Most GenAI pilots stall after demos. McKinsey’s rules for survival and Zhou’s Agentic Engineering framework aim to make AI scalable and sustainable
Six pillars of AI-ready data: contextual, unified, accessible, governed, accurate, and iterative. Clean data alone is not enough.
Benchmarking shows DuckDB crushing Spark on 500M+ row datasets, highlighting when a lightweight in-memory engine outperforms a multi-node cluster.
A post-mortem of a major Kafka outage with root cause, monitoring gaps, and fixes to strengthen resilience.
How Claude Code gains PDF and DOCX understanding with LlamaIndex, unlocking real enterprise workflows.
Industry benchmarks on GenAI adoption, MLOps maturity, and modernization trends shaping the next two years.
An open, next-gen columnar file format optimized for analytics and AI, with modern compression and extensibility.
A full JupyterLab running in the browser via WebAssembly. Ideal for demos, lightweight analysis, and docs.
K8s-native integration of Spark History Server for monitoring jobs and logs within Kubeflow pipelines.
A demo-driven talk on building LLM support agents with Effect, covering architecture, tradeoffs, and reliability.
Join Marek Wiewiórka and Radosław Szmit as they debate the strengths and trade-offs of vendor vs. open-source data catalogs in real-world data lakehouse.
Step-by-step on building low-latency feature pipelines for consistent ML training and serving.
An open-source platform that merges streaming and OLAP for real-time analytics with SQL queries and time travel.
Practical takeaways from building agents at five startups, covering prompt design, tool use, memory, and user feedback loops.