Stripo AI Assistant vs generic LLMs: Why HTML emails still break and how to build ones that work

More marketers are asking AI tools to create a ready-to-send HTML email instead of plain text. At first glance, this sounds simple: describe the layout, tone, and visuals, and get a full design back in seconds. But that’s where most people hit a wall.

These tools are built on models trained to produce web HTML, not a version that survives in Outlook, Gmail, or Apple Mail. They follow modern web standards using <div>, external CSS, and responsive grids, while email design relies on tables, inline CSS, and strict fallbacks to stay consistent across dozens of clients.

The result often looks perfect inside a browser preview, but falls apart once sent. Columns stack wrong, images disappear, buttons lose colors, and fonts reset to Times New Roman. What seemed like a finished email quickly turns into hours of manual repair.

Key takeaways

1. Generic LLMs and agents still build web HTML, not email HTML, which is why their output breaks in Outlook, Gmail, and Apple Mail.
2. Common problems include missing tables, no inline CSS, clipped content, and layout shifts that appear only after sending.
3. Tools like v0.dev, Cursor, Lovable, and Replit are designed for web apps, not for production emails. They can generate structure but lack email guardrails, testing, and ESP exports.
4. Stripo solves this by combining AI with an email-native editor that already follows industry standards: table-based modules, inline styles, and bulletproof elements.
5. The workflow speeds up content creation while keeping layouts accessible, responsive, and client-safe.
6. Manual review still matters for extreme visuals or legacy clients, but the gap between “generated” and “ready to send” is much smaller with Stripo.

What goes wrong in AI-built emails

When AI models create HTML emails, they typically generate clean web code that often fails in real-world inboxes. Most errors recur across various LLM-based tools, ranging from chatbots to code agents. Below are the most common ones developers see again and again.

Layout & CSS

AI tools prefer modern web structures, such as <div>, flex, or grid, instead of email-safe tables. Without table markup or hybrid fluid patterns, columns collapse in Outlook and mobile clients.

They also keep styles in <style> tags or external CSS files. Since many email clients strip those, colors, spacing, and fonts disappear. Inline CSS is mandatory, but LLMs rarely apply it correctly.

Before (AI-generated):

<div class="row">

  <div class="col">Product</div>

  <div class="col">Price</div>

</div>

After (email-safe):

<table role="presentation" width="100%">

  <tr>

    <td width="50%">Product</td>

    <td width="50%">Price</td>

  </tr>

</table>

Outlook & MSO specifics

Outlook still uses the Microsoft Word engine to render HTML, so it ignores modern CSS features. AI-built emails often lack VML fallbacks for background images and buttons, which makes them appear blank. Rounded corners and line-height values also break.

Bulletproof button example:

<!--[if mso]>

<v:roundrect xmlns:v="urn:schemas-microsoft-com:vml" href="#" style="height:40px;v-text-anchor:middle;width:200px;" arcsize="10%" stroke="f" fillcolor="#007BFF">

  <w:anchorlock/>

  <center style="color:#ffffff;font-family:Arial,sans-serif;font-size:16px;">Shop now</center>

</v:roundrect>

<![endif]-->

<![if !mso]>

<a href="#" style="background-color:#007BFF;color:#ffffff;padding:12px 24px;border-radius:4px;text-decoration:none;">Shop now</a>

<![endif]>

Gmail, Yahoo, and Apple Mail behaviors

Gmail cuts messages larger than roughly 102 KB, which truncates AI-generated layouts packed with inline styles. These models also call web fonts without defining system fallbacks, so typefaces revert to defaults. Head-level styles are removed, breaking layout consistency. None of the AI tools handle dark-mode adjustments, causing icons to vanish or invert.

Fix snippet for font fallback and dark mode:

font-family: Arial, Helvetica, sans-serif;

@media (prefers-color-scheme: dark) {

  .text { color: #ffffff !important; }

}

Accessibility and interactions

AI tools often skip accessibility basics:

• no alt text on images;
• missing lang attribute in <html>;
• color contrast below WCAG standards;
• tiny tap zones under 44 × 44 px.

Quick fixes checklist:

• add descriptive alt for each image;
• declare lang="en" (or other locale);
• keep contrast ratio ≥ 4.5:1;
• make all buttons large enough for touch.

Technical hygiene

Even when visuals look right, AI output tends to break small but vital rules:

• links use the wrong tracking parameters or open in the same tab;
• images lack defined width and height, causing layout jumps;
• multiple external hosts slow loading or get blocked by privacy filters.

Do/don’t table

Why generic LLMs and agents are prone to these failures

Most AI systems are trained on web development data, not email templates. While their datasets include modern frameworks, responsive websites, and CSS libraries, they feature almost nothing about the outdated table-based layouts that emails still rely on. As a result, they follow the logic of browsers, not inboxes.

There are no guardrails in these tools that warn when code will fail in Outlook or Gmail. An AI model doesn’t know that background images need VML in Outlook or that Gmail ignores <style> blocks. It just predicts what “looks” like valid HTML.

These systems also lack multi-client rendering checks. They can’t test how a layout behaves across clients or devices, so there’s no feedback loop to fix what breaks after sending.

Even tools that promise “Figma to HTML” or visual generation only match the appearance, not the underlying structure. They may reproduce a layout that looks identical on screen but isn’t email-safe. Each block still needs manual cleanup, inlining, table conversion, accessibility fixes, and link validation before it’s ready to send.

Tool landscape: What AI features actually do

This section maps what the main tools actually generate and where they fit in an email workflow. We focus on what ships: code type, editing flow, and export paths, not slogans or demos.

v0.dev (Vercel)

v0.dev is Vercel’s AI-powered builder that turns text, screenshots, or Figma files into production-ready web interfaces. It runs on a combination of generative models and React-based components, producing clean code with Tailwind and Shadcn UI. The platform includes Design Mode for visual edits and supports agent actions that handle layout changes, content updates, and quick deployments to Vercel.

Its strength lies in creating polished web UIs at high speed. But when it comes to email, v0.dev hits a clear limit. The system generates web HTML built with Next.js conventions, <div> grids, modern CSS, and JavaScript-based interactivity — all incompatible with email clients. There are no email-specific guardrails, inline-style enforcement, or export options to ESPs, so every generated layout still needs to be rewritten in table markup before it can be sent.

Cursor (AI IDE)

Cursor is an AI-driven coding environment that acts like a smart development partner. It connects directly to your codebase, understands its structure, and lets you interact with it through natural language. The editor includes codebase-aware chat, leverages autonomous agents, and uses the Model Context Protocol (MCP) for handling multiple tasks in the background. Developers can set custom rules, trigger refactors, and let background agents write or test code automatically.

Its strengths show up in software development, where precision and integration with repositories matter most. However, Cursor is not built for email creation. It has no templates, table-based layouts, or inline-style logic that email clients require. While it can write HTML and CSS, the patterns it uses are web-oriented, meaning they look fine in a browser but fail in Outlook or Gmail without major adjustments.

Lovable

Lovable is a conversational builder that lets you describe an idea and watch an autonomous agent turn it into a full web app. It combines code generation with visual editing, so you can click and adjust layouts without writing a line of code. The platform includes custom knowledge storage for project rules or design tokens, supports direct integrations with tools like GitHub and Supabase, and runs on its own managed hosting. Visual edits do not consume credits, which makes iteration fast and affordable.

Lovable’s agent works well for modern web development, but not for email production. The system relies on div-based layouts in a web technology stack, external CSS, and JavaScript-driven behavior with no table, inline, or VML standards built in. As a result, anything it generates must be reworked manually before it can render correctly across email clients.

Replit Agent

Replit Agent is an AI development assistant built into the Replit coding platform. It can take a short brief, generate an application, run tests, and deploy the result without leaving the editor. The system includes automatic testing, error correction, and rollback options that let developers restore any previous version. This makes it a powerful tool for rapid prototyping and debugging within a controlled environment.

Its focus, however, is purely web-based. Replit Agent works with browser rendering and web logic, not with the constraints of email clients. It does not apply inline styles, table layouts, or VML patterns. Because of that, even though it produces functional HTML, the output is not suitable for email delivery without significant manual cleanup.

Stripo (editor + AI)

Stripo combines a visual email editor with built-in AI tools that work inside an email-safe environment. Every template or block is based on email-native modules that use table layouts, inline CSS, and bulletproof patterns tested across major clients.

The AI Assistant lives directly inside the editor. It can write text, suggest structures, or build entire sections within verified blocks that already follow email standards. Stripo also includes a Brand Kit for consistent fonts and colors, accessibility helpers, and AI tools for image generation and automatic alt text.

All designs can be exported directly to ESPs or downloaded as HTML that renders correctly in Gmail, Outlook, and Apple Mail. While Stripo cannot perfectly convert a complex Figma layout without manual input, it significantly reduces the time and technical effort required to build responsive, client-safe emails.

Practical playbook: How to actually ship AI-assisted emails

1. Use an email-native editor as your main environment and connect AI inside it. This ensures that every block, image, and button follows safe patterns from the start.
2. Keep structural modules intact with able layouts, inline CSS, bulletproof buttons, and VML fallbacks. Add dark-mode rules to protect brand colors and icon visibility.
3. Follow accessibility basics by including alt text for all images, declare a lang attribute, readable contrast, and keep tap areas at least 44 × 44 px.
4. Control size and hosts to stay under Gmail’s clipping limit and avoid slow-loading assets. Stick to a few trusted domains for images and tracking.
5. Run tests on real clients using tools or inbox accounts instead of relying on browser previews. Check at least Outlook, Gmail, Apple Mail, and Yahoo before launch.
6. Export through ESP-ready paths to preserve inline CSS, links, and tracking parameters. This prevents corruption or missing assets after the send.

Limitations and honest notes

No AI tool can guarantee a perfect one-to-one match between a Figma design and the final email across every client. Each platform interprets HTML differently, and even small differences in rendering engines can shift alignment or spacing.

Edge clients and custom typography remain tricky. Outlook for Windows, older Android apps, and rare regional clients often ignore parts of the code. Custom fonts may also revert to system defaults unless a fallback is defined.

AI shortens the process and helps assemble layouts faster, but guardrails and human review are what keep an email production-ready. Testing, small manual tweaks, and visual checks still make the difference between “generated” and “ready to send.”

Wrapping up

AI tools for web development are impressive, but they still miss the mark when it comes to email creation. The main reason is simple: they’re built for browsers, not inboxes.

Stripo solves this gap by embedding AI directly into an email-native environment. The structure, styles, and exports all follow rules that real clients understand. You can still move fast, experiment, and use AI for content or layout ideas, but everything stays within guardrails that make an email safe to send.

If your goal is a working, responsive, and accessible HTML email and not just a pretty preview, build it where AI understands the medium. In Stripo, that’s already part of the system.