Short excerpt from a YouTube video arguing that building a reliable custom AI agent requires an AI engineer. The speaker emphasizes practical engineering concerns: agent architecture, model inventory, inference cost, nondeterminism, benchmarking, observability, and tracking, and warns against assuming prompting alone suffices.
Chapters
When it comes to custom agent development, there's a key reality that I think a lot of people aren't looking at, and that is that you still need an AI engineer. And I think there are a lot of people that think you can just magically, you know, one shot, prompt all this stuff and it works. But what I've found is you do really want to work with an expert who understands the agent architecture, understands the model inventory, understands the cost of running inference, like up and down the stack, understands the non determinism and how you have benchmarks and observability and tracking. And so there's just like a lot there. And so the opportunity is really big. But it's important to not be naive and think that you can kind of vibe code your way into having a custom agent.