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TUI as corpus producer

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paired_with: tui-corpus-producer.es.md
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The **TUI-as-Corpus-Producer** pattern designates the operator terminal interface (`slm-cli`) as a primary source of high-quality training data for the per-tenant model adapter. Every interaction with the Doorman through this interface is a curated corpus contribution. The pattern encodes Doctrine claim #45.
The **TUI-as-Corpus-Producer** pattern designates the operator terminal interface (`slm-cli`) as a primary source of high-quality training data for the per-tenant model adapter. Every interaction with the Doorman through this interface is a curated corpus contribution.

## Why terminal interactions are high-quality training data

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## Adapter quality budget

Published fine-tuning literature suggests 200 to 500 high-quality verdict-signed interactions are sufficient for a first adapter training cycle in a narrow domain. [^2] Foundry's intended sequence for each tenant is: accumulate signed interactions from dogfood operations, train the first per-tenant adapter, apply a validation quality gate, and promote the adapter to the deployment. Each subsequent training cycle incorporates additional interactions, progressively tuning the adapter to the customer's specific environment — their systemd units, their seed taxonomy, their workflow vocabulary.
Published fine-tuning literature suggests 200 to 500 high-quality verdict-signed interactions are sufficient for a first adapter training cycle in a narrow domain. [^2] The platform's intended sequence for each tenant is: accumulate signed interactions from dogfood operations, train the first per-tenant adapter, apply a validation quality gate, and promote the adapter to the deployment. Each subsequent training cycle incorporates additional interactions, progressively tuning the adapter to the customer's specific environment — their systemd units, their seed taxonomy, their workflow vocabulary.

## Per-tenant adapter ownership

The corpus produced by a customer's operators trains that customer's adapter, not a general adapter. Per the [[customer-owned-graph-ip]] convention, the trained adapter weights are the customer's property. Foundry distributes the model architecture and the training pipeline; the customer retains the trained adapter that results.
The corpus produced by a customer's operators trains that customer's adapter, not a general adapter. Per the [[customer-owned-graph-ip]] convention, the trained adapter weights are the customer's property. The platform distributes the model architecture and the training pipeline; the customer retains the trained adapter that results.

## Verdict capture discipline

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