Initially, we attempted to create a co-pilot for mechanical engineering, but we pivoted to focus on coding because we were more passionate about it and recognized the potential for AI to transform programming.

We initially explored automating mechanical engineering but pivoted to focus on programming, recognizing the potential for AI in that space.

My interest in computer science was influenced by the realization that AI could solve complex problems, leading me to shift from studying physics to focusing on AI and technology.

While coding is a primary focus, we see a transfer of skills from coding models to enhancing reasoning and agentic behavior in other applications.

We were inspired by the success of GitHub Copilot, which demonstrated that useful AI products could be created, motivating us to pursue our own ambitious ideas in AI.

We realized that the existing AI models were not sufficient for our needs, prompting us to develop our own models to enhance product quality.

When using AI for coding, there is often a gap between the code generated by AI and the user's ability to modify it effectively, highlighting the need for better tools.

Coding has rapidly evolved, with AI tools significantly impacting how software is developed, leading to nonlinear progress in the field.

The next priority for us is AI, as the world is being completely overhauled by it, and we need to create our own AI innovations that align with our strengths in front-end and design.