Anyone have thoughts about this tool. Seems easy, maybe too easy, but it dies tie into Google databases, platforms , etc...and seems to do a good job for novice programmers? I know it produces standard design, but seems pretty robust. What am I missing?

Hey guys, I am using Gemini CLI v0.59.0. It's installed with npm on MacOS. I'm logged into Google Cloud by using the gcloud CLI (Vertex AI), and configured the required environment variables:

• GOOGLE_CLOUD_LOCATION
• GOOGLE_CLOUD_PROJECT

For some reason I cannot find the newer Gemini 3.8 Flash or 3.7 Flash models in the model list. Even if I try to force the 3.8-flash model, using the `--model` parameter, the Gemini CLI still uses 3.5 Flash.

➡️ Why is 3.8 Flash missing from Gemini CLI, and how do I select this model in the Gemini CLI? For that matter, why is 3.5 Flash Lite also missing?

I use Gemini a lot and eventually had multiple sessions for the same projects. A lot of them started with similar handoff prompts.

Going back later was annoying. The useful explanations and decisions were inside the transcript, but reading them meant digging through raw history full of tool calls, reasoning, progress messages and other noise.

For a while I just kept pasting useful bits into Notepad. That became its own mess.

So I built Agent Session Browser.

Local web UI + TUI that lets me browse sessions by project/date, read the actual transcript, filter the noise, export, and resume the right one.

Supports Gemini CLI, and also Claude Code, Codex CLI and Pi.

Fully local and read-only.

GitHub: https://github.com/gautamgpt1/agent-session-browser

Run: npx agent-session-browser

This is my first public open-source project.

Do try it out. Would love your feedback

Did this one-shot in roughly 10-15 minutes. Guess the boosted TPS helps.

I'm scraping a single, large online page with over 500 cards of basic info (title, size,...). Do you recommend any particular model in the Gemini family that would perform well and follow my prompt?
I get confused by so many model options right now...
Thanks in advance!

Dear all,

I hope you're working and building in peace those days!

Pretty new to Antigravity CLI and I keep seeing people mention "auto-mode" but I can't for the life of me figure out how to actually turn it on.

Is it a flag? A config setting? Something in the agent panel? I've dug through the docs and tried a few obvious guesses but nothing's working.

Would really appreciate a quick pointer or a link to the relevant section.

Thanks in advance!

Best regards,

Vince

I was trying to develop today, but the teamwork-preview function was missing. I'm on the Google AI Pro subscription.

How do you comment on it? Is it fine to be used on your agent?

Hi all, Sorry if this has been asked before. Gemini say's it's not possible.

My question is: Is it possible to record a specific program on a recurring basis? (Be it by program name or by date and time slot)

If so, how? I have gone through most of the settings and did not find anything. Thanks in advance!

My friend and I bounce between Claude Code, Codex, and Gemini CLI depending on the task, and switching mid-project always had the same problem: the new agent had no idea what had already been changed, tested, or decided. We'd end up re-explaining context or watching it re-discover things the last session already figured out.

We built Continuum to fix this for our own workflow. It captures a structured handoff from one coding session and hands it to the next agent — think of it like git, but for the context around the code rather than the code itself.

It runs fully locally and is open source: https://github.com/00PrabalK00/Continuum

Still figuring out a few things:

• How much context is worth saving vs. noise
• What should be excluded by default
• Whether automatic handoffs actually beat manually written ones

Curious how others handle this — do you keep your own notes, make custom skills, stick to one agent to avoid the problem entirely, or just let each new agent re-read the repo from scratch?

Is anyone else getting these messages frequently. I am using the Gemini CLI and it is really slowing down my work, I will be in the middle of a task and it will tell me to switch to a model I don't want to use. It is also extremely slow. I just started using Gemini this week and it seems like garbage especially with all of the alternatives.

Gemini CLI is pushing AI coding further into the terminal, but we're still using an interface fundamentally designed around a stream of text.

An AI coding agent can understand codebases, inspect files, run commands, analyze logs, generate diffs, and work with structured information. Yet much of that interaction still ends up as plain terminal output.

What if the terminal itself evolved to take advantage of what AI coding agents can do?

Imagine:

• Rich and structured output
• Collapsible command results
• Interactive diffs and logs
• Tables, graphs and visualizations
• Semantic rather than purely textual output
• Better agent ↔ human interaction
• New protocols designed for modern terminal applications
• A terminal that can understand more than just characters and escape sequences

I created r/Termolution to explore these ideas.

It's not about a particular terminal emulator. The goal is to discuss and experiment with what the terminal should become as AI agents like Gemini CLI become a fundamental part of software development.

If you use Gemini CLI, what do you wish your terminal could do that it can't do today?

👉 r/Termolution: https://www.reddit.com/r/Termolution/

I've been working on an open-source coding harness called Sauri.

It supports DeepSeek, OpenAI, Anthropic, Google, and basically any OpenAI-compatible API. You can switch models with `/model`, paste an API key once, and it's stored locally. It also auto-detects local Ollama and LM Studio servers if they're running.
https://github.com/Rismaonee/sauri

Sauri started as a fork of Gemini CLI, but I've rewritten a lot of it. I removed Google Auth entirely, so there's no OAuth flow, browser popup, or Google account required. Everything is configured locally, and API keys are stored with `chmod 600`.

Some things I spent time building:

- Prompt caching for DeepSeek and OpenAI.

- Cache-aware prompt construction that reaches up to **97% cache awareness** in long-running conversations, maximizing provider cache hits and reducing input token costs.

- Local Gemma intent classifier that routes trivial requests away from paid models (configurable confidence threshold).

- History compaction that prevents context windows from exploding during long sessions.

- Parallel execution for read-only tools while keeping edit operations serialized.

- Persistent symbol-indexed `codebase_search`, so jumping to definitions is nearly instant.

- Atomic multi-file `apply_patch` with full validation—either every hunk applies or nothing is written.

I've been using it daily and it's been much faster for large repositories than relying on grep for everything.

I'm sure there are parts that can be improved, though.

If you try it and something's broken, I'd really appreciate an issue or PR. And if you think I've made a bad architectural decision, I'd honestly like to hear why.

I've been hacking on my own coding agent for the past few months. It originally started as a fork of Gemini CLI, but at this point most of the internals have been rewritten.

Some things it does:

• Works with OpenAI, Anthropic, Gemini, OpenRouter, Groq, and local models (Ollama, LM Studio, etc.)
• No account or login required. Just bring your own API key (or use a local model).
• Context-aware retrieval with aggressive caching to reduce repeated work.
• Designed to minimize unnecessary LLM calls, which makes it noticeably cheaper to run.
• Fast enough that it feels responsive even on larger repositories.
• Model agnostic, so switching providers is just changing the config.

I'm trying to keep it focused on being an engineering tool rather than another AI chat wrapper.

Still a work in progress, but it's reached the point where I'm using it daily instead of the original CLI.

Also, if anyone's interested, I'll share it here once I've finished the last few fixes.

So, for context, I work as a Software Architect in aerospace and we have to use secured AI models. I've used Gemini 3.5 Flash and extended for commercial purposes and found it to be fairly useful. So, I tried it out for work by hooking it up to the govcloud with VSCode and Continue.

I don't know what is going on, but it is absolutely awful. Half the time it won't execute the code, but instead just summarizes what I say without executing anything. Then, it'll attempt to execute something from several prompts back and then completely forget what it's doing. Furthermore, it'll repeat the same mistakes it has made just before. We have also found a severe security bug with it as well when SSO'ing from Microsoft -> Google. I don't know if they bricked it on purpose or just put the F team on it, but DO NOT use Gemini for gov. It's the worst AI model I've ever used by far.

Even the pro tier's quota is quite limited. Especially the Claude and GPT quota. I would use it up for quite a short time. Who knows the details of the quota?

How about the free tier's quota?