InfoQ - AI, ML & Data Engineering - Presentations

Presentation: Moving Mountains: Migrating Legacy Code in Weeks Instead of Years

David Stein — Fri, 12 Jun 2026 09:24:00 GMT

David Stein shares how to rethink large-scale architectural migrations using AI. He discusses ServiceTitan's "assembly line" pattern, explaining how decomposing legacy codebase refactoring into standardized tasks can achieve massive parallelization. He highlights the critical role of programmatically rigid validation loops to eliminate LLM hallucinations and accelerate engineering agility.

By David Stein

Presentation: Beyond Prompting: Context Engineering and Memory Management for AI Systems at Scale

Adi Polak — Wed, 10 Jun 2026 12:03:00 GMT

Adi Polak discusses the architecture required to transition from stateless prompts to state-aware, context-rich AI agents. Drawing on 15 years in distributed systems, she shares how engineering leaders can leverage Apache Kafka and Flink for real-time stream processing, dynamic memory tiering, and tool orchestration via MCP to solve token limits, cost spikes, and latency bottlenecks.

By Adi Polak

Presentation: Beyond Speed Limits: Exploring the Performance Power of Valkey

Viktor Vedmich — Mon, 08 Jun 2026 10:15:00 GMT

Senior Solution Architect Viktor Vedmich shares how engineering leaders can maximize application performance using Valkey. He discusses the open-source Redis fork's 100% API compatibility, explores advanced caching strategies like lazy loading, and explains how to implement powerful data structures for real-time analytics, rate limiting, and session stores to solve the thundering herd problem.

By Viktor Vedmich

Presentation: Platform Teams Enabling AI - MCP/Multi-Agentic Tools across Linkedin

Karthik Ramgopal, Prince Valluri — Fri, 05 Jun 2026 12:23:00 GMT

LinkedIn’s Karthik Ramgopal and Prince Valluri discuss leveraging AI as a new execution model for large-scale engineering. They explain how to move beyond fragmented implementations by building platform abstractions for orchestration, structured context, and safe tooling like MCP. They share architectural insights from real-world coding, observation, and UI testing agents built at LinkedIn.

By Karthik Ramgopal, Prince Valluri