Why I Built Chat Agency AI

After spending over two decades in product development—from creating video games at Pixar and Hasbro to leading UX and Content Strategy for Cisco.com's digital marketing team—I've gained a crucial insight: innovative ideas aren’t about reinventing the wheel. They are about understanding how to orchestrate proven building blocks in novel ways.

The AI Adoption Challenge

In early 2024, I witnessed something fascinating. Enterprise organizations were rapidly introducing Large Language Models (LLMs) from companies like OpenAI and Anthropic, driven by a fear of falling behind competitors. However, these powerful tools weren't seeing the adoption rates companies hoped for. Their response was predictable: invest millions in training to teach employees about LLM capabilities and prompt engineering.

But I saw the challenge differently. The slow adoption wasn't just about knowledge gaps—it stemmed from two fundamental issues:

1. Most employees lack the decades of experience needed to confidently delegate tasks to an AI system that appears to work autonomously.

2. Without deep technical expertise, choosing the right AI platform and crafting effective prompts becomes an overwhelming challenge.

The start of Chat Agency AI

Chat Agency AI emerged as a solution to bridge these gaps, built on four core principles:

1. Empowering Innovators

LLMs have been trained on vast repositories of human knowledge—far more examples and patterns than any individual or team could accumulate in a lifetime. This makes them ideal accelerators for innovation, helping teams rapidly prototype and iterate on ideas by leveraging this collective knowledge.

2. Preserving Human Intuition

While AI excels at pattern recognition and data processing, it lacks what Steve Jobs famously called "taste"—that uniquely human ability to make intuitive judgments about quality and appeal. That's why Chat Agency maintains human oversight rather than pursuing full automation. Our goal isn't to replace human creativity but to amplify it.

3. Leveraging Multiple AI Models

No single model excels at everything. To address this limitation, we developed a custom framework that orchestrates multiple AI models—both enterprise and open-source—working together to produce better results.

4. Building on Experience

Perhaps most crucially, I partnered with my cofounder Jeff Maling , bringing his 30+ years of consulting and product expertise into the platform. This collaboration allowed us to embed our combined knowledge directly into the system, eliminating the need for users to master prompt engineering. Instead, they can focus on what matters most: their innovative ideas.

Looking Forward

We're thrilled to officially launch Chat Agency AI. This platform represents more than just another AI tool—it's a bridge between human creativity and artificial intelligence, designed to amplify rather than replace human capabilities.

We're committed to evolving alongside our customers, welcoming feedback and continuously improving the experience for you and your teams. At its core, Chat Agency AI isn't about technology—it's about tools to empower people to innovate more effectively.

Give it a try at https://www.chatagency.ai