The future of AI in software development

What is that problem that we're trying to solve and how can we leverage AI better to help solve the problem versus what do we do with AI?

Inbal Shani is discussing how AI coding tools can free up developers' time by reducing the portion of their workday spent actually writing code.

Most developers span less than 25, some say less than 20% of their time writing in code. So if we're able to give them half an hour back, one, they can write more code. Second, they can have a break and take a breath so we don't burn them out and they're more happy. Third, we give them more time for collaboration and creative thinking, so that sparks innovation.

If you try to structure innovation, you're losing that organic spark that is humanity. Imagine that someone say you have 15 minutes a day to be creative. I don't think it's the pull. So it's encouraging that thinking more than structured.

Junior developers, when they start, usually we expect them to be able to write simple code. But if now there is an AI system that is helping them writing code, they can spend more time from the get-go understanding the system, understanding the environment that they're building, or understanding that product that they're building, which today they don't have time because they're still learning how to code.

Copilot is a copilot. It's not a pilot. You still need the human in the loop.

The design philosophy for Copilot is very much aligned with the working backwards concept. It's really putting yourself in the shoes of your customers and figuring out what is it that they need, how is that experience going to work for them? If it's an extra tool and if you need to ask for it and if you need to ask for it or if you need to wait for it, then developers will not adopt it.

Time is not quantifiable as a success metrics because you can write really bad code really fast.

We are in a world that there are no right metrics. There is no one metric to rule them all. It's a combination of the things that you're looking to measure out of adopting AI.

Instead of time, can we talk about time to value? So from the moment you put a developer on a task, how long did it take you until you realize the full potential or the full value of that, if it's generating revenue, if it's in adoption, if it's time to market?

The role of the chief product officer is so broad. You're not just the head of products. They need to have a business thinking. They need to understand their go-to market strategy. They need to understand the sales play. They need to understand how engineering are building products.

There are two elements for that. One is having the right people with the right mindset on the team, allowing them and giving them the bandwidth and freedom to innovate. And the second thing is that we're focusing on making things real. So we're not keeping them far or in disconnect from the product and engineering.