Agentic Systems on AI VOID

AI-Native Databases: Storing and Querying for Intelligent Applications

Fri, 20 Mar 2026 00:00:00 +0000

Introduction to AI-Native Databases

Welcome back, future AI architects! In our journey through the evolving landscape of AI engineering, we’ve explored how AI workflow languages streamline complex tasks, how agent operating systems provide a foundation for intelligent agents, and how orchestration engines coordinate their intricate dance. Now, imagine if these intelligent systems didn’t just process information, but could remember, understand context, and reason over vast amounts of data in a way that traditional databases simply can’t.

Systems Thinking, Tradeoffs, and Architecting for AI/Agentic Workflows

Fri, 15 May 2026 00:00:00 +0000

In the journey from a simple application to a complex distributed system, we’ve explored many patterns and practices. Yet, the most powerful tool in an engineer’s arsenal isn’t a specific technology or framework—it’s a way of thinking. This chapter brings it all together, focusing on systems thinking, the art of navigating architectural tradeoffs, and how these timeless principles are more critical than ever when building the next generation of AI and agentic workflows.

Appendix A: Advanced Prompting Techniques

Mon, 01 Jan 0001 00:00:00 +0000

Appendix A: Advanced Prompting Techniques

Introduction to Prompting

Prompting, the primary interface for interacting with language models, is the process of crafting inputs to guide the model towards generating a desired output. This involves structuring requests, providing relevant context, specifying the output format, and demonstrating expected response types. Well-designed prompts can maximize the potential of language models, resulting in accurate, relevant, and creative responses. In contrast, poorly designed prompts can lead to ambiguous, irrelevant, or erroneous outputs.