Interesting, I didn't know minutes where free before.
Stopped my recurring subscription at the end of last year when it started spinning up actions for review. Which as a side effect doubled the time (or so) to do a review. Whereas before that I would open a PR, wait at most a minute or two and the review was already done.
Expect to see more of these kinds of announcements as companies need to start showing returns on their AI investments. It's hard to say how subsidized the current AI products are[1] but we're definitely getting a free lunch at VC's expense the moment.
[1] Ed Zitron speculates the actual prices with token based billing for heavy users will be something like 10x the subscription price, but this seems high.
Not that I give much credence to anything Zitron says, but the amount of inference you can get on a £200 a month OpenAI or Anthropic subscription is easily an order of magnitude more than what you'd get paying the same amount at subscription rate.
Although I would also point out that OpenAI recently tripled the amount of Codex inference you get per month for £200 (and to head off the suggestion, this is distinct from their current 2x promotion on £100/month plans)
> Not that I give much credence to anything Zitron says, but the amount of inference you can get on a £200 a month OpenAI or Anthropic subscription is easily an order of magnitude more than what you'd get paying the same amount at subscription rate.
Neither of those is how much it actually costs the company selling the service. And I have feeling they are running at loss here so the play is "get everything possible using LLMs then jack up the pricing"
There have been plenty of studies which indicate that inference considered by itself is almost certainly quite profitable at all the frontier labs. The problem is amortizing the cost of all the expensive training runs required to train new models into the revenue stream.
Yeah, I'm sure the numbers are a bit inflated compared to API, but with my Claude $200/month subscription I've supposedly consumed 12,160,410,828 tokens in April for a cost of $22,733.03.
Inference is cheap but training is quite expensive. Plus all the money they've invested and keep investing on hardware, data centers, etc. And evidently they also need to make a profit at some point.
Maybe from the perspective of traditional, turn-based chat. But when you start having developers command an army of agents that work around the clock, those cheap tokens start adding up fast...
If the unit-economics work out and they can sell $0.99 of tokens for $1.00, doesn't matter how many agents you spin up. The flat rate subscriptions can't last though.
> If the unit-economics work out and they can sell $0.99 of tokens for $1.00
I think the margins have to be a lot higher than that in order to give investors the return they're expecting, to continue the never-ending training treadmill, and to build more and more datacenters to accommodate people basically DDOS'ing the GPUs in order to run their workloads.
Yes, in theory what you said makes sense. But the tightrope these companies have to walk is that the per-token costs still have to be low enough that developers and companies don't just say "ehhh I guess we can still do all this work the old-fashioned way" but ALSO high enough to cover the massive expenses AND astronomical returns everyone's expecting.
VC investment isn’t about margins, it’s about finding a unicorn. It doesn’t matter if margins are negative if your product is dominant in the market as you can fiddle with the margins after the fact. You just need to be invested long enough to see everyone else fail.
I imagine the calculus changes a little bit when you've invested hundreds of billions (trillions?) of dollars in a relatively short period of time. Priority number one is probably getting that money back. I think the fact that providers are RAPIDLY cutting back/jacking up prices points to this being the case.
The problem with AI is that there doesn't seem to be a durable barrier to entry for a "winner take all" dynamic to work. The biggest barrier to entry seems to be the capital needed to train the models, but even free models are getting "good enough" for some uses and there's little friction to stop users from switching between models. Many frontends make this explicit by letting you pick the model you want to run inside the same environment.
If prices go up, I suspect a bunch of folks will jump to cheaper, less capable models instead of eating the added cost. The whole value proposition of AI in enterprise is around cost-cutting, so that mentality is likely to persist when choosing which model to pay for.
It's gonna be interesting to see how this plays out. Usually a tech rugpull like this lasts a number of years. And this sort of has, but the agentic stuff has really only caught on like wildfire in the last, I dunno, six months or so. The rugpull would be way more effective if there could be several years of getting developers addicted to this development paradigm, but alas, the VC money burned was too great to subsidize for very long.
If that is true, we’ve discovered that offering a product for $1 the $17, yields to dramatically shorter runway but possibly more addicted users. Can’t wait for products offered at $1 the $100.
Its also a weird way to cede control of the market to the foreign model vendors, because I'm reasonably sure that DeepSeek et al aren't subsidising tokens to the same extent that the big 3's subscription models have been.
I think there's "sort of" a moat for non-Chinese vendors. As much as people distrust the US right now, I think deep down inside everyone knows that the second you let a Chinese provider do inference on your codebase they're gonna suck up every bit of it. But hey, cheap tokens, right?
So you'll probably never see government customers allow that and neither will a lot of commercial customers.
Why do we assume us providers aren't doing the same? Also all the Chinese providers are giving open weight models. Many you can run locally.
I don't see the risk. If your code is easily AI generated you don't have a moat anyways. A Chinese competitor probably won't have as easy of a time as a US one of you operate in the US
The US has robust IP and trademark law that allows companies some amount of chance to find a legal remedy to anyone who clones their business. China is notorious for protecting local companies from foreign IP suits.
Further, at a lot of companies, the risk has to be acceptable to shareholders and auditors. Perceived risk is often a more powerful motivator than actual risk.
Once your code, images, etc pass into the slop machine it is owned by whoever generated it later. Obviously they would need a new logo, llc, and some ui theme tweaks. Otherwise none of these AI coder products would exist.
Also, how long do you think openai, Microsoft, Google, anthropic, etc could delay a lawsuit while you pay hundreds of thousands in legal retainers? 5 years? 10?
From the perspective of someone currently living in the EU... I'd say thats pretty much a wash (or even slightly tilted in China's favour) for folks outside the US
Fortunately there’s plenty of open weight models that are just safetensors and you have a wide variety of providers to choose from, as well as just hosting it yourself.
Maybe, but this is also a company whose parent organization is worth a trillion+ dollars that have monopolies in multiple verticals. I know American corpos hate the idea of protecting the commons and would rather fuck it raw to fulfill their carnal urge for profit, but you know there are some public goods and services worth fulfilling for a highly productive industry.
Maybe the government should nationalize GitHub at this point as it is absolutely critical for US infrastructure and MSFT has shown to be a terrible steward for the public.
Agreed, especially weird since they just rolled out usage-based billing for Co-pilot. It would make a lot more sense to just re-use that usage instead IMHO
Yeah my mistake, I wasn't very clear in my comment.
Though actually the more I think about it, I think this change actually does make more sense. In the case of the AI running on GitHub side, that does feel pretty equivalent to CI minutes. I would hope that the number of minutes they bill for is pretty minimal though, since the vast majority of that will be I/O waiting on the agent to return
My guess is that they're moving to a spot where they can pitch an LLM "doing something" as an action, and copilot is their first move. I don't see it as crazy to think of a "copilot code review" in a similar way to other build actions.
But also - enterprise accounts already have budget assigned to github actions, and this allows them to start billing right away without having to actually get (or allow) businesses to evaluate the return of having copilot do code reviews.
So seems like it's a mix of immediate incentives and long term architecture. I don't like it, though. If I were an enterprise my first response would be to turn it off.
> enterprise accounts already have budget assigned to github actions, and this allows them to start billing right away without having to actually get (or allow) businesses to evaluate the return of having copilot do code reviews
Hang on, I read this as copilot reviews with bill both actions minutes and AI credits. Did I miss something?
I'm assuming the running of the model is consuming the tokens, and the client coordinating and orchestrating the calls to the model to perform the review is happening in an action runner, thus using action minutes.
Copilot Code Reviews are Actions workflows. Just privileged ones you can't edit the YAML for. They even litter your Actions tab list and Deployment environments.
For all the hate it gets, I use them regularly with little to no complaints.
I have always found it as a pretty nice to have feature if I am already using GitHub. It’s far from perfect or robust but I can get a lot of use out of it with low to no friction.
Which is fair but inversely we do many builds throughout the day most business days and have not had an impact where we noticed it. Could also be that we deploy often and frequently and have setup our builds to be as quick as possible so any issues would likely go unnoticed.
Yeah totally. We use GitHub + actions for backend, and self host Perforce + TeamCity for our main game codebase. We had 0 downtime in 12 months on our TC as a comparison. I know there’s a difference between running an internal service and developing a global scale platform that is abused, but as a user I don’t care about those concerns, I care about the platform being up!
Github has recently changed the way their status page tracks uptime in the name of "transparency"[0]. "Partial Outages" are now only worth 30% of their duration, and "Degraded Performance" is worth none, so their uptime values are now wildly inflated.
Cursed by mighty Redmond to roam the market wasteland until death, one of the seventy some odd beleaguered CoPilot products is now being lashed like a haggard burro to the dying light of a once prominent development platform that, upon itself, were pinned the hopes and dreams of a commercial software juggernaut to capture the hearts and minds of developers all around the world.
Good thing GitHub has plenty of built-up goodwill to spend down. If they didn’t this cascade of (probably necessary but nevertheless negative for customers) changes might be the tipping point to push a lot of companies to seek other options.
> Good thing GitHub has plenty of built-up goodwill to spend down
Do they, though? I don't know a single person who uses GitHub who actually likes it. It's far more often something like "it's fine, but I miss (GitLab|Gerrit)" or "I stopped using it for personal stuff and moved to (Codeberg|GitLab)."
The brand recognition among non-technical folks is really the strongest selling point in my eyes. And that's irrelevant to ~95% of software development.
GitLab is getting ensh*ttified as well. Rarely a day passes when they’re not trying to somehow push their AI features on me, even though I never asked for it. Thinking about moving to managed Forgejo.
They burned through their goodwill years ago and are insistent on reminding us all that they are now exactly as shitty as Microsoft because they it’s all Microslop worst customer practices.
But I think the issue is that my situation (solo dev, mono repo) is just not right for a dedicated instance.
With only 1-2 runners, the pipeline is slow (low parallelism) and resource constrained.
And at least 50% of the time its idle (I'm not working/sleeping).
I guess what I'm really looking for is for some kind of aggressive autoscaling, and aggressive caching.
I tried a couple of things (GHA, Dagger + Hertzner, Buildkite)
And Im just not too sure theres going to be any out of the box solution since my priority is essentially to minimize cost and maximize efficiency. Not really a great customer for any providers.
Im tempted to just get agent to build something out quickly with cloudflare workers + spot instances.
Not sure of what current prices look like but an old desktop sitting on the floor of your office might work well for you. You would need decent internet but running a single node kubernetes cluster as a GitHub action runner has worked well for others I know.
A buddy of mine runs his whole CICD setup off an old gaming desktop. They use tailscale to connect to their hosted infrastructure and set it up as a GitHub action runner.
I self-host Drone CI still. I think Harness is in the slow process of letting it rot (it still gets at least some updates, though), which is kind of a shame, but it still does just fine for my CI needs (solo usage as well).
Very easy to stand up, does just fine. Definitely doesn't have the "library" of prebuilt actions that GHA does, but for the most part... I consider that a plus.
Otherwise it's very similar in concept - define actions in a yaml file, run commands on an image, webhook integration with most repo providers.
I run it on some old hardware locally (k3s cluster on old machines) and it outperforms the 1000 minutes from GHA easily, and costs basically nothing but some maintenance and time.
I've been keeping my eyes open for something new in this space since Harness bought it, though - so if other folks have recommendations I'd be interested in alternatives.
The better your code is architected, the less powerful model you’ll need for it to make sense of it.
E.g. a well-designed deployment (infrastructure-as-code) repository doesn’t need a frontier model to be understood well-enough to create a new job / service using sibling jobs / services as templates.
And this already saves me dozens of minutes per week, although it’s not a 2x multiplier in my efficiency.
The issue is that local models are dumb and tend to make mistakes than look good at a first glance. So any "saving" is quickly ruined by having to do an extensive review. You might as well just write things yourself.
I use it as code scaffolding, which means in a way I’m often rewriting it. For me, writing from scratch isn’t the same amount of effort as using a code scaffolding tool.
Because it doesn't even come close to frontier models in intelligence/speed/price. I can run my 3090 nonstop and rack up an electricity bill that costs more than a subscription and get worse results that are slower. They are ok for simple/non complex things, but that's not really what I need AI for.
I feel the opposite. I do need AI for simple things. Complex things are usually so ill-defined that the actual bottleneck takes place in meatspace, not in my IDE.
The claim was "It is cheaper", not "It will be cheaper". Until it actually _is_ cheaper, it doesn't make much sense to purchase $10k+ in hardware to run local models that are still worse than the frontier offerings.
No it's not. AI products are quite often subsidized. AI inference very certainly is not.
There are more and more independent AI inference providers without VC backing that serve open weight models on a ~cost-plus basis that show that subsidies are not significant for AI inference.
They never really get tight very long: the various states are way too busy flooding the world with endless money printing to kick the can of the public debt always further.
Covid financial crash? We went to new highs. 2022 tech flash crash (Meta and Netflix did -75% for example): we then went to new highs.
The only way for governments who ever spend way more than they bring in taxpayer dollars is to de-valuate the currency.
So "financial markets getting tighter": probably won't last.
As you said yourself: Quantitative easing did not solve anything. We keep kicking the can down the road, and the problems grow exponentially every time. This approach won’t work forever. In fact, we may be past the tipping point already.
Local models are nowhere near the performance of frontier models. Unless you can fork out like £100k to get something passable in terms of performance.
Won't competition likely keep prices low? At first maybe not, but sooner or later open models will catch up, then it's a completely open market for anyone to host and sell services.
Unclear why this is so shocking. Sounds like they have been making migrations on their underlying systems and this better aligns with the cost to run. I would be curious how many are using their code review system.
is there any data on how many Actions minutes a single copilot review actually takes? the announcement doesn't mention it, and for a team doing 20+ PRs a day that number adds up fast.
They should also remove Copilot code reviews from being counted as metrics in a PR.
I've seen some projects that use it and you open the PR page to be greeted by every PR having 3-20 comments but when you goto the actual PR, there's no one except the contributor with a bunch of Copilot feedback.
It gives a false message that the PR is resonating with folks and has real activity. I wonder if GitHub did this on purpose to make engagement seem higher than it really is.
Reddit is slowly dying for me for that reason. So many bot / bot like accounts that seem ... off / hidden histories. Trust level with any given comment or post now is reaching 0 fast.
It's a bummer because it's hitting a lot of users and even valid users who don't communicate good are getting hit hard too with skeptical responses.
Yep, allowing users to hide history has made it straightforward for bots to exist unchallenged.
Previously a quick scan of comment history would make it obvious you're looking at an LLM, now you're stuck arguing over a one off comment where they can get away with benefit of the doubt.
Where I work that many comments could be taken as a bad thing: "i've seen too many comments finding issues or nitpicks with your PR, why aren't you doing a better job before submitting it for review??"
I started moving my repos off GitHub weeks ago, but I'm still waiting for a "good" GitHub competitor to appear. GitLab sucks (if you're not a company and like unnecessary complexity), Codeberg is slow and limited (and has weird mods), Sourcehut UX is weird (and being DDoS'd), Gitea Cloud didn't even have a working login page last time I tried, BitBucket isn't the worst but it has quite a few problems (& isn't set up for public repos/search). Please can somebody start a simple, reliable hosted GitHub alternative? I'd pay for it...
If you want collaboration for your team, then a small vm with forgejo (if you need PR) is enough. It can be behind a vpn if you do not want to bother with securing it against the whole internet.
If you want to make your repos public, you could use cgit and the like.
This is funny, but Copilot is still an interesting case-study and (probably) failed predictor of where we are headed.
We all know, and have known for a long time, that the AI labs selling dollars for a nickel are going to pull that rug, and up that price, at some point.
Copilot, though, has been consistently the weakest mainstream AI coding offering. Inferior to Cursor or Windsurf at editor completions, inferior to Codex, Claude, OpenCode, blah blah blah, at agentic coding and also the old-school chat-style...
And now, it's no longer cheap AND now sucks even more than it has all along — the new $39/month plan is not only worse than all its competitors, but worse than its own $10 plan was a month ago — by a lot.
The thing is, you can't jack the price up unless you're good enough — at least on some axis, to some customer segment — to jack the price. And when you're not good enough, and you have vastly superior competitors who are not doing that yet... you're just forfeiting the game.
Which I agree, Copilot should do — it's the Windows Phone of AI coding assistants, after all — it still seems weird to me to just commit humiliating suicide rather that trying to make some deal with one of those superior competitors.
Instead of just jumping into a dumpster and lighting yourself on fire.
Github was already struggling with bazillions of throw-as-much-crap-on-the-wall software running in actions, and now the world is running throw-as-much-LLM-crap-on-the-wall computation, as unstoppable as the pre-LLM era. Turning compute into excrement as fast as the planet is filled with it. Excrement being "Github Copilot code review" in compute world, and no need to draw what it is in our real world.
Weird that Anthropic decided to build a Claude Code Routines toilet.
We are slowly inching closer to the point where AI and AI products will be billed for what they cost. We are currently living in the heavily discounted world where everything subsidized to the point where a lot of it is free. It seems like they can't or won't keep that up anymore. My prediction is that whenever one of the big companies raise their prices or move features to higher tiers others will follow soon. They all feel the pressure and non of them want to give away more money than they need to.
I wonder if managers will be as excited about AI when the prices go up.
It's humorous to me that I can do the work of an AI with nothing but a coffee and an occasional sandwich and yet they talk about AI as if it's some sort of magic hack to productivity.
What they don't like is paying money for the work, that's all that matters to them.
This is already happening. For new Anthropic enterprise accounts you are billed at api token prices (maybe with a small volume discount). Anthropic makes a profit on those tokens. (Sure, that profit does not cover the model training costs, but that’s a separate issue.) It’s the subscriptions for individuals (e.g. Claude Max) that are still subsidized below cost.
> I wonder if managers will be as excited about AI when the prices go up.
Companies are willing to pay the api pricing. Engineering time is very expensive and AI coding agents actually work now since December and are actually showing measurable productivity gains, finally. It’s a good deal to make (obviously, with caveats: you need to make sure your tokens are going on productive tasks that will actually grow revenue) and anyone who penny-pinches is making a strategic mistake.
Stopped my recurring subscription at the end of last year when it started spinning up actions for review. Which as a side effect doubled the time (or so) to do a review. Whereas before that I would open a PR, wait at most a minute or two and the review was already done.
[1] Ed Zitron speculates the actual prices with token based billing for heavy users will be something like 10x the subscription price, but this seems high.
Although I would also point out that OpenAI recently tripled the amount of Codex inference you get per month for £200 (and to head off the suggestion, this is distinct from their current 2x promotion on £100/month plans)
Neither of those is how much it actually costs the company selling the service. And I have feeling they are running at loss here so the play is "get everything possible using LLMs then jack up the pricing"
Inference is cheap but training is quite expensive. Plus all the money they've invested and keep investing on hardware, data centers, etc. And evidently they also need to make a profit at some point.
Maybe from the perspective of traditional, turn-based chat. But when you start having developers command an army of agents that work around the clock, those cheap tokens start adding up fast...
I think the margins have to be a lot higher than that in order to give investors the return they're expecting, to continue the never-ending training treadmill, and to build more and more datacenters to accommodate people basically DDOS'ing the GPUs in order to run their workloads.
Yes, in theory what you said makes sense. But the tightrope these companies have to walk is that the per-token costs still have to be low enough that developers and companies don't just say "ehhh I guess we can still do all this work the old-fashioned way" but ALSO high enough to cover the massive expenses AND astronomical returns everyone's expecting.
If prices go up, I suspect a bunch of folks will jump to cheaper, less capable models instead of eating the added cost. The whole value proposition of AI in enterprise is around cost-cutting, so that mentality is likely to persist when choosing which model to pay for.
So you'll probably never see government customers allow that and neither will a lot of commercial customers.
I don't see the risk. If your code is easily AI generated you don't have a moat anyways. A Chinese competitor probably won't have as easy of a time as a US one of you operate in the US
Further, at a lot of companies, the risk has to be acceptable to shareholders and auditors. Perceived risk is often a more powerful motivator than actual risk.
lmao tell that to the artists, authors and foss contributors whose work has been cloned into the llm oracle
Also, how long do you think openai, Microsoft, Google, anthropic, etc could delay a lawsuit while you pay hundreds of thousands in legal retainers? 5 years? 10?
From the perspective of someone currently living in the EU... I'd say thats pretty much a wash (or even slightly tilted in China's favour) for folks outside the US
Maybe the government should nationalize GitHub at this point as it is absolutely critical for US infrastructure and MSFT has shown to be a terrible steward for the public.
That’s why.
Though actually the more I think about it, I think this change actually does make more sense. In the case of the AI running on GitHub side, that does feel pretty equivalent to CI minutes. I would hope that the number of minutes they bill for is pretty minimal though, since the vast majority of that will be I/O waiting on the agent to return
Done that way it obfuscates cost of the code review and I think that's on purpose
But also - enterprise accounts already have budget assigned to github actions, and this allows them to start billing right away without having to actually get (or allow) businesses to evaluate the return of having copilot do code reviews.
So seems like it's a mix of immediate incentives and long term architecture. I don't like it, though. If I were an enterprise my first response would be to turn it off.
Hang on, I read this as copilot reviews with bill both actions minutes and AI credits. Did I miss something?
[1] https://www.githubstatus.com/
I have always found it as a pretty nice to have feature if I am already using GitHub. It’s far from perfect or robust but I can get a lot of use out of it with low to no friction.
[0] https://github.blog/news-insights/company-news/bringing-more...
It seems that for "actions", the trailing twelve months availability is 98.67%.
Trailing 3 months is even worse :/
My org noticed the incident at 12:19p ET, Github pushed their first update at 12:38p, and pushed that it was mitigated at 5:48p.
[1] https://securitylab.github.com/resources/github-actions-prev...
Do they, though? I don't know a single person who uses GitHub who actually likes it. It's far more often something like "it's fine, but I miss (GitLab|Gerrit)" or "I stopped using it for personal stuff and moved to (Codeberg|GitLab)."
The brand recognition among non-technical folks is really the strongest selling point in my eyes. And that's irrelevant to ~95% of software development.
I’m blowing through my 1000 mins in days.
Thinking to either pool some free tiers or figure something out with spot instances.
Also is it just me or is CI/CD tooling still sort of rough all around.
Hetzner has cheap VPS that I host my CI on. It costs like $10/month.
Pick the cheapest region, since CI runners location doesn’t matter much.
But I think the issue is that my situation (solo dev, mono repo) is just not right for a dedicated instance.
With only 1-2 runners, the pipeline is slow (low parallelism) and resource constrained. And at least 50% of the time its idle (I'm not working/sleeping).
I guess what I'm really looking for is for some kind of aggressive autoscaling, and aggressive caching.
I tried a couple of things (GHA, Dagger + Hertzner, Buildkite)
And Im just not too sure theres going to be any out of the box solution since my priority is essentially to minimize cost and maximize efficiency. Not really a great customer for any providers.
Im tempted to just get agent to build something out quickly with cloudflare workers + spot instances.
I also have some other nice to have requirements:
- ts/code over config
- locally runnable and testable
- preferably no lock in
- repeatable/reproducible
A buddy of mine runs his whole CICD setup off an old gaming desktop. They use tailscale to connect to their hosted infrastructure and set it up as a GitHub action runner.
For a solo dev this might be the way to go.
My wife uses my old gaming desktop for her ux design work as well.
And I was thinking of using the gpu to run some tts models.
Now to just figure out a way to run it all on windows and have it auto start when she logs in.
So what? its $10 a month. Why do you need to chase 100% utilization?
And use can use that to host your website, a game server, maybe some other projects...
Best decision we ever made
https://docs.drone.io/server/provider/github/
Very easy to stand up, does just fine. Definitely doesn't have the "library" of prebuilt actions that GHA does, but for the most part... I consider that a plus.
Otherwise it's very similar in concept - define actions in a yaml file, run commands on an image, webhook integration with most repo providers.
I run it on some old hardware locally (k3s cluster on old machines) and it outperforms the 1000 minutes from GHA easily, and costs basically nothing but some maintenance and time.
I've been keeping my eyes open for something new in this space since Harness bought it, though - so if other folks have recommendations I'd be interested in alternatives.
It is time to setup local models. It is cheaper, and you already have a computer. Why keep it idle and pay someone else for their CPU?
E.g. a well-designed deployment (infrastructure-as-code) repository doesn’t need a frontier model to be understood well-enough to create a new job / service using sibling jobs / services as templates.
And this already saves me dozens of minutes per week, although it’s not a 2x multiplier in my efficiency.
Once it is cheaper, there will be more demand so it will no longer be cheaper. Buying now gets current prices (though demand is still fairly high).
There are more and more independent AI inference providers without VC backing that serve open weight models on a ~cost-plus basis that show that subsidies are not significant for AI inference.
They never really get tight very long: the various states are way too busy flooding the world with endless money printing to kick the can of the public debt always further.
Covid financial crash? We went to new highs. 2022 tech flash crash (Meta and Netflix did -75% for example): we then went to new highs.
The only way for governments who ever spend way more than they bring in taxpayer dollars is to de-valuate the currency.
So "financial markets getting tighter": probably won't last.
I've seen some projects that use it and you open the PR page to be greeted by every PR having 3-20 comments but when you goto the actual PR, there's no one except the contributor with a bunch of Copilot feedback.
It gives a false message that the PR is resonating with folks and has real activity. I wonder if GitHub did this on purpose to make engagement seem higher than it really is.
I want to know how many real humans read my post, commented, shared etc.
Clankers can keep their own counts.
It's a bummer because it's hitting a lot of users and even valid users who don't communicate good are getting hit hard too with skeptical responses.
Previously a quick scan of comment history would make it obvious you're looking at an LLM, now you're stuck arguing over a one off comment where they can get away with benefit of the doubt.
If you want to make your repos public, you could use cgit and the like.
We all know, and have known for a long time, that the AI labs selling dollars for a nickel are going to pull that rug, and up that price, at some point.
Copilot, though, has been consistently the weakest mainstream AI coding offering. Inferior to Cursor or Windsurf at editor completions, inferior to Codex, Claude, OpenCode, blah blah blah, at agentic coding and also the old-school chat-style...
And now, it's no longer cheap AND now sucks even more than it has all along — the new $39/month plan is not only worse than all its competitors, but worse than its own $10 plan was a month ago — by a lot.
The thing is, you can't jack the price up unless you're good enough — at least on some axis, to some customer segment — to jack the price. And when you're not good enough, and you have vastly superior competitors who are not doing that yet... you're just forfeiting the game.
Which I agree, Copilot should do — it's the Windows Phone of AI coding assistants, after all — it still seems weird to me to just commit humiliating suicide rather that trying to make some deal with one of those superior competitors.
Instead of just jumping into a dumpster and lighting yourself on fire.
Weird that Anthropic decided to build a Claude Code Routines toilet.
I wonder if managers will be as excited about AI when the prices go up.
What they don't like is paying money for the work, that's all that matters to them.
> I wonder if managers will be as excited about AI when the prices go up.
Companies are willing to pay the api pricing. Engineering time is very expensive and AI coding agents actually work now since December and are actually showing measurable productivity gains, finally. It’s a good deal to make (obviously, with caveats: you need to make sure your tokens are going on productive tasks that will actually grow revenue) and anyone who penny-pinches is making a strategic mistake.