u/Puzzleheaded-Lock825

I’m using my own API in TRAE, and while waiting for an agent to finish working on a project, I’d like the flexibility to open a new chat so another model can review other files in parallel.

At the moment, TRAE doesn’t allow opening a new chat until the current project has been fully completed. This limits multitasking and slows down the workflow.

Of course, this wouldn’t increase TRAE’s costs, since I’m using my own API from another provider. I’m simply using TRAE as my IDE.

VS Code already supports this kind of workflow, where I can open multiple chats and have 2–3 tasks or projects running in parallel. The difference is that VS Code’s built-in chat doesn’t support external APIs, so I’d need to rely on extensions. That’s actually why I prefer TRAE — the overall experience is better.

If TRAE added support for parallel chats while using external APIs, it would make the workflow significantly more efficient for power users.

One big reason? Messy code.

If your codebase is cluttered, inconsistent, or full of old hacks, AI has a harder time understanding what’s actually going on. It might follow outdated logic, fix the wrong thing, or create new bugs instead.

This gets even worse as your project becomes more complex. Even powerful models can struggle when the codebase becomes layers of patches on top of patches, with no proper cleanup—duplicate logic, old code, temporary hacks, and all the usual mess.

That’s why you need to regularly tell AI to clean things up, refactor code, remove duplicates, and simplify the structure—not just keep asking it to add more features on top of existing mess.

Things that make AI perform worse:

• Dead/unused code
• Huge files doing too many jobs
• Bad variable/function names
• Duplicate logic
• Old commented-out code
• Inconsistent coding patterns
• Poor project structure
• Temporary hacks left everywhere
• Too much irrelevant context
• Overcomplicated abstractions

AI works heavily on context. If the context is messy, the output gets messy too.

Clean code doesn’t guarantee perfect answers, but it gives AI a much better chance.

I see MiniMax making things worse and damaging the existing system if you use extension tools from VS Code, but it becomes good when you use an IDE other than VS Code.

I also think the choice of tools used to access the MiniMax model matters a lot, because every tool has its own prompting system, which can make the responses significantly worse. This is just based on my personal experience, though, since every project is different.

Right now, I’m using TRAE IDE from TikTok’s company. TRAE is basically a fork of VS Code, but with more advanced features.

Why did I suddenly lose the desire to use GitHub Copilot after finding out it switched to token billing? Even though I still have 290 requests left for this month.

I noticed that TRAE’s coding plan appears to use request-based billing instead of token-based billing or credits, though I could be mistaken. Is this a permanent pricing model, or just a temporary arrangement?

I’m a bit concerned about adopting it, only to have it suddenly switch to something like GitHub Copilot, where the pricing model unexpectedly changes to token-based billing. I’m a former Copilot user.

Hi, I recently started using TRAE IDE, and I really like TRAE’s UI and its support for various models. However, I noticed that TRAE does not support the latest DeepSeek V4 model.

I’m using my own API, but there’s no option for thinking mode like the one offered by DeepSeek, such as None, High, and Max Thinking.

A lot of people are frustrated because GitHub Copilot has switched to token-based billing. So today I’m sharing an alternative I’ve tried that still works inside VS Code. I’m using MiniMax 2.7 with a token plan (subscription, not API usage). The subscription they offer is quite affordable, and you can use your API within the VS Code extension.

Even though you’re using an API, it’s not billed per token usage — since you’re already subscribed, they mainly enforce rate limits instead. Besides MiniMax, I’ve also noticed that Xiaomi MiMo offers a similar token plan (subscription). So for those who can’t afford traditional API usage, this might be useful info.

So far, I’ve used both MiniMax and MiMo, and these models are among the more powerful ones for coding.

If you have any useful info or better alternatives, feel free to share it here — I’d really appreciate it.

Hey guys, quick one — do you all prefer using AI via API or just a subscription?

Which one do you use more, and what makes you stick with it? 🤔

Honestly, this move to usage-based token billing might push people away, especially those who liked Copilot for its simple and predictable pricing. If more developers start switching to alternatives that feel more worth it, it could slowly affect trust—and maybe even the company’s performance over time.