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Healthcare’s Agent Bytecode: X12 as the Harness for AI Agents

Conference Context

Session Description

LLMs made old languages newly useful: COBOL for mainframes, Fortran for scientific code, and Rust, SQL, and Prolog as strict substrates for agentic systems. Healthcare has its own old language hiding in plain sight: X12. Before LLMs, X12 was mostly treated as ugly plumbing: loops, delimiters, companion guides, clearinghouse edits, payer-specific quirks, rejections, and acknowledgments. In an agentic workflow, those constraints become the feature. They give stochastic agents a deterministic target. This talk shows how healthcare agents can compile messy operational evidence into X12-shaped workflows: chairside audio into 837D claim narratives, imaging systems into 275/PWK attachment flows, payer portals and phone calls into 270/271 eligibility and 276/277 claim status, preauth evidence into 278 workflows, and EOBs, scanned mail, and bank data into 835/820 payment reconciliation. The core pattern is simple: LLMs reason over ambiguity; X12 provides the syntactic and semantic harness for validation, auditability, acknowledgments, rejections, human review, and high-volume automation. This is not an EDI nostalgia talk. It is a production architecture talk about building reliable agents in one of the messiest enterprise domains.

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Healthcare’s Agent Bytecode: X12 as the Harness for AI Agents ## Conference Context - Date/time: 2026-07-01 · 1:55pm-2:15pm - Track/room: AI in Healthcare · Track 7 - Speaker(s): Vasant Kearney - Session type/status: session · confirmed - Track: AI in Healthcare - Room: Track 7 - Session type: session - Status: confirmed ## Session Description LLMs made old languages newly useful: COBOL for mainframes, Fortran for scientific code, and Rust, SQL, and Prolog as strict substrates for agentic systems. Healthcare has its own old language hiding in plain sight: X12. Before LLMs, X12 was mostly treated as ugly plumbing: loops, delimiters, companion guides, clearinghouse edits, payer-specific quirks, rejections, and acknowledgments. In an agentic workflow, those constraints become the feature.

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