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DTSTAMP:20260819T173711Z
LOCATION:Room 319
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UID:share_SHARE Pittsburgh 2026_sess327_TECH373@linklings.com
SUMMARY:Turbo Charge CICS Knowledge for AI Use
DESCRIPTION:Lewis James (IBM UK)\n\nExperienced CICS system programmers ar
 e often the single best knowledge base their organisation has — but much o
 f that value is scattered across inboxes, chat threads, ticket histories, 
 and, most critically, “tribal knowledge” that never makes it into formal d
 ocumentation. In this session, “Turbo‑charge CICS knowledge for AI use,” w
 e’ll show how to turn that fragmented expertise into an AI‑ready knowledge
  layer that can reliably support modern AI assistants and specialised CICS
  agents. We’ll focus on pragmatic, low-friction techniques for extracting 
 high-signal operational know‑how: structured SME conversations (remote-fri
 endly), capturing real troubleshooting narratives, and using transcripts a
 s raw material to produce curated, reviewable knowledge documents — so you
 r best practices and hard-won lessons become reusable, searchable, and con
 sistently available. You’ll learn how to prioritize what to capture (runbo
 oks, “why we do it this way,” failure modes, and decision heuristics), how
  to reduce ambiguity and “it depends” answers into context-rich knowledge,
  and how to establish lightweight validation so the content stays trusted 
 as CICS evolves. The goal: move from ad hoc expert interruption to scalabl
 e expertise-on-demand, enabling AI systems to go deep on CICS-specific que
 stions rather than staying generic.\n\nTrack: CICS\n\nAudience Level: All 
 Audiences\n\nLearning Objectives: Modernize Data Management and Analytics\
 n\nSession Chair: Andrew Smithson (IBM)\n\n
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