Putting an LLM in Production: Structure, Cost, and Prompt-Injection Defenses
This is the third post in a series about a WhatsApp lead-qualification agent we built at a CRM for small businesses. The first post covered the engine: durable agent runs on a Postgres table and Celery, with a lease for crash safety. The second post covered the loop: debouncing message bursts, polling the conversation, nudging through silence, and treating every exit as a designed outcome. This post is about the layer the other two exist to protect: the LLM calls. ...