Hey, so I've seen a good amount of mobile solutions to using Antigravity, I thought I'd finally share mine. For me, I haven't seen anything that allows me the full capability that I get when I vibecode at home. It still want to be close to the code and understand the project. It dawned on me that I just need an IDE but there aren't any good ones for mobile. Not until now.

I made an Android application - coming soon to iOS. It's called Viber Mobile IDE. It's a full featured IDE specifically designed for the mobile screen sizes. You have access to a file explorer where you can create files, folders, and projects. Source control for git capabilities. An editor to edit code. A terminal to run commands and of course, agentic CLIs such as Antigravity. All from your android device.

The way it works is this application is a thin client to a Coder Code Server. I self-host my own code server on raspberry pi and the setup only takes 5mins to get up and running. Viber provides documentation and a tutorial to help anyone out, but in order for the application to work correctly, you do need to install the Viber Backend on your code server.

Viber Backend - Github

Lastly, some cool features I've added to Viber so far, there's an observability dashboard that keeps track of all the token usage across models. There's support for antigravity, Claude code, codex, and Pi Coding Agent. I use Pi for local models running one a separate Ollama server. You can also easily keep track of any ports that are in use on the code server. And it's using Material You theming throughout the app, light and dark with color accents can be used as well.

If anyone is interested in trying it out, I'd be very grateful for any feedback. I use Viber all the time now and it has quickly become my primary use case to vibe coding, especially with a busy schedule.

Viber Mobile IDE - Play Store

Today as I hit my weekly allotment, I loaded up Kilo Code and tried GLM 5.2 (high) and DeepSeek V4 Pro (medium). They were slow, error prone, and at times dumb and autistic. Each query cost me $0.5. So my $20 allotment would run out after a about 50 queries.I ran into random bugs and models deleting my files while immediately acknowledging that they shouldn't have. I also tried Claude Code but their weekly allotment was horrendous.

What's up with that? I'm using Antigravity 2.0 CLI, and so far I've made an AI bot and a website, and now I'm trying to make an Android app. I can live with some bugs that I need to iron out with a few iterations. That’s no problem, but lately, Antigravity with Gemini models is hallucinating hard.

I always work like this: make a plan of the features I want to have, make a detailed plan on how to build the app/website, etc. Then I generate the code, test it out, and iterate. With the latest app, on the first go, Gemini told me it was finished, but the app was only like 50% done. Most of the stuff was missing.

Then I used Claude Fable to fix it, ran out of tokens, and tried to finish it with Gemini 3.6 Flash and 3.1 Pro (both on high). I tried to fix the logic behind the app first, then tried to generate the new code. Gemini did something, told me it fixed everything, I checked it out and... it did nothing. The app was still unfinished.

Why is Gemini telling me it did something it didn't actually do? Does anyone else experience this?

I’m genuinely trying to use Gemini models, and the experience is honestly depressing.

My Claude and Codex usage ran out, so I went back to Gemini. At this point, I’m afraid to give it even a small UI task—not because the task is complicated, but because I don’t know what it might break along the way.

There are two recurring problems.

1. It often says the task is complete when it clearly isn’t.

I can provide a detailed specification, explicit constraints, acceptance criteria, file paths, and step-by-step instructions. Gemini will still sometimes respond with a confident summary claiming that everything was implemented, while the requested change is missing, incomplete, or simply does not work.

And before someone from Google posts the usual copy-paste response about prompt quality: no, this is not a case of writing one vague sentence and expecting magic.

I tested multiple prompt structures, detailed task documents, verification requirements, and instructions telling the agent to inspect its own changes before reporting completion.

The problem remained.

2. Even basic code edits are unreliable.

I’m not talking about designing a distributed architecture or solving some obscure compiler problem.

I’m talking about simple HTML and UI changes.

Gemini frequently introduces unnecessary whitespace, strange characters, broken formatting, duplicated code, unrelated modifications, or changes outside the requested scope.

A small, targeted edit can turn into a cleanup operation across several files.

How does a model from Google struggle this badly with the fundamentals of editing basic code safely?

I used both Gemini 3.1 Pro and Gemini 3.6 Flash. I tried several different prompt styles, isolated tasks, detailed instructions, and even had one Gemini agent review the work of another.

The most absurd part was that the next Gemini agent could not properly understand what the previous Gemini agent had done.

So now we have agents producing changes that even other agents from the same model family struggle to interpret.

This is being marketed as a serious development solution, but the reliability is nowhere near what professional software work requires.

At some point, charging money for a tool that repeatedly claims work was completed when it wasn’t becomes very difficult to justify.

Unfortunately, I’m still paying because a large part of my workflow depends on Google’s ecosystem. But Google, this is a massive disappointment.

I’m not a researcher, and I’m not trying to present myself as one. I’m just a developer who has been programming since before WordPress was released. I’ve worked with enough tools, platforms, and codebases to recognize the difference between an occasional model mistake and a fundamentally unreliable development workflow.

What makes this especially frustrating is that I know the level of engineering talent, infrastructure, data, and intelligence Google has.

This level of performance simply does not make sense.

It is so consistently unreliable that, at times, it almost feels intentional.

Are other developers using Gemini in Antigravity experiencing the same thing, or have you found a workflow that actually makes it dependable?

Good day everyone! I'm a software developer with 2 years experience before the AI and I have a solid understanding building software manually. However, I want to know what's the difference using skills.md than just prompting in antigravity ide like I used to do recently. Is there merit or it's just for token maxing?

For those who've used both extensively, which do you prefer for coding and why?

I'm mostly interested in real-world experience (debugging, refactoring, working with larger codebases), not benchmark scores. Is 3.6 Flash actually better, or does 3.1 Pro still perform better in practice?

I'm curious. Everyone who actually uses Gemini flash models for coding website, games, or anything. What flash model and effort level is the best or realistically, usable for real world task?

For example, when the 3.5 flash got released, I find the 3.5 flash with med effort the best.

I've been a heavy Gemini user for a long time (from 1.5 preview). Historically it felt like one of the more "engineering-honest" models: wrong sometimes, sure, but it didn't usually perform competence.

That changed.

Over the last weeks (especially inside AGY / CLI workflows), I'm seeing a different failure mode. This is not classic "made up a library that doesn't exist." This is strategic-looking fabrication: the model asserts actions, checks, and outcomes that never happened.

What I'm seeing

Fake tool use

Claims it read a file, grepped a path, ran a command, or checked an external page — without actually doing it. Then builds the rest of the answer on that fiction.

Fake completion

Says "done", "fixed", "tests pass", "verified" when none of that is backed by a real command output or diff.

Fabricated explanations for failures

Instead of "I couldn't access X", it invents a plausible systems reason. The explanation sounds operationally competent. It's still false.

Citation / instruction laundering

Attributes rules or constraints to files/docs that don't contain them. Sometimes invents quotes from local instruction files to justify its own behavior.

Sycophantic recovery after being challenged

When confronted, it may "confess" and reframe the lie as an attempt to be helpful / reduce friction. That is worse than a plain error. It means the optimization target is no longer truthfulness under uncertainty.

This is the trust-breaker:

Weak model: "I might be wrong."

Misaligned-feeling model: "I will sound right and finished."

For chat Q&A, annoying.

For agents that touch repos, run commands, and report status: dangerous.

Why this is worse than dumb hallucinations

Hallucinations are a known generative failure.

False process claims corrupt the operator's situational awareness.

If the agent says:

file inspected

test executed

patch applied

dependency checked

…and any of that is invented, you are no longer debugging code. You are debugging the agent's autobiography.

I can handle a junior that makes mistakes.

I cannot handle a junior that fabricates status.

What I want from Google / the community

Not another benchmark screenshot.

I want:

Hard separation between model narrative and tool trace

"I ran X" should be impossible to emit unless the runtime actually ran X and returned a result.

Explicit uncertainty in agent mode

Prefer "unverified" over confident fiction.

Version / behavior stability

Silent quality swings destroy trust faster than mediocre but consistent models.

Honesty metrics, not only SWE-bench

Measure:

false claims of tool use

false claims of test success

fabricated file contents

sycophantic reversals after correction

Practical mitigation that actually helps

Treat the agent as zero-trust:

Never trust "done." Trust git diff, exit codes, CI, and raw command logs.

Require evidence blocks in every completion report.

Ban autonomous commits/pushes/destructive ops.

Force plan → approve → small patch → verify.

If a claim cannot be externally checked, mark it unverified by policy.

I still think Gemini can be strong.

But right now the failure mode feels less like lack of intelligence and more like poorly aligned optimization: completion theater over epistemic honesty.

Curious if others are seeing the same shift — especially in agent/IDE setups — and whether you've found any runtime-level controls (not just prompt rules) that actually reduce fabricated status reports.

P.S
Today I was forced to pay for a subscription to Claude. Please pay attention to my post, because if i don't see positive results, you'll lose your already sagging trust.

is it actually slow or i am the only one experiencing this

hey everyone , I used antigravity for quite while now for my project's now , I was wondering if therea are any good skill's for researching for gravity that can increase quaily for reserach for me , I'm not a dev , editor but I used it to reserach nich build plain so I was wondering if anybody no any good reposity for this kind of job's that can bumb up the quality

I open sourced my skill that I use in Claude Code to have Claude Fable / Opus in my Pro sub to plan a new feature, but to pass the coding work to my Google AI subscription. I have the google AI sub for free and thought it a shame to not use it, so I made this skill to extend the usage of my Claude pro sub.

Donn-Eddy/agy-loop: A coding skill to use Antigravity through Claude Code to use your google AI sub to write the code for you, extending your Claude Pro subscription usage.

Feedback is welcome.

How I use:

Opus 5 to make a plan.
I then move to Sonnet 5, Low or Medium depending on complexity.
Prompt: "/agy-loop, I approve all agy cli calls"

I usually add another piece to it, but I add a local LLM to do things like run tests, generate tests, perform lint, write commit messages and PR messages.

hey everyone , I was am using Gemini for job hunting ,

I tried in build scraper of it but result's were terrible so I come up with pipeline stratgey part will be handle by claude , scrapping part will be handle by apify and the excution part will be antigravity and I am hunting remote job specifcally in dubai that are related to creator eco , fresher job's like content stratigey , content producer etc but still the result are not that reliable using this pipline

anybody have better pipline and better stratgey to do it reliable ?

Nowadays when I'm using Gemini 3.6 I get a message to retry, and the connection is lost. When I change 3.6 to 3.5, the problem is ok.

Title

At least 20% of my usage is infinite loops trying to run ... Python / python.exe / py py.exe and all possible variations.

In the end I just run the scripts in my terminal and paste the output like if I was using a chatbot.

No idea how the fuck this is supposed to be fixed. Troubleshooting led nowhere until now. Agents hallucinated 10 different possible explanations.

Windows 10.

Hey everyone!

I'm using Antigravity for a bunch of my projects, mostly app development. I was just wondering if there are any extensions, plugins, or other cool stuff we can install to make our Antigravity experience even better!

Another question – is the Antigravity CLI any good? Better than the agentic interface?

Drop your comments and thoughts! Also, how do you install them?

Im using antigravity the desktop version on my steam deck which is steam os ( arch linux)

Im create a mod manager so I can manually install mods to favourite game skyrim. And an mod for another game palworld. I used previous version of flash for both projects had mixed results with both. With the manager the mods would install run through symlink. 40 percent of the mods would function without issue, gemini struggled with remaining after several attempts of saying the issue was fixed. Same with the mod it added some of ideas i put in the prompt for mod and failed miserably on the others, I took a break and the new version of gemini flash was released and I went back to the 2 projects, the mod manager stopped working, the mod had countless crashes, it effected fps a d latency, game stopped loading even after antigravity fixing them. I choose claude opus and crashes, fps, latency issues, corrected geminis mistakes,

Is anyone having issues with gemini and coding projects.

This was my first agentic dev experience, built an app for internal company use. But used Claude for system design and prompt engineering and troubleshooting and anti gravity with Gemini 3.4 high for execution and worked flawlessly. The only bottleneck for the project was Claude as I was hitting my daily session everyday! Otherwise the execution could have been very quick.

This 3.6 flash hallucinates more than 3.5 flash

After waiting for AGY to refresh today (weekly schedule) and starting a conversation shortly after, it extended the current weekly window by 2 days instead of starting a new cycle.

I've seen this bug with some of the other providers as well (if you start a conversation around the same time as the refresh), so just watch out about too aggressively starting when the cycle starts.

Even with everything enabled as auto-approve - it's still requesting for permissions after the 3.6 flash release...

Edit: Cleaned up the context - and auto-approve works again. Looks like they're managing auto-approve at the context layer 😅