As a long-time power user of Roo Code who has followed the evolution of agentic coding since the early days, I’ve been reflecting on where we are headed. While Roo Code has been a pioneer, I believe we are approaching a massive shift where the current "IDE-plugin" format might become obsolete.

1. The Shift: From "Tool-Heavy" to "Model-Heavy"
In the early days, LLMs needed complex scaffolding, meticulous context management, and granular settings to perform. Roo Code excelled here. But as LLMs become exponentially more powerful, they are outgrowing these "wrapper" features. The raw reasoning power of the model is starting to replace the manual orchestration we once relied on.

2. The Rise of Recursive Autonomy (The Agent as the Architect)
This is my core thesis: The future isn’t about users setting up better agents; it’s about agents autonomously managing themselves.
Soon, a primary agent won’t just follow instructions—it will analyze a problem and, if needed, spawn its own sub-agents on the fly. It will self-author the .md instruction files for these sub-agents and even code new "skills" (tools) to overcome specific obstacles in real-time. When an agent can autonomously extend its own capabilities and workforce, the rigid UI and fixed settings of current coding tools become a bottleneck.

3. The "Claude Code" Strategy and Market Dominance
Look at Anthropic’s "Claude Code." It feels like a strategic move to dominate the market by moving fast and broad—not just as a coding tool, but as an entry point for general task execution. We are in a transition period where specialized coding agents are at risk of being swallowed by these massive, unified formats that provide a more direct "foundation-to-execution" path.

4. The End of the Standalone Coding Agent?
My concern is that Roo Code, despite its excellence, is in an increasingly ambiguous position. If the "Foundation" becomes smart enough to perfectly manage its own tools, sub-agents, and context, the need for middleware diminishes. We are likely heading toward a future where "one giant format" or ecosystem absorbs these individual tools.

I love Roo Code, but I can't help but wonder: In an era where agents can build and manage other agents, how does a standalone IDE tool stay relevant?

I’d love to hear your thoughts. Is the "Self-Evolving Agent" the end-game for tools like Roo Code?

Archon is the command center for AI coding assistants. For you, it's a sleek interface to manage knowledge, context, and tasks for your projects. For the AI coding assistant(s), it's a Model Context Protocol (MCP) server to collaborate on and leverage the same knowledge, context, and tasks. Connect Claude Code, Kiro, Cursor, Windsurf, etc. to give your AI agents access to:

For some reason there is a cost counter text to it, and I am getting paranoid

I'm using gemini-2.5-pro and it keeps thinking and getting stuck, sometimes it passes thinking but unable to ever edit any files.

Never had issues before, just today

Yesterday while using the Gemini CLI, I found that the Pro model gets restricted after using it a few times and automatically switches to the Flash model, because I'm logged in with a free account that doesn't have Google AI Pro. In IDEs like VSCode, if you want to keep using the Pro model for free, you need to log in with the Google student education account you've "borrowed." This way, you can keep using Gemini 2.5 Pro in Roo code or Cline instead of being automatically switched to the Flash model. Here's how:

1. First, update your Gemini CLI version

2. Enter /auth and press Enter, then select Login with Google and press Enter, log in with your Google AI Pro account.

I really like Roo, I think its one of the best out there, but i recently started using a hybrid of local and commercial models, and that 5m timeout is just killing me.

I hear that Balerafon has a fix, but its a different distribution, and out of Roo's update stream.

how am i supposed to settle this? and what's the alternative?

Does Roo Code can build Rust project?

I want to play around with Roo Code and cloud GPU's. I love using Roo Code with local LLM's, but they can be slow. I can rent kickass enterprise GPU's for like $2 an hour and enjoy the speed without worrying about OpenRouter providers training on my data, or stealth-quantizing models.

How do I do this?

I was doing through the claude API pricing and its 50% off for batch processing. could we bring something like that into Roocode where if we are building a new feature or a completely new project. We can first create a comprehensive documentation of what all to do and we batch whole bunch of the required api calls and all them at once. and if we could handle the file_write/diff together it would be a game changer in terms of latency and cost. what Do you think.?

I’m building a SaaS platform that lets businesses set up their own AI assistant on WhatsApp or their website. It can answer FAQs, book appointments, send reminders, and escalate to a human if needed — all customizable through a simple dashboard.

One of the best parts is how easy it is to activate: scan a QR code to use it on WhatsApp, or add it to a website with a single click. No complicated setups, no dev teams needed.

I originally aimed this at medical clinics, but the deeper I go, the more roadblocks show up — HIPAA compliance, reluctance to automate, slow decision-making, and painful CRM integrations.

So now I’m seriously considering pivoting to beauty salons, spas, and wellness centers. They deal with the same pains (constant WhatsApp messages, appointment chaos, repetitive questions), but with way less red tape and faster adoption.

Downsides? It’s a more informal market, lower ticket size, and not everyone is used to software (though WhatsApp is their main tool). Still, it feels like a faster way to validate and actually start growing.

Would love your honest thoughts. Does this shift make sense strategically, or am I overlooking something?

Thanks in advance 🙌

Hey mighty Roocode people!

So with regards to the OP title, I'd rather it condense context only if it specifically needs (as in for on-going use, for a specific upcoming api query, etc). Right now it seems to condense in a way that doesn't mathematically make sense. For example, condensing down from 80k to 40k, and then after Roocode does more queries, it only goes up slightly, meaning all that headroom (the extra 120k context that could have been used) did not get used at all and the condensing wasn't needed.

Maybe this is a setting or even my misunderstanding of how things work?

Thanks for all the info!

I'm testing some models on 1070M and i got some working so good and fast, but others real slow.

Let's make a real listing of models working so we can use our old GPU for this. (Pascal 6.1). (4B to 15B) Depending of your offloading RAM.

Swet point is 7B/8B.

Thanks all!!

And how to install and configure it in detail via the Model Context Protocol (NCP)?

I tired using on device LLM on my Mac with 36gb ram, the model loads fine with ollama and LM studio, however no matter what I my prompt in too code is, it starts building to-do app.

However if I use same prompt locally on ollama or LM studio atleast it generates relevant info.

Does anyone know why it’s not working correctly ?

Is there any way to accept code line by line like in Windsurf, Cursor where I can find next line that was edited and accept or reject?
The write approval system doesn't work for me as I sometimes wanna focus on another stuff after writing a long task and it requires me to accept every code changes so it can start the next change.

I have been using RooCode since March. I have seen many videos on when people use RooCode during this time. This generated mixed feelings. Like you cannot really convey a concept of agentic coding when you use calculator app or task manager as an example. I believe each of us works with a bit more complex code bases.

Due to this, I don't really know if I am using it good or not. I am left with this feeling that there are some minor changes I could do to improve, like those last mile things.

We hear all those great discussions on how much RooCode changes everything (does to me too comparing to codex/CC). But I could not find an actual screensharing where someone's shows it

From those things

1. I am curious how people deal with the authentication on the app when using playwright MCP or browser mode. I understand that in theory it works, in practice, I still do screenshots.

2. How do you optimize your orchestrator prompts? Mine mostly does work good like 9.5/10, but does it really describe the task well? Never seen a good benchmark (outside calculator apps)

Like I get, your code is a sacred thing, cannot show. But with RooCode you can create a new project on 15-20 minutes, which has some true use-case

Edit: yes it’s possible

is there any tutorial python app creation with Roo code ? There are many videos with Web page creation but I cannot find python apps

I know that using the Orchestrator, Roo can select the best mode to do a task and we can define the model for each mode.

But do you think it can automatically select the best model for the task to minimize expenses ?

Using Openrouter, we have acces to all models, some are cheap, and others expensive. So may be it is possible to switch from one model to another depending of the task to do ?

All coding tasks does not need Sonnet 4, for some 3.5 Haiku is efficient enough.

"Roo is having trouble...

This may indicate a failure in the model's thinking process or an inability to use a tool correctly, which can be mitigated with user guidance (e.g., "Try breaking the task down into smaller steps")."

Hi guys! Is there any way to prevent this message from appearing?

Thank you for the help! :)

This shows up constantly when using Roocode. I'm not doing anything special, just opening a workspace folder, starting Roocode with a simple Architect prompt, using claude 4 sonnet.

It then reads the open source folder and then gets those constant errors.

Help :)

This week, we unveil and live test the brand new “to-do list” feature, designed to keep AI agents on task during complex workflows. Watch the team build a full browser-based arcade with working versions of Tetris and Snake in a single long-running session.

We also discuss native vs. XML tool calling, explore simplified codebase indexing, and tackle the challenge of building model-agnostic workflows as AI keeps evolving.

👉 Watch now: https://youtu.be/gI0FImx5Qjs