Introducing - the Agentic OS you've been waiting for. 🧩 Compose teams of specialised AI agents from plugins. No model lock-in. No vendor platform. Your infrastructure, your data. ✅ Privacy-first: sensitive data never leaves your infra in plaintext. Tokenised before every LLM call, with a verifiable receipt per round. ✅ Plugin-driven: channels, integrations, tools, sub-agents as signed ZIPs. ✅ Self-hostable: Docker Compose up and running in minutes. ✅ Built for EU operations: GDPR-aware by design, EN/DE bilingual. Public preview is live. 🌐 🔗 #OpenSource# #AI# #AIAgents# #Privacy# #SelfHosted#

Gentle reminder that all you need to start with local AI is: - 2x RTX 3090s (pick them up for $700-$900 a piece on r/hardwareswap) - Qwen 3.6 27B - Your favorite agent (Claude Code / OpenCode / etc) - Self-hosted SearXNG for web access And you got yourself Opus 4.5 at home

We’ve read your posts and heard your feedback. 1. We’re postponing the announced billing change for self-hosted GitHub Actions to take time to re-evaluate our approach. 2. We are continuing to reduce hosted-runners prices by up to 39% on January 1, 2026. We have real costs in running the Actions control plane. We are also making investments into self-hosted runners so they work at scale in customer environments, particularly for complex enterprise scenarios. While this context matters, we missed the mark with this change by not including more of you in our planning. We need to improve GitHub Actions. We’re taking more time to meet and listen closely to developers, customers, and partners to start. We’ve also opened a discussion to collect more direct feedback and will use that feedback to inform the GitHub Actions roadmap. We’re working hard to earn your trust through consistent delivery across GitHub Actions and the entire platform.

I think $WARD might be one of the most interesting AI x crypto infrastructure plays right now. Most AI inference today runs on blind trust: send prompt → receive output → assume the model actually did the work. But autonomous agents are already trading, managing capital, and making real economic decisions onchain. So the real question becomes: How do you verify the computation actually happened? That’s the thesis behind Warden Halo. It’s basically BitTorrent for AI inference: a peer-to-peer compute marketplace where idle GPUs, Mac Minis, Ollama nodes, and self-hosted agents serve inference across a global mesh. Tasks get distributed across independent operators and verified through SPEX fingerprints instead of centralized trust. The clever part: SPEX uses Bloom-filter fingerprints of model outputs to statistically verify whether computation was honestly performed. Honest runs converge. Fake outputs don’t. Meaning AI computation can be verified in seconds without massive latency overhead. The token design is clean too: Users pay in USDC. Operators earn in USDC. $WARD becomes the value-capture layer through automatic buybacks, staking rewards, and token burns tied directly to network usage. This feels less like an “AI coin” and more like infrastructure for the autonomous agent economy.

Great products are built by great teams. Category-defining ones are built by people like our new Chief Scientist. Meet our Chief Scientist: Fei. Fei joins Donut from the frontier of AI, working at the intersection of intelligence and real-world systems. From Tsinghua, Caltech, to Fei has helped shape how AI interfaces with societal needs across clinical trials, political systems, and education, not just in theory, but through systems that actually operate in the real world. At Donut, that thinking sharpens into something bigger. If machines can think, they can act with self-hosted infra, and if they can act, they can move money in every market when prioritizing constraints. That’s the direction we’re building with D0. Also, Fei loves 'games' like IOI (International Olympiad in Informatics), which has accidentally become a good label for modern AI.