Learn in Public means sharing your learning journey openly—writing notes, sharing insights, and teaching while you’re still figuring things out. Instead of waiting until you’ve “mastered” something, you learn out loud. This approach doesn’t just deepen your understanding; it creates feedback loops, builds your growth trajectory, and develops personal influence...

Google's latest announcements signal a profound shift in the AI industry. From AI as infrastructure to the rise of intelligent agents, here are the core implications for the future of technology and work.

The traditional SaaS narrative has focused on efficiency. But as AI advances, we're seeing a fundamental shift in value: AI is no longer just about adding features—it's about delivering real results.

Productionizing Machine Learning (ML) models effectively and at scale remains a significant challenge for many organizations. This article traces the architectural evolution of the MLOps platform at AstrumU over six years, highlighting the technical decisions, trade-offs, and lessons learned while building a sophisticated system for distributed data processing and ML...

AI systems are starting to look a lot like data systems. The recent launch of LangChain's Open Agent Platform reveals a fascinating pattern: AI engineering is following the same evolutionary path as data engineering, and this isn't just coincidence.