Editing Openai/6939b23e-87cc-8001-bdd9-9546d1143ce9 (section)

==== 1. Chunked row generation with summaries - After completing a row, generate a summary of that row (in concise token form). - Feed the summary back as context for future rows so the AI can reason over dependencies without including the entire previous row content. ====
# External memory / orchestrator - Keep a structured external table in your Python program. - AI generates one cell at a time → program inserts it in the table → program generates context snippet for the next AI call that includes only relevant info. - This reduces token pollution and allows linking prerequisites → enabler_results → outputs.
# Prompt engineering / explicit references - Instead of relying on AI to “remember column positions,” explicitly provide: ``<code> Row 3, Column: tech_name = "Firestarter" Previous columns: [...] Generate column: tech_output Dependencies: [...] </code>`` - The AI now has explicit table coordinates and dependencies, reducing hallucination.
# Generate columns in parallel (optional) - Some frameworks let you generate all cells of a row in one shot with a structured output (JSON). - This reduces inter-column sequential dependency errors, though the prompt becomes heavier.