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Gemini CLI tips and tricks for agentic coding

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101–110 of 152 posts

Re: Gemini CLI tips and tricks for agentic coding

#101

I really wish there were a de facto state-of-the-art coding agent that is LLM-agnostic, so that LLM providers wouldn't bother reinventing their own wheels like Codex and Gemini-CLI. They should be pluggable providers, not independent programs. In this way, the CLI would focus on refining the agentic logic and would grow faster than ever before. Currently Claude Code is the best, but I don't think Anthropic would pivo…

Model agnostic tools I would say:

Roo Code or maybe Kilo (which is a fork of Roo)

Re: Gemini CLI tips and tricks for agentic coding

#102

Earlier quoted context omitted.

> The engineer learns and next time gets it right. Antropomorphizing LLMs like that is the path to madness. That's where all the frustration comes from.

On the contrary; stubborn refusal to anthropomorphize LLMs is where the frustration comes from. To a first approximation, the models are like little people on a chip; the success and failure modes are the same as with talking to people. If you look, all the good advice and guidelines for LLMs are effectively the same as for human employees - clarity of communication, sufficient context, not distracting with bullshit,…

I treat LLMs as statistics driven compression of knowledge and problem solving patterns.

If you treat it as such it is all understandable where they might fail and where you might have to guide them.

Also treat it as something that during training has been biased to produce immediate impressive results. This is why it bundles everything into single files, try catch patterns where catch will return mock data to show impressive one shot demo.

So the above you have to actively fight against, to make them prioritise scalability of the codebase and solutions.

Re: Gemini CLI tips and tricks for agentic coding

#103
post #60

Earlier quoted context omitted.

I'm pretty sure we are in an apple vs android situation, where you give lifetime apple users an android phone, and after a day they report that android is horrid . In reality, they just aren't used to how stuff is done on android. I think many devs are just in tune with the "nature" of Claude, and run aground easier when trying to use gemini or Chatgpt. This also explains why we get these perplexing mixed signals fro…

There are some clear objective signals that aren’t just user preference. I shelled out the $250 for Gemini’s top tier and am profoundly disappointed. I had forgotten that loops were still a thing. I’ve hit this multiple times in Gemini CLI, and in different projects. It gets stuck in a loop (as in the exact same, usually nonsense, message over and over) and the automated loop detection stops the whole operation. It a…

have you received your money's worth in other products?

Re: Gemini CLI tips and tricks for agentic coding

#105
post #42
post #17

Earlier quoted context omitted.

> Set me back 2 weeks of work. How did this happen? Did you let the agent loose without first creating its own git worktree?

What's the benefit of git worktree? I imagine you can just not give the agent access to git and you're in the same spot?

I'll reply to myself since apparently people downvote and move on:

They're useful for allowing agents to work in parallel. I imagine some people give them access to git and tools and sandbox the agents, then let a bunch of them work in separate git worktrees pointed at the same branch, then they come back and investigate/compare and contrast what the agents have done, to accelerate their work.

I think there is value in that but it also feels like a lot of very draining work and I imagine long term you're no longer in control of the code base. Which, I mean, great if you're working on a huge code base since you already don't control that...

Re: Gemini CLI tips and tricks for agentic coding

#106

ymmv, but I think all of this is too much and you generally don't need to think about how to use an AI properly since screaming at it usually works just as well as very fine tuned instructions. you don't need claude code, gemini-cli or codex I've been doing it raw as a (recent) lazyvim user with a proprietary agent with 3 tools: git, ask and ripgrep and currently gemini 3 is by far the best for me even without all th…

I'm doing something very similar but even simpler and Gemini 3 is absolutely crushing it. I tried to do this with other models in the past, but it never really felt productive.

I don't even generate diffs, just full files (though I try and keep them small) and my success rate is probably close to 80% one-shotting very complex coding tasks that would take me days.

Re: Gemini CLI tips and tricks for agentic coding

#107
post #72

Gemini CLI at this stage isn't good at complex coding tasks (vs. Claude Code, Codex, Cursor CLI, Qoder CLI, etc.). Mostly because of the simple ReAct loop, compounded by relatively weak tool calling capability of the Gemini 2.5 Pro model. > I haven't tried complex coding tasks using Gemini 3.0 Pro Preview yet. I reckon it won't be materially different. Gemini CLI is open source and being actively developed, which is…

> I haven't tried complex coding tasks using Gemini 3.0 Pro Preview yet. I reckon it won't be materially different. In my limited testing, I found that Gemini 3 Pro struggles with even simple coding tasks. Sure, I haven't tested complex scenarios yet and have only done so via Antigravity. But it is very difficult to do that with the limited quota it provides. Impressions here - https://dev.amitgawande.com/2025/antigr…

Are we using different models? Here is a simulation of Chernobyl reactor 4 using research grade numerical modeling I made with it in a few days: https://rbmk-1000-simulator-162899759362.us-west1.run.app/

Re: Gemini CLI tips and tricks for agentic coding

#110
post #57

I am not doing any of this. It becomes obsolete in literally weeks, and it also doesn't work 80% of the time. Like why write a mcp server for custom tasks when I don't know if the llm is going to reliably call it. My rule for AI has been steadfast for months (years?) now. I write (myself, not AI because then I spend more time guiding the AI instead of thinking about the problem) documentation for myself (templates, c…

A perspective which has helped me is viewing LLM-based offerings strictly as statistical document generators, whose usefulness is entirely dependent upon their training data set plus model evolution, and whose usage is best modeled as a form of constraint programming[0] lacking a formal (repeatable) grammar. As such, and when considering the subjectivity of natural languages in general, the best I hope for when using…

Do you get tangibly different results if you don't capitalize MUST (NOT)?
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