The $8k Website AI Can Build in 33 Mins

The $8,000/Hour Agency Is Here

Eight thousand dollars for a website that takes 33 mins to build sounds like scammy webinar bait, but Jack Roberts treats it as a repeatable productized service. His pitch is simple: use Gemini 3.0 plus a lean tool stack to build and deploy a high-conversion, AI‑driven site fast enough that your effective rate looks like an $8,000/hour agency.

Roberts has receipts. He says he previously built and sold a top‑100 UK startup with more than 60,000 customers, and now runs a seven‑figure AI automation business selling websites and systems “for thousands of dollars” to clients. That background matters because his tutorial targets agency operators and freelancers who care about lead flow and sales, not just clean gradients.

His argument: Gemini 3.0 did not just change how websites get built, it changed who builds them. Instead of armies of front‑end devs and copywriters, he is training a new class of “AI system architects” who orchestrate models, templates, and integrations to solve business problems and then wrap that into a site. The value sits in designing the system and the offer, not in hand‑coding another hero section.

Roberts’ SITE framework starts with Strategy, not CSS. He forces you to define whether the site will handle: - Cold traffic that needs value and diagnostics - Warm traffic that needs a clear commitment step - Outbound prospects that mostly need trust and proof

From there, Gemini becomes the engine that turns that strategy into layout, copy, and code.

That mindset draws a sharp line between what Roberts sells and what most AI website builders ship. Template‑driven tools can spit out “pretty but dumb” front‑ends: static landing pages that look modern, load fast, and then do almost nothing for revenue. Roberts instead talks about “websites and systems,” where embedded AI—diagnostic flows, assistants, automated follow‑ups—directly moves visitors toward buying.

In his world, you are not a designer using AI; you are an operator packaging a conversion system. The $8k price tag is for that system, with the website as its most visible surface area.

Beyond 'Looks Good': The SITE Conversion Framework

Most AI website builders stop at “looks good.” Jack Roberts starts with SITE. His four-step framework—Strategy, Interface, Text, Engine—acts like a preflight checklist for conversion, forcing every decision to answer a blunt question: will this page actually create leads or sales for a real business?

Strategy comes first, long before Gemini 3 writes a headline or spits out a line of code. Roberts makes you define the site’s job: handling cold traffic, nurturing warm traffic, or supporting outbound outreach. Each path changes the architecture—cold visitors get value-heavy diagnostics and education, warm visitors see stronger calls to action, outbound prospects see proof and trust signals.

He drills into “viewer state” as a non‑negotiable input. You map the visitor’s three biggest problems, what they already believe, what they doubt, and what made them click in the first place. That strategic inventory then drives both layout and copy, so the eventual hero section, social proof, and forms exist to resolve specific objections, not just fill space.

Interface only starts once Strategy locks in. Roberts raids Dribbble, Mobbin, and reference sites like Base10 to assemble a mood board that matches the business goal: an “Apple‑esque” SaaS feel for an AI dental agency, or a more utilitarian dashboard vibe for B2B tools. Gemini 3 then uses those references to generate structure and components, but within the constraints of the conversion plan.

Text comes next as a direct output of the strategy work, not a creative afterthought. Headlines, subheads, and CTAs map to the problems and beliefs identified earlier, so “get a demo” might become “fill your calendar with high‑value patients in 21 days.” Roberts positions Gemini as a high-speed copywriter that still answers to a human‑defined narrative.

Engine is where the site becomes a system. Roberts wires in AI diagnostics, chatbots, and automations using tools like Google AI Studio, GoHighLevel, and Vercel so the site not only captures leads but also qualifies and routes them automatically. That stack turns a Gemini‑generated layout into what he calls a “conversion engine” that justifies $5,000–$8,000+ price tags.

Roberts sums it up bluntly: “What boat we’re rowing in is more important than how hard we row.” SITE is the boat. Gemini is the oars.

Strategy First: Define the Problem, Not the Pixels

Strategy, in Jack Roberts’ SITE framework, starts with a blunt question: what business problem should this website actually solve? For his $5,000–$8,000 builds, the goal is never “look modern” or “match the brand palette.” It is “book 40% more sales calls,” “qualify leads automatically,” or “turn cold traffic into email subscribers at 10% instead of 1%.”

Roberts forces that clarity by sorting every project into one of three traffic types. Each type gets a different primary job and a different yardstick for success. Strategy becomes a routing problem, not a mood-board exercise.

For cold traffic—people hitting a page from ads or search—the site’s main job is value and diagnosis. Roberts pushes for lead magnets, calculators, or quizzes that tell visitors what their real problem is and segment them. The KPI here is usually email capture rate or quiz completion, not immediate revenue.

For warm traffic—audiences from a list, social following, or referrals—the site can ask for a commitment. That might be a demo request, a booked call, or a low-friction trial. Roberts still layers value on top, but every section leans toward a single conversion event.

Outbound traffic flips the script again. When your agency cold-emails a prospect and links to a custom page, the page’s job is trust, not teaching. Expect proof walls: case studies, screenshots, Loom walkthroughs, and specific ROI numbers designed to answer “Why you?” in under 30 seconds.

Underneath those traffic buckets sits what Roberts calls viewer state. Before he prompts Gemini, he writes down: - The viewer’s three biggest problems - What they already believe about those problems - What uncertainty or curiosity made them click

Those answers become constraints. A dental agency landing page might target “empty appointment slots,” “no-shows,” and “Google reviews stuck under 4.0,” and assume the dentist believes “marketing agencies waste money.” Every headline, subhead, and CTA then attacks or reframes those beliefs.

Feed that level of context into Google AI Studio – Build with Gemini 3 and Gemini stops behaving like a generic homepage generator. Roberts uses it to output section-by-section wireframes, tailored copy, and even interactive diagnostics that mirror the exact viewer state. Strategy turns into structured raw material, and Gemini 3.0 turns that material into a conversion-focused website in about 33 mins.

The Multimodal Mood Board: Teaching AI Your Taste

Interface is where Jack Roberts stops talking strategy and starts feeding Gemini 3.0 actual taste. He raids Dribbble, Mobbin, and Design Joy for layouts that already convert, searching keywords like “SaaS dashboard” or “agency hero” to surface production-grade UI patterns instead of random Behance art projects.

From there, he builds a mood board, not a mood paragraph. Roberts opens a blank whiteboard in Canva, pastes full-page screenshots, and labels each one with blunt, designer-style notes: “I like the dotted lines and monochromatic feel of this hero section,” “Keep this card spacing but lose the gradients,” “Navigation minimal like this, no top-right clutter.”

Those annotations turn into a structured grid of intent. One tile might say “Hero – dotted system lines, Apple-esque typography,” another “Pricing – three-column layout, clear ‘Most popular’ badge,” another “Testimonials – circular avatars, muted background, no stars.” Each screenshot carries both the visual reference and a one-line spec for what to steal.

Gemini 3.0 suddenly has something text-only prompts never give it: concrete pixels. Roberts drags that Canva board into Google AI Studio, uploads it as images, and pairs the visuals with his text callouts so Gemini sees both the layout and the commentary at the same time.

Multimodal prompting matters here. Instead of typing “clean, modern B2B site,” he shows Gemini a Base Ten-style hero with dotted “system” lines and literally writes, “Recreate this feeling for a dental systems agency, not a dev tools startup.” Gemini can align typography, spacing, and hierarchy to a real example rather than hallucinating a generic template.

This workflow translates fuzzy taste into machine-readable constraints. Gemini receives a de facto design spec: - Use monochrome hero with dotted connectors - Keep navigation ultra-minimal - Match card density and whitespace from reference

By the time Roberts asks Gemini to build the page, the model is not guessing his aesthetic. It is following a multimodal brief that encodes his preferences as specific, repeatable instructions.

Crafting the God Prompt in Google AI Studio

Crafting an $8,000 website in 33 mins starts long before Gemini writes a single line of code. Jack Roberts treats Google AI Studio like a control panel, and the “god prompt” as the master blueprint that locks in strategy, style, and structure before Gemini ever improvises.

Roberts breaks that blueprint into a three‑part prompt. Each part maps directly to his SITE framework: the business goal, the interface aesthetics, and the conversion engine baked into the layout.

Part one is deceptively simple: the core request. Roberts opens with something like, “Design a website for an agency that helps dentists scale using AI systems and automation,” then immediately layers in audience, offer, and outcome: who the dentists are, how the agency works, and what “success” means in leads or booked calls.

He treats this core request as a mini creative brief. It includes traffic type (cold, warm, outbound), the viewer’s state, and the three biggest problems the site must address, so Gemini understands it is designing a sales asset, not a digital brochure.

Part two turns Gemini into a stylist who has studied the same mood board you have. Roberts uploads a multimodal mood board into Google AI Studio—screenshots from Dribbble, Mobbin, Design Joy, and even specific sites like Base10 with that “Apple‑esque” feel and dotted‑line system visuals.

He then spells out concrete stylistic guidelines tied to those images: “Use a soft animated background,” “Replicate the dotted‑line ‘system’ motif,” “Minimal, high‑contrast hero like this example,” and labels each screenshot in Canva with tags like “hero section” or “pricing.” Gemini now knows not just what looks good, but where and why.

Part three defines the website structure as a conversion funnel. Roberts explicitly lists the sections he wants, in order, with a sentence or two describing each section’s job.

Typical structure includes: - Hook (pattern‑interrupt headline for dentists) - Value Prop (how the AI systems increase revenue) - Proof (case studies, numbers, logos) - CTA (book a call, diagnostic, or demo)

Roberts insists that Gemini’s output quality tracks directly with prompt specificity and structure. Vague prompts yield pretty but generic websites; his three‑part god prompt gives Gemini enough constraints to ship something that looks custom, matches a defined aesthetic, and follows a proven conversion narrative on the first try.

The Modern AI Dev Stack: From Pixels to Production

Modern AI web studios now look less like design shops and more like tightly integrated dev pipelines. Jack Roberts’ stack runs from prompt to production in under 33 mins, turning a Gemini output into a hosted, client-ready asset with almost no manual scaffolding.

Everything starts in Google AI Studio, where Gemini 3 generates the first pass of the site. Roberts prompts it for full HTML/CSS/React layouts, componentized sections, and conversion-focused copy tailored to cold, warm, or outbound traffic. Google positions these same capabilities as part of Gemini’s agentic push in Gemini 3 for developers: New reasoning, agentic capabilities.

Raw code then moves into Cursor, the AI-assisted IDE that acts like a senior front-end dev on call. Roberts uses Cursor to: - Clean up Gemini’s markup and normalize styling - Refactor into reusable React components - Fix layout bugs and responsiveness issues across breakpoints

From there, the workflow shifts to GitHub as the source of truth. Cursor commits the refined code to a repo, giving Roberts version control, rollbacks, and a permanent record of each client build. Branches let him test new hero sections or pricing layouts without risking the live site.

Deployment lands on Vercel, which turns that GitHub repo into a one-click, globally cached site. A single push triggers automatic builds, preview URLs for client approvals, and production deploys wired to Vercel’s CDN and edge network. For agencies, that means sub‑5‑minute updates when a client wants new testimonials or an offer change.

Tied together, Gemini, Cursor, GitHub, and Vercel behave like a mini SaaS pipeline. Roberts doesn’t just export a zip of AI code; he ships a living, maintainable production website that can iterate as fast as his prompts.

Selling an 'AI System,' Not Just a Website

Eight thousand dollars stops sounding insane once you realize Roberts is not selling a homepage; he is selling an AI system that happens to wear a website as its skin. The landing page is the shiny artifact, but the billable value lives in everything wired behind it: automations, data flows, and agents that keep working long after the designer logs off.

Roberts positions the site as a front door to a full growth stack, usually anchored on platforms like GoHighLevel. Traffic hits a clean, Gemini‑generated interface, but every click, form fill, and quiz answer drops into a CRM, triggers workflows, and feeds a feedback loop that keeps nudging the prospect toward a sale.

Under the hood, that “website project” quietly includes a set of interlocking components that agencies used to quote separately. At minimum, clients get: - Automated lead capture forms tied to a CRM - Multi‑step email and SMS follow‑up sequences - Pipeline tracking and simple dashboards for owners

Roberts then layers AI on top of that scaffolding. Gemini‑powered diagnostic quizzes segment leads by problem and budget; embedded chatbots handle FAQs, objections, and appointment booking; AI voice or text agents built with tools like ElevenLabs and Claude can pre‑qualify leads before a human ever picks up the phone.

This packaging move reframes the sale from “a new design” to “a revenue system.” A dentist, coach, or SaaS founder does not care how Gemini structured the hero section; they care that the funnel adds 20–50 qualified leads per month and recovers deals they used to lose. That is the kind of math that makes a one‑time $8,000 fee feel conservative.

Because the system runs on standard platforms and no‑code tools, Roberts can build once and replicate the pattern across niches. Swap the copy, adjust the offer, plug into a different GoHighLevel account, and the same architecture becomes a “patient growth system,” a “B2B demo engine,” or a “high‑ticket coaching funnel.”

Clients buy faster when the offer comes with a clear, measurable promise. Roberts leans on outcomes like higher show‑up rates, shorter sales cycles, and automated nurture for cold traffic that would otherwise bounce. The website is just the interface the founder can see; the AI system behind it is what justifies the $8,000 line item.

The Human Touch: Why Your Taste Is the Real Value

AI can spit out a passable landing page in under a minute, but it still cannot fake taste. That is the quiet subtext of Jack Roberts’ 33‑minute, $8,000 build: the model handles the scaffolding, while a human decides what actually deserves to exist on screen.

Design leaders like Meng To have been blunt about this. Raw AI layouts often feel like a collage of trending components—over‑gradient buttons, bloated hero sections, generic SaaS blobs—that scream “template” rather than “brand.”

Roberts’ workflow depends on a human acting as creative director. He curates reference sites from Dribbble, Mobbin, and Design Joy, then uses a multimodal “mood board” to teach Gemini what “good” looks like for this specific client, niche, and traffic type.

That step is not decoration; it is product direction. A dental agency landing page, a text‑to‑speech startup like Glaido, and a B2B automation offer might all share the same AI engine, but they demand radically different pacing, visual hierarchy, and emotional tone.

Industry designers echo the same pattern: AI can generate 20 layout variants, and a human kills 18 of them in 30 seconds. The value lies in knowing which two survive and why—clarity of offer, frictionless CTA, believable social proof, and a story that matches the audience’s “state.”

Roberts’ $8,000 price tag hangs on four human levers:

• Strategic diagnosis of the business problem and traffic
• Design taste and pattern selection
• High‑leverage prompt engineering and iteration
• Systems thinking to wire Gemini, GoHighLevel, ElevenLabs, and Vercel into one pipeline

Clients do not buy HTML; they buy a conversion system that routes cold clicks into qualified leads, follow‑ups, and booked calls. That orchestration requires understanding sales funnels, not just CSS.

AI in this stack behaves like a force multiplier, not a founder replacement. Gemini 3.0 drafts the layout, writes first‑pass copy, generates code, and even powers on‑site assistants—roughly 90% of the tedious work—so the human can spend their billable hour on the remaining 10% that actually moves revenue.

The New Agency Model: Speed, Scale, and Strategy

Agencies built on billable hours just met their worst enemy: an AI stack that ships an $8,000 website in roughly 33 mins. When Gemini 3.0, GoHighLevel, Vercel, and ElevenLabs handle design, code, and deployment, the traditional “six-week project” collapses into a single working session. That compression doesn’t just raise margins; it rewrites what clients expect from digital shops.

Project timelines that once spanned 4–8 weeks now shrink to 2–4 hours of focused work, including strategy, build, and launch. A solo operator can realistically handle 5–10 full builds per week instead of one or two. For small agencies, that throughput turns a handful of retainers into a pipeline of high-ticket, fast-turnaround projects.

As tasks like layout, front-end code, and boilerplate copy become AI macros, the value shifts to strategy and systems thinking. Roberts doesn’t sell “a site”; he sells a traffic-aware funnel with integrated AI diagnostics, follow-up automations, and lead capture tuned to a specific business problem. The margin lives in choosing the right offer, traffic temperature, and growth model, not in manually pushing pixels.

Future-proof agencies start looking less like design studios and more like AI systems integrators. They orchestrate: - Gemini 3.0 for reasoning, copy, and code - GoHighLevel for CRM and automations - Vercel, GitHub, and Google Cloud for hosting and deployment - Embedded chatbots and voice agents via Claude and ElevenLabs

For readers who want to see the lower end of this stack, tutorials like How to Build a Site With Google Gemini in 8 Steps show how quickly a basic build now comes together.

The agencies that win this decade won’t be the ones with the biggest design teams; they’ll be the ones that can translate a messy business problem into a working AI-powered system before the client’s coffee gets cold. Speed becomes the product, and strategy becomes the only defensible moat.

Your First $8k AI Project: A 5-Step Launchpad

Start by choosing a narrow niche and a concrete promise. “I build AI-powered lead generation systems for dental clinics” beats “I build websites.” Pick an industry you understand, identify a painful revenue problem, and define one flagship outcome, like “20% more booked consultations in 60 days.”

Next, drill the SITE framework until you can run it in your sleep. Practice mapping traffic type (cold, warm, outbound), viewer state, and top three problems before you open Google AI Studio. Build a reusable “god prompt” that includes strategy, mood board references from Dribbble or Mobbin, and your preferred layout structure.

Then build a portfolio piece as if a real client paid you $8,000. Use Gemini 3 in Google AI Studio to generate layout, copy, and code, then ship it with Cursor, GitHub, and Vercel. Embed at least one AI feature—like a qualification chatbot or intake assistant—so it feels like a system, not a static brochure.

Package your offer so clients see a revenue engine, not a template. Spell out deliverables such as: - Conversion-focused landing page - AI triage chatbot and lead routing - Automated follow-up emails and CRM integration Price as a project or a setup fee plus monthly retainer for optimization and support.

Finally, use that single polished build as your spear. Reach out directly to 50–100 targets in your niche on LinkedIn and email, and send a short Loom walkthrough of the demo site. Anchor your pitch around outcomes (“more qualified leads with an AI system”) and social proof, not tech jargon or hours worked.

Frequently Asked Questions

What is the SITE framework for AI web design?

The SITE (Strategy, Interface, Text, Engine) framework is a four-step process that prioritizes business outcomes. It starts with defining the core business problem and user state before using AI to generate the design, copy, and code.

Can Gemini 3 generate production-ready website code?

Gemini 3 can generate high-quality HTML, CSS, and React code that is close to production-ready. However, it typically requires minor refinement and testing in an AI-assisted IDE like Cursor before final deployment.

How do you sell an AI-generated website for $8,000?

The high price is justified by selling a complete 'AI system,' not just a website. This includes the conversion-focused site, backend lead management (like GoHighLevel), and integrated AI tools (chatbots, diagnostics) that solve a core business problem for the client.

What tools are needed besides Google Gemini 3?

The core stack includes Google AI Studio (for Gemini), design inspiration tools (Dribbble, Mobbin), an AI-assisted IDE (Cursor), a deployment platform (Vercel), and a CRM/funnel builder (GoHighLevel) to handle leads generated by the site.