Take Away:

Artificial Intelligence (AI) is becoming part of everything we do at Tag1, from performance testing to content workflows, as we continue to prove its value inside our own operations first. This post launches our AI content series, sharing how we’re applying AI in practice, what we’re learning along the way, and the principles guiding us to deliver business value without the hype.

Cutting Through the Artificial Intelligence Hype

AI can be fun, amazing, and sometimes seem almost magical - but it can also be hilarious, confusing, and downright sloppy. And it's moving faster than anything we've seen before, showing up everywhere. Every product, every headline, every boardroom conversation seems to go down that rabbit hole. And yet, for most organizations, it’s still not clear how to move from hype to meaningful adoption. Should you be experimenting? Investing? Waiting? The noise makes it hard to know what’s real, and what’s just marketing.

At Tag1, we’ve been here before. We’ve seen technology trends come and go. The difference with AI is that it isn’t just a tool; it’s a capability that cuts across everything we do. That’s why we’re all in. But “all in” doesn’t mean “all figured out”. It means committing to a process of testing, learning, and proving what really works.

What “All In” Really Means

When we say “all in,” we don’t mean chasing the latest demo or just bolting AI to a pitch deck. We mean something more deliberate: weaving applied AI into the way we work, the systems we build, and the clients and communities we support. Applied AI, for us, starts with testing inside our own operations first. We use our own processes as a testing ground, ensuring any AI recommendation comes with documented evidence of what works and what doesn't.

Our Guiding Principles for AI

Like any transformative technology, AI comes with risks. Security, privacy, and ethical concerns aren’t afterthoughts for us, they’re design constraints.

Our principles are simple:
  • Responsible by Default – Every tool, model, and data source is vetted before entering our workflows.
  • Enterprise-Ready – AI integrations must meet the same standards of scalability, reliability, and security as any system we deliver.
  • Open by Nature – We share what we learn with the open-source community, contributing tools and lessons back.
  • Human-Centered – AI should empower people, not replace them. These principles keep our adoption thoughtful, so our clients can innovate without taking on unnecessary risk.

Where Artificial Intelligence (AI) Is Making an Impact Today

We are already seeing tangible benefits from applying AI with our internal teams. A few examples of how our team is building momentum include:

  • Our Company-Wide AI Portal - A centralized hub where the entire company can access Tag1’s AI resources, including LLM models hosted on our own infrastructure, sharing insights and helping us make sure AI adoption is coordinated and we are all learning from each other.
  • Claude Max Accounts for Every Team Member - Providing everyone with access to premium AI models enables unlimited contributions to open source with Tag1-funded resources.
  • AI as a Development Partner: - Recently, AI tooling helped me improve Goose, our open-source load testing tool. (You can read more about that in an upcoming blog post.) Fabian Franz, our VP of Software Engineering, has had some game-changing experiences with AI reviewing code and refactoring entire files. Engineers across the team are using AI to accelerate development in powerful new ways. Stay tuned for future posts where we’ll share more of these success stories.

Looking Ahead

This is just the beginning. This series isn’t abstract, we’re already putting AI to work inside Tag1. Every member of our team is running hands-on experiments. Each internal project is a learning opportunity.

Some experiments have become new best practices. Others may be dead ends, and we’ll share those lessons too. Each step helps us separate hype from impact, to build a practical playbook that our clients and the community can apply to real-world enterprise environments.

We’re excited to keep exploring and sharing what we learn, and we hope you’ll follow along.

Stay tuned for the next post in the series, where we explore “AI as a Development Partner”. And if you're curious about how AI could help your team or project, reach out to us, we would love to chat.

This post is part of Tag1’s Applied AI series, where we share how we're using AI inside our own work before bringing it to clients. Our goal is to be transparent about what works, what doesn’t, and what we are still figuring out, so that together, we can build a more practical, responsible path for AI adoption.

Image by Ronald Carreño from Pixabay