Overview
A workshop on agent-first data systems, agents for data science and analytics, and the future of data systems (part of CAIS 2026, The ACM Conference on AI and Agentic Systems, May 26, 2026, San Jose, California)
Today’s data systems were designed for a small number of careful human operators. But a growing share of analytics, data engineering, and ML workflows is increasingly being delegated to AI agents. This workshop will bring together researchers and practitioners to study how data systems should evolve for agents, and how agents themselves can help shape better systems.
The workshop is born out of recent work in data management (e.g. Supporting Our AI Overlords and Trustworthy AI in the Agentic Lakehouse), but generalizes to other directions at the intersection of data and agents. Our goal is to explore the full design space where data systems and AI agents meet, and we are open to creative interpretations of the theme (including demos, lessons from the trenches, preliminary results, controversial positions, failure stories).
The workshop is sponsored by Mozilla AI and Bauplan Labs.
Organizers
 Elaine Ang Columbia University |
 Shu Liu UC Berkeley |
 Aditya Parameswaran UC Berkeley |
 John Dickerson Mozilla AI |
 Jonathan Frankle Databricks |
 Jacopo Tagliabue Bauplan Labs |
Invited Speakers
Speaker lineup to be announced.
 Speaker TBD Affiliation TBD |
Speaker TBD Affiliation TBD |
Speaker bios
Speaker TBD — Bio TBD.
Speaker TBD — Bio TBD.
Call for Papers
We invite submissions on the emerging intersection of AI agents and data systems. Drawing from the workshop manifesto, we are mainly interested in contributions along these research directions:
- Productionizing agentic workloads. Capturing the nuances of agentic reasoning and engineering techniques across the entire data lifecycle.
- Optimizing agent semantics. Exploring the transition from deterministic SQL execution to agent-driven pipelines.
- Data systems for agents. Rethinking core system guarantees from the ground up to support non-human workloads.
- Agents for system design. Exploring the “self-driving” potential of the stack, where agents autonomously design, tune, and maintain the very infrastructure they inhabit.
Examples of topics include, but are not limited to:
- Agent-first OLAP architectures for safe, reproducible, and cost-efficient analytics
- Agentic analytics workflows, including human-in-the-loop patterns and production failure modes
- Evaluation methodologies, benchmarks, and workload traces for data agents
- LLM-assisted optimization and tuning for data systems
- War stories and postmortems from production deployments
- Agentic workflows for data engineering and data science
- Operational reliability for agent-driven automation, including observability, guardrails, governance, and cost controls
- Work-in-progress and early-stage results that showcase novel ideas or promising directions, even if not yet fully evaluated
Generally speaking, we will be open to creative interpretations of the workshop themes as long as contributions sit at the intersection of data and agents.
Submission formats
We solicit:
- Short research and position papers: up to 4 pages plus references
- Late-breaking results / extended abstracts: up to 2 pages plus references
Submissions will be reviewed in a single-blind process by members of the committee. We welcome overlapping submissions with other venues. Extended abstracts are particularly encouraged for work-in-progress ideas and early-stage explorations. Production war stories and postmortems need not be technically novel as long as they provide interesting insights and lessons relevant to the workshop theme. Accepted contributions will be presented at the workshop, and accepted materials will also be archived on the workshop website. For more background, recent relevant literature, and inspiring use cases, see our workshop proposal.
Program Committee
- Aldrin Montana — Bauplan Labs
- Alperen Keleş — University of Maryland
- Bonnie Xu — OpenAI
- Davide Eynard — Mozilla AI
- Eugene Wu — Columbia University
- Federico Bianchi — Together AI
- Gaetano Rossiello — IBM
- Jeremiah Milbauer — CMU
- Nandana Mihindukulasooriya — IBM
- Nicole Rose Schneider — University of Maryland
- Sesh Nalla — Datadog
- Stephanie Wang — MongoDB
- Tao Ye — Lyft
- Till Döhmen — MotherDuck
Awards
We are pleased to offer awards for outstanding contributions:
- Best Paper Award — with a monetary prize, recognizing the strongest accepted contribution to the workshop.
- Best Student-Led Paper Award — with a monetary prize, for the best paper with a student as the primary author.
Awards will be presented at the end of the day during a social gathering with drinks and informal discussion. Stay tuned!
Important Dates
| Milestone | Date |
|---|---|
| Submission deadline | Thu, April 30, 2026 |
| Accept / reject notification | Fri, May 8, 2026 |
| Camera-ready | Tue, May 12, 2026 |
| Workshop | Tue, May 26, 2026 |
Panel
The workshop will conclude with a panel discussion bringing together different perspectives on agentic data systems, from infrastructure and optimization to safety and deployment. Panelists will be added soon.
Program (Tentative)
May 26, 2026 — In person in San Jose, California. The schedule below is tentative.
| Time | Activity | Details |
|---|---|---|
| 15 min | Welcome | Introductory remarks |
| 40 min | Keynote 1 | Academic keynote |
| 40 min | Contributions | Lightning talks / spotlights |
| 40 min | Keynote 2 | Industry keynote |
| 40 min | Contributions | Lightning talks / spotlights |
| 60 min | Panel | Moderated by the organizers |
| 5 min | Closing | Closing remarks |
| After hours | Pizza, drinks and awards | Informal discussion and awards |
Contact
For questions, please contact:
Jacopo Tagliabue
jacopo.tagliabue@bauplanlabs.com
Elaine Ang
ra3448@columbia.edu