Turning abstract product power into tangible value

TL;DR

Dust’s homepage solves the “blank canvas” problem for AI agent platforms by showing specific, instantly relatable use cases for sales, marketing, and support teams, rather than abstract technical potential.

By leading with concrete examples and workflows, Dust makes its flexible tool feel relevant and easy to grasp for every buyer, reducing cognitive load and letting prospects see themselves in the product right away.

What makes Dust’s homepage stand out

The unique challenge for AI agent platforms is that they’re “blank canvas” tools.

Traditional SaaS platforms do specific tasks well. They have clear use cases built in. Some handle invoicing, others manage inventory. Even unaware buyers can get a grasp of what these tools do.

Things are different with AI agent platforms. Unlike traditional SaaS, they are programming environments that users can configure to do almost anything. They provide the underlying infrastructure and the ability to build AI agents that can connect to any data source, use any tools, automate any workflows. It’s incredibly powerful, but it’s also incredibly abstract.

When prospects visit SaaS homepages, they’re evaluating a finished product. When they visit AI agent platform homepages, they’re evaluating potential, what they can build if they put in the work to configure it.

This creates unique messaging challenges:

• Buyers need not only to understand the product, but also to imagine what they’d build with it.
• The value isn’t in the platform itself, but in the specific agents they’d create.
• Success stories aren’t about using the product, but about what customers built on top of it.

While SaaS companies show use cases by demonstrating their existing product capabilities, AI agent platforms need to show use cases by demonstrating what’s possible to build. It’s the difference between showing a finished house and showing construction materials.

That’s why I love the simple solution Dust uses for its homepage messaging.

Instead of leading with generic platform capabilities, Dust presents its multi-purpose AI agent platform through specific use cases that prospects immediately recognize.

Dust offers a tool that lets people to build AI agents for almost any kind of repetitive task. Anyone, from operations and HR to product management, could use Dust for almost any workflow they need.

But instead of introducing this tool as a universal solution to … everything, Dust’s homepage presents it through specific use cases focused on Sales, Marketing, and Customer Support teams. Each team can see different scenarios and concrete AI agents they could build.

This approach works because:

• It reduces cognitive load and abstraction.
  • The homepage doesn’t just talk about AI agents. It shows exactly how sales teams, marketing teams, and support teams use these agents for recognizable tasks.
• Specific use cases replace abstract features
  • Each section demonstrates concrete workflows like “Write on-brand content in minutes,” rather than “Build custom AI agents.”
• Multiple entry points for different stakeholders
  • A sales person immediately sees sales use cases, while a support manager sees support workflows. No translation required.

The AI agent tool capabilities are contextualized through a lens different prospect types already understand. There’s no need to “figure out how this applies to me.”

And that’s exactly what AI buyers want:

• Immediate relevance: Does this solve problems I recognize?
• Cognitive ease: Can I quickly understand what this tool does?
• Fit: Is it built for people like me?

By leading with specific use cases, Dust removes the translation work for buyers. It shows how multi-purpose AI agent tools should be presented: specific, relevant, and immediately understandable.

When to apply this approach

• When your AI agent platform is highly flexible and covers multiple purposes.
• When buyers need to see finished “examples,” not just technical potential.
• When your tool is a “blank canvas” and buyers must imagine their own workflows.
• When prospects repeatedly ask, “But how would we actually use this AI tool?”