As AI becomes more capable, the question is not only who builds the best models. It is who gets to build them at all. A founder’s view from @eisokant on where Poolside stands today.

Just finished reading the latest technical report released by @poolsideai for Laguna. It is so well written and information-dense, covering all stages of a large-scale training run. Each decision and assumption was clearly explained and concisely referenced. The Model Factory was a very interesting piece, describing how they turned the whole pipeline of training, checkpointing, ablating, and data versioning into an industrial process. This made it easier for researchers to focus on coming up with hypotheses and testing them. My favourite sections were the Model Factory, Data Versioning, and the infrastructure setup (i really love the DevOps stuff). What did you guys like?

those GPUs are waiting go build something fun with Laguna XS.2!

Love seeing the work @RedHat_AI and @vllm_project are doing to make Laguna XS.2 easier to run. Red Hat AI trained a DFlash speculator: a 0.6B drafter that predicts 8 tokens per pass, with Laguna verifying the output. So builders get faster generation without changing output quality. With vLLM support and FP8/NVFP4/INT4 checkpoints through LLM Compressor, it’s also easier to tune for different latency, memory, and hardware constraints. Grateful for the team building the infra that makes open models easier to use, serve, and improve!

Super comprehensive writeup that covers many frameworks & case studies on async RL. I learned a lot from the discussion of adding bias to the objective and how techniques that introduce bias (e.g., TIS CISPO) help stabilize smaller batches but scale more poorly.

London raised the bar. SF, gear up 👀

this week I was at the @poolsideai talk hosted by @CrusoeAI and heard @varunrandery discuss what he calls the "agent API." tldr; we stop sending text and getting text back, and start sending a unit of work and getting the finished result back, technically it's clean, and I liked it. then I thought about it longer and started to wonder what's left for the rest of us to build, and what it means for SaaS more broadly. wrote it up: dennisy.me/notes/from-chat-c…

What a weekend. Around 30 teams showed up to build on Laguna XS.2, and the bar was very, very high. Winners below 🏆 1st: Overthinking Machines Labs @emilfristed Pseudo-full-duplex with text-only models through dialogue modeling with silence tokens. huggingface.co/spaces/poolsi… 2nd: Coding Kernels by the Pool Charlie Masters, Evan O’Leary, Jessica Mak Laguna-Dense: a ~3B fully dense distillation of Laguna XS.2 for generating CUDA kernels from PyTorch. huggingface.co/EvanOLeary/la… 3rd: attnvq @alaradirik Attention-aware product vector quantization of KV caches. huggingface.co/spaces/adirik… Honorary mention: Laguna Vision Aaron Kazah @aaronkazah A SigLIP vision encoder resampler LoRA adapters, trained on 300k examples to give Laguna XS.2 a native visual input path. huggingface.co/poolside-lagu… Huge congrats to the winners, and thank you to everyone who hacked, demoed, judged, helped, and pushed Laguna XS.2 in directions we would not have found on our own! @nvidia @PrimeIntellect @adaption_ai @huggingface

London cookers are taking Laguna XS.2 to the moon 🚀 Huge shout to @PrimeIntellect @nvidia @huggingface @adaption_ai for making this possible!

Loving the @latentspacepod breakdown of our Laguna M.1/XS.2 Technical Report! The Latent Space paper club just did a deep dive, and their takeaways perfectly capture what we set out to build with our Model Factory. A few quotes from the video 🧵👇 (1/6) youtu.be/QLfZamyMls0

Laguna M.1 is now top 20 on @OpenRouter by weekly tokens served. Please keep on cooking.

If you’re in London tonight, come hear @varunrandery at @CrusoeAI Talks! He’ll unpack harnesses, agent APIs, and the blurring boundaries between models, tools, and products.

Honored to be included in @Redpoint 2026 InfraRed 100, recognizing the companies shaping the future of infrastructure and AI. Congratulations to all the companies featured this year!