Frontend teams often get bogged down with repetitive, low-value work — spinning up new pages, wiring up forms, and fixing small design inconsistencies over and over again.
By introducing Cursor, paired with Figma MCP integration and a small set of internal rules, we were able to transform that process. The results were dramatic: faster delivery, cleaner code, fewer QA cycles, and developers spending more time solving real problems instead of reworking boilerplate.
This isn’t about replacing developers. It’s about removing friction so teams can build products faster and more consistently, without cutting corners on quality or security.
If you’ve ever built a complex application — a customer portal, a multi-flow dashboard, an enterprise tool — you know how much time is lost on setup and repetition.
Every new page follows a familiar checklist:
Individually, none of these steps are hard. But together, they slow projects down — especially when deadlines are aggressive and teams are working across multiple features at once.
Automation has already transformed areas like testing and deployment. Frontend development, though, remained largely manual. That’s where we saw an opportunity for AI to make a real difference.
AI tools don’t just “know” how your team works. Out of the box, they’ll make guesses — and often the wrong ones.
The turning point for us was realizing that structure is everything.
We built a lightweight rules file that acts like a shared brain for Cursor. It explains how we build our frontends, including:
With that context in place, Alexey Shulga, one of our frontend engineers, can prompt Cursor with something as simple as:
“Create a Preferences page with company selector, description, and Submit.”
And within moments, Cursor generates:
The output is ready for review immediately — no mystery styles, no one-off components, no “we’ll fix it later” cleanup.
For developers, this means far less time spent on grunt work.
For leaders, it means faster timelines and fewer surprises late in the release cycle.
Before Figma MCP, our workflow relied on screenshots or manual inspection of designs. That meant a lot of back-and-forth — QA catching spacing issues, mismatched components, and minor inconsistencies that added up to major delays.
Now, Cursor doesn’t just look at designs — it reads the actual design data.
Figma MCP gives Cursor direct access to:
When Cursor generates code, it matches the design system perfectly from the start. Designers stay in their flow, developers focus on logic and performance, and QA isn’t stuck chasing down pixel errors.
This one change alone has cut weeks out of the design-to-development cycle.
AI-generated code isn’t something you just take and ship. It has to be part of the process, not a shortcut.
Here’s how we manage it:
This creates a feedback loop. The more the system learns, the more predictable the output becomes, and the less cleanup is needed over time.
The goal isn’t to trust the AI blindly — it’s to collaborate with it effectively.
Moving faster doesn’t mean taking risks with client data or intellectual property.
Our approach to AI is built on strict security practices:
AI is a tool, but governance is non-negotiable.
Once we fully integrated Cursor and Figma MCP, the difference was obvious:
These aren’t abstract metrics. They translate directly into faster releases, lower costs, and better team morale.
For engineering leaders — CTOs, VPs, product owners — this approach means projects stay on schedule, budgets stay predictable, and releases are cleaner from day one.
For senior developers, it means fewer repetitive tasks and more time spent solving interesting problems.
And for QA, it means higher-quality code landing in testing earlier, with fewer surprises.
The end result is a team that delivers faster, calmer, and with higher confidence.
This isn’t about adopting AI because it’s trendy. It’s about identifying specific, repeatable pain points and applying AI carefully to eliminate them.
At Forte Group, we help teams implement this workflow step by step:
If you’re ready to see what this could look like for your team, let’s start a conversation.