Question 1

AI summaries of production status that drift from the source of truth

Accepted Answer

Precast production has exact counts — slabs cast, cured, stockpiled, shipped. An LLM summary that says "roughly 40 slabs ready" instead of the exact number erodes operator trust on the first mistake. Counts must come from the ERP, not from model text.

Question 2

Schedule changes emitted as text instead of as structured actions

Accepted Answer

When a user says "push the job to Thursday", the model must emit a structured schedule-change action the scheduler can apply — not a paragraph of prose. Typed UI contracts are the fix.

Question 3

Quote generation with missing constraints

Accepted Answer

A precast quote must carry transport, crane lift, site-access, and cure-time constraints. An LLM-generated quote that leaves any of these blank looks plausible and is commercially wrong. The contract between the model and the quote tool must enforce completeness.

Question 4

Integration with legacy scheduling software via screen scraping or CSVs

Accepted Answer

Many precast shops run on scheduling software that pre-dates modern APIs. The temptation is to bolt a chat widget onto the side. The durable pattern is a typed integration boundary — the copilot operates against a clean interface, the legacy scheduler keeps owning persistence.

AI for Precast Concrete Operations