GitHub's problems can technically be solved, but that doesn't mean they can be solved in a way where the economics still work out.
If AI use is 10x-ing the amount of infrastructure costs for GitHub but not 10x-ing the amount of money Microsoft brings in from GitHub then there is certainly no guarantee they will bother to solve these issues adequately.
And I'd be shocked if the revenue side of things isn't lagging way behind the extra usage post-AI-era, both because a lot of the new use is probably on the GitHub free tier, and because even on the paid tier most usage (other than CI/Actions, AFAIK) are on a fixed subscription cost per user regardless of how much you are slamming their servers and it is unclear how much they can raise that price without current enterprise users fleeing.
Twitter had a clearer goal that aligned with the financials... support more people stably, show more ads. Things are less clear with GitHub's business model where the free tier is a loss leader for the paid tier but the expansion in usage is likely to balloon the free tier usage at a far faster rate than the paid tier usage.
Also (and this part is admittedly far more speculative) if AI labs are to be believed this is still early days for AI usage and we'll still see massive usage growth over the next few years. If GitHub is already having existential trouble at the beginning of the curve, what hope do they have to scale up with their current business model if AI usage actually does ramp up exponentially?
I'd guess most of the costs incurred to GitHub outside of Actions as part of the enterprise flat-rate tier are a fraction of what enterprises are paying for AI in order to incur those costs in the first place.
If a company has to pay $5 extra to GitHub for every $100 of extra AI spend due to that AI use creating disproportionate load, I've got a hard time imaging that GitHub will be the thing that gets fled from.
As far as the free tier goes, it seems like there should be a path to making prohibitively-cost-incurring usage models high-friction. (e.g. limit the free Actions minutes that you get to a certain number per month.) As long as the limits are roughly proportional to the actual costs incurred, there's not too much risk of people fleeing to a competing service, because the only way a competing service would be able to undercut the costs is by taking steep losses themselves, which isn't much of a business model in order to attract people's code repositories.
But getting this infrastructure right is crucial for a future where most of the code is AI generated. GitHub puts microsoft in a good position to experiment and learn how to optimize GitHub (enterprise) for the future.
Nate b Jones on youtube, https://youtu.be/FDkvRl1RlT0?si=AEYlUchm_oalMSzf, argues that Atlassian might be an interesting acquisition for Anthropic, as it provide most of the context AI at enterprises need. When executed well, GitHub enterprise, can offer microsoft the same value: the context AI needs in the future.
That's not the problem. The revenue model they have is based on a certain amount of usage from the people who do not pay (you, for example), and a certain amount of usage from the people who do pay (enterprises).
If you 100x you usage, then they need 100x the infra, which means they need 100x the revenue.
At that sort of usage enterprises would rather self-host, and github would be left with only the free users, who are almost all like you now - hammering their servers but not paying for it.
If you self-host, for $5/m you can have your own VPS, but doesn't really solve the problem as much as you'd think - those are all vCPUs and shared, so you can't hammer them all the time either because then the provider has to increase their infra as well so fewer accounts share a single CPU.
Either way, if you want to generate code with AI at the speed that an agent can, you'll have to pay for it one way or another.
If that is the future, then source code hosting will be the least of our worries. The entire industry will collapse because the software will stop working.
