Make Money With Gemini 4 Argon: Greg Isenberg's 3 Plays

Greg Isenberg has a website that cost his team around $200,000 to build.

He says it helped bring in more than $40 million in revenue for his holding company. Then he asked Google's new model to rebuild it. It came back with a better version, with mini games and sound design, in a few prompts.

That demo sold me on digging into the whole episode. Greg spent 7 days trying to make money with Gemini 4 Argon, Google's new frontier model, and found three specific plays where it beats everything else he's tested: vibe marketing, vibe manufacturing, and rebuilding boring SaaS.

I pulled the episode apart and checked his claims against what Google has confirmed since launch. All three plays are below, with the numbers.

Quick disclosure Greg makes himself: Google sponsored the episode and gave him early access. The builds are his, and so are the opinions. I've run the same test on other models before, when Claude Fable 5 dropped and again with GPT-6 Astra, so consider this the third chapter in the series.

What Gemini 4 Argon actually is

Google unveiled Gemini 4 Argon on September 30, 2026, and started rolling it out in Antigravity (its coding app and CLI) on October 13.

The specs that matter for builders:

• Roughly 1 million tokens of combined context (1,048,576 to be exact)
• Intro API pricing of $2 per million input tokens and $10 per million output tokens through November 30
• In Antigravity, it's only on Google AI Ultra at $100/month. The $19.99 Pro plan gets you Argon in the Gemini app, but not the Antigravity app or CLI

Greg's one-line review of the use: Antigravity is not his favorite yet. He kept missing other coding tools while using it. His review of the model inside it: good enough that he built real, working things in all three categories below.

Play 1: Vibe marketing (websites people actually share)

Back to that $200,000 website.

It's latecheckout.studio, the site for Greg's holding company. A little interactive city where every building is one of his businesses: LCA, Boring Marketing, the whole portfolio. People compliment it constantly. It's also a pain to update, so he mostly doesn't.

He asked Argon to make a better one, gave it Mondrian (the painter) as a style reference, and got back an interactive version with a world passport, sounds on every building, and a basketball mini game where you shoot three-pointers.

His argument: why would you launch a normal static website in 2026? The thing that stands out on X, TikTok, and Instagram is a site that feels like a game. That used to cost six figures. Now the constraint is your imagination, not the budget.

One warning from his testing, and it's the most useful line in the episode.

His first attempt was terrible. He asked for "a better version of latecheckout.studio" with no references and got something he compares to Zuckerberg's infamous metaverse avatar. Too many buildings, Roblox energy, nothing premium about it.

→ Argon needs good references for good creative. Feed it real inspiration (an artist, a screenshot, a site you love) or you'll get the average of the internet.

He also points to Justine Moore from a16z, who asked Argon for an interactive museum of Apple computers with zero assets provided. It scraped archival Mac photos, wrote its own tool to clean the images, pulled 50 years of specs, and built a 3D cover flow with UI that morphs to match each decade.

The writing trick: clone your own voice in one prompt

Greg calls Argon the best frontier model for writing right now, and his setup is one prompt: "I want you to research everything about how I write. I write on X, I do email newsletters, how I speak on YouTube. Internalize all of it into a skill. Then I'll give you a topic and test you."

Argon built him a full skill package: a core voice file with his sentence rhythm rules and mental models, a vocabulary file with phrases he's coined, and verbatim samples with templates.

Then he asked it to write a post on marketing engineers. It came back with his old-world-versus-new-world framing, micro products instead of PDF lead magnets, tweet-size landing pages (his actual belief that a first landing page should fit in 280 characters), and it even signed off "be well, Greg" like his newsletter does.

His score: about a 9.2 out of 10. His words: if a human writer sent him that, he'd be telling his co-founder about the hire.

The rule he lands on is 95/5. AI does the plumbing, humans bring the taste.

If you don't have a public body of work yet, upload whatever you've written. Old emails, internal docs, anything. The skill gets built from your words either way.

Play 2: Vibe manufacturing (custom physical products)

This one is the sleeper.

Greg had a viral tweet about "vibe manufacturing": using AI to generate STL files (the format 3D printers read) and turning them into customized physical products. In the episode he shows Argon doing the whole chain: wireframe, layers, CAD, then an export-ready STL you can send straight to a Bambu Lab printer.

His demo product is an espresso portafilter station. The demand signal came from r/espresso, where people who spent $2,500 on machines will happily pay $49 for a custom accessory. One printer can run four units overnight, about 8 hours of print time.

The bigger idea sitting inside it: he had Argon build an embeddable Shopify widget where customers customize a product (size, color, live 3D preview) and buy it for something like $39. There are millions of Shopify stores and almost nobody offers real customization.

Two ways to run it:

• Own the niche yourself. You know your audience: famous mountains for a snowboard brand, custom desk gear for espresso nerds, whatever your corner of the internet obsesses over. No printer? Slant 3D has a print-on-demand API, so you aggregate demand and never touch hardware.
• Or sell it as a service. Pitch existing stores: "I'll add custom physical products that build fandom for your brand, we split the margin." Greg puts the margins anywhere from 40% to 70% depending on pricing.

Greg's bet is that customization is why people pay the premium: when someone configures a thing themselves, they're attached to it before it ships.

Play 3: Rebuild boring SaaS and give it away free

Greg hears "SaaS is dead" in his comments daily. His answer: that's indie hackers selling to indie hackers. Normal businesses still gladly pay for software that makes their week easier.

The play:

• Find a recurring, boring problem. Mine G2, Capterra, and Reddit complaints about legacy tools (he also plugs Idea Browser, his own free daily-idea product)
• Build one very focused product for one niche
• Make the first tool free to get in front of likely buyers, then charge for the second, third, and fourth

His test prompt: "Build a working web app for a commercial cleaning company that turns site visit notes into a reviewed price proposal." A focused replacement for a quoting spreadsheet. Argon nailed the engineering on the first prompt, interactive margin calculators included. Not beautiful (creative still needs references), but it worked, and he calls it more solid than the vibe-coded stuff he was scared to deploy a year ago.

Think about the wedge here. Thousands of legacy tools charge monthly for what is now a one-day build. You show up free, win trust, then sell the rest. Pair the free tool with simple business automations so the quote, the follow-up, and the invoice send themselves, and a one-person shop looks like a real vendor.

I keep hearing versions of this wedge from founders on the podcast. The free thing gets you noticed. The paid things behind it are where the revenue lives.

6 hacks Greg found for getting more out of Argon

He frames these as the stuff most people won't figure out for months:

• /plan: agree on what to build before it touches files. He skipped it on the website rebuild and regretted it
• /subagents: split independent jobs so research and checks run in parallel. The voice-skill build would have been better with it
• /goal: mid-project, he told it "make this amazing" with a reference image. Costs more tokens, but the output jumped. His math: the original site made tens of millions, a few extra dollars of tokens is nothing
• /browser: Argon opens your app and tests the actual user journey itself
• /learn: turns your corrections into reusable project rules and skills
• Effort on high: he started on medium, moved to high, and stayed there. Noticeably better output

His closing advice is the same thing I tell Club members about niches: marry the niche, date the product. You can swap products forever. You have to love the people you serve.

FAQ

Can you actually make money with Gemini 4 Argon?

The model doesn't make you money, the distribution does. Greg's three plays all have a built-in customer path: shareable interactive sites that spread on social, custom physical products sold into niches that already spend (like r/espresso buyers paying $49 on top of $2,500 machines), and free rebuilds of boring SaaS that win trust before you charge. Argon just collapses the build cost.

Do you need Google AI Ultra to use Gemini 4 Argon?

For the full builder setup, yes. Argon inside Antigravity (the app and CLI) requires Google AI Ultra at $100/month. The $19.99 Pro plan gets you Argon in the Gemini app for chat and smaller tasks, but not Antigravity. Developers can also hit the API directly at $2 per million input tokens and $10 per million output through November 30.

What is vibe manufacturing?

Using AI to design customized physical products and send them straight to 3D printers. Argon generates the CAD and an export-ready STL file, which goes to your own Bambu Lab printer or to a print-on-demand API like Slant 3D. The business model is personalization: customers configure a product in a widget on your store and pay a premium because it's theirs.

Is Gemini 4 Argon better than Claude or GPT-6 for building a business?

Depends on the job. Greg rates Argon as the best writer among frontier models right now and was impressed by its engineering on first prompts, while admitting the Antigravity use still trails the competition. For creative work it needs strong references. My earlier breakdowns of the Claude Fable 5 and GPT-6 Astra playbooks cover the other side of that comparison.