Ignoring the VC economics and awful name, I won’t be as pessimistic as everyone. I see the vision. That said, nobody knows what the AI future looks like. Entire’s entire thesis is a solution for something we don’t even know we need. It’s a massive bet and uphill battle. Traditionally, dev tool success stories come from grassroots projects of developers solving their own problems and not massive VC funded efforts that…
Ex-GitHub CEO launches a new developer platform for AI agents
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Re: Ex-GitHub CEO launches a new developer platform for AI agents
#242Either the models are good and this sort of platform gets swept away, or they aren’t, and this sort of platform gets swept away.
Re: Ex-GitHub CEO launches a new developer platform for AI agents
#243>CLI to tie agent context into Git on every push. Is this the product? I don't want to jump on the detractor wagon, but I read the post and watched the video, and all I gathered is that it dumps the context into the commit. I already do this.
> I already do this. Hows your ability to get an enterprise to mandate their 5000 employees to use it? That's what most of these types of rounds are about.
Re: Ex-GitHub CEO launches a new developer platform for AI agents
#244Re: Ex-GitHub CEO launches a new developer platform for AI agents
#245Either the models are good and this sort of platform gets swept away, or they aren’t, and this sort of platform gets swept away.
The most interesting thing about everyone trying to position themselves as AI experts is the futility of it: the technology explicitly promises tomorrows models will be better then todays, which means the skill investment is deflationary: the best time to learn anything is tomorrow when a better model will be better at doing the same work - because you don't need to be (conversely if you're not good at debugging and…
On the other hand, deeply understanding how models work and where they fall short, how to set up, organize, and maintain context, and which tools and workflows support that tends to last much longer. When something like the “Ralph loop” blows up on social media (and dies just as fast), the interesting question is: what problem was it trying to solve, and how did it do it differently from alternatives? Thinking through those problems is like training a muscle, and that muscle stays useful even as the underlying technology evolves.
Re: Ex-GitHub CEO launches a new developer platform for AI agents
#246Re: Ex-GitHub CEO launches a new developer platform for AI agents
#247Whether or not useful for agent collaboration, the data here will be more valuable than gold for doing RL training later on.
Re: Ex-GitHub CEO launches a new developer platform for AI agents
#248> Checkpoints are a new primitive that automatically captures agent context as first-class, versioned data in Git. When you commit code generated by an agent, Checkpoints capture the full session alongside the commit: the transcript, prompts, files touched, token usage, tool calls and more. This thread is extremely negative - if you can't see the value in this, I don't know what to tell you.
Re: Ex-GitHub CEO launches a new developer platform for AI agents
#249Re: Ex-GitHub CEO launches a new developer platform for AI agents
#250> Checkpoints are a new primitive that automatically captures agent context as first-class, versioned data in Git. When you commit code generated by an agent, Checkpoints capture the full session alongside the commit: the transcript, prompts, files touched, token usage, tool calls and more. This thread is extremely negative - if you can't see the value in this, I don't know what to tell you.
E.g., if you’ve ever wondered why code was written in a particular way X instead of Y then you’ll have the context to understand whether X is still relevant or if Y can be adopted.
E.g., easier to prompt AI to write the next commit when it knows all the context behind the current/previous commit’s development process.