
Before trying Gemini, I struggled to onboard onto complex, messily documented codebases, which constantly dragged down my daily performance.Now, the AI intelligence handles the heavy lifting. I can just feed a massive local repository straight into the context window, and it instantly maps out the entire UI/UX logic and backend connections for me. The IDE integrations fit right into my existing VS Code setup without a hitch, saving me a ton of setup time. On top of that, Google's documentation and support made the initial onboarding a breeze.From a pricing and ROI standpoint, it easily pays for itself by cutting my development and debugging time roughly in half, letting me ship clean features way faster than before. Review collected by and hosted on G2.com.
While the massive context window is great, the latency can be a real drag. When you actually feed it a large codebase, response times slow down significantly, and it occasionally hits a wall or throws a generation error midway through writing a file. Another frustrating thing is the aggressive safety filtering. It sometimes flags completely benign backend logic or SQL queries as unsafe, forcing you to waste time rewriting prompts just to get past the filter. Lastly, the code suggestions in the IDE plugin can sometimes be overly aggressive, occasionally overwriting local lines you didn't want touched. Review collected by and hosted on G2.com.