Introducing 
Express — Go from prompt to pipeline in minutes.
In episode five of DatAInnovators & Builders, GrowthX founder Marcel Santilli explains the delegation test for AI and why poor context, not weak models, is the real reason AI initiatives fail to scale.
AI systems fail when context doesn’t scale. This article explains the limits of context graphs, why static relationships break for enterprise AI, and what’s needed to deliver accurate, trustworthy AI outputs at scale.
Context engineering is the systematic practice of designing and controlling the information AI models consume at runtime, ensuring outputs are accurate, auditable, and compliant.
In episode four of DatAInnovators & Builders, BigID’s Stephen Gatchell explains the data governance gap blocking AI production, why unstructured data breaks legacy models, and how data product frameworks enable scale.
In the News: betanews.com: In this Q&A, Saket Saurabh explains why context engineering is key to reliable, compliant, and intelligent enterprise AI workflows.
AI is shifting data engineering from code-heavy ETL to prompt-driven pipelines. Explore where LLMs fit, common pitfalls, and how Nexla makes AI-ready data workflows practical.
A research-backed framework for evaluating LLM-generated data transformations. Learn how datasets, sandboxed execution, and automated judging reveal failure patterns and model performance across real-world data engineering tasks.
In this third episode of DatAInnovators & Builders, BigPanda’s Alexander Page shares how his team designs AI agents that internalize corrections, evaluate tool use, and scale reliably in production.
Explore how Express.dev makes AI agents capable of generating rich, interactive UI for structured data workflows. From XML-driven forms to real-time validation and OAuth flows, generative UI turns chat into a truly collaborative experience.
While it is true that AI offers enormous opportunities for innovation and success, its reliance on personal data raises urgent concerns about privacy, ethics, and governance
In this second episode of DatAInnovators & Builders, Ashish Thusoo breaks down how CurieTech AI uses benchmarks-first discipline and AI-driven build loops to achieve 70–80% productivity gains.
In this first episode of DatAInnovators & Builders, Databricks’ Robin Sutara reveals why generic AI training doesn’t stick and how persona-based enablement drives real adoption.
