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04:5504:55, 29 October 2026 AI Agents: A Primer (hist | edit) [30,813 bytes] Ajshen (talk | contribs) (Created page with " Category:AI Tools '''Agentic AI''' tools are AI systems that don't just answer questions: they take actions. An agent can search for papers, read your files, write and run code, launch jobs on a cluster, and look at the results, all in a loop, until the task you gave it is done. For statistical research, the most mature agents today are '''AI coding agents''' such as [https:...")

20:5320:53, 26 October 2026 Docker Sandboxes for AI Agents (hist | edit) [17,078 bytes] Ajshen (talk | contribs) (Created page with " Category:AI Tools Category:Containers and Virtual Environments '''[https://docs.docker.com/ai/sandboxes/ Docker Sandboxes]''' (the <code>sbx</code> command-line tool) runs AI coding agents such as Claude Code, Codex, Copilot, and Gemini inside disposable, isolated micro virtual machines ('''microVMs'''). Inside the sandbox the agent has a full Linux machine to do whateve...")

22:5122:51, 18 October 2026 Overleaf Git Integration (hist | edit) [17,642 bytes] Ajshen (talk | contribs) (Created page with " XX If your experiment code lives in a GitHub repository and your paper lives on Overleaf, you have probably done '''the upload dance''': rerun an experiment, hunt down the regenerated figure on disk, open Overleaf, delete the old file, upload the new one, and repeat for every figure and table that changed. It is slow, it is easy to le...") originally created as "Overleaf GitHub Integration"
22:4922:49, 18 October 2026 Overleaf (hist | edit) [13,212 bytes] Ajshen (talk | contribs) (Created page with " XX If your experiment code lives in a GitHub repository and your paper lives on Overleaf, you have probably done '''the upload dance''': rerun an experiment, hunt down the regenerated figure on disk, open Overleaf, delete the old file, upload the new one, and repeat for every figure and table that changed. It is slow, it is easy to le...")

04:3704:37, 4 September 2026 Setting up a local coding agent (hist | edit) [57,936 bytes] Ajshen (talk | contribs) (Created page with "= Deploying Qwen3.8-27B with OpenCode on a single 48 GB GPU = This page is a complete, standalone recipe for standing up an OpenAI-compatible [https://docs.vllm.ai vLLM] endpoint serving <code>Qwen/Qwen3.8-27B-FP8</code> on '''one''' 48 GB Ada-generation GPU (L40, L40S, or RTX 6000 Ada), and wiring [https://opencode.ai OpenCode] to it as an agentic coding CLI. When you are done you have a local, private coding assistant with a 128k context window that runs entirely on y...")

22:0522:05, 26 August 2026 End-to-end AI Scientist Trials (Methods/Applied Research) (hist | edit) [8,187 bytes] Ajshen (talk | contribs) (Created page with "(Check the last updated timestamp on this page, since this field moves fast) Given the rise of agentic AI and its use in academic research, the computing committee ran a few tests of cutting AI products and their ability to completely (or almost completely) automate the research process end-to-end, from literature review and hypothesis generation to final paper writeup. As of this writing, the models appear to still have a ways to go. Some caveats about these trials:...") Tag: Visual edit

20:1020:10, 19 August 2026 Agentic Workflow via GitHub Issues (hist | edit) [5,716 bytes] Ajshen (talk | contribs) (Created page with "Category:Computing_Workflows Agentic coding tools can act as automated research assistants, directly interacting with your terminal and file system to write scripts, run data pipelines, and manage your compute jobs. While this can drastically speed up iteration, managing these AI agents across different machines and lengthy experiments can quickly become chaotic. This article outlines a robust workflow for managing long-running agentic experiments. == 1. Introduct...")

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