattern rather than a tool to grab this week.

17:45 Apple closes Siri off

At WWDC on June 8, Apple unveiled a ground-up Siri for iOS 27 — but locked the model shut. You cannot bring your own AI; it’s a closed garden. Apple’s own newsroom says Siri is custom-built “in collaboration with Google and its Gemini models” alongside Apple’s foundation models.

Honest scorecard — a MISS. Chris had called Apple going bring-your-own-model at the OS layer. Apple did the opposite: closed, unified, no model choice. Apple reportedly tested letting normal users bring their own key and found it too complicated, so it defaulted to a single locked experience.

Chris’s strategic worry: for Apple to close off the phone right now — the most important moment since the 2007 iPhone — is suspect. Using your phone as an edge-compute device is the future, and locking it creates a vacuum a more open platform (an Elon “Xphone,” or Google leaning harder into Android) could fill. Olga’s blunter take: Siri has had the biggest head start of anything and done nothing with it. She uses Grok in the car, never Siri.

22:57 Google’s Live Translate keeps your own voice in 70 languages

On June 9, Google released Gemini 3.5 Live Translate — low-latency, speech-to-speech translation across 70+ languages that keeps your tone, pace, and pitch, switches languages automatically, and doesn’t wait for you to finish a sentence. It expands Google Meet from 5 languages to 70+.

The Universal Translator, Shipping

The old way was a three-step pipeline: transcribe, translate, then synthesize robotic audio. This goes audio-to-audio directly and maps the emotion, tone, and inflection of your voice into the translation. It’s the sci-fi one that’s actually here.

Olga is as bullish on this as anything in AI. The business angle: if you’re marketing a product across borders, you no longer need perfect English — you speak, and it comes out in the target language with your own voice and tone. The honest caution she added: it’s confident even when it’s subtly wrong, so use it for a conversation, not a high-stakes negotiation or a contract.

24:37 Seattle hits pause on data centers

On June 9, the Seattle City Council unanimously enacted an emergency one-year moratorium on large new data centers — those above a roughly 20-megawatt power threshold, not literally all of them — citing pressure on the local power grid and land use. A major US city just told the AI buildout to wait.

The hosts’ read: this won’t slow the global buildout — the capacity just goes somewhere with cheaper power and looser rules, like Singapore (this week’s biggest funding round) or Texas, where a “TerraFab” facility is set to become one of the largest buildings in the world. Chris’s tongue-in-cheek prediction: in a year, when the ban lifts, watch for a big player to announce data-center plans that were ready all along. Olga’s broader point, drawing a parallel to a grim EU economic outlook: anti-energy and anti-business stances are self-defeating, and AI growth will simply route around the places that resist it.

28:09 Should the public own a stake in the AI companies?

Floated, not announced. Aboard Air Force One (June 5), President Trump floated the idea of the public — or the government on its behalf — holding equity stakes in major AI companies so Americans “share in the wealth.” There’s no deal, no policy, no legislation. It’s a remark, not a headline.

Olga, who grew up in the Soviet Union, gets nervous when she hears “the government on your behalf” — nothing good follows. But the underlying argument is interesting: the models are trained on the public’s collective data and powered by a public electrical grid, so society holding equity is logically consistent from a pure-resource standpoint. Chris took it further: today money only flows upstream — we pay to use services and our data goes in, but no value flows back. With AI, he argued, monetary flows will eventually run both ways, and the data we produce in everyday life will be compensated in some form. Whether equity is the right mechanism is unclear; that the question is coming is not. Olga’s filter on the news cycle: notice how fast “he floated it” becomes “it’s happening,” and don’t let it.

32:46 The one news takeaway: don’t get locked into one model

Key Takeaway: The single biggest takeaway from the week — do not get locked into one model. Be open, play with other models, don’t build everything on one thing. The models can change, and what’s available to you is a constant tug-of-war. Go play with Fable (half price through June 22 via Claude Desktop, per Ken’s tip — and it rips through tokens), and try Google’s live translation, which is about to make selling across languages a lot easier.

That rule — stay model-agnostic — is the through-line that connects the locked-down frontier (Mythos), the self-editing memory (ChatGPT), and the closed assistant (Apple). The same week the frontier got more powerful, it also got more controlled. The defensive move for any operator is the same: keep your options open.

34:06 The internet’s new customer isn’t human anymore

The first deep dive — published in full as The Internet’s New Customer Isn’t Human — is built on Greg Isenberg’s video “the next hundred-billion-dollar market: selling to AI agents,” and starts from a shift: for the whole history of the web, the user was a person — search, read, compare, click, buy — and your beautiful site existed to persuade them. The agent web is the opposite. The user is an AI agent acting for someone, and it discovers, evaluates, invokes tools, pays, and renews. It wants structured capability, permission, and trust — not a hero video.

Two Internets, Two Customers

Billions of new customers (agents) are coming online, with real money ready to be spent — but almost no one is building for them yet. The gap is technical debt: legacy systems built on code that isn’t AI-friendly, with companies bolting on solutions AI can’t run smoothly.

That’s the “two websites” thesis Chris has pushed: one customer wants to be persuaded, the other wants to be able to act. Your business now has two design jobs. The agent doesn’t care how pretty your site is — it may not even see it. The opportunity is that agent-operability can reach a higher efficiency than any human UI ever could, so there’s more capture to be had there.

40:34 How an AI agent actually buys from your business

The agent’s buying journey, walked through from Greg’s piece: it gets a goal (“find a payroll tool for 40 contractors”), goes looking across sources, then reads the real stuff — docs, pricing, APIs, reviews — not your marketing. It checks if you’re safe (policy, limits, identity, who it’s acting for), does the deal (paying, booking, subscribing), operates the product (filing tickets, changing settings, pulling reports), and then tells other agents. Agents referring agents — an agent referral program — is the weird new frontier.

Then the missing infrastructure: six things agents need that humans never did, and each is a company waiting to be built. Identity (who is this agent acting for, and on whose authority?), a wallet with its own spending authority so it can’t drain your bank account, real tools it can safely use, and more. Chris’s counterintuitive pick for the identity play: simulated customers — AI modeling buying patterns. He cited a company this week reportedly predicting customer behavior at ~90% accuracy using AI instead of traditional focus groups, more accurately and far cheaper than 40 years of human surveys. The new layer underneath all of it, he argued, is skills — software deployed to cover capabilities that didn’t exist before.

48:21 Which businesses win first when agents start shopping

Olga’s honest reframe (with the full deal-size research laid out in the deep-dive page): the agents won’t be running loose buying things anytime soon. OpenAI launched autonomous checkout in February 2026 and quietly pulled it back a month later — people browsed but wouldn’t let it buy. The real bottleneck isn’t capability, it’s trust, and trust scales with deal size:

  • Agent transacts start to finish — low-dollar, low-risk, routine: office supplies, SaaS reorders, API usage, refunds. A wrong call isn’t a lawsuit; you set a spend cap and let it run. If your business lives here, let it rip and own the workflow early.
  • Agent operates, human approves — mid-size deals with some risk: vendor switches, larger orders, contract renewals. The agent does the legwork and stages the decision; a human taps yes.
  • Agent does legwork, human signs — high-regret, six-figure-plus deals, anything with a contract and a lawyer. The agent researches; the human closes.

The counterintuitive build: The first wave is “deal hunter” agents — you set a $160 cap on a hard-to-find item and the agent hunts daily, or “find me a house in Austin under $3M with these features” and it reports back. But Chris’s twist: it’s not the buyer’s agent that’s the business — it’s the seller (the real estate company, the vendor) that should build the agentic functionality, because that’s how they capture the customers whose agents come knocking.

The Money Behind It

Morgan Stanley projects $190B–$385B in US agentic e-commerce spend by 2030. Olga’s lived example: she switched her ATS to Loxo after Claude (her agent) did all the research, compared the AI-native platforms, and surfaced the docs, MCP, and APIs — she just booked the demo and made the call. The vendors who’d dialed in their documentation won the agent’s evaluation.

Both hosts agreed Main Street gets reshaped faster than enterprise: real estate, ordering and delivery, bookings, travel, and luxury — anything procedural and repeat. In cities like New York, a class of customers already won’t pick up a phone or click around; if the agent can’t do it, they won’t do it.

1:06:52 Put any HTML file on your own site just by talking to AI

The second deep dive is the demo. Olga makes a ton of beautiful HTML content for the show every week, and until now it either lived on her local machine or on Cloudflare if she wanted to share it. Both fine — but she’s greedy: she wants every asset she creates to live on her own domain and compound her GEO over time, not sit on someone else’s server. So she asked Chris to build an API path for PageMotor where publishing any HTML file is just a matter of talking to AI. He shipped it this week.

Key Takeaway: Here’s the process Chris narrated. Her Claude is already connected to the pagemotor.com MCP server — the bridge that lets it act on the site. She points it at the finished HTML file and says “I want to put this on my PageMotor site; ask me any questions to clarify before you publish anything.” It reads PageMotor’s API docs, asks where the page should live, shows her the URL slug to approve, then publishes — folding the page into her live site in about four minutes. She never opened the admin panel or saw a line of code.

The result: the live page on her domain is identical to the Cloudflare original — same animations, same lighting. It lives at a clean, searchable URL (pagemotor.com/practical-ai/episode-45/…), and it carries the technical details that make a page part of a website: schema/JSON-LD data, title tags, and Google Analytics tracking. It’s not just an HTML file sent to a website; it became part of the website. And editing is just as easy — when Olga realized a link was missing, she told her AI to add it and it was done in seconds, no admin login, no pulling the file down.

Pro tip: The power of the AI-plus-MCP connection is actually greater than the UI. You can say “on slide four, change this text” and the AI goes straight to the right spot and makes the edit — no scrolling through HTML you don’t understand, hoping not to break something. Chris noted these published pages even load faster than template pages, by microseconds.

1:18:38 Turn everything you make into compounding AI search

Now that the process is set, Olga plans to port months of past content onto her site — and the slide decks too. She showed that the same publish-by-talking flow works for an HTML slideshow (the news as a clickable PowerPoint on a single URL with keyboard navigation), not just scrolling pages. (Watch the 7-minute demo of the talk-to-publish build.) She also added an email-capture form to another site the same way, just by prompting.

Why it compounds: Making your site citable by AI is the key to search now — when people search Google, they get an AI synopsis pulling from cited websites, and you want to be cited. Olga has been creating these documents since January, but because they only lived locally or on Cloudflare, they weren’t an archive — they were going to die, like Word files from 2014. Publish each episode’s docket of assets onto the domain and they become a living, GEO-optimized archive that works for your search footprint instead of rotting.

And the SEO/GEO details get layered in automatically — schema, title tags, analytics — work a technical user would never know how to do by hand. As Chris framed the bigger picture: your data can exist anywhere, you hook your AI to it, the AI synthesizes a report as an HTML page that goes onto your website, and everyone can view it. Internal dashboards, company documents behind a login — your business hub is now your website, and there are no boundaries on what can live there.

1:25:29 Funding: the week AI got physical

The Week’s Funding (Crunchbase, Week 28)

$7.78 billion into AI, 51.4% of all venture dollars, across 77 of 185 funded companies. It looks like AI doubled from last week’s $3.46B — but strip out one $2.5B data-center round and the pure-AI market was $5.3B, still up ~53% week over week. The biggest check of the week wasn’t an AI company. It was a building.

The funding tracker itself now lives on the PageMotor site, updated every week — see the full breakdown in The Week AI Got Physical and the running 28-week tracker. The top rounds told one story — AI got physical:

  • DayOne — $2.5B (Singapore). Hyperscale data centers: the power, cooling, and racks AI actually runs inside. The largest check of the week is real estate, not a model. Seattle shuts data centers down; Singapore builds them.
  • NEURA Robotics — $1.4B (Germany). Full-stack collaborative and humanoid robots — the largest round ever for a robotics company. Notable that $1.4B went to Germany, a country with a deep engineering legacy that’s been stifled; the hosts hoped it signals a sleeping giant waking up.
  • Supabase — $500M (San Francisco). Open-source backend and database now positioned as agentic infrastructure, valued at $10.5B, with Stripe and Salesforce doubling in. The plumbing a huge share of AI apps get built on.
  • Flourish Labs — $500M (New York). AI-powered mental health and employee coaching — the rare consumer health-AI play in a week of robots and infrastructure.
  • Generalist AI — $400M (San Mateo). NVIDIA- and Bezos-backed robotics foundation models — the AI “brains” that let robots do real-world physical tasks, at a $2B valuation on a Series B.

The takeaway: Also notable — TensorWave ($350M) is an AMD-exclusive AI cloud, the first real funded crack in NVIDIA’s monopoly. The trend across 28 weeks: the money is drifting from “who has the best model” to “who owns the robots, the chips, and the power to run them.” This week it voted for the physical layer. Watch whether that holds — because when the smart money stops buying software and starts buying buildings, that tells you where they think the bottleneck really is.

1:33:09 The mindset that keeps you ahead of the shift

Chris’s close on the demo: the paradigm of what web design even is has changed. We went from arguing about which software is better to speaking to an AI and having the outcome just happen — create whatever you want, with no existing design to fit into, and ship it to your website where it benefits you over time. The boundaries are gone.

Olga’s takeaway for the viewer: this is the 45th episode, and the speed of change means you have to unlearn a lot. She described operating like she’s five years old again — knowing nothing, asking the craziest questions — because AI can either find a way to make it happen or tell you it can’t. The people willing to unlearn the old way are the ones who go places. Her own plan: make all her sites agent-friendly so her “store is ready when the agents come knocking,” because leads already find her recruiting company through ChatGPT. The job now is to keep dreaming bigger about what your website can do for you — and build toward it before the world catches up.

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