Make Large Context Observable
A large context window can hold more evidence. It cannot tell you which evidence was noticed, current, authoritative, or safe to act on. Place and retrieve critical facts to reduce lost-in-the-middle failures. Trim tool output without losing provenance, errors, conflicts, or decision-relevant detail. Propagate complete, partial, and blocked results through agentic workflows. Use manifests, scratchpads, subagents, and compaction for different large-codebase jobs. Calibrate confidence and stratify human review from evidence and consequence. Preserve source identity, dates, conflicts, and content type through ingestion and rendering. A migration coordinator receives 140 files, three architecture documents, a dependency report, test logs, and results from four subagents. The prompt fits inside the advertised context window. The final plan still violates a security rule. The rule appears once near the middle of a long architecture document. A tool result containing the failed integration test was shortened to "tests mostly passed." One subagent timed out after reviewing 18 of 24 files, but its prose summary looks complete. A Markdown table lost its column relationships during extraction, so a deprecated dependency appears supported. Nothing exceeded the nominal token limit. The system failed because important facts had weak placement, metadata disappeared, partial work looked complete, and nobody defined an escalation rule. Context reliability is not the ability to fit more text. It is the ability to preserve the…
Make Large Context Observable: A large context window can hold more evidence. It cannot tell you which evidence was noticed, current, authoritative, or safe…
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