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Long-Context Compaction — Chapter Boundaries vs Token Cuts

Domain 5 · 15% ~12 min Hinglish narration

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Scenario anchor

Aaranya IT ke ek BFSI engagement mein aap ek 200-page regulatory audit trail ko Claude se process karwa rahe hain — RBI compliance report, quarterly reconciliation, aur inter-bank settlement logs sab ek saath. Midway mein Claude ka context window pressure hit hota hai, aur aapka orchestration layer blindly token-cut kar deta hai — ek critical settlement boundary ke beech mein. Output mein figures match nahi karte, aur client escalation aati hai. Yeh lesson exactly wahi failure mode address karta hai: chapter boundaries par compact karo, arbitrary token cuts par nahi.

Key Takeaways

Compact at semantic chapter boundaries — section headers, transaction delimiters, protocol state transitions — never at raw token limits; boundary-aware compaction preserves referential integrity across the retained context.
Treat compaction fidelity as a first-class SLA: after each compaction pass, run a schema-validation checkpoint against required fields (entity IDs, monetary amounts, timestamps) before the next inference call proceeds.
Context window pressure is a runtime signal, not just a capacity metric — instrument your orchestration layer to detect approaching limits early enough to reach the next clean boundary before compaction is forced.
Memory anchor under exam pressure: 'Schema-validation checkpoint — compact at the boundary, validate the schema, then continue; never cut mid-clause.'

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