Launch HN: Augento (YC W25) – Fine-tune your agents with reinforcement learning 17 by lmeierhoefer | 1 comments on Hacker News. Hi HN, we’re the cofounders of Augento ( https://augento.ai/ ). We’re building Deepseek R1-like fine-tuning as a service. You connect your agent, tell us when it’s right or wrong, and we deliver an LLM optimized for that agent. There’s a demo video https://www.youtube.com/watch?v=j5RQaTdRrKE , and our docs are at https://ift.tt/k7udEKq . It’s open for anyone to use at https://augento.ai . Agents fail all the time, especially when you try to use them for something actually useful. Current solution approaches suck: prompting has intrinsic limits and supervised fine-tuning requires big explicit datasets that are hard to collect. Two months ago, the DeepSeek R1 paper outlined a way to post-train LLMs with (almost) pure reinforcement learning. We took up their research and built a fine-tuning platform around that. You let us intercept your agent's data flow,...