Building Resilience: The Next Decade of Open Source
Over 25 years, open source has become vital digital infrastructure. However, its future relies on human resilience, not just code. To combat burnout, funding gaps, and new regulations, we must move beyond old methods and address sustainability through global policy, security, and community health.
10x CouchDB Performance Gains for a AAA Game Launch
All software benchmarks and claims of performance are carefully crafted lies and this talk is no different. Instead of giving you a quick “do steps one, two, three for a magic speedup”, we aim to explain how we arrived at the changes we made and how we rigorously tested those changes to make sure we understand their impact.
When better retrieval makes agents worse
Agentic systems can break not because information is missing, but because persuasively wrong context gets promoted into action. We examine a recurring pattern: retrieval metrics improve while agent behavior degrades as distractors enter multi-step loops. We show why relevance, reliability, and security are tightly connected in agentic retrieval.
Beyond Grep: Search for Reliable Coding Agents
Coding agents succeed in verifiable loops (compiler + tests), but large repos still expose retrieval weaknesses.
This session explores how lexical, structural, and semantic search can provide cleaner context for LLMs. We compare tradeoffs and evaluation approaches to improve reliability without inflating token cost.
Correctness Too Cheap To Meter: Formal Verification and LLMs
Formal methods are powerful tools to verify software systems’ correctness and reliability. However, manually writing system specs is time-consuming and hard to maintain. LLMs can help with this burden.
We’ll share new research into tools to automate formal methods workflows and learnings from how LLMs currently perform.
Agentic Retrieval: Building Self-Optimizing Search Systems
Relevance feedback loops used to take months. AI agents can now compress the process to seconds. This talk explores agentic retrieval: systems where agents adjust scoring models, schema, and indexing in real time. Learn how to build retrieval infrastructure with verifiable APIs that enable agents to optimize their own search context.
The Three-Body Problem of Inverse Hybrid Search
When users expect alerts for new products matching an uploaded image, the problem becomes inverse hybrid search. Unlike top-K search, alerting must guarantee fetch-all semantics: zero missed matches across all saved searches, combining vector similarity, boolean filters, and lexical signals. We show why this breaks traditional scaling intuition.
How Apache Iceberg Enables Multi-Engine Data Platforms
the session will cover operational best practices, including metadata management, file sizing, compaction strategies, and performance tuning at scale. Attendees will leave with practical guidance for designing &operating open, flexible, multi-engine data architectures built on Apache Iceberg, enabling faster analytics, lower operational flexibility
The Agent Era: How AI Agents Are Reshaping Data Platforms
AI agents have quietly become some of the most demanding users of modern data platforms and most weren’t built with them in mind. In this panel, leaders from Snowflake, Elastic, MotherDuck, and Xata share what agentic workloads actually look like in production: what broke, what had to be rebuilt, and where the architecture is heading.
Ultraviolet: Turn Hidden Document Data into an AI Advantage
Every PDF hides a world of structure, metadata and embedded signals that can silently influence AI based processing. With ultraviolets, we reveal how those can be exploited for malicious purposes and even become powerful tools for smarter applications. Designing for both humans and machines become a vital aspect of AI experience design.