Transcript
At Slingshot, we do a lot of new greenfield projects. We always start with market research, user interviews, and really understanding the problem we’re trying to solve.
Before, that was a pretty manual process. We’d have interviews, take a lot of physical notes, record them, and then have to relisten. Notes would get turned into stickies on a board, and we’d pull out features that made the most sense. From there, we’d start sketching them out, build the full design in Figma, make it picture-perfect, and then hand it off to a developer.
AI has really transformed how we build products. From the start, we’re able to research more robustly and quickly. When we get into user interviews, we can collaborate with our LLMs to understand the best approaches for how we’re running those conversations. That thinking ability has really changed the kind of conversations we have.
We use AI tools to record interviews, centralize the recordings, and look for patterns. We can pull out consistent insights and turn those into features. Of course, we still use our human brains to guide creative vision and direction, but AI helps us lean into that process.
Once we have a feature set, we collaborate as a product team. We run those conversations again through LLMs to refine and understand what the features look like, then move them right into our building tools. We’ll use platforms like Lovable or Cursor to get the first pass of what we’re building, and then continue using those tools to build out the front end.
Now, roles are blending more. The product person is also the designer, the designer is also the developer, and the developer is also thinking about product. We’re all becoming super technical assets. I don’t have to spend as much time manually typing out every detail of my vision, because I can actually get in there and build the thing.
Using these tools, I can take the first requirements and iterate myself. I don’t have to run everything through layers of design. Design can come in behind me to refine UX/UI, while dev starts on the backend.
One example is an app we’re building right now. I had an idea to hold down a part of the screen and have a box-breathing exercise appear. Normally, that kind of feature might end up dead in the backlog. But since I could just implement it myself in 15 minutes, it became a really cool part of the product.
AI gives us the opportunity to use it either as an efficiency tool or as a tool to elevate our thinking. It’s not just about making things faster or cheaper. It’s about capitalizing on the time and energy freed up to build better, more interesting products.
AI has absolutely reshaped what my role looks like. With AI, I’m able to think more creatively about products and features. I’m finding that with AI in product development, we can go further, faster, and ultimately deliver better products.
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Edited by: Savannah Cherry
Savannah is our one-woman marketing department. She posts, writes, and creates all things Slingshot. While she may not be making software for you, she does have a minor in Computer Information Systems. We’d call her the opposite of a procrastinator: she can’t rest until all her work is done. She loves playing her switch and meal-prepping.
Expert: Sarah Bhatia
Sarah Bhatia brings people together. In her decade plus of product and product-adjacent experience, her focus has been on cross-functional collaboration, asking lots of questions, and getting big results. She excels at strategy development, and getting the right brains in the room to solve big problems. Sarah would describe herself as a daredevil, because she’s not afraid to ask “dumb“ questions, get smart answers, and take (calculated) risks.
