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Prompt Engineering: The Future of AI-Driven Development
AI won’t replace software developers. However, the required skills are going to change drastically
ChatGPT and other generative AI services have been around for less than a year and have already taken the world over by storm. We see more and more use cases popping up every day on social media showing how these services solve a cool new problem. It’s thrilling to see the surge of innovation pop up seemingly overnight.
A couple of weeks ago, I wrote an article about how ChatGPT changed the way I write software. The article discussed some new use cases available at our fingertips and shared a couple of pragmatic examples to get your gears turning.
Today we’re going to take it a step further. We will discuss how you can write software to take advantage of services like ChatGPT. To do that, let’s walk through an example: an unanswered question chatbot.
What We’re Building
Whenever you go into a busy livestream or popular chatroom, hundreds of messages fly across the screen every minute. It’s impossible to carry on a conversation, let alone get an answer to a question. Moderators do a decent job wading through questions, but that’s a manual task relying on their judgment and ability to parse through dozens of messages a second. Questions get missed, and wrong answers are given… a lot.
I want to fix that with an AI-powered bot that answers these questions. We’ll call it the “no question left behind” bot. Here are the requirements:
- Answer any questions that have been asked but received no answer
- Answer any questions that have been asked but received an incorrect answer
- Tag the person who asked the unanswered or incorrect question in the response
- Do not respond to questions that were answered correctly, either by a human or the bot
- Run automatically on a one-minute interval
Before the introduction of generative AI, this project would have been next to impossible to build. But with proper prompt engineering, we can build it in just a couple of hours.
