We built a conversational terraform platform at work, you describe what you need for your infra and it produces the terraform code following company standards and rules. What is important for us is the LLM never writes any code. It just extracts a structured spec from the conversation, and a deterministic engine (plain python, no LLM) renders the code from approved modules only. So there is no "code quality" discussion at all, and since the spec is structured and not natural language, you don't need another LLM to verify it, the risk moves to the extraction step which is small and easy to eval. But probably this only works in narrow domains where the output is composable from approved blocks (IaC, config etc), and its not a new idea, just old discipline behind a chat interface. But in that slice the speedup is way beyond 2x.
Sure, structured output gives you valid syntax, but thats not the problem we are solving. Our engine simply cannot produce anything outside of the approved module registry (pinned versions, mandatory tags etc). LLM with structured output still can produce plausible but wrong configs. Also same spec always renders the same code, thats what reviewers and auditors actually care
The leaderboard with acorns is a smart touch. gamification might actually solve your price freshness problem better than anything else. If updating a price earned acorns too, your top contributors would keep the data current for you. Nice project, and the 10% to food banks commitment on the about page is a good look.
Thank you! Yes, updating prices give you acorn and badge as well. I might expand more incentives to update prices, like suggestion from comments, for restaurants.
Food bank commitment is built in from start. I plan to display transparent donation amount if we ever make money. (fingers crossed!)
