I used GenAI for a year - and here's what I learned

This past year, I went from exploring generative AI to building real-world solutions. Along the way, I learned that success didn’t come from prompts alone—it came from clarity. There were two questions that made all the difference:

• What kind of AI agent am I building—and what do I want it to do?
• What knowledge assets do I already have to train the agent?

Whether I was creating agents for nonprofits, healthcare, or internal operations, these questions kept me focused on value, not hype. And when the answers were strong, the agents delivered real outcomes—faster service, lower costs, better experiences.

But here’s the hardest part: GenAI doesn’t just require tools—it requires time, effort, and passion. I had to become a learner again. To roll up my sleeves, experiment, fail, adjust, and build again. That investment has been worth it—because now I see what’s possible.

If you’re thinking about diving into GenAI, start with those two questions. Clarity beats complexity.

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