typedef reinforced the lesson that context must be represented as a living system rather than assembled as a prompt at the beginning of a task.
Published
Signal category
Research & Knowledge
Quote
“At typedef, our work keeps reinforcing the same lesson: context has to be represented as a living system, not assembled as a prompt at the beginning of a task.”
— Yoni Michael|typedef team
Company
typedef
Data Engineering Agents - powered by full data stack context.
- Industry
- Software Development
- Company size
- 8 employees
Typedef builds AI agents for data engineering teams. Our agents automate impact analysis, root cause debugging, model refactoring, report reconciliation, and semantic validation. These are tasks that traditionally require hours of manual investigation across multiple tools. The core innovation is the data context layer: a continuously-updated understanding of your entire data stack. It is a comprehensive context view of warehouses, transformation frameworks, orchestration pipelines, BI platforms, and source systems. This gives agents the system-level context they need to operate reliably. Agents with our data context layer achieve an 82% task success rate on real-world data engineering tasks, compared to 46% without it. Same model, same tasks, but context is all the difference.