2026
GenAI Transforming Engineering
Research harnesses, low-code feature engineering, ranking migrations accelerated by code-agent benchmarking, coding agents for ML pipelines, and a panel on the evolving AI engineer role.
- 01Talk 01
Research Harness Engineering for Model Development
How an agentic research harness enables structured experimentation and faster iteration in applied AI.
Florian HönickePrincipal AI Engineer · Elastic - 02Talk 02
Low-Code Feature Engineering with Agentic Support
Configuration-driven feature pipelines that reduce infrastructure friction and shorten the route to production.
Ola WahabZalando - 03Talk 03
Ranking Logic Migration from Monolith
Using code-agent loops and async-profiler to benchmark a latency-critical ranking migration and close the p99 gap.
Ivan PotapovZalando - 04Talk 04
Coding Agents for ML Pipelines & AI Systems
Prompt-driven development, problem decomposition, and experimentation workflows for production ML systems.
Jim DowlingCEO · Hopsworks - 05Panel
Product Mindset in Engineering: The Evolution of the AI Engineer
With Jim Dowling (Hopsworks), Leela Sharma (Zalando), Alexey Grigorev (DataTalks.Club), and Florian Hönicke (Elastic).
Hosted by Ivan PotapovZalando



