AI That Ships: Live Gemini 3 Builds & What to Do After the Demo

Practical AI: Episode 17

AI That Ships: Live Gemini 3 Builds & What to Do After the Demo

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Published: November 21, 2025

TL;DR

Google’s Gemini 3 represents a major leap in AI coding—jumping from 60% to 76% accuracy on coding benchmarks and 5% to 31% on visual reasoning. This episode demonstrates live builds turning napkin sketches into deployable websites, explains how to actually ship AI-generated code via Vercel and GitHub, and analyzes Fyxer AI’s path to $25 million ARR in 14 months with just 10-15% AI costs. The vertical AI market has exploded from $13 billion to $115 billion, with $12.3 billion deployed in a single week.

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

  • Learn how Gemini 3’s breakthrough capabilities transform napkin sketches into production-ready applications in minutes, with benchmark improvements showing 60% to 76% on coding tasks and 5% to 31% on visual reasoning. Understand why this represents a fundamental shift from college-level AI to PhD-level problem-solving.
  • Discover the strategic difference between vibe coding and shipping real products. Through live demonstrations, see exactly how to take AI-generated websites from demo to deployment using Vercel, GitHub, and custom domain hosting. Learn why the creative prototyping value often exceeds the final output.
  • Understand Google’s vertical integration advantage and why it threatens the entire AI wrapper economy. With Gemini running on Google’s own compute at roughly half the price of competing LLMs ($2 per million input tokens), companies like Cursor face structural pricing challenges they cannot overcome.
  • Gain insight into Fyxer AI’s economics—a company that grew from bootstrap to $25 million ARR in 14 months with just 10-15% AI costs versus the 20-30% industry average. Learn why workflow-focused AI wrappers with narrow, specific use cases create sustainable businesses.
  • See the vertical AI market explosion from $13 billion to $115 billion, with $12.3 billion in funding deployed in a single week across 230 deals. Understand which sectors are attracting capital—healthcare AI hitting inflection points, fintech-AI convergence, and infrastructure plays.

Biggest Takeaway to Implement

Stop treating AI tools as finished product generators and start using them as creativity accelerators. The real value of Gemini 3 and similar platforms isn’t in deploying exactly what they output—it’s in rapid prototyping that surfaces ideas you couldn’t conceptualize alone. Use these tools to prototype three variations of your next project in an hour, extract the best elements from each, then build the real version with those insights. This transforms AI from a replacement tool into a creative multiplier that enhances rather than replaces your strategic thinking.

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Frequently Asked Questions

What is Gemini 3 and how does it compare to previous versions?

Gemini 3 is Google’s latest AI model released November 18, 2024. It shows major improvements over Gemini 2.5: coding accuracy jumped from 60% to 76%, while visual reasoning leaped from 5% to 31%. The hosts describe this as moving from college-level to PhD-level problem-solving capability. Read more below.

What is Google Anti-Gravity?

Anti-Gravity is Google’s new AI-first coding environment that directly challenges Cursor. Gemini 3 agents can write, test, debug, and browse for references autonomously within this platform. Google’s vertical integration means they can offer it at roughly $2 per million input tokens—about half the price of competing LLMs. Read more below.

How do you deploy AI-generated websites from Gemini 3?

Three main paths: download code for Vercel deployment (free static hosting with custom domains), push to GitHub for version control, or use platforms like PageMotor for dynamic features requiring databases and user management. Gemini 3 excels at frontend generation but lacks hosting infrastructure. Read more below.

What is Fyxer AI and why is their business model significant?

Fyxer AI is an email automation company that reached $25 million ARR in 14 months with only 10-15% AI costs (versus the 20-30% industry average). They work exclusively with text—the cheapest AI operation—and focus narrowly on email composition rather than attempting broader functionality. Read more below.

What is vibe coding?

Vibe coding refers to rapidly generating code prototypes using AI tools without deep planning, focusing on creative exploration rather than production-ready output. The hosts argue its greatest value is as a creativity accelerator—surfacing ideas you couldn’t conceptualize alone—rather than as a finished product generator. Read more below.

How big is the vertical AI market?

The vertical AI market exploded from $13 billion to $115 billion. In just one week, $12.3 billion was deployed across 230 deals with a $20 million median—above historical venture norms. Healthcare AI, fintech-AI convergence, and infrastructure companies are attracting the most capital. Read more below.

Practical AI: AI That Ships – Live Gemini 3 Builds & What to Do After the Demo

Key Definitions

What is vibe coding? Vibe coding is the practice of rapidly generating code prototypes using AI tools with minimal upfront planning. Rather than treating AI output as production-ready, vibe coding uses AI as a brainstorming tool to quickly explore multiple approaches and surface unexpected ideas.

What is the AI wrapper economy? The AI wrapper economy describes businesses that build products on top of foundation model APIs (like OpenAI or Anthropic) and charge users a premium. These companies face structural challenges because their margins depend on API pricing they don’t control.

What is vertical AI? Vertical AI refers to AI applications built for specific industries or narrow use cases (healthcare, legal, finance) rather than general-purpose tools. These specialized solutions often demonstrate better product-market fit and unit economics than horizontal AI tools.

What are AI costs as percentage of revenue? This metric measures how much of a company’s revenue goes to AI API calls and compute. Fyxer AI achieves 10-15% (considered excellent), while many AI startups run 20-30% or higher, making profitability difficult.

Quotable Moments

“The real value of Gemini 3 isn’t in deploying exactly what it outputs—it’s in rapid prototyping that surfaces ideas you couldn’t conceptualize alone.”

“Google’s vertical integration provides structural advantages that wrapper companies cannot match.”

“AI tools riff effectively on provided content but struggle to generate compelling specifics independently. Effective prompting means providing the substance while letting AI handle presentation.”

00:00 Intro and What’s Coming Today

Episode 17 delivers live building with Google’s newly released Gemini 3, moving beyond theoretical discussion to actual creation. The hosts demonstrate real workflows and analyze Fyxer AI’s growth to $25 million ARR, balancing hands-on technical demonstrations with signature economics analysis for builders navigating the rapidly evolving AI landscape.

01:56 Gemini 3 Launch Highlights and Benchmarks

Key Stat: Gemini 3 Performance Jumps

Coding accuracy increased from 60% to 76%, while visual reasoning leaped from 5% to 31%—improvements far exceeding typical incremental gains.

Gemini 3 launched November 18, 2024, with performance jumps exceeding typical improvements. The breakthrough transforms messy inputs—sketches, screenshots, competitor examples—into production-quality code on first attempt, compressing what previously took days of iteration into minutes of initial generation.

03:49 Anti-Gravity: Google’s New AI Coding Environment

Key Stat: Google’s Pricing Advantage

Gemini 3 costs roughly $2 per million input tokens after generous free rate limits—about half the price of competing LLMs.

Google’s Anti-Gravity tool directly challenges Cursor’s market position as an AI-first coding environment. Gemini 3 agents write, test, debug, and browse for references autonomously within this platform. The competitive dynamics create immediate pressure for Cursor, whose business model depends on paying Google and OpenAI for API access while charging users a premium.

Google’s vertical integration provides structural advantages that wrapper companies cannot match. With Gemini running on Google’s own compute infrastructure, the company doesn’t face the unit economics challenges that plague middleman platforms. This pricing power, combined with native integration across Google’s ecosystem, positions Anti-Gravity as a strategic threat to the entire AI wrapper economy.

07:21 Gemini 3 vs 2.5: The Big Leap

The performance comparison illustrates AI’s exponential improvement curve. Gemini 2.5 operated at college level, struggling with novel expert questions, while Gemini 3 reliably solves PhD-level problems. In coding, the leap from 60% to 76% accuracy crosses practical usefulness thresholds—moving from a tool requiring constant supervision to one producing consistently usable output. For visual reasoning, 5% to 31% represents transforming near-uselessness into genuine utility.

08:45 Where Gemini 3 Really Shines

Gemini 3’s strength lies specifically in UI generation and visual input processing, ideal for rapid prototyping, frontend development, and agencies creating client mockups. The tool excels at single-page applications, landing pages, and visual prototypes where design matters more than complex business logic. Understanding these boundaries enables strategic deployment—using it for visual translation while employing other approaches for backend complexity.

12:36 Live Demo: Turning a ChatGPT Prompt into a Full Website

Key Insight: AI Prompting Strategy

AI tools riff effectively on provided content but struggle to generate compelling specifics independently. Effective prompting means providing the substance while letting AI handle presentation.

The live demonstration uses a straightforward prompt describing Revenue Hire’s boutique sales recruiting business. Gemini 3 processes minimal context—company focus, target market, value proposition—generating a complete website in approximately 160 seconds total.

21:00 Adding AI Features and Multi-Page Live

Prompting Gemini 3 to add five AI features and multi-page functionality tests its ability to embed functional capabilities beyond static content. The tool integrates three interactive features: AI hiring assistant, job description generator, and interview question generator—each functional through the Gemini API with proper context management and prompt engineering handled automatically. This represents significant value creation, as building custom AI features previously required substantial development resources.

26:46 Screenshot to Website Magic

Uploading a screenshot of PageMotor.com’s homepage—just the visible browser window portion—Gemini 3 recreates the site with remarkable accuracy after one minute of processing. This proves particularly valuable for design-challenged founders who can find inspiration and replicate it legally through AI interpretation. The tool captures gradient treatments, section structure, and visual hierarchy while applying its own implementation.

30:09 Simple Prompt Demo and Embedded AI Assistant

Gemini 3’s annotation feature enables surgical edits to specific page elements without regenerating entire sites. Users draw rectangles around elements, add targeted prompts, and the tool updates only that section—dramatically improving iteration speed. The embedded AI assistant functionality creates live, interactive tools running through Gemini’s models with proper context management.

41:06 How to Actually Ship It

Three Deployment Paths

1. Vercel: Free static hosting with custom domains. 2. GitHub: Version control for collaboration. 3. PageMotor: Full-stack solutions with databases and user management for dynamic features.

After creating demos in Gemini 3, deployment requires strategic tool combination. This highlights a crucial market distinction—Gemini 3 excels at frontend generation but lacks hosting infrastructure, creating opportunities for platforms combining AI generation with complete deployment stacks.

56:40 Quick News Hits

Chinese state-sponsored hackers used Claude for cyber attacks in September, with AI performing 80-90% of work through jailbroken security testing prompts. Microsoft and Nvidia’s $15 billion Anthropic investment ($5B Microsoft, $10B Nvidia) signals strategic OpenAI diversification, pushing Anthropic’s valuation near $350 billion. Apple’s mini app program strategically targets Stripe by reducing commissions from 30% to 15% for Apple Pay users.

1:13:49 Vertical AI Boom: $13B to $115B Market

Key Stat: Vertical AI Market Explosion

The vertical AI market grew from $13 billion to $115 billion. Specialized applications in healthcare, legal, and finance demonstrate better product-market fit than horizontal tools.

Investment patterns favor narrow, deep solutions over broad, shallow ones. Healthcare AI reached inflection with 13 funded companies this week, fintech-AI convergence accelerates, and infrastructure providers capture compute demand regardless of individual startup success—strategic positioning insight for investors and founders.

1:21:16 Deep Dive: Fyxer AI

Key Stat: Fyxer AI Economics

Bootstrap to $25 million ARR in 14 months. AI costs run 10-15% versus the 20-30% industry average. Gross margins: 75-85%. Users: 180,000 with 100+ enterprises.

Fyxer AI’s trajectory provides a masterclass in sustainable AI business models. The company maintains low AI costs because they work exclusively with text—the cheapest AI operation. Their workflow analyzes users’ Gmail sent folders to learn individual writing tone, then drafts emails in that personalized voice. This narrow focus on email composition, rather than attempting broader functionality, enables exceptional unit economics.

The business model’s brilliance lies in building on existing workflows from their previous agency business. Unlike open-ended coding assistants like Cursor, Fyxer’s narrow scope enables aggressive prompt optimization and cost control. This strategic discipline creates competitive moats—they can afford per-seat pricing that traditional SaaS customers understand, while compute-heavy competitors struggle with consumption-based models.

1:35:28 This Week’s Funding

Key Stat: Weekly AI Investment

$12.3 billion deployed across 230 AI deals with a $20 million median—above historical venture norms. 44 seed deals indicate sustained pipeline development.

Capital concentration shows infrastructure dominance alongside vertical growth. Companies providing compute and foundational tools capture disproportionate value regardless of application winners, suggesting better risk-adjusted returns in picks-and-shovels infrastructure over specific applications.

1:41:55 Final Takeaways

Gemini 3, while powerful, remains fundamentally limited as a UI creator with narrow scope. Its greatest value lies in accelerating creative processes through rapid prototyping that generates ideas and clarity informing better final products. The episode reinforces commitment to practical, actionable AI education through demonstrations over pure discussion.

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