AI Website Design Prompts: How to Stop Getting Generic Hero Sections

AI website design prompts are often blamed when a landing page comes back looking generic. But a recent r/SaaS post makes a more useful argument: the weak link is usually not the model—it is the gap between a founder’s vague creative ambition and the concrete directions a model needs to turn that ambition into a credible hero section.

The distinction matters for anyone using AI to build a launch page, redesign a SaaS homepage, or move faster on experiments. Asking for “modern,” “clean,” or “premium” can produce competent interface code. It rarely produces a point of view. The result is familiar: a large centered headline, a purple or blue gradient, three benefit cards, rounded glassmorphism panels, and an abstract visual that could belong to almost any startup.

The original Reddit author described burning through roughly three weeks and hundreds of messages trying to improve a single hero. Their eventual conclusion was that they had been supplying moods rather than usable instructions, then compensating for the lack of direction with more iterations. That diagnosis has broader value than the product promotion attached to the post. It explains why AI-built sites often look technically polished but strategically interchangeable.

The real problem with generic AI landing pages

A hero section has to do several jobs at once. It needs to establish a brand impression, make the value proposition understandable, direct attention to the next action, and create enough visual confidence that a visitor does not immediately assume the product is unfinished or untrustworthy.

That is a dense creative brief, not a one-word style setting.

When a prompt says “make this feel high-end,” the model must invent answers to a long list of unanswered questions:

• Is the brand quiet and editorial, loud and kinetic, technical and precise, or playful and human?
• Is the visual anchor a product screenshot, a customer, a physical object, a landscape, a texture, an illustration, or typography itself?
• Should the headline occupy the center, a corner, or a split layout?
• Is the page meant to resemble a software company, a magazine, a fashion label, a developer tool, or a marketplace?
• Is the primary conversion action a trial, a demo request, a waitlist, a purchase, or documentation?
• What visual conventions should the design explicitly avoid?

A model will fill in these blanks using statistically common patterns. That is why “premium SaaS landing page” tends to create an average of existing premium-SaaS-looking pages rather than a distinct composition. The output is not necessarily bad. It is just optimized for plausibility, not for differentiation.

This is also why endless prompting can become deceptive. Each revision may be visibly different, but not meaningfully closer to a business goal. Changing colors, button labels, shadows, or card shapes can feel like progress while leaving the central creative decision untouched: what should a visitor see first, and why?

The Reddit post’s useful insight: prompts need art direction

The r/SaaS post framed the lesson plainly: descriptions such as “sleek” and “premium” are wishes, while useful design prompts are instructions. That is an oversimplification in one sense—experienced designers do use emotional language—but it is an excellent operating rule for builders working with AI.

A designer can hear “premium” and bring context from brand strategy, visual references, category knowledge, typography, photography, layout, and prior critique. An AI coding tool has none of that context unless it is provided. It can generate an attractive implementation, but it cannot know which of dozens of attractive directions fits the company.

The practical replacement is not a longer adjective list. It is a compact creative brief with decisions that constrain the output in productive ways:

1. A reference world: what recognizable visual language should influence the work?
2. A spatial composition: where should major elements sit before their styling is decided?
3. A real visual anchor: what image, footage, product screen, illustration, or object is the layout built around?
4. A conversion hierarchy: what must a new visitor understand and do within the first screen?
5. Constraints: what familiar patterns, colors, effects, or interaction choices should be avoided?

These inputs make a prompt more like a creative director’s handoff and less like a request to decorate a wireframe.

Start with a reference, not a mood

The strongest recommendation from the original post is to name a concrete reference instead of relying on broad aesthetic labels. This is not a license to copy another company’s website. It is a way to communicate a visual grammar quickly.

“Modern and elevated” could mean almost anything. “Editorial travel journal, sun-faded film grain, asymmetric type, one warm directional light, generous negative space” tells the model far more about texture, balance, color temperature, photography, and composition.

References compress many hidden decisions

A good reference phrase acts as shorthand. Consider the difference between these two directions:

Weak:

Design a premium homepage for an analytics product with a modern look.

More actionable:

Build a restrained editorial homepage for an analytics product. Use the visual restraint of an architecture journal: oversized black serif headline, warm off-white background, fine gray rules, a single product chart cropped large on the right, and no gradients, glass cards, floating badges, or icon grids.

The second direction does not guarantee an excellent result. But it tells the AI what to prioritize and what to reject. It also gives the builder something specific to evaluate. Does the page feel like an architecture journal? Is the product screenshot being treated as the visual object? Has the layout avoided the banned startup defaults?

Build a reference stack, not a single imitation

One reference can accidentally pull a design too close to a specific brand. A better approach is to use a stack of three reference types:

• Category reference: a product in your market that handles clarity well.
• Editorial reference: a magazine, campaign, album cover, or retail experience with the desired visual atmosphere.
• Behavior reference: a site or interface that demonstrates a useful interaction, motion style, or content hierarchy.

For example, a developer-infrastructure startup might combine a technical documentation reference for information density, a Swiss-poster reference for typography, and an ecommerce product gallery reference for how screenshots are framed. The outcome is more original because the model is synthesizing a direction rather than reproducing a single template.

Reference-driven prompting is also becoming easier to operationalize. Prompt libraries and open design repositories now package examples, code, and reusable design assets rather than treating a prompt as the whole deliverable. The open-source Open Design project, for example, describes itself as a workspace for prototypes, landing pages, templates, and agent-driven design workflows, illustrating the wider move from one-off chat prompts toward repeatable systems. (github.com)

Describe the composition before the decoration

The second major lesson is about layout. Builders frequently describe colors and effects first—dark theme, glass panels, soft gradients, neon accents—while leaving the composition unspecified. That is how a tool ends up arranging everything in the same vertically centered stack.

Layout is not a finishing detail. It is the mechanism that determines attention.

Before writing a visual prompt, decide where each important element belongs:

• Where does the eye land first?
• Where is the headline anchored?
• Where does the product proof live?
• Is the primary CTA close to the value proposition or separated by a visual pause?
• Where is the empty space, and what job does it perform?
• On mobile, what is preserved, hidden, cropped, or reordered?

Use plain-language positioning instructions

You do not need to write CSS Grid coordinates to get much better output. Natural language can establish a strong composition:

Keep the navigation light and fixed at the top. Pin the headline and CTA to the lower-left quadrant. Let a large product image occupy the right two-thirds, cropped at the edge so it feels oversized. Preserve clear empty space in the upper-left. On mobile, show the headline first, then the product screen at a 4:5 crop.

That one paragraph resolves decisions that an AI tool otherwise makes by default. It tells the model that the design is asymmetric, that the screenshot should feel dominant, that whitespace is intentional, and that the mobile state must be designed rather than merely collapsed.

Make hierarchy measurable

A useful test is to look at a grayscale screenshot for three seconds. A new visitor should still be able to identify:

1. The main promise.
2. The primary action.
3. The strongest evidence that the promise is credible.

If all three compete at the same weight, the design may be attractive but inefficient. In AI-generated work, this often appears as too many equal cards, too many badges, multiple competing buttons, or a giant decorative background with no product proof.

A founder should be able to state the hero hierarchy in a single sentence: “The visitor sees the outcome, then the product evidence, then the action.” If that sentence is hard to write, no amount of styling will fix the underlying indecision.

Assets are not decoration—they are the hero’s operating system

The post’s most important claim is that the missing asset is often the real reason an AI hero looks synthetic. That idea deserves emphasis.

A full-bleed photo, a well-cropped product recording, a customer image, a physical artifact, or a distinctive illustration gives the layout something to organize around. Without one, many generators compensate with gradients, blobs, translucent cards, and abstract glows. Those techniques can be useful, but they are frequently serving as visual filler where there should have been a focal point.

A hero asset makes several brand decisions at once: color palette, contrast, subject placement, emotional tone, crop, scale, and visual story. It creates constraints. Constraints are precisely what prevent a page from looking like a broadly optimized template.

Choose the asset type based on the product’s proof problem

Different products need different hero assets.

For a B2B SaaS company, the default should rarely be a decorative background. A cropped product screen, a customer outcome, or a visual representation of the workflow usually gives visitors more reason to believe the claim.

Design around the asset, then optimize it

There is an important technical caveat. Hero media can improve brand expression while hurting performance if it is treated casually. Google’s web.dev guidance identifies Largest Contentful Paint as a Core Web Vital tied to when the main visible content renders, with a good threshold of 2.5 seconds or less for at least 75% of visits. Large hero images are frequently central to that measurement. (web.dev)

That means the answer is not “put autoplay video behind everything.” It is “use a meaningful asset and engineer it responsibly.” For a visual landing-page hero, that commonly means:

• Use an actual <img> element for the primary image when possible, rather than hiding it only in CSS.
• Serve modern image formats and responsive sizes.
• Reserve dimensions to reduce layout movement.
• Preload the true above-the-fold image only when it is genuinely the LCP candidate.
• Use a poster image for video and avoid forcing visitors to download a huge file before seeing the message.
• Keep overlays readable without making the visual subject disappear.
• Test mobile data conditions rather than approving the page only on a fast desktop connection.

The visual asset is part of conversion design and performance design. It is not a separate task for later.

A better AI website design prompt template

The most repeatable solution is to create a brief template your team uses before opening an AI builder. It should be short enough to complete in ten minutes and concrete enough to reduce unproductive back-and-forth.

The creative-brief prompt

Use this structure for a homepage or landing-page hero:

Build a responsive hero section for [product and audience].

Business goal:
[What should a first-time visitor understand and do?]

Core message:
[One clear outcome-focused headline idea.]

Reference world:
[Two or three non-competing visual references. Describe the qualities to borrow, not a brand to copy.]

Composition:
[State the location of nav, headline, proof, CTA, and visual anchor. Include mobile order.]

Hero asset:
[Name the supplied screenshot/photo/video/illustration, subject placement, crop, and overlay treatment.]

Typography and color:
[Specify type personality, contrast, palette, and any existing brand tokens.]

Proof:
[Customer logo, metric, testimonial fragment, product detail, or integration signal to include.]

Interaction:
[State motion behavior, duration, and reduced-motion fallback—or say no decorative motion.]

Avoid:
[List visual defaults and UX patterns that would make this feel generic.]

Implementation requirements:
[Framework, accessibility expectations, semantic structure, image optimization, and performance constraints.]

A worked example

Here is what that looks like for an imaginary AI reporting product:

Build a responsive hero for a reporting tool used by small marketing teams.

Business goal: make a demand-generation manager understand that weekly reporting can be automated, then start a free trial.

Core message: Turn campaign performance into a client-ready report before your coffee gets cold.

Reference world: editorial business publication meets a carefully labeled scientific notebook. Use confidence, calm whitespace, thin rules, and real data—not luxury gradients or futuristic neon.

Composition: navigation floats at the top with a small wordmark on the left and one CTA on the right. Headline, supporting copy, and CTA occupy the lower-left half. A large report screenshot occupies the right side and slightly extends below the fold. Leave the upper-left area mostly empty.

Hero asset: use the attached report screenshot. Crop it to show an executive summary and one chart. Add a soft paper-like shadow and a subtle warm-gray background, not a glass panel.

Typography and color: deep ink text, warm white background, muted moss accent, serif display type only for the headline and a neutral sans-serif for UI.

Proof: show “Built for HubSpot, Google Ads, and Meta Ads” below the CTA.

Interaction: no autoplay video. On hover, the report can rise by 4px. Respect reduced motion.

Avoid: centered stack, floating gradient blobs, three feature cards, stock photography, fake dashboard numbers, excessive rounded rectangles, and more than one primary CTA.

Implementation requirements: semantic HTML, keyboard-visible focus states, optimized hero image, responsive layout that places the screenshot below copy on mobile, and no layout shift.

The point is not that every prompt needs this exact format. The point is that a useful prompt makes creative choices inspectable. If the result is wrong, the builder can revise a specific decision—such as the crop, reference world, hierarchy, or proof element—instead of asking for something to feel “more premium.”

Why more iterations do not always improve the result

The original author’s account of repeated prompting is recognizable because AI tools make iteration cheap enough to become compulsive. But cheap iteration has a hidden cost: it can delay a decision that should be made by the person who understands the customer.

There are two kinds of revision loops.

Execution loops are healthy. The direction is clear, and the team is refining implementation: reducing contrast, adjusting the crop, simplifying copy, fixing mobile stacking, or making a CTA more prominent.

Direction loops are expensive. The team keeps asking for “bolder,” “cleaner,” or “less AI-looking” because no one has agreed on what the page needs to communicate or which visual world belongs to the brand.

The fix is to stop after two or three direction-level variations and hold a brief review. Ask:

• What is the intended message hierarchy?
• What specific part looks generic?
• Is the missing ingredient a layout decision, an asset, a proof element, or brand material?
• Would a human designer be able to act on the feedback without asking follow-up questions?

If the answer to the last question is no, the feedback is not ready for an AI tool either.

The community reaction exposed a different issue: execution credibility

The Reddit comments did not only debate the creative advice. Several commenters criticized the post’s AI-like promotional writing and reported basic site issues, including navigation and pricing-page failures in Safari. Another commenter asked why they should choose the promoted product over Open Design and its open-source templates and plugins.

That reaction is a useful warning for founders in the AI-building era. You cannot market a cure for generic, low-effort output with generic, low-effort output—and you cannot sell design assets while your own conversion path breaks.

Product quality is part of the argument

A builder who promotes a library of hero sections, prompts, code, and assets has to demonstrate value in the product experience itself. The website should answer basic questions without friction:

• What exactly is included: prompts, source code, assets, licenses, or all of them?
• Which files are production-ready and which are inspiration only?
• Are images and video licensed for commercial reuse?
• What framework and styling approach does the code use?
• Can a buyer preview mobile behavior and accessibility states?
• Does the navigation work across major browsers?
• Is pricing reachable, understandable, and reliable?

The underlying lesson applies to every SaaS launch. A compelling positioning statement earns attention; a working product flow earns belief. If a visitor encounters broken navigation, inaccessible contrast, or a dead pricing page, the marketing claim becomes harder to trust regardless of how strong the visual concept may be.

AI-written launch copy raises the bar, not lowers it

The sharpest comment on the post objected to the use of AI-like launch copy. The criticism is not that founders must handwrite every word. AI can be excellent for outlining, editing, localization, and generating variants. The issue is whether the final communication contains evidence of firsthand thought.

A credible founder post includes details that generic marketing language cannot replace: the specific failure mode, the surprising metric, the design tradeoff, the browser bug that was fixed, the negative result, the customer objection, or the reason a particular feature was left out.

That standard is especially important when selling to technically literate builders. They have seen enough vague AI-generated claims to recognize content that has not been shaped by experience. The solution is not to avoid AI; it is to own the final judgment.

Templates, source code, and open-source alternatives

The product promoted in the Reddit post centers on a reasonable idea: a hero-section resource is more useful when it includes the prompt, source code, and the actual assets used to create the preview. That bundle solves a real reproducibility problem. A beautiful screenshot alone rarely tells a buyer whether the result came from a proprietary image, complicated animation setup, unusual fonts, or a fragile codebase.

But it is not the only route available.

Open Design positions itself as an open-source, agent-oriented design workspace with templates, systems, and plugins. Its public repository shows an active ecosystem organized around reusable components and design workflows, so founders evaluating paid prompt libraries should compare not only visual quality but also the degree of control, cost, licensing, and maintenance they need. (github.com)

How to choose the right option

A paid hero library may be worthwhile when you need curated direction, polished assets, faster implementation, and commercial clarity. It is most useful when the supplied examples already resemble the level of craft and category relevance your brand needs.

An open-source or self-built route may be better when your team needs deep customization, wants to integrate a design system, is comfortable working in code, or needs to avoid recurring creative-tool costs. Open tools also make sense when the differentiator is not the initial landing page but a proprietary product experience that must evolve continuously.

Evaluate any resource against this checklist:

1. Visual specificity: Does it offer real art direction, or just familiar card-and-gradient variations?
2. Asset rights: Are photography, illustration, fonts, and video cleared for the intended commercial use?
3. Code quality: Is the code semantic, responsive, maintainable, and framework-compatible?
4. Performance: Are hero assets optimized, and can the template reach a healthy LCP target?
5. Accessibility: Are keyboard states, headings, contrast, motion preferences, and screen-reader behavior addressed?
6. Conversion fit: Does the template support your product’s sales motion, rather than merely looking impressive in a gallery?
7. Portability: Can you own, modify, and move the result without rebuilding it from scratch later?

A library can save hours, but it cannot decide what your product needs to say. A template is a starting point for judgment, not a substitute for it.

Practical workflow: from blank prompt to launch-ready hero

The fastest path is not prompt, generate, and publish. It is a short production workflow that separates strategy, design direction, implementation, and validation.

Step 1: Write the one-screen message

Before opening any AI tool, write the following in plain text:

• Audience: who is this page for?
• Pain or desire: what outcome matters now?
• Promise: what changes after using the product?
• Proof: why should the visitor believe it?
• Action: what is the lowest-friction next step?

If you cannot fit that logic into a screen, the design will have to carry too much explanatory weight.

Step 2: Assemble an asset pack

Collect the actual inputs: product screenshots, a short recording, customer logos with approval, approved fonts, a color palette, a logo, and two or three visual references. If no distinctive visual exists, create one intentionally—a product screen, a photographic shoot, a diagram, or an illustration system—rather than asking AI to manufacture a generic substitute.

Step 3: Prompt for two intentional directions

Ask for two clearly separated concepts, not ten cosmetic variations. For example, request an editorial asymmetrical concept and a product-first technical concept. Give each its own reference world and composition.

This makes comparison productive. You are choosing between strategies, not endlessly tuning the same undifferentiated default.

Step 4: Review against a conversion checklist

Use a small review group and ask them to answer without scrolling:

1. What does this product do?
2. Who is it for?
3. What would you click next?
4. What makes the claim believable?
5. What felt confusing, generic, or distracting?

Do not ask whether they “like” it first. Preference is useful, but clarity and trust come before taste.

Step 5: Test real implementation details

Inspect the page on Safari, Chrome, mobile browsers, slower connections, and keyboard-only navigation. Check that the pricing route, CTAs, forms, and browser-back behavior work. The community response to the original post is a reminder that these basics are publicly visible—and that they can outweigh a beautiful design concept.

Step 6: Measure after launch

Track hero CTA clicks, scroll depth, trial starts or demo requests, bounce behavior, mobile conversion, and page-speed data. A distinctive hero is not automatically a high-converting hero. Let user behavior refine the next version, but preserve a clear hypothesis about what changed and why.

What “less AI-looking” should actually mean

“Make it less AI-looking” is now common feedback, but it is too vague to be useful on its own. In practice, people usually mean one or more of the following:

• The design relies on overused visual defaults.
• The imagery has no relationship to the business.
• The hierarchy is technically balanced but emotionally flat.
• Every section has the same density and card treatment.
• The copy makes claims without proof or specificity.
• The page does not reveal a human decision, a brand point of view, or a real customer context.

The antidote is not necessarily maximalism. A quiet page can be highly distinctive. A minimal hero with a surprising crop, a specific product insight, a confident type decision, and one relevant proof point will generally outperform a busier page built from generic decorations.

The desired result is not “human-looking” in a sentimental sense. It is intentional-looking. Visitors should be able to sense that someone made choices for this particular company, audience, and conversion moment.

Conclusion: bring the opinion, not more adjectives

The useful takeaway from the r/SaaS discussion is not that prompt engineering alone turns anyone into an art director. It is that AI works better when founders stop treating creative direction as a vague feeling to be inferred.

Give the model a reference world. Tell it where the important elements belong. Supply an asset that gives the page a real focal point. State what must be avoided. Then judge the output against message clarity, proof, performance, and working product mechanics—not merely whether the latest version looks different from the last.

AI can dramatically reduce the cost of producing landing-page variations. It cannot remove the need for a point of view. The teams that get distinctive results will be the ones that use AI for execution speed while retaining ownership of the creative and commercial decisions that make a homepage worth remembering.

FAQ

What are AI website design prompts?

AI website design prompts are structured instructions used with AI coding or design tools to generate web pages, components, or visual concepts. Strong prompts include business context, hierarchy, references, layout, assets, constraints, and implementation requirements—not just style adjectives.

Why do AI-generated hero sections look so similar?

They often start with vague directions and no meaningful visual asset. When the creative brief leaves major choices unresolved, models tend to select common patterns from familiar landing pages, such as centered copy, gradient backgrounds, rounded cards, and generic dashboard visuals.

Should I use a background video in my hero section?

Only if it strengthens the story and can be delivered without harming usability or page speed. Use an optimized poster image, keep the video short and secondary to the message, respect reduced-motion preferences, and test performance on mobile networks.

How many design references should I include in a prompt?

Two or three complementary references are usually enough: one for category clarity, one for visual atmosphere, and optionally one for interaction or content hierarchy. Explain the qualities to borrow so the AI does not attempt a direct imitation.

Are paid hero-section libraries better than open-source templates?

Not automatically. Paid libraries can save time with curation, assets, and support, while open-source options can provide more flexibility and ownership. Compare licensing, code quality, performance, accessibility, integration needs, and whether the design supports your conversion goal.