Dosu

Sad to see how companies are using OSS for training data without recognition of the undue burden it puts on maintainers. But very proud to see Dosu called out as a positive force in OSS ecosystem working in directly with maintainers to save them time and reduce their workload. If you're an OSS project struggling with an influx of low quality issues, reach out to us! We are collaborating with open-core companies like Prisma, Astronomer, Langflow to enforce higher quality issues and streamline the triage process.

Back by popular demand - our AI Agent Hackathon returns! ?? After launching fascinating projects like AI shopping assistants, virtual tutors, and even an AI companion for preserving family memories, we're bringing together the brightest minds for our first massive collab of 2025! ?? 2 DAYS. $35K+ IN PRIZES. GAME-CHANGING PROJECTS. ?? Feb 15-16, 2024 Why You Can't Miss This: ? Power your project with Google Cloud, Gemini & sponsor APIs ? Network with top AI engineers ? Hack at W&B’s gorgeous Mission office ? Special prize for using W&B's Weave tool! ?? For the curious: Full schedule at link below, from breakfast to awards! ?? Milestone alert: Our first-ever 2-day hackathon! More time = bigger ideas ?? Proudly supported by: CreatorsCorner, Google Cloud & Gemini Google, Weights & Biases, Together AI, Stytch, VESSL AI, LlamaIndex, Dosu, Fly.io, Marly.ai, and us Senso ?? Limited spots. Solo or team welcome. Register: https://lu.ma/fyu8iqnk?

Dosu is hiring for Founding BizOps Lead. If you know anyone who might be a good fit, please have them reach out! https://lnkd.in/gr9xHdGT

We just dropped a new Open Source release ??? ?? Ollama new Structured Output ?? Phi4, Lllama3.3 models support ?? Dosu Bot ?? New Browsers Support ?? Bug Fix ?? Refactoring Examples Folder ?? Refactoring OSS docs (in progress...) Check it out and let us know what you think! https://lnkd.in/eCfhgdUb

I love the idea of "just-in-time" documentation - a how-to guide, onboarding guide, or cookbook generate for your exact use-case whenever you need it. It's the dream devX for any software library or service. This recent example of Dosu on Langfuse (YC W23) highlighted the potential of "just-in-time" docs: https://lnkd.in/gx6qyWuc A user wanted to know how to integrate Langfuse with Gradio, but there isn't any documentation for their use-case, so they created a new discussion on GitHub. Within minutes of posting the user and Dosu collaborated to generate a near-perfect cookbook for the Gradio x Langfuse use-case. The reaction of the user sums it up perfectly: "I love this tool even more!!" Overtime, I think users will expect "just-in-time" documentation to be the default documentation experience for integrations, how-to guides, and other use-case specific docs in the future.?

Here is one more alternate view of modern AI stack. There are apps like amazon.com, hotels.com etc which exists today which most likely will become transaction rails backbone in future. The new world of agents will use these transaction rails for task completion. An agent at the top will use an orchestration layer to route between planning of the tasks (using model layer) and task completion (tooling layer). Tooling layer will provide agent-to-app pathway for transaction completion. Following companies are interesting backbone of this stack > Agentic layer : Decagon, Replit, Harvey, Dosu, Perplexity > Orchestration layer: LlamaIndex, LangChain, CrewAI, phidata, Letta > Tooling layer: Plotch.ai, Composio, Browserbase > Genai layer: Copy.ai, Synthesia, Runway > Model layer: Sarvam, OpenAI > GPU Layer: NVIDIA > CPU layer: Intel Corporation How will this modern AI stack unfold in 2025? Lets see

Here is one more alternate view of modern AI stack. There are apps like amazon.com, hotels.com etc which exists today which most likely will become transaction rails backbone in future. The new world of agents will use these transaction rails for task completion. An agent at the top will use an orchestration layer to route between planning of the tasks (using model layer) and task completion (tooling layer). Tooling layer will provide agent-to-app pathway for transaction completion. Following companies are interesting backbone of this stack > Agentic layer : Decagon, Replit, Harvey, Dosu, Perplexity > Orchestration layer: LlamaIndex, LangChain, CrewAI, phidata, Letta > Tooling layer: Plotch.ai, Composio, Browserbase > Genai layer: Copy.ai, Synthesia, Runway > Model layer: Sarvam, OpenAI > GPU Layer: NVIDIA > CPU layer: Intel Corporation How will this modern AI stack unfold in 2025? Lets see

We are a proud partner of this year's virtual #AINativeDevCon. The team Tessl has put together an incredible lineup of world-leading experts in AI software development. This is not one to miss. We hope to see you there! https://tessl.co/3U7zyXa