InfoQ - QCon AI 2025 - Presentations

Presentation: Autonomous Data Products for the Autonomous Era: Rethinking Data Architecture for GenAI

Jörg Schad — Fri, 24 Jul 2026 13:30:00 GMT

Jörg Schad explains how to tame the complex "data management hairball" to build scalable, safe architectures for AI. He shares how autonomous data products act like containers for data, encapsulating pipelines, schemas, and metadata. Discover how progressive tool discovery via protocols like MCP limits context rot, enforces governance policies, and ensures reliable, multi-modal access.

By Jörg Schad

Presentation: From Copy-Paste to Composition: Building Agents Like Real Software

Jake Mannix — Wed, 22 Jul 2026 11:57:00 GMT

Jake Mannix discusses moving AI agents past chaotic "1970s BASIC" architectures. He shares how implementing an intermediate protocol layer allows engineering leaders to build versioned, encapsulated "virtual tools." This design enables interface mapping, dynamic schema projection, and runtime taint tracking to proactively eliminate data exfiltration risks without slowing velocity.

By Jake Mannix

Presentation: From OTEL to SLMs: Distilling Frontier Model Behaviour from Production Telemetry

Ben O'Mahony — Fri, 17 Jul 2026 13:17:00 GMT

Ben O'Mahony discusses building custom AI-powered Language Server Protocols (LSPs) that go beyond standard rule-based checkers. He explains how to instrument AI agents natively with OpenTelemetry to track concrete user actions (accepting, dismissing, or regenerating code fixes) as implicit labels, creating a continuous data flywheel to distill frontier capabilities into cheaper, local SLMs.

By Ben O'Mahony

Presentation: Postgres for Production Agents: Your Relational Foundation for Enterprise AI

Gwen Shapira — Wed, 15 Jul 2026 12:57:00 GMT

Gwen Shapira shares how teams are scaling AI features using PostgreSQL for mission-critical apps. She explains how to leverage Postgres's multi-modal capabilities - including JSONB parsing and high-recall HNSW vector indexing - to deliver deterministic and semantic context to LLMs. She also discusses vector quantization to speed up queries by 4x and strategies for managing agentic memory.

By Gwen Shapira