Fluent, Inc. Innovation, Technology & Agility

What is the unique story that you feel your company has with AI? If you were writing about it, what would the title of your blog be?
The title would be "Aim High," and it would tell the story of a small, focused tech team looking to make a big impact in the market. From optimizing ad targeting to automating internal workflows, we treat AI as a tool for leverage, not just a buzzword for marketing material.

Side projects spark platform improvements. R&D isn't siloed — it’s woven into our culture. We aim high by thinking small: fast iterations, scrappy testing and a strong feedback loop between business outcomes and AI capabilities. That’s how we build smarter, faster and with fewer resources than larger players.

What are you most excited about in the field of AI right now?
Lately, I’ve been diving deep into the world of AI agents — systems designed with distinct roles, responsibilities and the ability to operate semi-independently. The idea that these agents can go beyond simple instruction-following to become collaborative, task-oriented partners is incredibly exciting. These agents can plan, prioritize and interact with tools or even each other to achieve goals with minimal human input.

What fascinates me most is the democratizing potential of this shift. Until recently, innovation at scale has often been limited to organizations with massive resources and teams. But autonomous AI agents are changing that equation. They offer leverage for small teams, solo entrepreneurs and startups, allowing them to punch well above their weight.

Imagine a two-person team managing what used to take 10 — handling customer support, internal operations, content creation, data analysis and even product research — simultaneously, thanks to a constellation of smart agents. This newfound operational efficiency doesn't just reduce costs; it creates more space for creativity, experimentation and R&D.

How do you learn from one another and collaborate?
The most successful teams I’ve worked with are built on strong relationships and open communication. Learning thrives when people feel safe to share ideas, ask questions and challenge norms — something that starts with trust.

On our team, collaborative learning often happens informally: someone drops a podcast in Slack, shares a tool they’re testing or flags a piece of code worth rethinking. These small moments spark deeper conversations and sometimes lead to major improvements.

We’ve seen side projects and experiments directly influence our roadmap — whether it’s a codebase refactor, a new ML service or a shift in architecture to support scale. The person who brings it forward often leads the implementation, which builds real ownership and confidence.

We also run regular “lunch and learn” sessions where anyone can demo a tool, break down a concept or get feedback on an idea.