When every customer needs different fields, let an AI agent propose the database tables from the conversation--but only create them after a person approves, and only allow adding tables and columns, never deletes: AI agent prompt

Working Surface (Nov 5, 2026 issue; summarizing a Japanese LayerX Ai Workforce engineering write-up by suna dated around Nov 4) describes a trial design where an AI agent designs and creates the PostgreSQL tables that store each customer's business data for work such as invoice checks and contract review. Customer field needs often appear only after work starts; the old flexible storage made types hard to enforce and forced the agent to scan every record to match invoices to purchase orders. In the new design the agent proposes real tables, asks clarifying questions, and creates them only after a person approves. The agent may add tables and columns but not delete or rename; every record change is shown first, approved by the user, and reported back with prior values. Working Surface notes there is no release date; treat this as an engineering account of a trial, not a shipped product promise.

OperationsHuman-approved agent schema designintermediate

The prompt

Help me let an AI agent design storage for a workflow where each customer needs different fields. Workflow: [e.g. invoice check / contract review]. Examples of fields we've seen: [list]. Rules I want: human approves schema; agent may add tables/columns only; no deletes or renames; every row change needs approval and must show old values. 1) Interview me with up to 8 questions to learn entities, keys, and which fields must be typed vs free text. 2) Propose a first schema (tables, columns, types, indexes) in plain language and as SQL CREATE statements. 3) List what you are unsure about and will not create until I answer. 4) Write the approval card text I should see before any CREATE runs. 5) Give a safe migration plan from a flexible/EAV store to these tables, including how matching [e.g. invoice to PO] gets faster with real columns. Do not run DDL or change data yourself.
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Works with: LayerX Ai Workforce (trial pattern), ChatGPT, Claude, PostgreSQL

Real-world example: workingsurface.ai/links/2026-11-05-02/

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