Open Source Science: agent-assisted research with ado

Are you looking to accelerate your research velocity, ensure computational reproducibility, and seamlessly integrate AI into your scientific workflows?
Join us for this hands-on, tailored tutorial where we will dive into how you can combine Coding Agents with ado (Accelerated Discovery Orchestrator)—an open-source platform that provides the perfect scaffolding for experimental research—to create an AI Research Assistant.

🚀 Why ado for Research?

Leveraging AI can dramatically accelerate discovery, but it can be difficult to integrate it reliably into research workflows. ado provides a structured view of experimentation that solves this problem:
Build Your AI Research Assistant: ado provides a robust, programmable view of empirical research that can augment AI coding agents into research assistants, allowing them to safely execute experiment campaigns, automate repetitive tasks, and analyze experimental data.
For Researchers: It handles the heavy lifting of tracking results and transitioning from local experiment development to large-scale experiment campaigns on HPC clusters, freeing you up to focus on the science rather than boilerplate code.
For PIs: ado automatically tracks data provenance, meaning research work is fully observable and reproducible across your group's activities. This observability can be leveraged by AI to provide summaries and suggest next steps. Similar to the revolution of coding agents, greybeard researchers may find they can do actual research once again!