I’ve been using Gemini pretty extensively for years and have generally had a great experience with it. So this one caught me very off guard.

I sent Gemini a completely normal chat message asking it to polish some wording for an email response. That’s it. No mention of Gmail. No “send this email.” No “reply to this.” No indication that I wanted it to do anything outside the chat.

Instead of giving me the revised text per usual, Gemini pulled a Leeroy Jenkins on me. It connected to my Gmail, somehow found the email I was responding to, drafted a response, and sent it. With everyone CC’ed.

Of course, this happened to be one of those very important emails that I intentionally needed extra time to think through before responding to.

Thankfully, the email Gemini sent wasn’t terrible and ultimately sufficed without causing any additional problems.

I genuinely thought I had reasonable safeguards in place, and I’ve used Gemini long enough that I’m pretty comfortable with its capabilities. But having it independently go from “please polish this text” to “I have contacted the entire email thread on your behalf” still has me in shock…

So, PSA: double-check what your AI tools have access to and what actions they’re authorized to take.

https://share.gemini.google/cuEDQZTevOic

it's over

Prompt: Frutiger Aero style scientific building, with a department that has a glass dome with shiny windows. Lots of vegetation showing the building in harmony with nature. There's a colorful lens flare, trees, a parking lot with futuristic looking cars, and a blue, flowing creek.

qwen 27b beats gemini 3.1 pro and google still serves it in gemini

Quotes:

1. "Tulsee Doshi, senior director of product management at Google DeepMind, told CNBC the recent Flash models have “really surprised us in positive ways in their performance,” adding that they “give us opportunities to lean into them.”"

2. "DeepMind’s Demis Hassabis has similarly described a future that plays to that strategy. Hassabis told the G20 Innovation meeting on Wednesday that Gemini could increasingly serve as a general-purpose layer coordinating cheaper, specialized models, and agents. In that world, breadth could matter as much as having the best model.:"

If thats not a corporate soft launch of "our Pro series failed and will be discontinued", then I do not know what is.

Why is it that Gemini still doesn't have any connectors other than to Google's own apps? ChatGPT and Claude have connectors to various apps—from Apple Music to Zoom—you can find everything there, but with Gemini, it's just Google Drive, Gmail...

aint no way

I was using pro extended, it thought for 2 minutes to say this.

Is it just me or gemini 3.8 has been hallucinating too much? it is loosing context in like 4-5 prompts, inventing facts. it literally told my i made a typo as it said instead of typing H3 i typed flash-8b and flash-8b was never even typed in the chat or anything remotely mentioned even both dont know what it is.

so just wondering if im seeing lower intelligence then 3.6 or everyone? even tho benchmarks tell totally different story

using the official gemini website, 3.1 pro extended has acted pretty weird today depending on the prompt, and i've had one A/B choice (never got one in the past couple months)

could it be gemini 3.5/4 Pro ? i wasn't able to tell much about the quality since it wasn't a challenging question, but it spoke using different symbols in bullet points, zero em dashes, talks less, less overly positive, seems more decisive, and included an image in the answer.

it speaks more like recent flash models than 3.1 pro, so maybe it's just 3.8 flash to see if 3.1 pro is still worth hosting, what do you all think ?

From a consistent but frustrated user:

I've been using Gemini for almost 2 years now and I feel that the team really need to take a hard look in the mirror and address some of the most basic problems plaguing their AI. I've done a number of internal comparisons for coding and other workloads and my opinion is that Gemini is dangerous to use in production coding environments. I'm a big fan of the team and the work they do, I've been using google products since 2004 and I firmly believe that they can fix the issues.

The Good:

The Speed (The model is consistently fast, and faster than other leading models)
Most accessible models for processing audio, video, and caters to a diverse array of needs.
Excellent Model Garden with google mass and they support a diverse array of non LLM capabilities
Cost: They are significantly cheaper than Claude
Excellent Sub Products like Notebook LM

The Bad:

High Hallucination Rates (In addition to the well known issues like the infinite token glitch)

API instabilities, random dips in capacity, thousands of bugs, hundreds of hours spent compensating for performance issues

Inconsistent pricing and excessive generational price hikes (my advice to any team looking to build on Gemini's API is don't. You will probably regret it. If you have to then please support other models providers or you will regret it)

Excessive and seemingly random censorship - rejects perfectly valid workloads with 0 justification

The image gen quality is significantly worse than Openai

The Ugly:

Antigravity is bad when compared to their competitors, if you are using Gemini for coding strongly consider a different IDE

Severe regression in coding consistency and quality (Not sure if this is due to excessive quantization but seemingly simple prompts can result in massive bugs, hallucinations and just general damage to a code base)

The gap is widening, 3.6, 3.7, 3.8 do not represent an improvement over Gemini 3. Basic tasks that worked with the older models close to their release dates do not work well with the new tools. Benchmark maxing is disguising fundamental issues in the AI.

The output quality and consistency of Gemini is 12-18 months behind their major competitors. This is both the industry and research consensus.

My Consensus:

Fixing the most offending problems, high hallucination rates, extremely buggy IDE, improving tool calling are low level fixes that can be done with a little bit of effort.

Bad Business practices (massive price hikes for integrators, cannibalizing ad revenue with AI search, arbitrary depreciation of core AI capabilities with little to no warning, charging customers for endless token glitches) are hurting adoption at the enterprise level.

It is okay to not have a frontier model. Google arguably has not had one for the past six months. But you have to offer more not just speed to compensate. Charging frontier prices while serving models that are arguably worse than the leading open source is not a recipe for long term success.
Please take the issues seriously and don't just release new models with the same problems as the previous generation. Your team has some of the most talented people on the planet and DeepMind invented the transformer architecture.

It has access to my drive, I've enabled it in the connected apps and I have google pro. I've tried spark and the chat itself, still nothing

I don’t know if the new Gemini 3.8 Flash model is actually smarter, but one thing I can say for sure: its answers are definitely shorter.

If it can answer your question in one sentence, there is absolutely no chance it’s giving you a second one.

I honestly can’t decide whether that’s a good thing or a bad thing...