Data, Cloud and AI in Dublin

• Speaker: Rahul Nair, IBM Research
• Description: An introduction to Mellea (mellea.ai) an open-source Python library for building predictable generative programs. We'll cover the core abstractions — instructions, requirements, sampling strategies, and verifiers — and show how treating model calls as structured, testable operations changes what you can build. Live coding, real examples, and a look at how Mellea composes with the rest of the Python ecosystem.

Talk 3: FactReasoner: Porting a Probabilistic Factuality Assessor to Mellea

• Speaker: Radu Marinescu, IBM Research
• Description: FactReasoner (paper , code) is IBM's probabilistic long-form factuality assessor — it decomposes generated text into atomic claims and reasons over their support against retrieved evidence. This talk walks through the port from a bespoke implementation to Mellea, the reliability improvements and speedups that came out of it, and what porting an existing system teaches you about where Generative Computing pays off in practice.

Talk 4: The Mellea Skills Compiler: From Plain-Language Specs to Governed Pipelines

• Speaker: [TBD], IBM Research
• Description: The Mellea Skills Compiler takes a plain-language skill specification and compiles it into a governed, certified generative pipeline — with evaluation harnesses, requirement checks, and provenance baked in. We'll show the compiler end-to-end on a worked example and discuss what "certification" means for LLM-backed skills, and how this closes the loop between rapid iteration and auditable production deployment.