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Michaela Santl2 min read

Cursor AI meets design-aware context of knowis Cloud Solution Workbench

Cursor AI meets design-aware context of knowis Cloud Solution Workbench
3:04
We gave Cursor, a popular GenAI Coding Assistant, a design file created with our knowis’ Workbench. Here is what happened.

AI is changing everything - including how we build software. Coding assistants are everywhere, and the hype is real. But so are the concerns:

  • Will it scale?
  • Can I trust the output?
  • What happens when things go wrong?

We get it. We are a software company ourselves and like everyone else: we are under pressure to deliver more, faster and smarter.

So we asked us a simple question: what if we could make AI coding assistants "safe by design"?

knowis workbench meets coding assistant

In our workbench, architecture and design are not an afterthoughts. They are executable assets packaged as living design files that define: what gets built, how it works and why it matters.
From ideation to architecture to design specs, we align early and keep everything versioned and in sync with Git repo, pipelines and stacks.

So we took Cursor - one of the most used coding assistants these days - to run a hackathon. We didn’t write user stories. We didn’t hand over vague requirements. Instead, we fed the coding assistant the structured design artifacts generated from the knowis Workbench. Simple.

The Result? It worked well:

  • Code generation was fast, focused, and aligned with our intent.
  • Architecture guardrails stayed intact, even with rapid iterations.
  • Review and testing? Easier than ever.

Want to know how it works? Have a free trial or book a demo.

When an AI Coding Assistant meets design-aware context

We know GenAI is changing everything, including how we build software. Coding assistants are everywhere, and the hype is real. But so are the concerns.

  •  Will it scale? 
  •  Can I trust the output? 
  •  What happens when things go wrong? 

We are a software company ourselves and like everyone else: we are under pressure to deliver more, faster and smarter. Our simple and beautiful idea is: using knowis Cloud Solution Workbench, we make AI coding assistants "safe by design".

"Shift left" matters

Shifting the (investment) focus to the "left" of the software development process doesn’t just mean testing earlier. It means thinking, designing earlier. Better. Because AI accelerates code but architecture and design defines what gets built.

Conclusion and Recommendation

In a few words: you don’t need to fear coding assistants. You need to feed them better inputs. Learn more about knowis Cloud Solution Workbench and our vision of software development acceleration.

Frequently Asked Questions about this Blog

How does the Workbench may complement a Coding Assistant? The Workbench fills the gap a typical Coding Assistant doesn’t cover: it provides architecture- and design-aware guidance, preserves business context and connects these to the code generation process. Together they ensure the right code gets generated in the right place with the right context.
What benefits could teams gain by using Workbench and a Coding Assistant?

By combining the two tools, teams could:

  • better align architecture/design with implementation.

  • reduce repetitive coding tasks.

  • maintain coherence between business intent, design and deployed code leading to higher productivity.

How does it affect the current dev workflow? There is no changes in the overall flow and no risk associated. Workbench is designed to integrate with existing toolchains. When paired with a Coding Assistant, this simply means the generated code is aligned with the architecture context / intend that the Workbench manages.

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Michaela Santl
As a Senior Product Owner, Michaela Santl is responsible for prioritizing and shaping product features based on customer value. With over a decade of experience at knowis, she brings deep technical expertise and a strong user perspective to the table. Previously leading a development team and working as a software architect, she now drives the continuous evolution of the product.
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