video1.0<iframe src="https://www.loom.com/embed/b813b69a22b9410097a1d8fe9c8e2fd5" frameborder="0" width="1920" height="1440" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>14401920Loomhttps://www.loom.com14401920https://cdn.loom.com/sessions/thumbnails/b813b69a22b9410097a1d8fe9c8e2fd5-5ef2358257edf301.gif627.865This Loom explains Forge, an AI powered app compiler built as a four stage pipeline. It generates structured outputs through intent extraction, system design, separate LLM calls for database, API, and UI schemas, then a repair stage that fixes invalid JSON, missing Pydantic fields, and cross layer inconsistencies via up to three targeted repair passes. The author reports an 83.3 percent overall success rate on 12 distressed prompts plus 6 normal prompts and 6 edge cases, with average latency of 58.54 seconds, and notes failures were due to truncated JSON from max token limits and an intentional rejection of the vague prompt CRM. Key design trade offs include temperature 0 for determinism, 4 to 5 LLM calls for reliability, and using Grok with Llama 3 with key rotation for resiliency.