AI Peer Learning Labs
Interactive, peer-to-peer tutorials where attendees share practical ways they use AI in their work. Rather than traditional expert-led workshops, these informal sessions focus on community knowledge-sharing, real-world examples, and hands-on learning. If you are interested in facilitating, the submission deadline is Tuesday, September 15.
Apply HereAI Community Gathering
Building on the community’s mission to foster a vibrant, inclusive, and impactful space for interdisciplinary thinking, collaboration, rigorous research, mentorship, and policy/practice impact, the gathering will offer an informal opportunity for members to connect and identify shared priorities. This community will meet at #2026APPAM on Friday, November 6, 10:15 – 11:15 am.
Learn MoreAI Trainings
Join us for a hands-on, two-part workshop series led by Brian Heseung Kim, Founder & Chief Data Scientist at Open Augments. Across two 90-minute sessions, Part 1 on Thursday followed by Part 2 on Friday, you will learn how to evaluate AI outputs, refine results using advanced prompting and tools, and integrate AI assistants into your research workflows. Space is limited to 40 participants per group and is for current APPAM professional members only. A $20 non-refundable registration fee is required to reserve your seat in this limited workshop series.
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Beyond the Hype: Building a Critical Intuition for Effective Uses of AI Assistants for Research
(Workshop Part 1 – Thursday)
AI assistants are increasingly capable — but they can also hallucinate, produce unverifiable output, and confidently present wrong answers as fact. For researchers, this creates a real tension: the tools are becoming too useful to ignore, but remain too unreliable to trust without a critical framework for evaluating what they produce. In this workshop, we develop a stronger mental model of how these tools actually work—what they’re doing mechanically when they generate text—so attendees can operate with a robust intuition for where and how AI can contribute to their workflows more reliably. Attendees will learn the three main levers that improve AI output quality (the model, the tools it has access to, and user prompting skill), learn best practices to get auditable and high-quality AI assisted work, and leave with concrete strategies for getting consistently more useful results from AI assistants in their own day-to-day research work. This workshop will also cover the basics of core AI concepts like Agents, Skills, context window management, token usage management, and data privacy/security.
From Chats to Pipelines: An Introduction to Multi-Stage Task Orchestration for Research Workflows with Claude Code and the Data Analyst Augmentation Framework
(Workshop Part 2 – Friday)
Even with a strong grasp of how LLM assistants/agents work, using them well requires a great deal of effort and intention. Getting reliable output means carefully structuring many prompts, providing the right context and files, checking results, and then repeating the whole process again for each task. This session provides researchers with an approachable framework for realizing the benefits of AI agents for more complex research workflows, while mitigating their very real risks, using the Data Analyst Augmentation Framework (DAAF): an open-source set of tools for Claude Code designed to accelerate and enhance data analysis while strictly enforcing transparency, reproducibility, and rigor. In addition to building familiarity with how to use and extend DAAF for their own purposes (or even making their own separate toolkit), attendees will leave with a strong understanding of the pros and cons of current AI agent frameworks for data analysis workflows, the main design considerations involved in robust “context engineering” and “agentic orchestration” practices, what these tools currently can and cannot do, as well as the intuition needed to evaluate their appropriateness across their own workflows.
AI Office Hours
AI capabilities have advanced enormously over the past year, and these changes aren’t slowing down any time soon. But with the rapid pace of developments and wild degree of hype permeating the AI space, it’s also increasingly difficult to make sense of everything that’s going on: what do I actually need to know? What skills should I be learning? And what do these new AI tools actually mean for policy researchers like me?
In this session, APPAM will host an Office Hours session with Brian Heseung Kim, an education policy researcher who’s used the technology underlying modern AI systems in his research since 2019. He now provides strategic advising, coaching, and workshops on responsible AI use for teams at institutions including Harvard University, the University of Pennsylvania, the Urban Institute, Boston University, the University of Virginia, and more.
Attendees will be able to bring their questions, concerns, and ideas at all levels of technicality and experience for Brian to respond to, offering resources, guidance, and opportunities for further learning ahead of our planned conference workshops.
Virtual Office Hours Webinar:
Wednesday, October 14: 2:00 – 3:00 pm
Learn More
#2026APPAM Office Hours at APPAM Central exhibit booth:
Thursday, November 5: 10:30 – 11:30 am
Friday, November 6:
- 11:30 – 12:30 pm
- 1:00 – 2:00 pm
Questions about the 2026 Annual Fall Research Conference? Please reach out to [email protected].