Inside Rival: How We Use What We Build
This blog is part of Inside Rival, a series where our team shares how we use Rival in our everyday work. From favorite tools to AI agents and automations, we're showing you what we're building, how we're using it and what we've learned along the way.
I'm surrounded by some of the smartest developers in AI. People with impressive technical backgrounds who spend their days building technology I couldn't begin to code myself.
And then there's me. The marketing girl at Rival. I can build a go-to-market strategy, position a brand, and tell you exactly where AI could make a business more efficient. But ask me to write a line of code? Not happening.
You'd think working alongside people who build AI every day would mean I've got this whole AI thing figured out. But even with a front-row seat to the industry, keeping up can feel like a full-time job.
Every day there's a new platform, a new agent, a new model, or another LinkedIn post about how someone built an entire business with AI over the weekend. Meanwhile, I'm still trying to figure out which of the 15 tools I bookmarked last week are actually worth using.
And I know I'm not the only one.
Somewhere along the way, we went from learning how to prompt ChatGPT to being expected to build agents, connect workflows, and automate everything ourselves. Which got me thinking. Why are we all spending so much time learning how to build AI when some pretty brilliant people have already done the hard part?
Someone Already Built It. Why Am I Starting From Scratch?
One of the perks of working at Rival is seeing what goes into building AI solutions. And the more I'm exposed to that process, the more I realize I don't necessarily need to understand how to build the technology to get value from it. That's what I appreciate about Rival's Marketplace.
Instead of starting with a blank canvas, I can explore AI functions that developers have already built. I can evaluate what they do, think about how they might fit into my work, and focus on solving a problem rather than figuring out how to engineer the solution.
And with Rival Rooms, I can interact directly with AI agents through conversation. I can explain what I'm trying to accomplish, ask questions, provide direction, and work through a task without needing to understand the code behind it. For someone who spends her days in brand and marketing strategy, that feels pretty natural.
It's also given me a level of confidence with AI that I didn't expect to have without a technical background. I'm not suddenly going to start debating technical architecture with our developers. But I can recognize opportunities to use AI, understand what capabilities are available, and actually put them to work.
And isn't that what we're all trying to do?
I Don't Need Another 15 AI Tabs Open.
I've worked on marketing teams where it felt like we had a different tool for every part of the job. I'd have one tab open for research and analysis, another for strategy, another for copywriting, and probably a few more for whatever else I was working on that day. Each tool promised to make something easier, and individually, some of them did.
But getting everything to work together? That was a different story.
I'd spend time moving information between platforms, repeating context, reviewing outputs, and trying to piece everything together into something we could actually execute. And when you're working across a team, that fragmentation becomes even more frustrating. Suddenly, the technology that's supposed to save you time is creating an entirely new layer of work.
I think that's also where a lot of the pressure to "keep up with AI" comes from. When you're constantly learning another platform or figuring out how to connect multiple solutions, it's easy to feel like you're falling behind. Like everyone else has somehow figured out how to make AI work for them, and you're still trying to get your tools to cooperate.
But maybe we're looking at the problem the wrong way. Maybe we're not falling behind. Maybe AI solutions haven't been built around how most of us actually work.
For a long time, so much of the market has focused on what individual AI tools can do, rather than how those capabilities fit into a bigger picture. We have no shortage of impressive technology. What we're missing is a simpler way to put it all to work.
The Rival platform gives me a central place to discover functions that developers have already built, while Rooms lets me interact directly with AI agents through conversation. Instead of starting from scratch with every new task, I have a more approachable way to explore capabilities and get work moving.
It's not that every challenge disappears or that one platform can do absolutely everything. But the experience feels less like managing a collection of disconnected tools and more like actually working with AI.
And that's a pretty meaningful difference.
Maybe We're Thinking About AI Expertise All Wrong.
I think we've created this expectation that being good at AI means knowing how to build with it. And if you're a developer, that makes sense. But for the rest of us, I think being good at AI can mean something different.
Knowing how to identify a problem worth solving. Knowing what questions to ask. Understanding which capabilities can help. And knowing how to take what AI produces and turn it into something useful. That's where my perspective has shifted.
Working at Rival has shown me just how much technical expertise goes into building AI, but using Rival has also shown me how much I can accomplish without having that same expertise myself. I can leave the building to people who know how to build and focus on what I know how to do. So if you're like me, interested in AI but stuck on the hamster wheel of trying to learn every new tool, here's my advice.
Stop trying to learn everything at once. Start with a problem you want to solve. Explore the functions already available in Rival's Marketplace. Go into Rival Rooms, talk to an agent, and see what you can accomplish. You might be surprised by how much you can do without ever touching a line of code. I still can't code. I still ask our developers plenty of questions. And I'm still learning something new about AI almost every day. But I'm starting to feel like an AI expert in my own right.
Not because I know how to build it. Because I know how to use it.
About the Author
Lauren is the Manager of Brand & Strategic Marketing at Rival, where she focuses on brand positioning, go-to-market strategy, and connecting emerging AI technology to real business challenges. Working alongside Rival's developers gives her a unique perspective on both the possibilities of AI and the challenges of making it accessible. She brings a strategic marketer's perspective to an industry often dominated by technical conversations, with a focus on making AI practical, approachable, and genuinely useful.