Scott Dietzen

A couple of different points to make. You know, AIs have gotten good at making incremental changes, at least when they understand customer software. So first and the biggest limitation that these AIs have today, They really don't understand anything about your code base.

If you take GitHub Copilot, for example, it's like a fresh college graduate understands some programming languages and algorithms, but doesn't understand what you're trying to do. And as a result of that, something like two thirds of the community on average drops off of the product, especially the expert developers. Augment is different.

We use retrieval augmented generation to deeply mine the knowledge that's inherent inside your code base. So we are a co-pilot that is an expert and that can help you navigate the code base, help you find issues and fix them and resolve them over time much more quickly than you can trying to tutor up a novice on your software.

I think it was a great 1.0 product. And I think they've done a huge service in promoting AI. But I think the game has changed. We have moved from AIs that are new college graduates to in effect AIs that are now among the best developers in your code base. And that difference is a profound one for software engineering in particular.

You know, if you're writing a new application from scratch, you want a web page that'll play tic-tac-toe, piece of cake to crank that out. But if you're looking at, you know, a tens of millions of line code base, like many of our customers, Lemonade is one of them. I mean, 10 million line monorepo as they move engineers inside and around that code base and hire new engineers.

Just the workload on senior developers to mentor engineers. people into areas of the code base they're not familiar with is hugely painful. An AI that knows the answer and is available seven by 24, you don't have to interrupt anybody and can help coach you through whatever you're trying to work on is hugely empowering to an engineer working on unfamiliar code.

A couple of different points to make. You know, AIs have gotten good at making incremental changes, at least when they understand customer software. So first and the biggest limitation that these AIs have today, They really don't understand anything about your code base.

If you take GitHub Copilot, for example, it's like a fresh college graduate understands some programming languages and algorithms, but doesn't understand what you're trying to do. And as a result of that, something like two thirds of the community on average drops off of the product, especially the expert developers. Augment is different.

We use retrieval augmented generation to deeply mine the knowledge that's inherent inside your code base. So we are a copilot that is an expert and that can help you navigate the code base, help you find issues and fix them and resolve them over time much more quickly than you can trying to tutor up a novice on your software.

I think it was a great 1.0 product, and I think they've done a huge service in promoting AI. But I think the game has changed. We have moved from AIs that are new college graduates to, in effect, AIs that are now among the best developers in your code base. And that difference is a profound one for software engineering in particular.

You know, if you're writing a new application from scratch, you want a web page that'll play tic-tac-toe, piece of cake to crank that out. But if you're looking at, you know, a tens of millions of line code base, like many of our customers, Lemonade is one of them. I mean, 10 million line monorepo as they move engineers inside and around that code base and hire new engineers.

Just the workload on senior developers to mentor engineers. people into areas of the code base they're not familiar with is hugely painful. An AI that knows the answer and is available seven by 24, you don't have to interrupt anybody and can help coach you through whatever you're trying to work on is hugely empowering to an engineer working on unfamiliar code.

And as a result of that, something like two thirds of the community on average drops off of the product, especially the expert developers. Augment is different. We use retrieval augmented generation to deeply mine the knowledge that's inherent inside your code base.

So we are a copilot that is an expert and that can help you navigate the code base, help you find issues and fix them and resolve them over time much more quickly than you can trying to tutor up a novice on your software.

So you're often compared to GitHub Copilot. I got to imagine that you have a hot take. What's your hot take on GitHub Copilot?

I think it was a great 1.0 product. And I think they've done a huge service in promoting AI. But I think the game has changed. We have moved from AIs that are new college graduates to, in effect, AIs that are now among the best developers in your code base. And that difference is a profound one for software engineering in particular.

You know, if you're writing a new application from scratch, you want a web page that'll play tic-tac-toe, piece of cake to crank that out. But if you're looking at, you know, a tens of millions of line code base, like many of our customers, Lemonade is one of them. I mean, 10 million line monorepo.

As they move engineers inside and around that code base and hire new engineers, just the workload on senior developers to mentor engineers. people into areas of the code base they're not familiar with is hugely painful.

An AI that knows the answer and is available seven by 24, you don't have to interrupt anybody and can help coach you through whatever you're trying to work on is hugely empowering to an engineer working in unfamiliar code.

Very cool. Well, friends, Augment Code is developer AI that uses deep understanding of your large code base and how you build software to deliver personalized code suggestions and insights. A good next step is to go to AugmentCode.com. That's A-U-G-M-E-N-T-C-O-D-E.com. Request a free trial, contact sales, or if you're an open source project, Augment is free to you to use.

Okay, friends, I'm here in the breaks with Annie Sexton over at Fly. Annie, you know we use Fly here at ChangeLog. We love Fly. It is such an awesome platform and we love building on it. But for those who don't know much about Fly, what's special about building on Fly?

So we use Tigress here at Changelog. Are they built on top of Fly? Is this one of those examples of being able to build on Fly?

Learn more at AugmentCode.com. That's A-U-G-M-E-N-T-C-O-D-E.com. AugmentCode.com.

Very cool. Thanks, Annie. So Fly has everything you need. Over 3 million applications, including ours here at ChangeLog, multiple applications, have launched on Fly. Boosted by global anti-cast load balancing, zero configuration private networking, hardware isolation, instant WireGuard VPN connections, push-button deployments that scale to thousands of instances. It's all there for you right now.

Deploy your app in five minutes. Go to fly.io. Again, fly.io.

Well, friends, before the show, I am here with a new friend of mine, Scott Dietzen, CEO of Augment Code. I'm excited about this. Augment taps into your team's collective knowledge, your code base, your documentation, your dependencies. It is the most context-aware developer AI, so you won't just code faster, you'll also build smarter. It's an ask-me-anything-for-your-code.

It's your deep-thinking buddy. It's your Stan Flo antidote. Okay, Scott. So for the foreseeable future, AI assisted is here to stay. It's just a matter of getting the AI to be a better assistant. And in particular, I want help on the thinking part, not necessarily the coding part. Can you speak to the thinking problem versus the coding problem and the potential false dichotomy there?

a couple of different points to make you know ais have gotten good at making incremental changes at least when they understand customer software so first and the biggest limitation that these ais have today they really don't understand anything about your code base if you take github copilot for example it's like a fresh college graduate understands some programming languages and algorithms but doesn't understand what you're trying to do

A couple of different points to make. You know, AIs have gotten good at making incremental changes, at least when they understand customer software. So first and the biggest limitation that these AIs have today, They really don't understand anything about your code base.

If you take GitHub Copilot, for example, it's like a fresh college graduate understands some programming languages and algorithms, but doesn't understand what you're trying to do. And as a result of that, something like two thirds of the community on average drops off of the product, especially the expert developers. Augment is different.

We use retrieval augmented generation to deeply mine the knowledge that's inherent inside your code base. So we are a co-pilot that is an expert and that can help you navigate the code base, help you find issues and fix them and resolve them over time much more quickly than you can trying to tutor up a novice on your software.

I think it was a great 1.0 product. And I think they've done a huge service in promoting AI. But I think the game has changed. We have moved from AIs that are new college graduates to, in effect, AIs that are now among the best developers in your code base. And that difference is a profound one for software engineering in particular.

You know, if you're writing a new application from scratch, you want a web page that'll play tic-tac-toe, piece of cake to crank that out. But if you're looking at, you know, a tens of millions of line code base, like many of our customers, Lemonade is one of them. I mean, 10 million line monorepo as they move engineers inside and around that code base and hire new engineers.

Just the workload on senior developers to mentor engineers. people into areas of the code base they're not familiar with is hugely painful. An AI that knows the answer and is available seven by 24, you don't have to interrupt anybody and can help coach you through whatever you're trying to work on is hugely empowering to an engineer working on unfamiliar code.

2023.

80%, 110%.

We use retrieval augmented generation to deeply mine the knowledge that's inherent inside your code base. So we are a copilot that is an expert and that can help you navigate the code base, help you find issues and fix them and resolve them over time much more quickly than you can trying to tutor up a novice on your software.

I think it was a great 1.0 product, and I think they've done a huge service in promoting AI. But I think the game has changed. We have moved from AIs that are new college graduates to, in effect, AIs that are now among the best developers in your code base. And that difference is a profound one for software engineering in particular.

You know, if you're writing a new application from scratch, you want a web page that'll play tic-tac-toe, piece of cake to crank that out. But if you're looking at, you know, a tens of millions of line code base, like many of our customers, Lemonade is one of them. I mean, 10 million line monorepo as they move engineers inside and around that code base and hire new engineers.

Just the workload on senior developers to mentor engineers. people into areas of the code base they're not familiar with is hugely painful. An AI that knows the answer and is available seven by 24, you don't have to interrupt anybody and can help coach you through whatever you're trying to work on is hugely empowering to an engineer working in unfamiliar code.

Oh, man, what is this?

Bye, friends.

A couple of different points to make, you know, AIs have gotten good at making incremental changes, at least when they understand customer software. So first and the biggest limitation that these AIs have today, they really don't understand anything about your code base.

If you take GitHub Copilot, for example, it's like a fresh college graduate understands some programming languages and algorithms, but doesn't understand what you're trying to do. And as a result of that, something like two thirds of the community on average drops off of the product, especially the expert developers. Augment is different.