Platform Engineering
From Consumers to Builders: Turning 200 of our Team into Agent Creators in 2 Weeks
Monday Jun 1 / 11:30AM EDT
Most organizations approach "AI democratization" by giving coding assistants to engineers and simplistic chatbots to business users. Yet, building sophisticated, high-value AI agents remains a bottleneck restricted to a few specialists.
Ben Maraney
Principal Engineer @Forter, Previously @BigPanda and @Klarna
Batch Intelligence at Scale: Cost-Efficient Multi-Agent LLM Workflows with Built-In Resilience
Tuesday Jun 2 / 03:40PM EDT
Most teams building production LLM systems face a hard tradeoff: premium models with low latency or cost-efficient inference with unpredictable quality. This talk presents a third path, one validated at Walmart, the largest retailers in the world.
Aditya Mulik
Senior Software Engineer @Walmart Global Tech
Prompt to Prod: Engineering an Autonomous SDLC at Scale
Monday Jun 1 / 03:40PM EDT
Engineering organizations are hitting a Productivity Paradox. AI tools are generating more code than ever, yet the time it takes to ship that code safely to production in large-scale environments remains stagnant.
Andrew Swerdlow
Sr. Director of Software @Roblox, Author of "Tech Leadership: The Blueprint for Evolving from Individual Contributor to Tech Leader", Previously @Google and @Instagram
Building GenAI Platform at DoorDash
Tuesday Jun 2 / 10:20AM EDT
When we started adopting LLMs across DoorDash, every team was implementing the same infrastructure: retry logic, fallback mechanisms, cost tracking, prompt versioning, and batch processing pipelines. Engineering time was wasted on repetitive plumbing work instead of building features.
Siddharth Kodwani
Tech Lead, AI Infrastructure @DoorDash
Swaroop Chitlur
Staff Engineer / Engineering Manager Machine Learning Platform @DoorDash
Adaptive Recommenders in the Real World: Inference, Evals, and System Design
Tuesday Jun 2 / 01:20PM EDT
Modern personalization systems are shifting from hand-tuned heuristics to AI-native architectures, but building an adaptive recommendation engine in production—one that continuously learns, evolves, and delivers measurable business value—requires far more than deploying a model.
Mallika Rao
Senior Engineering Manager @Zocdoc, Previously @Netflix, @Twitter and @Walmart