Prompts as Functions: The BAML Revolution in AI Engineering

Episode Notes: https://thedataexchange.media/baml-revolution-in-ai-engineering/
David Hughes, Principal Data & AI Solution Architect at Enterprise Knowledge. Our discussion centers on BAML, a domain-specific language that transforms prompts into structured functions with defined inputs and outputs, enabling developers to create more deterministic and maintainable AI applications.
**Sections**
David's "Aha" Moment with BAML - 00:00:47
BAML's Structured Approach to Prompt Engineering - 00:02:58
How BAML Changed David's Approach to Prompt Engineering - 00:03:28
BAML as a Programming Language and its Learning Curve - 00:04:45
BAML as a Replacement for Other Frameworks - 00:05:38
Comparison of BAML with Other Frameworks - 00:07:16
BAML and the Future of Prompt Engineering - 00:09:28
BAML's Philosophy: Composability and Small Language Models - 00:10:42
BAML's Approach to Cost Monitoring and Reduction - 00:12:26
BAML's Schema-Aligned Parser and Reduction of Parsing Errors - 00:13:53
BAML's Polyglot Nature and Cross-Language Compatibility - 00:15:24
BAML's Role in Agentic AI Applications - 00:16:36
BAML's Roadmap and Future Developments - 00:18:24
BAML's Impact on Testing and Debugging - 00:20:17
BAML's Community and Support - 00:21:54
Introduction to Multimodal Graph RAG - 00:23:48
Multimodal Graph RAG: Core Concept and Benefits - 00:25:55
Challenges in Knowledge Graph Construction and BAML's Role - 00:27:46
The Future of Automatic Knowledge Graph Construction and BAML's Relevance - 00:29:31

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