The 4 Big Challenges of building AI products
A few days ago, I was speaking at an event about how to move from using ChatGPT at a personal level to implementing AI-powered technical solutions for teams and companies. We covered everything from prompt engineering and fine-tuning to agents and function calling. One of the questions from the audience stood up to me, even though it was one I should have expected: “How long does it take to get an AI-powered feature into production?”
In many ways, integrating AI into features can be incredibly easy. With recent progress, leveraging a state-of-the-art LLM can be as simple as making an API call. The entry barriers to use and integrate AI are now really low. There is a big but though. Getting an AI feature into production while accounting for all risks linked with this new technology can be a real challenge.
And that’s the paradox: AI feels easier and more accessible than ever, but its open-ended (free input / free output…
