Anand Kulkarni

Probably the most difficult decision we made to roll back technically was building on Vue. We built in Vue a whole bunch of front end. And today, very little of our front end is in Vue. We ended up changing it all to React. And that's one that was painful to walk back from, no question. Look, all code is temporary. That's the way to think about it.

Probably the most difficult decision we made to roll back technically was building on Vue. We built in Vue a whole bunch of front end. And today, very little of our front end is in Vue. We ended up changing it all to React. And that's one that was painful to walk back from, no question. Look, all code is temporary. That's the way to think about it.

Probably the most difficult decision we made to roll back technically was building on Vue. We built in Vue a whole bunch of front end. And today, very little of our front end is in Vue. We ended up changing it all to React. And that's one that was painful to walk back from, no question. Look, all code is temporary. That's the way to think about it.

You become very comfortable with driving the right technical decisions and learning to challenge that debt wherever you're able to.

You become very comfortable with driving the right technical decisions and learning to challenge that debt wherever you're able to.

You become very comfortable with driving the right technical decisions and learning to challenge that debt wherever you're able to.

So if you look at what Credbotics does at our core, we're doing three things with customers. We're doing requirements capture, meaning you show up for the code base. I want to make requirements that describe that code base accurately and completely. The second is we want to make it easier for customers to analyze, extend and modify, reimagine those requirements.

So if you look at what Credbotics does at our core, we're doing three things with customers. We're doing requirements capture, meaning you show up for the code base. I want to make requirements that describe that code base accurately and completely. The second is we want to make it easier for customers to analyze, extend and modify, reimagine those requirements.

So if you look at what Credbotics does at our core, we're doing three things with customers. We're doing requirements capture, meaning you show up for the code base. I want to make requirements that describe that code base accurately and completely. The second is we want to make it easier for customers to analyze, extend and modify, reimagine those requirements.

How do I talk to my code base or talk to my requirements about this code base and say what needs to change? What is working? Where in my code can I change X? And then we want to help customers do requirements-driven development.

How do I talk to my code base or talk to my requirements about this code base and say what needs to change? What is working? Where in my code can I change X? And then we want to help customers do requirements-driven development.

How do I talk to my code base or talk to my requirements about this code base and say what needs to change? What is working? Where in my code can I change X? And then we want to help customers do requirements-driven development.

How do I take a set of requirements that I've got, modify those using intelligent agents inside Cloudbotics and inside my AI software engineering tool, GitHub Copilot, which works very well as a combined effort. Okay, if you go through those three things, first, you've got to have a working baseline flow, which is the thing I talked about that took us nine to 12 months to build.

How do I take a set of requirements that I've got, modify those using intelligent agents inside Cloudbotics and inside my AI software engineering tool, GitHub Copilot, which works very well as a combined effort. Okay, if you go through those three things, first, you've got to have a working baseline flow, which is the thing I talked about that took us nine to 12 months to build.

How do I take a set of requirements that I've got, modify those using intelligent agents inside Cloudbotics and inside my AI software engineering tool, GitHub Copilot, which works very well as a combined effort. Okay, if you go through those three things, first, you've got to have a working baseline flow, which is the thing I talked about that took us nine to 12 months to build.

It gets you all the way from starting with a code base over to I am now building software and modernizing code using this end-to-end system. You've got to do it in a way that gets better over time. So when we look at our roadmap, we are looking at ways that we can assess systematically how good we are at each one of those activities.

It gets you all the way from starting with a code base over to I am now building software and modernizing code using this end-to-end system. You've got to do it in a way that gets better over time. So when we look at our roadmap, we are looking at ways that we can assess systematically how good we are at each one of those activities.

It gets you all the way from starting with a code base over to I am now building software and modernizing code using this end-to-end system. You've got to do it in a way that gets better over time. So when we look at our roadmap, we are looking at ways that we can assess systematically how good we are at each one of those activities.

And then we take a look at what steps we need to carry out to improve those capabilities in a place that's going to have the biggest impact for our customers based on what our customers tell us that they think they want. and on the metrics that we have in our own forecast for how this works.

And then we take a look at what steps we need to carry out to improve those capabilities in a place that's going to have the biggest impact for our customers based on what our customers tell us that they think they want. and on the metrics that we have in our own forecast for how this works.