[ojr]

I primarily use Gemini 3 Flash with a GUI coding agent I made by myself and its been able to successfully one-shot mostly any task I throw at it. Why would I ever use a more expensive reasoning and slower reasoning model? I am impressed with the library knowledge Gemini knows, I don't use any skills or MCP and its able to implement functions to perfection. No one crawls more data than Google and their model reflects that in my experience.

[port11]

My experience with Antigravity was that 3 Pro can reason itself out of Gemini’s typical loops, but won’t actually achieve it (it gets stuck).

3 Flash usually doesn't get into any loops, but then again, it’s also not really following prompts properly. I’ve tried all manner of harnesses around what it shouldn’t do, but it often ignores some instructions. It also doesn’t follow design specs at all, it will output React code that is 70% like what it was asked to do.

My experience with Stitch is the same. Gemini has nice free-use tiers, but it wastes a lot of my time with reprompting it.

[ojr]

I don't use Stitch it doesn't have the context of my codebase, I just tell Gemini to make the UI directly and its able to do it. The only time it failed is when my prompt and goal was bad. I told it to swap expo-audio with react-native-track-player and it was able to do it in one-shot. Implement Revenue Cat and it did it in one shot. I do task by task like all the other agent tools recommended. The harness I made doesn't install packages, it just provides code. I don't use Anitgravity or any Electron-based coding agent, mine has a Rust core and different prompt engineering, not sure why it works so well but it does.

Demo: https://www.youtube.com/watch?v=jKMrvh56F0M Website: https://slidebits.com/isogen

I need to implement a better free trial plan, it's reached enough maturity where its my only and primary way I write code, I also use web chats to help me craft prompts. Reach out to test. https://slidebits.com/support

[Alex-Programs]

I'm curious, what's the agent like?

If I were to build something for Gemini models I'd plan around ingesting a bunch of context then oneshotting it.

[ojr]

you can run into payload too large errors, ingesting bunch of context, I use vercel's ai sdk so I can interchange between models but have 0 OpenAI and Claude credits or subscriptions. I use a combination of grepping files like a terminal tool and implemented a vector search database for fuzzy searches, Gemini chooses what tool it wants to use, I provide it create, read, update, delete, functions. There's a few tricks I do as well but if I tell you, you can probably prompt a clone . Sharing the full implementation is basically open sourcing the code.

Demo: https://www.youtube.com/watch?v=jKMrvh56F0M Website: https://slidebits.com/isogen

if you want to try it out let me know, I'll provide free access and a gemini test key

https://slidebits.com/support