Your agent is leaking PII, recommending competitors, and costing you triple.

Your agent is live. A customer asks a product question and your agent says "actually, competitor has a better deal." Your logs are full of customer phone numbers and emails in plain text, a GDPR and PIPEDA violation nobody on the team noticed. The same question asked twice gives two different answers because the prompt has no structure. Your monthly bill is 3x what you estimated because nothing limits how many tokens a single conversation burns. These are not edge cases. This is what most agents in production look like right now.

Attendees build a production-ready agent from scratch using LangChain and Google ADK. A middleware layer that scans every message for PII and redacts it before anything reaches the model or the logs. Guardrails that block competitor mentions, off-topic answers, and hallucinated claims. Structured prompts so the same input produces consistent output regardless of phrasing. Token budgets and response caching so cost stays predictable. Async tool calls so the agent stays responsive on slow APIs. The finished agent deploys to Google Cloud Run with Secret Manager handling credentials. Attendees leave with the full codebase and a pattern they can reuse on every agent after this.