Posts tagged with "Gemini"

While it did appear something had changed for the better yesterday evening, things looked different again this morning. Before getting to work, I did a couple of quick changes to BlogMore; this time Antigravity seemed to use up a bit more quota in the same amount of time as I was working last night, but this time the reset window is much bigger.

I'm sure there's a method to this, but at the moment I'm really unclear what it is.

I guess I could ask it...

Yeah, let's do that.

Can you explain your quota cooldown time for me? Sometimes it seems to count down from 1 hour, others 5. Am I not reading this correctly?

You are reading the quota cooldown correctly! The reason the timer fluctuates between 1 hour, 5 hours, or other times is due to how the rolling usage window and compute-based limits work.

1. Rolling 5-Hour Window

Your usage limit is evaluated on a rolling window (typically 5 hours) rather than resetting at a fixed time of day.

• If you see a 5-hour cooldown: You likely used a large portion of your compute capacity very recently. You have to wait for that recent window to clear.
• If you see a 1-hour cooldown: You are close to the edge of your rolling window. A batch of high-compute requests you made 4 hours ago is about to fall out of the 5-hour window, which will free up capacity for you in 1 hour.

2. Compute-Based Usage (Not Message Count)

Your quota is consumed by compute rather than a flat number of messages. Compute is affected by:

• Chat Length: Every time you send a new message, the model re-processes the entire chat history. Longer conversations consume your quota much faster.
• Task Complexity: Tasks like code generation, deep thinking, or agentic workflows require more processing power and consume more quota.

Tips to Manage Your Quota:

• Start New Chats: For new topics or tasks, start a fresh conversation. This prevents the model from having to re-read long histories and saves significant compute.
• Use Clear, Targeted Prompts: Try to combine instructions rather than sending multiple short follow-up messages.

So, I don't think I'm any wiser after that. The explanation for the 1-hour countdown I saw last night has no connection to anything I did yesterday; I wasn't using Antigravity 4 hours earlier when I checked the quota near the end of that session. Guess I need to go and find and RTFM. Just like we used to in the good old days.

Something has changed with Antigravity since I first tried it out the other day. While looking at adding a related posts feature to BlogMore, I thought I'd give it another try out (having gone back to using Gemini CLI while I still could).

That first (and last) time I tried it, while on whatever model it decided for me out of the box, it chewed through most of the quota, with a 5 hour reset, in very little time at all. It was obvious that I'd never get anything of significance done in a good session.

This evening has been quite different. It wrote a very comprehensive change, doing quite a lot of work, and left me with a lot of quota and a short reset time once done.

A bit more testing and tweaking of the documentation followed, with me setting it off on a couple of bug hunts (which it found and fixed). By the time I was happy to call it an evening on this round of modifications, it had reset and I was green across the board again.

Now this I can work with!

I don't really know what's changed¹, or why. I think I saw something the other day about quotas being tripled, but this seems even more generous (at least in terms of the reset window). I guess I'm going to have to go digging to see if I can find what the story is.

I'm not getting my hopes up -- what can be given can be taken away at any moment (which is, of course, the ongoing theme of what I'm documenting here) -- but this does soften the landing somewhat.

As I've written about a few times in the last week or so, the journey with AI-based coding tools has hit an interesting time when it comes to prices, quotas, usage, availability and all that. Having come into all of this via a place where it was a flat fee, and where I didn't really need to think about input tokens and output tokens and so on, I'm pretty ignorant of what that all means in terms of scale. If I'm looking at a new tool and I see prices and/or quotas for in/out tokens, it means nothing to me. I can't relate to it. I've never had to care about it.

While using Gemini CLI to quickly make a change to BlogMore this morning, I was reminded that at the end of a session it does tell me this:

Seeing that got me thinking: is there a way to get the total usage for all of my sessions, or at least the sessions that have still been retained (I'm guessing they expire after a wee while)? After a little bit of searching I found ccusage. That looked exactly like the sort of thing I was after.

Now, this is only going to be good for Gemini (it says it supports Copilot too, but it seems to be failing to find any Copilot sessions), but it should give me a feel for what my token usage looks like.

I work on BlogMore on two different machines: the MacBook Air and also a Mac Mini I have in my office. Here's all of the available token usage data I can get out of the Air:

And also the same for the Mac Mini (which gets used less frequently for this sort of thing):

In both cases I've removed a couple of columns to make the tables fit better. The first was the model name (varying between gemini-3-flash-preview and gemini-3.1-pro-preview), the second was Cache Create (which was always 0 all the way down).

From what I can see, it would appear that these two tables do cover my increasing use of Gemini CLI for doing work on BlogMore (the first intensive use being back around the 5th of this month, if I recall correctly). So this would seem to be a reasonably informative way to view things.

All of which is to say, over a roughly three week period, while getting things done, I've used getting on for 20,000,000 input tokens, and around 600,000 output tokens (presumably I do also need to be keeping the 114,300,000 cache read tokens in mind too). With this in mind I might now be able to make more sense of the pricing I see for various tools.

The recent changes to pricing and usage, in relation to AI, aren't just about agents and coding. Not only have I seen GitHub Copilot and Gemini CLI hugely restrict their offerings for the same price, it's also come to at least one "general" tool I use too.

For a while now, as part of a Google One subscription I keep, I've had a Gemini AI Pro subscription. I've generally found this useful, mainly using the Gemini app on my iPhone to research things¹, and also commonly using the web application to help proofread blog posts, and sometimes explore coding problems. Another way I use it is via NotebookLM. The subscription has meant that I can do all of this without ever having to worry about hitting any usage limits. While I'm sure they were there, I was never aware of them and never hit them.

In the last 48 hours, along with the changes to the coding agent offerings, Gemini itself has moved to a compute-based usage limit approach.

Gemini will move to compute-based usage limits that will refresh every 5 hours until you reach your weekly limit. Calculation of your usage will factor in the complexity of your prompt, the features you use, and the length of your chat. Paid users have higher limits than users without a Google AI subscription.

The thing that bothers me about this -- and I've seen this with other companies in this market too -- is just how vague the wording is. Look at this table that is supposed to inform you about your usage limits, depending on your plan:

Okay, great, thanks to my Pro plan I get 4x the limits. Awesome. But... 4x what exactly? What exactly are the standard limits? How do I assess which plan is better for me? How do I compare Google's product against another offering?

I suspect, for the most part, I'll be fine where I am. So far today I've used Gemini to proofread the previous post I wrote, there was a bit of back and forth as I edited my post, and that cost me 1% of my five hour window.

What impact that has on my weekly usage, I don't know, but based on this it would appear to be almost nothing.

I can appreciate that it's been a bit of a free party for a while, and now each provider has to start to have this cost them less -- if not actually make them money -- before the whole thing collapses. Fair enough. But it's annoying as hell to not be able to gauge what I'm actually getting, or easily compare products.

That's not to say that I know how this can be communicated well. There's a flip-side to all of this. If I go and look at the Anthropic website and their detailed pricing information it seems to take it to the other extreme. There's so much you need to know and understand, and you'd need to know so much about how their models work and how your needs would interact with them... it feels like you need specialised training to comprehend any of it. While I can't find it back at the moment, I seem to remember a similar issue with trying to follow such information with GitHub Copilot.

If it doesn't exist already, I suspect there's a market here for a site that makes it incredibly simple to plug in your requirements and have a product recommendation be made.

Well, what a surprise, nobody could have seen it coming: it does seem to be bait and switch season in LLM/agent land.

As I mentioned earlier today, when I ran up Gemini CLI to have it work on a change to BlogMore in the background, I got a notification that I should be swapping to Antigravity CLI instead. I let Gemini CLI get on with the change anyway, but resolved to install Antigravity CLI and give it a go. While there's still a touch under a month of use of Gemini CLI to go (based on the blog post), it seems sensible to get to know the new tool as soon as possible.

Installing Antigravity was a little bit of a faff. Looking at the documentation, you have to install the main application itself first, authorise with that, and then you can install and use the CLI. Fair enough. Rather than download the DMG from their website, I decided to go with the Homebrew installation (I like to try and keep track of what I have installed and this helps me do that).

So I installed that, ran it up, went through some setup questions, then finally got dropped in something that looked like it wanted to be an IDE of sorts. Nah, I'm fine, I like to work elsewhere. But that was okay given that I just wanted to get to the CLI anyway. Before I did that though, having installed this app, I saw that it was showing a "Restart to update" notification. So I did that, waited a wee while, and then finally was presented with something that looked totally different. Now I had an application that looked almost exactly like the main Gemini website (or the Gemini macOS application).

So that was kind of weird.

Finally I was in a position to install the CLI itself. From what I can see it's not available via Homebrew yet, and the installation instructions are the usual "curl this through bash, trust me bro" affair. Having done that (yes, yes, I know...), I was all set.

Credit where it's due, when I ran it up it just worked. As in: I didn't need to authorise again or anything like that; the fact that I'd set everything up via the main application did seem to have done that job.

After this though, it kind of went a little downhill. The first thing I noticed was the set of models available was rather different from Gemini CLI. I mean, okay, that's fair, I guess you expect things like that to change, but in my inexperienced¹ view of what these agentic tools offer, it looked like all the options were a little more... pricey, perhaps?

Still, I'm sure that sensible defaults are chosen out of the box, so it seemed like a good time to give this new tool a shot. I had a nice little problem for it to work on so that felt like a great test. It's hard to say for sure, but I feel like an issue like that, with the right prompt, would have used up somewhere between 3% and 5% of the daily quota in Gemini CLI, using Auto (Gemini 3). That was the default out of the box and, aside from tapping the models to try and unstick them, I've never really set it to anything else and the results have always been fine. With all this in mind I set Antigravity to work. Given that there didn't seem to be any sort of "Auto" option, I let it go with Gemini 3.5 Flash (High), which is what it was set to out of the box.

Yikes.

As I read that, and as I recall what happened, it took about 25 minutes to get to a reasonable solution to the request, with me pushing back on a couple of wild choices it made about how to change the code around. In doing this it left me with just 20% of the quota free for the next four and a half hours.

Yikes.

This is fine in this particular situation, where I'm conducting a long-term experiment and often letting the tool run at reasonably self-contained problems, in the background, while I get on with other more important things. But if I were to try and use this, as I have Gemini CLI, for an evening of sofa-hacking, refactoring lots of code or adding a handful of new features... that's not going to be sustainable. Any such session is going to grind to a halt pretty quickly. Presumably the intended solution here is that I buy myself lots of "AI credits".

I will experiment more, and intend to try and work out what the point, purpose and impact of each of the models are, as found in Antigravity. Doubtless there's a smarter approach I can take where it'll cost less quota for similar results. What is for sure though is that Antigravity CLI is not a drop-in replacement for Gemini CLI. It seems to be a different way of working, with different models, and different considerations. Also with less openness too.

It's interesting to drop in on the Gemini CLI subreddit, where the members seem to be experiencing what the Copilot folk were a week or so back. People finding they're chewing through their quota in no time, only with the added frustration of having to transition to a whole new application that seems to be lacking some features they're used to.

None of this is shocking to me -- although I'll admit that I thought the Gemini CLI ride might last a wee while longer than it did -- nor, I'd hope, to anyone else, but it continues to be fascinating to watch the squeeze being applied all around this tool space. This is going to be an increasingly worse time for anyone wanting to mess with agents for hobby projects. The idea of a tool that lets you get unambitious projects done for the price of a coffee or two, per month: that was a reasonable prospect. When the real cost turns out to be similar to an actual utility bill for your home... I know some people have expensive hobbies, but this would not seem to be a rewarding one at the sorts of costs we're starting to look at.

Once again, it's going to be interesting to see how engineering departments, and AI-embracing companies as a whole, react, as they become more and more invested in these third-party services, and less able to actually do things themselves, while at the same time the suppliers of those services squeeze them harder to try and make this adventure pay off.

I just sat down at my desk and fired up Gemini CLI to get it to make a change to BlogMore, and I see this:

I've yet to actually look at Antigravity, so I know pretty much nothing about it at this point. After a brief glance at the link that was given it seems like it's a positive change, perhaps. Honestly, I'm not sure. But that's kind of moot, I don't really have a choice. Within a month Gemini CLI is going to stop working anyway.

This is yet another reminder that, while plenty of folk are pushing these tools as the answer to the "problem" of software development, they're not really stable tools, it's not really a stable market, and, to some degree, if you fully rely on these tools, you're constantly at the mercy of the whims of some other company.

I'm glad I have a project where I'm forcing reliance on them as an experiment, so I can see and experience this first-hand, but I'd be very concerned for someone who's fully bought into them.

Perhaps there's a market here for a "Killed by AI" website, much like Killed by Google?

Or, maybe I'm being unfair here; it could be that this is more akin to Google solving the chat problem by constantly moving people from one chat application to another, while also having chat abilities in all sorts of other products...

The first company I worked for full-time had two offices. One in the south of England, another in the north. Despite being a northern lad, I'd somehow found myself working in the southern office. While the company used a few languages, there was a split between the two offices, mostly driven by the fact that the northern office was more minicomputer-based (lots of DEC stuff as I recall), whereas at our office it was more PC-based (we were an Apricot dealership, amongst other things). At our office, the predominant language was Clipper (later to be called CA-Clipper).

At one point, at the other office, they hired someone to start doing Clipper coding up there too, and he was handed his first project, to add a new report to an existing system. After around three weeks, he just didn't turn up for work one day, called in to say he'd quit (or so I was told). Meanwhile, the work he had done didn't seem to be working. If someone took the newly-compiled system and ran the new report, nothing happened.

When the code was looked at, it became clear why. The new module had one line of code. Well, not one line of code exactly: it had a one-line comment.

* This is too hard. I can't do this.

That was it. He'd spent those weeks appearing to work on the requirement, but never produced a single line of actual code.

I felt really bad for the guy. He'd somehow managed to make it through the interview, somehow managed to convince others, and himself, that he was capable of working with Clipper and writing code (probably made easier by the fact that the office in question wasn't a "Clipper shop"). But when it came to actually getting on with a job, he'd been unable to get it done (and, apparently, had felt unable to ask anyone around him for help, which probably says a lot about that office and the industry at the time¹).

I bring this up because I was reminded of this story when I was tinkering with Gemini last night. While working on the optimised images PR, towards the end of the session, I asked it to make a particular change. It then started "thinking", and after a couple of minutes appeared to get to work on the problem. It kept printing, scrubbing out and printing again, lines of text of what it was apparently doing. This went on for something like five minutes. Eventually it announced that the work had been done, explained what it had changed, and how it had implemented the requirement.

I flipped to another terminal to test out the work and... no changes. Zero changes. Nothing to diff, nothing to commit.

I flipped back to the CLI app, mentioned that nothing had changed, and it then very quickly made some edits; nothing spectacular, a 14-line diff affecting five lines (to start with).

This is the first time I've seen this, and I guess yet another thing I need to keep an eye out for. Of course I would notice if I asked for some work to be done and it wasn't done (I did), but it feels like another method via which this "productivity tool" can make you less productive.

If you give me the under-qualified, solution-paralysed, entry-level developer who doesn't know how to proceed, I can help them. Their current inability to actually bash on the keyboard and make code appear isn't the problem here. Giving them a tool that will busy-work for five minutes and produce nothing isn't going to help them, neither will things improve if they're given a tool that does emit all the code. Removing the human element is going to remove safety, growth and also domain knowledge. I feel it's going to rot software engineering departments from within, if handled badly.

Watching people talk about agents as if they're the solution, and that writing code is now a solved problem, really troubles me. I won't question the idea that it can be a very useful tool -- goodness knows I've found it useful recently -- but I do question the common assertion that it finally is a silver bullet. I find this to be lazy, dangerous and harmful thinking.

Following on from this morning's initial experiment, I think I'm settling on a winner. Rather than be annoying and have you scroll to the bottom to find out: it's Gemini CLI. Here's how I found the process played out, and why I'm settling for one over the other.

Gemini CLI¶

Initially this was an absolute mess. After letting it initially work on the problem, the resulting code didn't even really run. The first go, and the three follow-up prompt/result cycles that followed, all resulted in code that had runtime errors. I'm pretty sure it didn't even bother to try and do any adequate testing. This is odd given I've generally seen it do an okay job when it comes to writing and running tests.

Once I had the code in a stable state, with all type checking, linting and testing passing, it still didn't work. No matter how I tried to use the new facility it just didn't make a difference. No images were optimised. In the end I dived into the code, with the help of its attempt at debugging (it added print calls to try and get to the bottom of things -- how very human!), diagnosed what I thought was the issue (it was looking in the wrong location for the files to optimise), told it my hypothesis and let it check if I was right. It concluded I was and fixed the problem.

Since then I've had a working implementation of the initial plan.

Once that was in place it's been a pretty smooth journey. I've asked it questions about the implementation, had my concerns set to rest, had some concerns addressed and fixed, improved some things here and there, added new features, etc.

All of this has left me with 18% of my daily quota used up. While I think this is the highest I've ever got while using Gemini CLI, it still feels like I got a lot of things done for not a lot of quota use.

GitHub Copilot¶

Initially I thought this had managed to one-shot the problem. Once it had finished its initial work the code ran without incident and produced all the optimised files. Or so I thought. Doing a little more testing, though, it became clear it was only optimising a subset of the images and it didn't seem to be producing the actual HTML to use the images.

On top of this it didn't even follow the full plan that was laid out in the issue it was assigned. For example: once I'd got it doing the main part of the work, it became apparent that it had pretty much ignored the whole idea of using a cache to speed this process up. I had to remind it to do this.

At one point I switched from the in-PR web interaction with Copilot, and used the local CLI instead. When I ran that up it warned me that I was already 50% of the way through some sort of rate limit and this wouldn't reset for another 3 hours. I think I was about 40 minutes into letting it try and do the work at this point.

After a bit more testing and follow-up prompts, I got to a point where I had something that looked like it was working; albeit in a slightly different way from how Gemini CLI did it (the Copilot approach was writing the optimised images out to the extras directory, mixing them in with my own images; Gemini opted for having a separate directory for optimised images within the static hierarchy).

At this point I will admit to not having carefully reviewed the code of either agent; that's a job still to do. But while Gemini got off to a very rocky start, with a bit of guidance it seemed to arrive at an implementation I'm happy with, and one that seems to be working as intended. While it didn't anticipate all the edge cases, when I asked about them it easily found and implemented solutions for them. Moreover, the fact that I could do all of this and confidently know the "cost" made a huge difference. Copilot seems to generally approach this like a quota or rate limit should be a lovely surprise that will destroy your flow; Gemini has it there and in front of you, all the time.

As for the general idea that I'm working on: I think I'm going to implement it. Weirdly I'm slightly nervous about building the blog such that it won't be using the images I created, but I also recognise that that's a little irrational. Meanwhile I'm very curious about the impact this might have on the PageSpeed measurement of the blog. While it's far from horrific, image size optimisation and size declaration seem to be fairly high on the things that are impacting the performance score (currently sat at 89 for the front page of the blog, as I type this).

The other thing that gives me pause for thought about merging this in, and then subsequently using it, is that I've just finished migrating all images to webp, and so saving a lot of space in the built version of the blog. Generating all the responsive sizes of the images eats that up again. With this feature off, the built version of the blog stands at about 84MB; with it on, this rises to 133MB. That extra 49MB more than eats up the 24MB saving I made earlier.

On the other hand: storage is a thing for GitHub to worry about, what I'm worrying about here, and aiming to improve, is the reader's experience.

I'm going to sit on this for a short while and play around with it, at least until I get impatient and say "what the hell" and run with it.

Given I'm almost certainly going to drop GitHub Copilot starting next month, I'm using Gemini CLI more and more for BlogMore. Yesterday evening, I used it to plan out an idea for a change to the application. Now that I've migrated all images to WebP, I thought it might be interesting to look at the idea of having a responsive approach to images. This is something I don't know a whole lot about (never having needed to bother with it before), but it also happens that I need to read up on this anyway for something related to the day job; given this, it felt like a good time to experiment.

Together with Gemini CLI a plan was created.

This morning, over second coffee, I've kicked off the job of implementing it and, honestly, Gemini CLI is really struggling. It "implemented" the change pretty quickly, within minutes, but it just plain didn't work. Since then I've had it iterate over the issue four times and now it's struggling to make it work at all. It's still beavering away on this as I type, and consuming daily quota at a fair rate too.

So, while I still have GitHub Copilot, this feels like a good point to play them off against each other at least one more time. Having saved the plan Gemini wrote last night as an issue, I've assigned it to Copilot (using Claude Sonnet 4.6). As I type this, I have Gemini racing to get this working in a terminal window behind Emacs, meanwhile there's Claude doing its thing in GitHub's cloud.

It'll be interesting to see if Copilot manages to one-shot this, for sure Gemini is far off a one-shot implementation.

As I've mentioned a few times recently, I'm using Google's Gemini CLI more at the moment; in part because I have a Gemini Pro account so it makes sense to use it, but also in anticipation of dropping anything to do with Copilot.

While I've had some troubles with it -- as can be seen here, here and here for example -- I'm mostly having an okay time. The code it writes isn't too bad, and while it seems to need a little more direction and overseeing than I've been used to while using Copilot/Claude, it generally seems to arrive at sensible solutions for the problems I'm throwing at it¹.

One difference with working with Copilot CLI that I have noticed, however, is that Gemini doesn't seem to care for cleaning up after itself. When faced with a problem it'll often write a test program or two, perhaps even create a subdirectory to hold some test data, run the tests and be sure about the outcome. This is good to see. It's not unusual for me to do this myself (or at least in the REPL anyway). But it really doesn't seem to care to actually clean up those tests. A handful of times now I've had it leave those files and directories kicking around. I've even said to it "please clean up your test files" and it's gone right ahead and done so, which suggests it "knows" what it did and what it should do.

This also feels like a new source of mess for all the people who commit their executables and the like to their repositories. That should be fun.

The thing I don't know or understand, at least at the moment, is if this is down to the CLI harness itself, or the choice of model, or a combination of both, or something else. I'm curious to know more.