This was 10x boost for my dev speed - @gitbutler, I now work on multiple branches at the same time in the same running build with multiple agents, it works great for non-conflicting things, I am always building multiple features at the same time - when things do in fact conflict, usually when I want to review someone's else branch, an agent resolves it within a minute or less - no complicated learning of git butler, I control it via agent, it manages everything, I almost never use the butler app, all done via cli This will be 100x boost: - now that multi-branch workflow is solved, the next massive boost will come from multiplayer git butler like workflow, where we in fact work on multiple branches at the same time together with agents, everyone's always on the latest. It will happen sooner than people think. Going back to standard git workflow will feel like working with a shovel instead of an excavator

⋈ GitButler v0.22.0 is out with full support for native @github stacked PRs. It's the easiest way to get your Claude Code or Codex to fluently stack. Have multiple agent sessions operate on different parts of the stack in parallel, it 'just works' docs.gitbutler.com/ai-agents…

Today we are releasing Laguna S 2.1. At 118B total parameters, with 8B active per token, it does the work of models several times its size on agentic coding. It is remarkably persistent across long-horizon tasks. And it is small enough to run on a single NVIDIA DGX Spark. It is far more capable than anything we have created before, and I think it redefines what a model in its weight class can do. Laguna S 2.1 is an important model for Poolside. What it represents is even more important. If, five years ago, I had read a book that said that by 2030 everything economically valuable, scientifically interesting, and personally meaningful would be built on intelligence contracted from three or four companies, I would have called it dystopian science fiction. We are at a fork in the road of what kind of world we can have. I believe intelligence should and will become a commodity. The question is whether that intelligence comes from three companies, or from many people who can build it, own it, and shape it. The open ecosystem will not win by being the best in its own category. No one cares who is king of the open-source kingdom. People want the best intelligence for the task they are trying to do, with the right balance of quality, speed, cost, and control. If we want a different future, open models have to be on par with, or better than, their closed equivalents. Laguna S 2.1 is a meaningful step in that direction: capable enough to compete far above its weight class, efficient enough to run on hardware you can own, and open-weight so anyone can build on it. Open-weighting our models is the contribution we can make today toward a world where intelligence can be built and owned by many. And we will keep doing it. I am very proud of this team’s work. A big shout out to everyone at Poolside who made this possible, from infrastructure and data to architecture, pretraining, post-training, evaluations, and inference. Laguna S 2.1 is available today under the OpenMDW-1.1 license, with weights on Hugging Face and access through OpenRouter and our API. We are building toward a future where the most capable intelligence in the world can be owned and shaped by anyone. Laguna S 2.1 is one step. We are going to keep building until that future exists. poolside.ai/blog/introducing…