- Generative AI is turning people that don’t know how to code into coders, and software engineers into software engineers with 1000x the attitude
- GPT-4 is no longer your copilot, it is now your captain as it builds the app your worked 3 weeks on in just 30 minutes
- Developers are already thinking about new programming languages designed to work with large language models
- It turns out that the AI can be pushed to role-play as an expert, explain its reasoning, and/or self-plan to massively improve the generated output
- It also turns out that the AI can create imaginary worlds that follow rigid rules: like when it pretends to be a Linux terminal
- It also turns out that you can use AI to automatically correct bugs in your mediocre code, creating a “self-healing” program
- Meanwhile, somebody managed to replace the brain of Siri with GPT-3 and the answers you get, finally, don’t cause you fits of anger
- The next step, as shown by Meta AI, is an AI that can learn what’s the best API to call to achieve the goal indicated in your prompt
- The next-next step is replacing all legacy backends like databases with a large language model.
Alright. Time to talk about the impact of AI on software development.
This is a theme I’m especially close to because I’ve spent the last 13 months of my past life (when I was responsible for the business and product strategy of the automation business in Red Hat) on it.
During that experience, I worked side by side with an IBM Fellow (a rare privilege), VP, and Chief of Research at IBM Research. This person is also the former CTO of IBM Watson, the AI that beat humans in the TV show Jeopardy in 2011. An even rarer privilege.
Five years ago, way before GitHub Copilot was a thing and the entire world would go crazy for ChatGPT, I started thinking about using machine learning to generate automation workflows for Ansible, the open source automation software that Red Hat acquired in 2015 (I was part of the acquisition team, too).
Struggling to find the expertise and support within Red Hat at that time, I shelved the idea for 3 years. However, thanks to IBM’s acquisition of Red Hat in 2019, I had a chance to convince this Chief of Research in IBM Research to pursue the opportunity.
The idea was received with enthusiasm and, as result, I had the privilege to lead a team of brilliant machine learning engineers that helped me bring to life a 5 years old idea as what the world has known as Project Wisdom.
1/ Finally, I can unveil *a glimpse* of the project I've been working on for over 1 year with @IBMResearch: Wisdom.
— Alessandro Perilli ✍️ Synthetic Work 🇺🇦 (@giano) October 18, 2022
Then, I left Red Hat and now, I’m here telling you all about how AI is changing the world of software development.
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