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From Design to a Shipped Product. Where AI Worked (and Where It Didn’t)

While developing Audio Radar 2.0 with AirDrop Gaming, we used AI-assisted tools to support parts of the product development process. Some helped the team move faster. Some created new problems to solve. At Tech Week Grand Rapids, we’re sharing what held up, what didn’t, and what we’d do differently next time.

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Digital product design always involves a translation, designers create interfaces and mock-up workflows, while developers translate those ideas into working code. Many details can be lost in translation. What if AI could close the gap?

We wanted to find out, so we partnered with AirDrop Gaming to develop their product, Audio Radar 2.0.

Audio Radar turns game audio into directional light around the screen, helping players see the sound of footsteps, gunfire, flanks, and other audio cues instead of relying on sound alone. Audio Radar 2.0 is the next generation of that technology.

While developing Audio Radar 2.0 with AirDrop Gaming, we had a chance to see how the latest AI tools are rewriting the digital product development process.

Not in a demo or a prototype. In a real product, with real customers, physical hardware, technical constraints, accessibility needs, and a deadline.

Tim Murphy and the AirDrop Gaming team brought years of understanding of the product, the technology behind it, and the community it serves. Nextpoint Studio brought product strategy, user research, UX, digital design, and software development.

As the team moved from a defined experience into implementation, AI-assisted tools became one more part of the workflow.

In some cases, AI helped us move faster. In others, it gave us outputs that looked convincing but missed the mark entirely. That gap became one of the most insightful aspects of the project.

How To Stay Human-First with AI, Without Giving Up Efficiency

On September 15, Nextpoint founder Danny Gaydou and AirDrop Gaming founder Tim Murphy will walk through the project at Tech Week Grand Rapids.

They’ll share where AI-assisted tools genuinely helped the team move faster, where the output broke down, and what the project taught us about using these tools inside a real product development process.

If you've seen enough AI demos and want to hear about an actual shipped software and hardware product, join us to learn more.

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