Building Reliable Agentic AI Systems
3.80T1 sourcemartinfowler.com (Exploring Gen AI series, incl. Böckeler)
Source record
Published by martinfowler.com (Exploring Gen AI series, incl. Böckeler) (T1 source). The original is at https://martinfowler.com/articles/reliable-llm-bayer.html.
Pipeline notes
The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.
SummaryPRINCE is a cloud-hosted agentic AI platform built by Bayer AG with Thoughtworks for pharmaceutical drug development. It uses Agentic RAG and Text-to-SQL to query decades of safety study reports, evolving from keyword search to a research assistant that drafts regulatory documents. The paper details context engineering and harness engineering decisions for reliability and governance.
Why it mattersConcrete production case study from Bayer and Thoughtworks with specific patterns for context engineering, harness engineering, and multi-agent orchestration — useful for teams building agentic systems beyond prototypes.
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