Building the Data Layer for AI

Exploring the complex challenges of managing temporal data in AI systems and why building time-aware agents is a unique engineering feat.

Introducing an open-source tool designed to give AI agents reliable, secure, and precise SQL database access.

How we use Large Language Models to bridge the gap between natural language prompts and precise database queries.

Exploring the security risks and execution challenges of letting AI agents generate and run raw SQL code.

How transforming LLM outputs into reliable, structured data objects ensures consistency and seamless system integration.

A deep dive into building a multi-model workflow that combines the unique strengths of different AI systems to achieve hyper-realistic results.

A case study on using AI to analyze complex usage data and deliver personalized, transparent messaging during a pricing model shift.

A look at how AI-driven storytelling can transform raw data into compelling narratives that drive social impact and engagement.

Announcing a new milestone to accelerate the development of an AI-powered platform for automated business intelligence and reporting.

Exploring why deep IDE integration can limit flexibility and how a decoupled approach empowers developers to build better AI tools.

A new space for sharing technical insights, engineering challenges, and the latest breakthroughs in AI and data engineering.