While it can be super powerful, I wish there was a quicker "in memory" agent solution where each agent keeps in its own RAM the list of files modifications ("patch") it recommends to apply to solve current issue. Then we could apply that patch depending on what we're doing, if we have others patches to apply before etc.
Also even if agents can work in parallel, sometimes we only have 1 of them in front of us and if we already know what's the next thing we're gonna ask, we'll still wait for the previous task to be completed before sending the new prompt. I'm not sure how to improve this async problem, I guess I could launch multiple agents in parallel but I wouldn't get sharing of the chat history between the different agents, and when I work I usually work on related issues that depend on each others, thus I do need some kind of global or shared context between agents analyzing codebases and creating patches.
Anyone has ideas over how to improve those AI coding agents workflows ? Maybe latest versions of GitButler https://gitbutler.com/ but I'm not sure, and it does use git worktree behind the hood
In Counter-Strike, smoke grenades used to (and still do, to an extent) dip your FPS into a slideshow. You want to ensure your opponent can't exploit these things.
1. Valve wants to avoid regulatory scrutiny over loot boxes
2. Valve wants to limit prices; the Steam marketplace only allows items up to 2500 usd to be traded. By averaging out the item prices (knives drop, covert-class increases) they are able to indirectly limit the usefulness and harmful side effects (money laundering, decentralized liquidity) of 3rd party trading sites